Landmark Graphics Corporation

United States of America

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E21B 41/00 - Equipment or details not covered by groups 239
E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions 216
E21B 47/00 - Survey of boreholes or wells 173
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1.

ADJUSTING FLUID INJECTION INTO A WELLBORE BASED ON RELATIVE PERMEABILITY OF A FORMATION

      
Application Number 18148852
Status Pending
Filing Date 2022-12-30
First Publication Date 2024-07-04
Owner Landmark Graphics Corporation (USA)
Inventor
  • Hinkley, Richard
  • Eker, Erdinc

Abstract

A fluid injection process for injecting fluid into a wellbore can be adjusted based on relative permeability. An actual trapped gas saturation of a formation can be determined from a maximum gas saturation, a maximum trapped gas saturation, and an actual gas saturation. A pseudo-maximum gas saturation can be determined from the actual trapped gas saturation, the maximum trapped gas saturation, and actual gas saturation. A relative permeability of the formation can be determined by mapping the pseudo-maximum gas saturation along a drainage curve. The fluid injection process can be adjusted based on the relative permeability.

IPC Classes  ?

  • E21B 43/16 - Enhanced recovery methods for obtaining hydrocarbons
  • E21B 49/08 - Obtaining fluid samples or testing fluids, in boreholes or wells

2.

ADJUSTING FLUID INJECTION INTO A WELLBORE BASED ON RELATIVE PERMEABILITY OF A FORMATION

      
Application Number US2022082654
Publication Number 2024/144813
Status In Force
Filing Date 2022-12-30
Publication Date 2024-07-04
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Hinkley, Richard
  • Eker, Erdinc

Abstract

A fluid injection process for injecting fluid into a wellbore can be adjusted based on relative permeability. An actual trapped gas saturation of a formation can be determined from a maximum gas saturation, a maximum trapped gas saturation, and an actual gas saturation. A pseudo-maximum gas saturation can be determined from the actual trapped gas saturation, the maximum trapped gas saturation, and actual gas saturation. A relative permeability of the formation can be determined by mapping the pseudo-maximum gas saturation along a drainage curve. The fluid injection process can be adjusted based on the relative permeability.

IPC Classes  ?

  • E21B 43/16 - Enhanced recovery methods for obtaining hydrocarbons
  • E21B 43/20 - Displacing by water

3.

GRIDLESS VOLUMETRIC COMPUTATION

      
Application Number US2022081479
Publication Number 2024/129120
Status In Force
Filing Date 2022-12-13
Publication Date 2024-06-20
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Shi, Genbao
  • Medina, Raquel
  • Strebelle, Sebastien Bruno

Abstract

In some embodiments, a method for computing, by a volume data processor, volumetrics of a subsurface region without gridlines associated with the subsurface region comprises creating, in the volume data processor, a geometry representing the subsurface region and first bounding box about the geometry, computing a first probability that a group of sampled points inside the first bounding box are inside the geometry, and computing a gross rock volume (GRV) of the geometry by multiplying the first probability by a volume of the first bounding box.

IPC Classes  ?

  • G01V 1/48 - Processing data
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling

4.

GRIDLESS VOLUMETRIC COMPUTATION

      
Application Number 18079655
Status Pending
Filing Date 2022-12-12
First Publication Date 2024-06-13
Owner Landmark Graphics Corporation (USA)
Inventor
  • Shi, Genbao
  • Medina, Raquel
  • Strebelle, Sebastien Bruno

Abstract

In some embodiments, a method for computing, by a volume data processor, volumetrics of a subsurface region without gridlines associated with the subsurface region comprises creating, in the volume data processor, a geometry representing the subsurface region and first bounding box about the geometry, computing a first probability that a group of sampled points inside the first bounding box are inside the geometry, and computing a gross rock volume (GRV) of the geometry by multiplying the first probability by a volume of the first bounding box.

IPC Classes  ?

  • G01V 99/00 - Subject matter not provided for in other groups of this subclass
  • E21B 49/00 - Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells

5.

Historical Geological Data for Machine-Learning

      
Application Number 18072990
Status Pending
Filing Date 2022-12-01
First Publication Date 2024-06-06
Owner Landmark Graphics Corporation (USA)
Inventor
  • Wrobel-Daveau, Jean-Christophe
  • Baines, Graham
  • Nicoll, Graeme
  • Verma, Shashwat
  • Fogat, Mrigya

Abstract

A system can be used to incorporate historical geological data into machine learning techniques. The system can receive historical geological data. The system can pre-process the historical geological data by applying a selected, relative-time pre-processing technique to the historical geological data with respect to time-attributed geological phenomena. The system can train a machine-learning model using the pre-processed historical geological data. The system can apply the trained machine-learning model to generate predictions of geological phenomena. The system can provide a user interface to provide a visualization of the predictions of geological phenomena.

IPC Classes  ?

6.

HISTORICAL GEOLOGICAL DATA FOR MACHINE-LEARNING

      
Application Number US2022051603
Publication Number 2024/118081
Status In Force
Filing Date 2022-12-02
Publication Date 2024-06-06
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Wrobel-Daveau, Jean-Christophe
  • Baines, Graham
  • Nicoll, Graeme
  • Verma, Shashwat
  • Fogat, Mrigya

Abstract

A system can be used to incorporate historical geological data into machine learning techniques. The system can receive historical geological data. The system can pre-process the historical geological data by applying a selected, relative-time pre-processing technique to the historical geological data with respect to time-attributed geological phenomena. The system can train a machine-learning model using the pre-processed historical geological data. The system can apply the trained machine-learning model to generate predictions of geological phenomena. The system can provide a user interface to provide a visualization of the predictions of geological phenomena.

IPC Classes  ?

  • G06N 20/00 - Machine learning
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling

7.

DS365

      
Serial Number 98518962
Status Pending
Filing Date 2024-04-25
Owner Landmark Graphics Corporation ()
NICE Classes  ? 09 - Scientific and electric apparatus and instruments

Goods & Services

computer software for use in the exploration and production of hydrocarbons in the oil and gas industry

8.

BRITTLE-BURST STRENGTH FOR WELL SYSTEM TUBULAR INTEGRITY

      
Application Number 17970862
Status Pending
Filing Date 2022-10-20
First Publication Date 2024-04-25
Owner Landmark Graphics Corporation (USA)
Inventor
  • Liu, Zhengchun Michael
  • Samuel, Robello
  • Gonzales, Adolfo
  • Kang, Yongfeng

Abstract

A system can receive data relating to a tubular of a well system. The system can execute a first module to determine first outputs. The system can execute a second module to determine second outputs based on the first outputs. The system can execute a third module to determine third outputs based on the first outputs. The second outputs can include a crack-initiation fracture pressure, and the third outputs can include a crack-propagation fracture pressure. The system can identify a brittle-burst strength of the tubular from among the second outputs, the third outputs, and a standard burst strength of the tubular. The system can provide the brittle-burst strength of the tubular to facilitate an adjustment to the tubular to optimize a wellbore operation associated with the well system.

IPC Classes  ?

  • E21B 47/007 - Measuring stresses in a pipe string or casing

9.

BRITTLE-BURST STRENGTH FOR WELL SYSTEM TUBULAR INTEGRITY

      
Application Number US2023030883
Publication Number 2024/085947
Status In Force
Filing Date 2023-08-23
Publication Date 2024-04-25
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Liu, Zhengchun Michael
  • Samuel, Robello
  • Gonzales, Adolfo
  • Kang, Yongfeng

Abstract

A system can receive data relating to a tubular of a well system. The system can execute a first module to determine first outputs. The system can execute a second module to determine second outputs based on the first outputs. The system can execute a third module to determine third outputs based on the first outputs. The second outputs can include a crack-initiation fracture pressure, and the third outputs can include a crack-propagation fracture pressure. The system can identify a brittle-burst strength of the tubular from among the second outputs, the third outputs, and a standard burst strength of the tubular. The system can provide the brittle-burst strength of the tubular to facilitate an adjustment to the tubular to optimize a wellbore operation associated with the well system.

IPC Classes  ?

  • E21B 47/06 - Measuring temperature or pressure
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
  • E21B 43/267 - Methods for stimulating production by forming crevices or fractures reinforcing fractures by propping
  • E21B 47/04 - Measuring depth or liquid level

10.

FAULTED SEISMIC HORIZON MAPPING

      
Application Number 17951250
Status Pending
Filing Date 2022-09-23
First Publication Date 2024-04-04
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Possee, Daniel James
  • Baines, Graham

Abstract

Disclosed herein are embodiments of a method, a non-transitory computer readable medium, and an apparatus for faulted seismic horizon mapping. In one example, a method comprises: obtaining seismic data for a seismic volume that corresponds to a subsurface formation; generating a map of at least one horizon in the subsurface formation based on the seismic volume; identifying at least one fault intersecting the at least one horizon; determining a throw of the at least one fault; and updating the map of the at least one horizon to incorporate the at least one fault based on the throw of the at least one fault.

IPC Classes  ?

  • G01V 1/34 - Displaying seismic recordings
  • E21B 49/00 - Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
  • G01V 1/30 - Analysis

11.

PACK OFF INDICATOR FOR A WELLBORE OPERATION

      
Application Number US2023021697
Publication Number 2024/072490
Status In Force
Filing Date 2023-05-10
Publication Date 2024-04-04
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Liu, Zhengchun Michael
  • Samuel, Robello

Abstract

A system can generate, via a software model, downhole pressure estimations and downhole debris estimations using caving parameters. Additionally, the system can generate, via the software model, settled caving volume percent estimations using the caving parameters. The system can determine a pack off volume percent using the downhole pressure estimations, the downhole debris estimations, and the settled caving volume percent estimations. The system can output, via a user interface, the pack off indicator and a subset of the caving parameters for use in adjusting a wellbore operation. The user interface can provide a plot of the pack off volume percent horizontally offset with respect to a plot of the subset of the caving parameters and a depth of the wellbore.

IPC Classes  ?

12.

GRAPH BASED MULTI-SURVEY HORIZON OPTIMIZATION

      
Application Number 17950995
Status Pending
Filing Date 2022-09-22
First Publication Date 2024-03-28
Owner Landmark Graphics Corporation (USA)
Inventor
  • Possee, Daniel James
  • Baines, Graham

Abstract

A method for processing seismic data by a seismic data system. The method comprises acquiring a plurality of first traces each corresponding to a respective first trace location. The method comprises expressing the first traces as first vertices in a first graph in which first edges connect the first vertices, wherein the first edges indicate positioning of the first vertices.

IPC Classes  ?

13.

PACK OFF INDICATOR FOR A WELLBORE OPERATION

      
Application Number 17952785
Status Pending
Filing Date 2022-09-26
First Publication Date 2024-03-28
Owner Landmark Graphics Corporation (USA)
Inventor
  • Liu, Zhengchun Michael
  • Samuel, Robello

Abstract

A system can generate, via a software model, downhole pressure estimations and downhole debris estimations using caving parameters. Additionally, the system can generate, via the software model, settled caving volume percent estimations using the caving parameters. The system can determine a pack off volume percent using the downhole pressure estimations, the downhole debris estimations, and the settled caving volume percent estimations. The system can output, via a user interface, the pack off indicator and a subset of the caving parameters for use in adjusting a wellbore operation. The user interface can provide a plot of the pack off volume percent horizontally offset with respect to a plot of the subset of the caving parameters and a depth of the wellbore.

IPC Classes  ?

  • E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
  • E21B 47/04 - Measuring depth or liquid level
  • G01V 99/00 - Subject matter not provided for in other groups of this subclass

14.

FAULTED SEISMIC HORIZON MAPPING

      
Application Number US2022077032
Publication Number 2024/063803
Status In Force
Filing Date 2022-09-26
Publication Date 2024-03-28
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Possee, Daniel James
  • Baines, Graham

Abstract

Disclosed herein are embodiments of a method, a non-transitory computer readable medium, and an apparatus for faulted seismic horizon mapping. In one example, a method comprises: obtaining seismic data for a seismic volume that corresponds to a subsurface formation; generating a map of at least one horizon in the subsurface formation based on the seismic volume; identifying at least one fault intersecting the at least one horizon; determining a throw of the at least one fault; and updating the map of the at least one horizon to incorporate the at least one fault based on the throw of the at least one fault.

IPC Classes  ?

  • G01V 1/40 - Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging
  • G01V 1/28 - Processing seismic data, e.g. analysis, for interpretation, for correction

15.

GRAPH BASED MULTI-SURVEY HORIZON OPTIMIZATION

      
Application Number US2023065971
Publication Number 2024/064424
Status In Force
Filing Date 2023-04-19
Publication Date 2024-03-28
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Possee, Daniel James
  • Baines, Graham

Abstract

A method for processing seismic data by a seismic data system. The method comprises acquiring a plurality of first traces each corresponding to a respective first trace location. The method comprises expressing the first traces as first vertices in a first graph in which first edges connect the first vertices, wherein the first edges indicate positioning of the first vertices.

IPC Classes  ?

  • G01V 1/30 - Analysis
  • G01V 1/36 - Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy

16.

METHOD AND SYSTEM FOR PREDICTION AND CLASSIFICATION OF INTEGRATED VIRTUAL AND PHYSICAL SENSOR DATA

      
Application Number 17766775
Status Pending
Filing Date 2019-11-07
First Publication Date 2024-03-21
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Ramsay, Travis St. George
  • Marotta, Egidio
  • Madasu, Srinath

Abstract

The present disclosure is related to improvements in methods for evaluating and predicting responses of virtual sensors to determine formation and fluid properties as well as classifying the predicted as plausible or outlier responses that can indicate the need for maintenance of downhole physical sensors. In one aspect, a method includes detecting a change to a system of operating a wellbore to yield a determination, the system including a virtual sensor, the virtual sensor including a physical sensor placed in the wellbore for collecting one or more physical properties inside the wellbore; and based on the determination, performing one of retraining a machine learning model for predicting an output of the virtual sensor or predicting an output of the virtual sensor using the machine learning mode, the predicted output being indicative of at least one of sub-surface formation or fluid properties inside the wellbore.

IPC Classes  ?

  • E21B 49/08 - Obtaining fluid samples or testing fluids, in boreholes or wells
  • E21B 43/16 - Enhanced recovery methods for obtaining hydrocarbons

17.

FRICTION FOR CUTTING PLUG

      
Application Number US2023065974
Publication Number 2024/050155
Status In Force
Filing Date 2023-04-19
Publication Date 2024-03-07
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Zhang, Yuan
  • Samuel, Robello
  • Liu, Zhengchun Michael

Abstract

A method for controlling computerized operations related to a wellbore comprises drilling the wellbore in a subsurface formation with a drill string including a drill bit. The method comprises acquiring a plurality of drilling parameters while drilling the wellbore. The method comprises determining, based on the plurality of drilling parameters, solids properties for solids forming a cutting plug up hole of the drill bit. The method comprises determining a length of the cutting plug based on the solids properties. The method comprises determining a cutting plug friction force based on the cutting plug length and a pressure differential across the cutting plug. The method comprises performing a drilling operation based on the cutting plug friction force.

IPC Classes  ?

  • E21B 44/02 - Automatic control of the tool feed
  • E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
  • E21B 29/00 - Cutting or destroying pipes, packers, plugs, or wire lines, located in boreholes or wells, e.g. cutting of damaged pipes, of windows; Deforming of pipes in boreholes or wells; Reconditioning of well casings while in the ground

18.

Friction for cutting plug

      
Application Number 17902487
Grant Number 11920455
Status In Force
Filing Date 2022-09-02
First Publication Date 2024-03-05
Grant Date 2024-03-05
Owner Landmark Graphics Corporation (USA)
Inventor
  • Zhang, Yuan
  • Samuel, Robello
  • Liu, Zhengchun Michael

Abstract

A method for controlling computerized operations related to a wellbore comprises drilling the wellbore in a subsurface formation with a drill string including a drill bit. The method comprises acquiring a plurality of drilling parameters while drilling the wellbore. The method comprises determining, based on the plurality of drilling parameters, solids properties for solids forming a cutting plug up hole of the drill bit. The method comprises determining a length of the cutting plug based on the solids properties. The method comprises determining a cutting plug friction force based on the cutting plug length and a pressure differential across the cutting plug. The method comprises performing a drilling operation based on the cutting plug friction force.

IPC Classes  ?

  • E21B 44/02 - Automatic control of the tool feed
  • E21B 47/06 - Measuring temperature or pressure
  • E21B 47/08 - Measuring diameters or related dimensions at the borehole

19.

INFERRING SUBSURFACE KNOWLEDGE FROM SUBSURFACE INFORMATION

      
Application Number 18305601
Status Pending
Filing Date 2023-04-24
First Publication Date 2024-02-29
Owner Landmark Graphics Corporation (USA)
Inventor
  • Singh, Satyan
  • Jiang, Fan
  • Osypov, Konstantin
  • Toms, Julianna

Abstract

A geoscience knowledge system can be obtained, where the geoscience knowledge system can include one or more of publicly available information, industry information, proprietary information, or task specific information. The geoscience knowledge system can be represented as a graph, graph data, network nodes, image data, tokenized data, or textualized data. Subsurface information can be obtained such as from seismic images or other types of sensor data. The subsurface information can be transformed or pre-processed, such as denoising, to make it suitable for use by the geoscience knowledge system. Then subsurface knowledge can be inferred from the subsurface information using the geoscience knowledge system. The subsurface knowledge can provided estimates, approximations, or value of the subterranean formation of interest in order to calculate an economic model parameter, such as a hydrocarbon distribution proximate the subterranean formation of interest.

IPC Classes  ?

20.

LEARNING HYDROCARBON DISTRIBUTION FROM SEISMIC IMAGE

      
Application Number 17896748
Status Pending
Filing Date 2022-08-26
First Publication Date 2024-02-29
Owner Landmark Graphics Corporation (USA)
Inventor
  • Osypov, Konstantin
  • Jiang, Fan
  • Gomes, Marcelo
  • Singh, Satyan

Abstract

The disclosure relates to determining rock properties of subterranean formations and learning the distribution of hydrocarbons in the formations. A geometrical element spread function is disclosed that quantifies distortion of the geology as seen by the geophysicists who process seismic images of the subterranean formations. A method of determining the rock properties using the seismic images and synthetic images is provided. In one example, the method includes: (1) obtaining seismic data from a subterranean formation using a seismic acquisition system, (2) generating one or more seismic images of the subterranean formation using the seismic data, (3) creating one or more synthetic images from the one or more seismic images, and (4) determining rock properties of the subterranean formation based on the one or more seismic images and the one or more synthetic images.

IPC Classes  ?

  • G01V 1/30 - Analysis
  • E21B 49/00 - Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
  • G01V 1/34 - Displaying seismic recordings

21.

INFERRING SUBSURFACE KNOWLEDGE FROM SUBSURFACE INFORMATION

      
Application Number US2023019842
Publication Number 2024/043953
Status In Force
Filing Date 2023-04-25
Publication Date 2024-02-29
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Singh, Satyan
  • Jiang, Fan
  • Osypov, Konstantin
  • Toms, Julianna

Abstract

A geoscience knowledge system can be obtained, where the geoscience knowledge system can include one or more of publicly available information, industry information, proprietary information, or task specific information. The geoscience knowledge system can be represented as a graph, graph data, network nodes, image data, tokenized data, or textualized data. Subsurface information can be obtained such as from seismic images or other types of sensor data. The subsurface information can be transformed or pre-processed, such as denoising, to make it suitable for use by the geoscience knowledge system. Then subsurface knowledge can be inferred from the subsurface information using the geoscience knowledge system. The subsurface knowledge can provided estimates, approximations, or value of the subterranean formation of interest in order to calculate an economic model parameter, such as a hydrocarbon distribution proximate the subterranean formation of interest.

IPC Classes  ?

  • G06N 20/00 - Machine learning
  • G06N 3/042 - Knowledge-based neural networks; Logical representations of neural networks
  • G06N 5/04 - Inference or reasoning models

22.

REAL-TIME DRILLING OPTIMIZATION IN A METAVERSE SPACE

      
Application Number 17821660
Status Pending
Filing Date 2022-08-23
First Publication Date 2024-02-29
Owner Landmark Graphics Corporation (USA)
Inventor
  • Samuel, Robello
  • Crawshay, David James
  • Agrawal, Abhishek

Abstract

A system can be used for optimizing a wellbore operation via a metaverse space that can include one or more avatars. The system can provide access to the metaverse space for an entity. The metaverse space can be a computer-generated representation of a location relating to a wellbore operation. The system can receive, via an avatar in the metaverse space, a query from the entity relating to the wellbore operation. The avatar can include software applications for performing tasks in the metaverse space. The system can execute, via the avatar, a request to a micro-service for at least one solution parameter based on the query. The request can cause the micro-service to generate the at least one solution parameter. The system can receive the at least one solution parameter from the micro-service. The system can output the at least one solution parameter for adjusting the wellbore operation.

IPC Classes  ?

  • G06F 30/20 - Design optimisation, verification or simulation
  • G06F 40/40 - Processing or translation of natural language
  • G06T 15/00 - 3D [Three Dimensional] image rendering

23.

TRAJECTORY TRACKING AND OPTIMIZATION FOR DRILLING AUTOMATION

      
Application Number 17895746
Status Pending
Filing Date 2022-08-25
First Publication Date 2024-02-29
Owner Landmark Graphics Corporation (USA)
Inventor
  • Zhang, Shang
  • Codling, Jeremy
  • Agrawal, Abhishek
  • Samuel, Robello

Abstract

Processes to receive user input parameters and system input parameters associated with a borehole undergoing active drilling operations to continually update drilling directions with wholistically applied optimizations to bring the actual borehole trajectory closer to the planned borehole trajectory. The processes can project ahead of the drilling assembly to determine the actual trajectory of the borehole and generate corrections to reduce the gap between the actual and planned trajectory paths. Various optimizations can be applied to the corrections to avoid overstressing systems or reducing the borehole productivity. Conflicts between optimizations can be resolved using a weighting or ranking system. More than one set of corrections can be determined and a user or a machine learning system can be used to select the one set of corrections to use as the results to be communicated and applied to the drilling operation plan or a borehole system, such as a geo-steering system.

IPC Classes  ?

  • E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
  • E21B 7/04 - Directional drilling

24.

TRAJECTORY TRACKING AND OPTIMIZATION FOR DRILLING AUTOMATION

      
Application Number US2022041692
Publication Number 2024/043903
Status In Force
Filing Date 2022-08-26
Publication Date 2024-02-29
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Zhang, Shang
  • Codling, Jeremy
  • Agrawal, Abhishek
  • Samuel, Robello

Abstract

Processes to receive user input parameters and system input parameters associated with a borehole undergoing active drilling operations to continually update drilling directions with wholistically applied optimizations to bring the actual borehole trajectory closer to the planned borehole trajectory. The processes can project ahead of the drilling assembly to determine the actual trajectory of the borehole and generate corrections to reduce the gap between the actual and planned trajectory paths. Various optimizations can be applied to the corrections to avoid overstressing systems or reducing the borehole productivity. Conflicts between optimizations can be resolved using a weighting or ranking system. More than one set of corrections can be determined and a user or a machine learning system can be used to select the one set of corrections to use as the results to be communicated and applied to the drilling operation plan or a borehole system, such as a geo-steering system.

IPC Classes  ?

  • E21B 47/09 - Locating or determining the position of objects in boreholes or wells; Identifying the free or blocked portions of pipes
  • E21B 47/04 - Measuring depth or liquid level
  • E21B 41/00 - Equipment or details not covered by groups
  • E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions

25.

LEARNING HYDROCARBON DISTRIBUTION FROM SEISMIC IMAGE

      
Application Number US2022041773
Publication Number 2024/043907
Status In Force
Filing Date 2022-08-27
Publication Date 2024-02-29
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Osypov, Konstantin
  • Jiang, Fan
  • Gomes, Marcelo
  • Singh, Satyan

Abstract

The disclosure relates to determining rock properties of subterranean formations and learning the distribution of hydrocarbons in the formations. A geometrical element spread function is disclosed that quantifies distortion of the geology as seen by the geophysicists who process seismic images of the subterranean formations. A method of determining the rock properties using the seismic images and synthetic images is provided. In one example, the method includes: (1) obtaining seismic data from a subterranean formation using a seismic acquisition system, (2) generating one or more seismic images of the subterranean formation using the seismic data, (3) creating one or more synthetic images from the one or more seismic images, and (4) determining rock properties of the subterranean formation based on the one or more seismic images and the one or more synthetic images.

IPC Classes  ?

  • G01V 1/46 - Data acquisition
  • G01V 1/30 - Analysis
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling

26.

REAL-TIME DRILLING OPTIMIZATION IN A METAVERSE SPACE

      
Application Number US2022075359
Publication Number 2024/043929
Status In Force
Filing Date 2022-08-23
Publication Date 2024-02-29
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Samuel, Robello
  • Crawshay, David James
  • Agrawal, Abhishek

Abstract

A system can be used for optimizing a wellbore operation via a metaverse space that can include one or more avatars. The system can provide access to the metaverse space for an entity. The metaverse space can be a computer-generated representation of a location relating to a wellbore operation. The system can receive, via an avatar in the metaverse space, a query from the entity relating to the wellbore operation. The avatar can include software applications for performing tasks in the metaverse space. The system can execute, via the avatar, a request to a micro-service for at least one solution parameter based on the query. The request can cause the micro-service to generate the at least one solution parameter. The system can receive the at least one solution parameter from the micro-service. The system can output the at least one solution parameter for adjusting the wellbore operation.

IPC Classes  ?

  • G06Q 50/10 - Services
  • G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
  • G06T 13/40 - 3D [Three Dimensional] animation of characters, e.g. humans, animals or virtual beings
  • G06T 19/00 - Manipulating 3D models or images for computer graphics
  • G06F 21/30 - Authentication, i.e. establishing the identity or authorisation of security principals
  • E21B 41/00 - Equipment or details not covered by groups

27.

TRIP MAP FOR ADJUSTING A TRIPPING OPERATION IN A WELLBORE

      
Application Number US2022075039
Publication Number 2024/039397
Status In Force
Filing Date 2022-08-16
Publication Date 2024-02-22
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor Samuel, Robello

Abstract

A system can generate a trip map for adjusting a tripping operation in a wellbore. The system can receive input data from a downhole tool in a wellbore. The system can determine parameters for the tripping operation. The system can determine an overall condition for an interval of the wellbore based on the parameters. The system can determine a status for the parameters and for the overall condition based on a difference between the parameters or the overall condition and a corresponding optimized value. The system can generate a trip map using the parameters and the overall condition. The trip map can include a background shape and a polygon that can be positioned on the background shape. The polygon can include corners corresponding to the parameters and overall condition that are positioned angularly around the background. The trip map can be output to adjust the tripping operation.

IPC Classes  ?

  • G01V 99/00 - Subject matter not provided for in other groups of this subclass
  • G01V 3/18 - Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination or deviation specially adapted for well-logging
  • E21B 41/00 - Equipment or details not covered by groups

28.

ANALYZING BOREHOLE PATHS USING STRATIGRAPHIC TURNING POINTS

      
Application Number US2022035661
Publication Number 2024/005819
Status In Force
Filing Date 2022-06-30
Publication Date 2024-01-04
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Butt, Alice
  • Ponomarev, Mykhailo
  • Mageroy, Einar

Abstract

The disclosure presents processes to determine turning points in stratigraphy (TPS) which can be used to improve the representation of the borehole path in relation to layers of the subterranean formation. The TPS can be determined by analyzing each directional survey point in relation to the nearest layer of the subterranean formation. In determining which layer is the nearest layer, the process can analyze the layer type, such as conformable or unconformable, whether a fault intersects the borehole, the angle of the layer in relation to the borehole path, or whether the true stratigraphic thickness (TST) changes from one of a positive parameter or negative parameter to the other. The generated TPS can be used by a system as input or can be displayed for a user where the segmented borehole path can be aligned using the calculated TST to improve the ability of the user to analyze the representation.

IPC Classes  ?

  • G01V 1/46 - Data acquisition
  • G01V 1/50 - Analysing data
  • E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
  • E21B 47/04 - Measuring depth or liquid level

29.

Trip map for adjusting a tripping operation in a wellbore

      
Application Number 17820181
Grant Number 11859485
Status In Force
Filing Date 2022-08-16
First Publication Date 2024-01-02
Grant Date 2024-01-02
Owner Landmark Graphics Corporation (USA)
Inventor Samuel, Robello

Abstract

A system can generate a trip map for adjusting a tripping operation in a wellbore. The system can receive input data from a downhole tool in a wellbore. The system can determine parameters for the tripping operation. The system can determine an overall condition for an interval of the wellbore based on the parameters. The system can determine a status for the parameters and for the overall condition based on a difference between the parameters or the overall condition and a corresponding optimized value. The system can generate a trip map using the parameters and the overall condition. The trip map can include a background shape and a polygon that can be positioned on the background shape. The polygon can include corners corresponding to the parameters and overall condition that are positioned angularly around the background. The trip map can be output to adjust the tripping operation.

IPC Classes  ?

  • E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions

30.

OPTIMIZING DRILLING PARAMETERS FOR CONTROLLING A WELLBORE DRILLING OPERATION

      
Application Number US2022033578
Publication Number 2023/244224
Status In Force
Filing Date 2022-06-15
Publication Date 2023-12-21
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Agrawal, Abhishek
  • Zhang, Shang
  • Samuel, Robello

Abstract

A system can receive input data indicating a current state of a wellbore drilling operation. The system can determine, by a set of software applications, constraints associated with the wellbore drilling operation. The system can optimize, by an optimization model and using the input data, a drilling parameter subject to the constraints associated with the wellbore drilling operation. The system can output the optimized drilling parameter for controlling the wellbore drilling operation.

IPC Classes  ?

  • E21B 49/00 - Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
  • E21B 43/30 - Specific pattern of wells, e.g. optimizing the spacing of wells
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
  • E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions

31.

DETERMINING CELL PROPERTIES FOR A GRID GENERATED FROM A GRID-LESS MODEL OF A RESERVOIR OF AN OILFIELD

      
Application Number US2022033616
Publication Number 2023/244225
Status In Force
Filing Date 2022-06-15
Publication Date 2023-12-21
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor Hassanpour, Mehran

Abstract

A system can receive a grid-less point cloud model of a geological formation, the grid-less cloud point model that includes data points. The system can determine, by a machine-learning model for clustering data points, clusters for the data points according to a heterogeneity index. The system can determine an outline for each cluster. The system can generate a grid corresponding to the geological formation, the grid comprising a plurality of cells for each cluster of the plurality of clusters, each cluster having cell properties. The system can output the grid for the geological formation to a graphical user interface, the grid usable for executing a flow simulation at the graphical user interface.

IPC Classes  ?

  • G01V 1/40 - Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging
  • G01V 1/28 - Processing seismic data, e.g. analysis, for interpretation, for correction
  • G06N 20/00 - Machine learning
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling

32.

DETERMINING CELL PROPERTIES FOR A GRID GENERATED FROM A GRID-LESS MODEL OF A RESERVOIR OF AN OILFIELD

      
Application Number 17840393
Status Pending
Filing Date 2022-06-14
First Publication Date 2023-12-14
Owner Landmark Graphics Corporation (USA)
Inventor Hassanpour, Mehran

Abstract

A system can receive a grid-less point cloud model of a geological formation, the grid-less cloud point model that includes data points. The system can determine, by a machine-learning model for clustering data points, clusters for the data points according to a heterogeneity index. The system can determine an outline for each cluster. The system can generate a grid corresponding to the geological formation, the grid comprising a plurality of cells for each cluster of the plurality of clusters, each cluster having cell properties. The system can output the grid for the geological formation to a graphical user interface, the grid usable for executing a flow simulation at the graphical user interface.

IPC Classes  ?

  • G06F 30/28 - Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]

33.

OPTIMIZING DRILLING PARAMETERS FOR CONTROLLING A WELLBORE DRILLING OPERATION

      
Application Number 17840314
Status Pending
Filing Date 2022-06-14
First Publication Date 2023-12-14
Owner Landmark Graphics Corporation (USA)
Inventor
  • Agrawal, Abhishek
  • Zhang, Shang
  • Samuel, Robello

Abstract

A system can receive input data indicating a current state of a wellbore drilling operation. The system can determine, by a set of software applications, constraints associated with the wellbore drilling operation. The system can optimize, by an optimization model and using the input data, a drilling parameter subject to the constraints associated with the wellbore drilling operation. The system can output the optimized drilling parameter for controlling the wellbore drilling operation.

IPC Classes  ?

  • E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions

34.

EMISSIONS ESTIMATIONS AT A HYDROCARBON OPERATION LOCATION USING A DATA-DRIVEN APPROACH

      
Application Number US2022032412
Publication Number 2023/239351
Status In Force
Filing Date 2022-06-06
Publication Date 2023-12-14
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Srivastav, Shreshth
  • Kaushik, Ashutosh
  • Hungund, Bilal

Abstract

A system can collect a first set of equipment data and emissions data from a first hydrocarbon operation location. The system can train at least one machine-learning model to estimate an emission factor of at least one equipment component of the first hydrocarbon operation location using the first set of equipment data and the emissions data of the first hydrocarbon operation location. The system can then apply the at least one machine-learning model to a second set of equipment data to estimate total emissions over a predetermined amount of time at a second hydrocarbon operation location.

IPC Classes  ?

  • G06Q 50/26 - Government or public services
  • G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
  • G06N 20/00 - Machine learning
  • E21B 44/02 - Automatic control of the tool feed

35.

EMISSIONS ESTIMATIONS AT A HYDROCARBON OPERATION LOCATION USING A DATA-DRIVEN APPROACH

      
Application Number 17833873
Status Pending
Filing Date 2022-06-06
First Publication Date 2023-12-07
Owner Landmark Graphics Corporation (USA)
Inventor
  • Srivastav, Shreshth
  • Kaushik, Ashutosh
  • Hungund, Bilal

Abstract

A system can collect a first set of equipment data and emissions data from a first hydrocarbon operation location. The system can train at least one machine-learning model to estimate an emission factor of at least one equipment component of the first hydrocarbon operation location using the first set of equipment data and the emissions data of the first hydrocarbon operation location. The system can then apply the at least one machine-learning model to a second set of equipment data to estimate total emissions over a predetermined amount of time at a second hydrocarbon operation location.

IPC Classes  ?

  • E21B 49/08 - Obtaining fluid samples or testing fluids, in boreholes or wells
  • E21B 47/10 - Locating fluid leaks, intrusions or movements

36.

BUILDING SCALABLE GEOLOGICAL PROPERTY MODELS USING MACHINE LEARNING ALGORITHMS

      
Application Number 17585441
Status Pending
Filing Date 2019-12-03
First Publication Date 2023-11-16
Owner Landmark Graphics Corporation (USA)
Inventor
  • Hassanpour, Mehran
  • Bardy, Gaetan
  • Shi, Genbao

Abstract

A method of predicting rock properties at a selectable scale is provided, including receiving coordinates of locations of respective sample points, receiving measurement data associated with measurements or measurement interpretations for each sample point, receiving for each sample point a scale that indicates the scale used to obtain the measurements and/or measurement interpretations, wherein different scales are received for different sample points. A deep neural network (DNN) is trained by applying the received coordinates, measurement data, and scale associated with each sample point and associating the sample point with a rock property as a function of the coordinates, measurement data, and scale applied for the sample point. The DNN is configured to generate rock property data for a received request point having coordinates and a selectable scale, wherein the rock property data is determined for the request point as a function of the coordinates and the selectable scale.

IPC Classes  ?

  • G01V 99/00 - Subject matter not provided for in other groups of this subclass
  • G06N 3/091 - Active learning

37.

AUTOMATED FAULT SEGMENT GENERATION

      
Application Number 17738247
Status Pending
Filing Date 2022-05-06
First Publication Date 2023-11-09
Owner Landmark Graphics Corporation (USA)
Inventor
  • Nguyen, Xuan Nam
  • Tufekci, Sinan
  • Jaramillo, Alejandro

Abstract

The disclosure presents processes to automatically generate one or more set of fault segments from a fault plane pointset. The processes can identify a predominant direction and derive a set of fault segments from the fault plane pointset, where the fault segments are generated by using slices of data from the fault plane pointset that are perpendicular to the predominant direction. For each slice of data, the fault segments can be analyzed with neighboring fault segments to determine if they are overlapping. Fault segments that block or overlap other fault segments can be assigned to a different subset of fault segments from the underlying fault segments. Gaps in the fault plane pointset, and the resulting set of fault segments, can be filled in by merging neighboring fault segments above and below the gap if the neighboring fault segments satisfy a criteria for filling the gap.

IPC Classes  ?

  • E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
  • G01V 1/30 - Analysis
  • E21B 49/00 - Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells

38.

AUTOMATED FAULT SEGMENT GENERATION

      
Application Number US2022028268
Publication Number 2023/214977
Status In Force
Filing Date 2022-05-09
Publication Date 2023-11-09
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Nguyen, Xuan Nam
  • Tufekci, Sina
  • Jaramillo, Alejandro

Abstract

The disclosure presents processes to automatically generate one or more set of fault segments from a fault plane pointset. The processes can identify a predominant direction and derive a set of fault segments from the fault plane pointset, where the fault segments are generated by using slices of data from the fault plane pointset that are perpendicular to the predominant direction. For each slice of data, the fault segments can be analyzed with neighboring fault segments to determine if they are overlapping. Fault segments that block or overlap other fault segments can be assigned to a different subset of fault segments from the underlying fault segments. Gaps in the fault plane pointset, and the resulting set of fault segments, can be filled in by merging neighboring fault segments above and below the gap if the neighboring fault segments satisfy a criteria for filling the gap.

IPC Classes  ?

39.

SUSTAINABILITY RECOMMENDATIONS FOR HYDROCARBON OPERATIONS

      
Application Number US2022026488
Publication Number 2023/211432
Status In Force
Filing Date 2022-04-27
Publication Date 2023-11-02
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Nielsen, Roxana Mehrabadi
  • Horbatko, Morgan Michelle
  • Rees, Emily

Abstract

A system can receive a sustainability target for a level of assessment for a hydrocarbon operation. The system can receive actual data for an activity associated with the hydrocarbon operation. The system can generate a sustainability metric based on the actual data and one or more parameters of the activity. The system can generate, by at least one algorithm, a predicted sustainability state for the level of assessment at a subsequent point in time based on the sustainability metric, the actual data, and the one or more parameters of the activity. The system can generate a recommendation for at least one action based on the predicted sustainability state and the sustainability target for the hydrocarbon operation. The system can output the recommendation for the at least one action for adjusting the activity of the hydrocarbon operation.

IPC Classes  ?

40.

RETROFITTING EXISTING RIG HARDWARE AND PERFORMING BIT FORENSIC FOR DULL BIT GRADING THROUGH SOFTWARE

      
Application Number US2022050960
Publication Number 2023/204852
Status In Force
Filing Date 2022-11-23
Publication Date 2023-10-26
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Samuel, Robello
  • Srinivasan, Nagaraj

Abstract

The disclosure provides an automated process for determining the wear condition of a downhole tool that removes the subjectivity associated with manual observation. The automated process can advantageously evaluate a wear condition of a downhole tool using visual analytics and real-time analysis after the downhole tool has been extracted from the wellbore. An example of a method includes: (1) securing a downhole tool in a rig assembly, (2) obtaining, using sensors, surround tool data of the downhole tool in the rig assembly, wherein the surround tool data includes a first set of surround tool data obtained before a downhole operation by the downhole tool and a second set of surround tool data obtained after the downhole operation, and (3) automatically determining a wear condition of the downhole tool in real time by comparing the second set of surround tool data to the first set of surround tool data.

IPC Classes  ?

  • E21B 47/002 - Survey of boreholes or wells by visual inspection
  • E21B 12/02 - Wear indicators
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
  • E21B 12/06 - Mechanical cleaning devices
  • E21B 44/02 - Automatic control of the tool feed

41.

FREQUENCY-DEPENDENT MACHINE LEARNING MODEL IN SEISMIC INTERPRETATION

      
Application Number 17825914
Status Pending
Filing Date 2022-05-26
First Publication Date 2023-09-14
Owner Landmark Graphics Corporation (USA)
Inventor
  • Jiang, Fan
  • Jaramillo, Alejandro
  • Angelovich, Steven Roy

Abstract

Frequency-dependent machine-learning (ML) models can be used to interpret seismic data. A system can apply spectral decomposition to pre-processed training data to generate frequency-dependent training data of two or more frequencies. The system can train two or more ML models using the frequency-dependent training data. Subsequent to training the two or more ML models, the system can apply the two or more ML models to seismic data to generate two or more subterranean feature probability maps. The system can perform an analysis of aleatoric uncertainty on the two or more subterranean feature probability maps to create an uncertainty map for aleatoric uncertainty. Additionally, the system can generate a filtered subterranean feature probability map based on the uncertainty map for aleatoric uncertainty.

IPC Classes  ?

42.

FREQUENCY-DEPENDENT MACHINE-LEARNING MODEL IN SEISMIC INTERPRETATION

      
Application Number US2022031179
Publication Number 2023/172278
Status In Force
Filing Date 2022-05-26
Publication Date 2023-09-14
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Jiang, Fan
  • Jaramillo, Alejandro
  • Angelovich, Steven Roy

Abstract

Frequency-dependent machine-learning (ML) models can be used to interpret seismic data. A system can apply spectral decomposition to pre-processed training data to generate frequency-dependent training data of two or more frequencies. The system can train two or more ML models using the frequency-dependent training data. Subsequent to training the two or more ML models, the system can apply the two or more ML models to seismic data to generate two or more subterranean feature probability maps. The system can perform an analysis of aleatoric uncertainty on the two or more subterranean feature probability maps to create an uncertainty map for aleatoric uncertainty. Additionally, the system can generate a filtered subterranean feature probability map based on the uncertainty map for aleatoric uncertainty.

IPC Classes  ?

43.

DETERMINING RESERVOIR HETEROGENEITY FOR OPTIMIZED DRILLING LOCATION

      
Application Number US2022017732
Publication Number 2023/163703
Status In Force
Filing Date 2022-02-24
Publication Date 2023-08-31
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Davies, Andrew
  • Simmons, Michael
  • Cowliff, Lawrence
  • Kozlowski, Estanislao Nicolás

Abstract

A system can determine a heterogeneity and a score for a reservoir for optimizing a drilling location. The system can receive a wireline log associated with a well that is positioned in a subterranean formation that includes a reservoir. The system can determine, using the wireline log, at least one statistical parameter for an interval of the well. The system can determine, using the at least one statistical parameter, a vertical heterogeneity of the reservoir. The system can determine, using the vertical heterogeneity, a score associated with the reservoir. The score can indicate an extraction difficulty and a carbon intensity of the reservoir. The system can output the score for optimizing a drilling location.

IPC Classes  ?

  • E21B 43/30 - Specific pattern of wells, e.g. optimizing the spacing of wells
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
  • E21B 47/26 - Storing data down-hole, e.g. in a memory or on a record carrier
  • E21B 41/00 - Equipment or details not covered by groups

44.

Determining reservoir heterogeneity for optimized drilling location

      
Application Number 17679996
Grant Number 11905809
Status In Force
Filing Date 2022-02-24
First Publication Date 2023-08-24
Grant Date 2024-02-20
Owner Landmark Graphics Corporation (USA)
Inventor
  • Davies, Andrew
  • Simmons, Michael
  • Cowliff, Lawrence
  • Kozlowski, Estanislao Nicolás

Abstract

A system can determine a heterogeneity and a score for a reservoir for optimizing a drilling location. The system can receive a wireline log associated with a well that is positioned in a subterranean formation that includes a reservoir. The system can determine, using the wireline log, at least one statistical parameter for an interval of the well. The system can determine, using the at least one statistical parameter, a vertical heterogeneity of the reservoir. The system can determine, using the vertical heterogeneity, a score associated with the reservoir. The score can indicate an extraction difficulty and a carbon intensity of the reservoir. The system can output the score for optimizing a drilling location.

IPC Classes  ?

  • E21B 43/25 - Methods for stimulating production
  • E21B 43/16 - Enhanced recovery methods for obtaining hydrocarbons
  • E21B 47/003 - Determining well or borehole volumes
  • E21B 47/0224 - Determining slope or direction of the borehole, e.g. using geomagnetism using seismic or acoustic means
  • E21B 49/00 - Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells

45.

MODELING A KARST FORMATION FOR A WELLBORE OPERATION

      
Application Number 17669902
Status Pending
Filing Date 2022-02-11
First Publication Date 2023-08-17
Owner
  • Landmark Graphics Corporation (USA)
  • Petróleo Brasileiro S.A. - Petrobras (Brazil)
Inventor
  • Pereira, Marcio Rogerio Spinola
  • Renaut, Erwan Yann
  • Cazarin, Caroline Lessio
  • Santos, Luiz Eduardo Pinheiro
  • Quadros, Franco Borges

Abstract

A system can model a karst formation for controlling a wellbore operation. The system can receive first input data that includes a set of fracture properties in a fracture network of a subterranean formation. The system can receive second input data that includes a set of point sets from a fracture geometry of the fracture network. The system can generate a set of fracture skeletons from the first input data and the second input data. The system can model a karst feature based on the plurality of fracture skeletons. The system can output the karst feature for controlling a wellbore operation.

IPC Classes  ?

46.

MODELING A KARST FORMATION FOR A WELLBORE OPERATION

      
Application Number US2022016178
Publication Number 2023/154055
Status In Force
Filing Date 2022-02-11
Publication Date 2023-08-17
Owner
  • LANDMARK GRAPHICS CORPORATION (USA)
  • PETRÓLEO BRASILEIRO S.A. - PETROBRAS (Brazil)
Inventor
  • Pereira, Marcio Rogerio Spinola
  • Renaut, Erwan Yann
  • Cazarin, Caroline Lessio
  • Santos, Luiz Eduardo Pinheiro
  • Quadros, Franco Borges

Abstract

A system can model a karst formation for controlling a wellbore operation. The system can receive first input data that includes a set of fracture properties in a fracture network of a subterranean formation. The system can receive second input data that includes a set of point sets from a fracture geometry of the fracture network. The system can generate a set of fracture skeletons from the first input data and the second input data. The system can model a karst feature based on the plurality of fracture skeletons. The system can output the karst feature for controlling a wellbore operation.

IPC Classes  ?

  • E21B 43/30 - Specific pattern of wells, e.g. optimizing the spacing of wells
  • E21B 43/267 - Methods for stimulating production by forming crevices or fractures reinforcing fractures by propping
  • E21B 47/26 - Storing data down-hole, e.g. in a memory or on a record carrier

47.

ADVANCED TUBULAR DESIGN METHODOLOGY WITH HIGH TEMPERATURE GEOTHERMAL AND OIL/GAS CYCLIC THERMAL LOADING EFFECT

      
Application Number 17592989
Status Pending
Filing Date 2022-02-04
First Publication Date 2023-08-10
Owner Landmark Graphics Corporation (USA)
Inventor
  • Kang, Yongfeng
  • Samuel, Robello
  • Kumar, Vagish

Abstract

The disclosure addresses the existing gap in tubular designs and monitoring of tubulars in wellbores by considering high temperature, cyclic thermal loading effects. An example method of designing tubular for use in a well is provided that includes: (1) receiving a well configuration for a well and at least one type of well operation for the well, (2) receiving a selection of a tubular for use in the well, (3) generating a temperature history and a pressure history for the well using the well configuration, the selection of the tubular, the at least one type of well operation, and one or more simulators, and (4) determining, using the temperature history and the pressure history, a derated strength of the tubular based on one or more effects of high temperature, cyclic thermal loadings on the tubular.

IPC Classes  ?

  • G06F 30/18 - Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
  • E21B 47/07 - Temperature
  • E21B 41/00 - Equipment or details not covered by groups

48.

ADVANCED TUBULAR DESIGN METHODOLOGY WITH HIGH TEMPERATURE GEOTHERMAL AND OIL/GAS CYCLIC THERMAL LOADING EFFECT

      
Application Number US2022015416
Publication Number 2023/149901
Status In Force
Filing Date 2022-02-07
Publication Date 2023-08-10
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Kang, Yongfeng
  • Samuel, Robello
  • Kumar, Vagish

Abstract

The disclosure addresses the existing gap in tubular designs and monitoring of tubulars in wellbores by considering high temperature, cyclic thermal loading effects. An example method of designing tubular for use in a well is provided that includes: (1) receiving a well configuration for a well and at least one type of well operation for the well, (2) receiving a selection of a tubular for use in the well, (3) generating a temperature history and a pressure history for the well using the well configuration, the selection of the tubular, the at least one type of well operation, and one or more simulators, and (4) determining, using the temperature history and the pressure history, a derated strength of the tubular based on one or more effects of high temperature, cyclic thermal loadings on the tubular.

IPC Classes  ?

  • E21B 41/00 - Equipment or details not covered by groups
  • E21B 47/06 - Measuring temperature or pressure
  • E21B 47/007 - Measuring stresses in a pipe string or casing

49.

RESERVOIR TURNING BANDS SIMULATION WITH DISTRIBUTED COMPUTING

      
Application Number 17646705
Status Pending
Filing Date 2021-12-31
First Publication Date 2023-07-06
Owner Landmark Graphics Corporation (USA)
Inventor
  • Shi, Genbao
  • Ranzinger, Kurt Alan

Abstract

Some implementations relate to a method for parallelizing, by a geological data system, operations of a geostatistical simulation for a well data set via a plurality of processing elements (PEs). The method may include determining a reservoir area for the well data set. The method may include determining a set of turning band lines for the reservoir area. The method may include dividing the reservoir area into a plurality of tiles, each tile including a respective subset of the set of turning band lines. The method may include assigning at least one of the tiles to each of the PEs. The method may include determining, in parallel for each tile, intermediate results with respect to each respective subset of turning band lines. The method may include aggregating the intermediate results to form a final result of the geostatistical simulation.

IPC Classes  ?

  • G01V 99/00 - Subject matter not provided for in other groups of this subclass
  • G06F 30/20 - Design optimisation, verification or simulation

50.

RESERVOIR TURNING BANDS SIMULATION WITH DISTRIBUTED COMPUTING

      
Application Number US2021073209
Publication Number 2023/129185
Status In Force
Filing Date 2021-12-31
Publication Date 2023-07-06
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Shi, Genbao
  • Ranzinger, Kurt Alan

Abstract

Some implementations relate to a method for parallelizing, by a geological data system, operations of a geostatistical simulation for a well data set via a plurality of processing elements (PEs). The method may include determining a reservoir area for the well data set. The method may include determining a set of turning band lines for the reservoir area. The method may include dividing the reservoir area into a plurality of tiles, each tile including a respective subset of the set of turning band lines. The method may include assigning at least one of the tiles to each of the PEs. The method may include determining, in parallel for each tile, intermediate results with respect to each respective subset of turning band lines. The method may include aggregating the intermediate results to form a final result of the geostatistical simulation.

IPC Classes  ?

  • G01V 99/00 - Subject matter not provided for in other groups of this subclass
  • G01V 1/28 - Processing seismic data, e.g. analysis, for interpretation, for correction
  • G01V 1/30 - Analysis

51.

MACHINE LEARNING ASSISTED PARAMETER MATCHING AND PRODUCTION FORECASTING FOR NEW WELLS

      
Application Number US2021064335
Publication Number 2023/121641
Status In Force
Filing Date 2021-12-20
Publication Date 2023-06-29
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Bansal, Yogesh
  • Mijares, Gerardo

Abstract

Systems and methods for machine learning (ML) assisted parameter matching are disclosed. Wellsite data is acquired for one or more existing production wells in a hydrocarbon producing field. The wellsite data is transformed into one or more model data sets for predictive modeling. A first ML model is trained to predict well logs for the existing production well(s), based on the model data set(s). A first well model is generated to estimate production of the existing production well(s) based on the predicted well logs. Parameters of the first well model are tuned based on a comparison between the estimated and an actual production of the existing production well(s). A second ML model is trained to predict parameters of a second well model for a new production well, based on the tuned parameters of the first well model. The new well's production is forecasted using the second ML model.

IPC Classes  ?

  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
  • E21B 41/00 - Equipment or details not covered by groups
  • G06N 20/20 - Ensemble learning

52.

MACHINE LEARNING ASSISTED COMPLETION DESIGN FOR NEW WELLS

      
Application Number 17560982
Status Pending
Filing Date 2021-12-23
First Publication Date 2023-06-29
Owner Landmark Graphics Corporation (USA)
Inventor
  • Bansal, Yogesh
  • Mijares, Gerardo

Abstract

Systems and methods for completion design are disclosed. Wellsite data is acquired for one or more existing production wells. The wellsite data is transformed into model data sets for training a first machine learning (ML) model to predict well logs. A first well model uses the well logs to estimate production of the existing well(s). Parameters of the first well model are tuned based on a comparison between the estimated and actual production of the existing well(s). A second ML model is trained to predict parameters of a second well model for a new well, based on the tuned parameters of the first well model. The new well's production is forecasted using the second ML model. Completion costs for the new well are estimated based on the well's completion design parameters and the forecasted production. Completion design parameters are adjusted, based on the estimated completion costs and the forecasted production.

IPC Classes  ?

  • G06F 30/27 - Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
  • G06F 30/13 - Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
  • E21B 47/00 - Survey of boreholes or wells
  • E21B 49/00 - Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells

53.

RECOMMENDATION ENGINE FOR AUTOMATED SEISMIC PROCESSING

      
Application Number US2021064555
Publication Number 2023/121654
Status In Force
Filing Date 2021-12-21
Publication Date 2023-06-29
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Angelovich, Steven
  • Bhardwaj, Manisha

Abstract

System and methods for automated seismic processing are provided. Historical seismic project data associated with one or more historical seismic projects is obtained from a data store. The historical seismic project data is transformed into seismic workflow model data. At least one seismic workflow model is generated using the seismic workflow model data. Responsive to receiving seismic data for a new seismic project, an optimized workflow for processing the received seismic data is determined based on the at least one generated seismic workflow model. Geophysical parameters for processing the seismic data with the optimized workflow are selected. The seismic data for the new seismic project is processed using the optimized workflow and the selected geophysical parameters.

IPC Classes  ?

  • G01V 1/28 - Processing seismic data, e.g. analysis, for interpretation, for correction
  • G01V 1/24 - Recording seismic data
  • G01V 1/30 - Analysis
  • G01V 1/00 - Seismology; Seismic or acoustic prospecting or detecting

54.

MACHINE LEARNING ASSISTED COMPLETION DESIGN FOR NEW WELLS

      
Application Number US2021065094
Publication Number 2023/121672
Status In Force
Filing Date 2021-12-23
Publication Date 2023-06-29
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Bansal, Yogesh
  • Mijares, Gerardo

Abstract

Systems and methods for completion design are disclosed. Wellsite data is acquired for one or more existing production wells. The wellsite data is transformed into model data sets for training a first machine learning (ML) model to predict well logs. A first well model uses the well logs to estimate production of the existing well(s). Parameters of the first well model are tuned based on a comparison between the estimated and actual production of the existing well(s). A second ML model is trained to predict parameters of a second well model for a new well, based on the tuned parameters of the first well model. The new well's production is forecasted using the second ML model. Completion costs for the new well are estimated based on the well's completion design parameters and the forecasted production. Completion design parameters are adjusted, based on the estimated completion costs and the forecasted production.

IPC Classes  ?

  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
  • E21B 47/008 - Monitoring of down-hole pump systems, e.g. for the detection of "pumped-off" conditions
  • E21B 43/16 - Enhanced recovery methods for obtaining hydrocarbons
  • G06N 20/00 - Machine learning

55.

SEISMIC NAVIGATION DATA QUALITY ANALYSIS

      
Application Number 17553091
Status Pending
Filing Date 2021-12-16
First Publication Date 2023-06-22
Owner Landmark Graphics Corporation (USA)
Inventor
  • Roy, Samiran
  • Srivastav, Shreshth
  • Mandapaka, Bhaskar
  • Priyadarshy, Satyam

Abstract

The disclosure presents processes to select cartographic reference system (CRS) recommendations from a CRS model where the CRS recommendations are matched to received seismic data. A learning mode can be used to build the CRS model where seismic data is matched to CRS. The learning mode can be automated using natural language processing system to parse the meta data for the seismic data, such as the name, area, or code, or label. The CRS model can be updated using an output from a user system, such as when a user manually matches a CRS to seismic data. The matched seismic data to CRS, e.g., seismic data-CRS match, can be used as input to a user system or a computing system, such as a borehole operation system.

IPC Classes  ?

  • G01V 1/30 - Analysis
  • G06N 20/00 - Machine learning
  • E21B 49/00 - Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells

56.

DETERMINING PARAMETERS FOR A WELLBORE OPERATION BASED ON RESONANCE SPEEDS OF DRILLING EQUIPMENT

      
Application Number 17553738
Status Pending
Filing Date 2021-12-16
First Publication Date 2023-06-22
Owner Landmark Graphics Corporation (USA)
Inventor
  • Kumar, Swaminathan Kiran
  • Samuel, Robello

Abstract

Drilling parameters for a wellbore operation can be determined based on resonance speeds. For example, a system can receive real-time data for a drilling operation that is concurrently occurring with receiving the real-time data. The system can determine, for a drilling depth, a rotations-per-minute (RPM) value corresponding to a resonance speed based on a weight-on-bit (WOB) value and the real-time data. The system can generate a plot of the WOB value and the RPM value corresponding to the resonance speed. The system can determine drilling parameters for the drilling operation based on the plot. The drilling parameters can exclude, for the WOB value, the RPM value corresponding to the resonance speed.

IPC Classes  ?

  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
  • E21B 45/00 - Measuring the drilling time or rate of penetration

57.

Recommendation engine for automated seismic processing

      
Application Number 17557287
Grant Number 11782177
Status In Force
Filing Date 2021-12-21
First Publication Date 2023-06-22
Grant Date 2023-10-10
Owner Landmark Graphics Corporation (USA)
Inventor
  • Angelovich, Steven
  • Bhardwaj, Manisha

Abstract

System and methods for automated seismic processing are provided. Historical seismic project data associated with one or more historical seismic projects is obtained from a data store. The historical seismic project data is transformed into seismic workflow model data. At least one seismic workflow model is generated using the seismic workflow model data. Responsive to receiving seismic data for a new seismic project, an optimized workflow for processing the received seismic data is determined based on the at least one generated seismic workflow model. Geophysical parameters for processing the seismic data with the optimized workflow are selected. The seismic data for the new seismic project is processed using the optimized workflow and the selected geophysical parameters.

IPC Classes  ?

  • G01V 1/32 - Transforming one recording into another
  • G01V 1/28 - Processing seismic data, e.g. analysis, for interpretation, for correction
  • G01V 1/30 - Analysis

58.

DETERMINING PARAMETERS FOR A WELLBORE OPERATION BASED ON RESONANCE SPEEDS OF DRILLING EQUIPMENT

      
Application Number US2021063924
Publication Number 2023/113808
Status In Force
Filing Date 2021-12-16
Publication Date 2023-06-22
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Kumar, Swaminathan Kiran
  • Samuel, Robello

Abstract

Drilling parameters for a wellbore operation can be determined based on resonance speeds. For example, a system can receive real-time data for a drilling operation that is concurrently occurring with receiving the real-time data. The system can determine, for a drilling depth, a rotations-per-minute (RPM) value corresponding to a resonance speed based on a weight-on-bit (WOB) value and the real-time data. The system can generate a plot of the WOB value and the RPM value corresponding to the resonance speed. The system can determine drilling parameters for the drilling operation based on the plot. The drilling parameters can exclude, for the WOB value, the RPM value corresponding to the resonance speed.

IPC Classes  ?

  • E21B 47/04 - Measuring depth or liquid level
  • E21B 47/26 - Storing data down-hole, e.g. in a memory or on a record carrier
  • E21B 44/04 - Automatic control of the tool feed in response to the torque of the drive
  • E21B 49/00 - Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells

59.

SEISMIC NAVIGATION DATA QUALITY ANALYSIS

      
Application Number US2021064026
Publication Number 2023/113814
Status In Force
Filing Date 2021-12-17
Publication Date 2023-06-22
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Roy, Samiran
  • Srivastav, Shreshth
  • Mandapaka, Bhaskar
  • Priyadarshy, Satyam

Abstract

The disclosure presents processes to select cartographic reference system (CRS) recommendations from a CRS model where the CRS recommendations are matched to received seismic data. A learning mode can be used to build the CRS model where seismic data is matched to CRS. The learning mode can be automated using natural language processing system to parse the meta data for the seismic data, such as the name, area, or code, or label. The CRS model can be updated using an output from a user system, such as when a user manually matches a CRS to seismic data. The matched seismic data to CRS, e.g., seismic data-CRS match, can be used as input to a user system or a computing system, such as a borehole operation system.

IPC Classes  ?

  • G01V 1/30 - Analysis
  • G01V 1/00 - Seismology; Seismic or acoustic prospecting or detecting
  • G01V 1/28 - Processing seismic data, e.g. analysis, for interpretation, for correction
  • G01V 1/34 - Displaying seismic recordings
  • G06N 20/00 - Machine learning

60.

SCORING A FINAL RISK FOR IDENTIFIED BOREHOLE DESIGN CONCEPTS

      
Application Number 17553219
Status Pending
Filing Date 2021-12-16
First Publication Date 2023-06-22
Owner Landmark Graphics Corporation (USA)
Inventor
  • Parra, Margareth Gibbons
  • Gonzales, Adolfo
  • Chaudhari, Nitish Damodar
  • Tirado, Gabriel

Abstract

The disclosure presents processes for evaluating a borehole design against one or more identified risks. The processes can determine borehole design concepts for the borehole design. Each borehole design concept can have multiple risks assigned, which can be selected from a library of risks, a risk matrix or template, a risk model, or user entered risks. The risks can be scored using one or more statistics-based algorithms, such as a sum, an average, a mean, or other algorithms. The risks can be grouped by a risk level, forming a sub-risk score for each risk level for each borehole design concept. A final risk score can be generated using the sub-risk scores for the borehole design. More than one borehole design can be evaluated using a risk tolerance parameter and the borehole design that satisfies the risk tolerance parameter can be selected as the recommended borehole design.

IPC Classes  ?

  • E21B 41/00 - Equipment or details not covered by groups
  • G06F 30/27 - Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling

61.

MACHINE LEARNING ASSISTED PARAMETER MATCHING AND PRODUCTION FORECASTING FOR NEW WELLS

      
Application Number 17556092
Status Pending
Filing Date 2021-12-20
First Publication Date 2023-06-22
Owner Landmark Graphics Corporation (USA)
Inventor
  • Bansal, Yogesh
  • Mijares, Gerardo

Abstract

Systems and methods for machine learning (ML) assisted parameter matching are disclosed. Wellsite data is acquired for one or more existing production wells in a hydrocarbon producing field. The wellsite data is transformed into one or more model data sets for predictive modeling. A first ML model is trained to predict well logs for the existing production well(s), based on the model data set(s). A first well model is generated to estimate production of the existing production well(s) based on the predicted well logs. Parameters of the first well model are tuned based on a comparison between the estimated and an actual production of the existing production well(s). A second ML model is trained to predict parameters of a second well model for a new production well, based on the tuned parameters of the first well model. The new well’s production is forecasted using the second ML model.

IPC Classes  ?

  • E21B 49/08 - Obtaining fluid samples or testing fluids, in boreholes or wells
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling

62.

SCORING A FINAL RISK FOR IDENTIFIED BOREHOLE DESIGN CONCEPTS

      
Application Number US2021064031
Publication Number 2023/113815
Status In Force
Filing Date 2021-12-17
Publication Date 2023-06-22
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Parra, Margareth Gibbons
  • Gonzales, Adolfo
  • Chaudhari, Nitish Damodar
  • Tirado, Gabriel

Abstract

The disclosure presents processes for evaluating a borehole design against one or more identified risks. The processes can determine borehole design concepts for the borehole design. Each borehole design concept can have multiple risks assigned, which can be selected from a library of risks, a risk matrix or template, a risk model, or user entered risks. The risks can be scored using one or more statistics-based algorithms, such as a sum, an average, a mean, or other algorithms. The risks can be grouped by a risk level, forming a sub-risk score for each risk level for each borehole design concept. A final risk score can be generated using the sub-risk scores for the borehole design. More than one borehole design can be evaluated using a risk tolerance parameter and the borehole design that satisfies the risk tolerance parameter can be selected as the recommended borehole design.

IPC Classes  ?

  • E21B 43/30 - Specific pattern of wells, e.g. optimizing the spacing of wells
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
  • E21B 41/00 - Equipment or details not covered by groups
  • G06N 20/00 - Machine learning

63.

INTEGRATED SURVEILLANCE AND CONTROL

      
Application Number 18106882
Status Pending
Filing Date 2023-02-07
First Publication Date 2023-06-15
Owner Landmark Graphics Corporation (USA)
Inventor
  • Rangarajan, Keshava
  • Winston, Joseph Blake
  • Jain, Anuj
  • Wang, Xi

Abstract

A method of managing oilfield activity with a control system is provided having a plurality of virtual sensors and integrating the virtual sensors into a virtual sensor network. The method includes determining interdependencies among the virtual sensors, obtaining operational information from the virtual sensors, and providing virtual sensor output to the control system based on the determined interdependencies and the operational information.

IPC Classes  ?

  • E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
  • G06N 3/08 - Learning methods
  • G06N 20/00 - Machine learning
  • H04L 67/125 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
  • G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
  • G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric

64.

RANDOM NOISE ATTENUATION FOR SEISMIC DATA

      
Application Number US2021059438
Publication Number 2023/091124
Status In Force
Filing Date 2021-11-16
Publication Date 2023-05-25
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Singh, Satyan
  • Norlund, Philip
  • Sanchez Rodriguez, Adrian
  • Wolfe, Eugene
  • Angelovich, Steven

Abstract

System and methods of random noise attenuation are provided. A first model may be trained to extract random noise from seismic datasets. A second model may be trained to reconstruct leaked signals from the random noise extracted by the first model. A seismic dataset corresponding to a subsurface reservoir formation and including random noise may be obtained. Using the trained first model, at least a portion of the random noise may be extracted from the first seismic dataset. Using the trained second model, a leaked signal, which includes a portion of the seismic dataset, may be reconstructed from the extracted random noise. A cleaned seismic dataset is generated based on the reconstructed leaked signal and the extracted random noise. The cleaned seismic dataset may include a quantity of random noise that is less than that of the original seismic dataset.

IPC Classes  ?

  • G01V 1/36 - Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
  • G01V 1/30 - Analysis

65.

DYNAMIC FILTER FOR SMOOTHING VELOCITY MODEL FOR DOMAIN-CONVERTING SEISMIC DATA

      
Application Number US2021058672
Publication Number 2023/086077
Status In Force
Filing Date 2021-11-09
Publication Date 2023-05-19
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor Fink, William

Abstract

A system can be provided for applying a dynamic filter to a velocity model for converting the domain of seismic data. The system can receive a velocity model for a geological area of interest. The system can apply a dynamic filter to the velocity model for smoothing an anomaly included in the velocity model. The system can apply the velocity model with the smoothed anomaly to seismic data associated with the geological area of interest for converting the domain of the seismic data.

IPC Classes  ?

  • G01V 1/30 - Analysis
  • G01V 1/36 - Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
  • E21B 47/26 - Storing data down-hole, e.g. in a memory or on a record carrier

66.

RANDOM NOISE ATTENUATION FOR SEISMIC DATA

      
Application Number 17527245
Status Pending
Filing Date 2021-11-16
First Publication Date 2023-05-18
Owner Landmark Graphics Corporation (USA)
Inventor
  • Singh, Satyan
  • Norlund, Philip
  • Sanchez Rodriguez, Adrian
  • Wolfe, Eugene
  • Angelovich, Steven

Abstract

System and methods of random noise attenuation are provided. A first model may be trained to extract random noise from seismic datasets. A second model may be trained to reconstruct leaked signals from the random noise extracted by the first model. A seismic dataset corresponding to a subsurface reservoir formation and including random noise may be obtained. Using the trained first model, at least a portion of the random noise may be extracted from the first seismic dataset. Using the trained second model, a leaked signal, which includes a portion of the seismic dataset, may be reconstructed from the extracted random noise. A cleaned seismic dataset is generated based on the reconstructed leaked signal and the extracted random noise. The cleaned seismic dataset may include a quantity of random noise that is less than that of the original seismic dataset.

IPC Classes  ?

  • G01V 1/36 - Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
  • G01V 1/28 - Processing seismic data, e.g. analysis, for interpretation, for correction

67.

Dynamic filter for smoothing velocity model for domain-converting seismic data

      
Application Number 17522839
Grant Number 11940581
Status In Force
Filing Date 2021-11-09
First Publication Date 2023-05-11
Grant Date 2024-03-26
Owner Landmark Graphics Corporation (USA)
Inventor Fink, William

Abstract

A system can be provided for applying a dynamic filter to a velocity model for converting the domain of seismic data. The system can receive a velocity model for a geological area of interest. The system can apply a dynamic filter to the velocity model for smoothing an anomaly included in the velocity model. The system can apply the velocity model with the smoothed anomaly to seismic data associated with the geological area of interest for converting the domain of the seismic data.

IPC Classes  ?

  • G01V 1/32 - Transforming one recording into another
  • G01V 1/28 - Processing seismic data, e.g. analysis, for interpretation, for correction
  • G01V 1/30 - Analysis

68.

DETERMINING FAULT SURFACES FROM FAULT ATTRIBUTE VOLUMES

      
Application Number US2021055607
Publication Number 2023/069080
Status In Force
Filing Date 2021-10-19
Publication Date 2023-04-27
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Nguyen, Xuan Nam
  • Jaramillo, Alejandro

Abstract

Hydrocarbon exploration and extraction can be facilitated by determining fault surfaces from fault attribute volumes. For example, a system described herein can receive a fault attribute volume for faults in a subterranean formation determined using seismic data. The fault attribute volume may include multiple traces with trace locations. The system can determine a set of fault samples for each trace location. Each fault sample can include fault attributes such as a depth value, an amplitude value, and a vertical thickness value. The system can determine additional fault attributes such as a dip value and an azimuth value for each fault sample of each trace location. The system can determine fault surfaces for the faults using the fault samples and fault attributes. The system can then output the fault surfaces for use in a hydrocarbon extraction operation.

IPC Classes  ?

  • G01V 1/30 - Analysis
  • G01V 1/36 - Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
  • G01V 1/40 - Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging

69.

Determining fault surfaces from fault attribute volumes

      
Application Number 17505033
Grant Number 11965997
Status In Force
Filing Date 2021-10-19
First Publication Date 2023-04-20
Grant Date 2024-04-23
Owner Landmark Graphics Corporation (USA)
Inventor
  • Nguyen, Xuan Nam
  • Jaramillo, Alejandro

Abstract

Hydrocarbon exploration and extraction can be facilitated by determining fault surfaces from fault attribute volumes. For example, a system described herein can receive a fault attribute volume for faults in a subterranean formation determined using seismic data. The fault attribute volume may include multiple traces with trace locations. The system can determine a set of fault samples for each trace location. Each fault sample can include fault attributes such as a depth value, an amplitude value, and a vertical thickness value. The system can determine additional fault attributes such as a dip value and an azimuth value for each fault sample of each trace location. The system can determine fault surfaces for the faults using the fault samples and fault attributes. The system can then output the fault surfaces for use in a hydrocarbon extraction operation.

IPC Classes  ?

70.

TECHNIQUES FOR EXTRACTION OF VECTORIZED CONTENT OF AN OIL AND GAS PLAY WITHIN AN UNSTRUCTURED FILE

      
Application Number 17047272
Status Pending
Filing Date 2020-01-14
First Publication Date 2023-04-20
Owner Landmark Graphics Corporation (USA)
Inventor
  • Fletcher, Ian A.
  • Slidel, Daniel James David
  • Ivko, Benjamin Patrick

Abstract

A method includes retrieving an unstructured document and defining an area of interest of the unstructured document that visually represents geological formation information. The method also includes extracting a set of vectorized polygons from the area of interest. Additionally, the method includes assigning properties from the unstructured document to each of the vectorized polygons in the set of vectorized polygons. Further, the method includes assigning a coordinate reference frame to the set of vectorized polygons and generating a user-interactive document from the set of vectorized polygons.

IPC Classes  ?

  • G06F 40/166 - Editing, e.g. inserting or deleting
  • G06V 30/422 - Technical drawings; Geographical maps
  • G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
  • G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
  • G06F 16/93 - Document management systems
  • G06F 40/151 - Transformation

71.

Determining characteristics of fluid loss in a wellbore

      
Application Number 17497155
Grant Number 11629562
Status In Force
Filing Date 2021-10-08
First Publication Date 2023-04-13
Grant Date 2023-04-18
Owner Landmark Graphics Corporation (USA)
Inventor
  • Samuel, Robello
  • Adari, Rishi

Abstract

A system can provide for determining characteristics loss in a wellbore. The system can include a processor and a non-transitory memory with instructions that are executable by the processor for causing the processor to execute operations. The operations can include receiving, from sensors in a wellbore, data corresponding to loss indicators. The operations can include determining a loss probability for each loss indicator. The operations can include determining a total loss probability of fluid loss in the wellbore based on the loss probabilities. The operations can include outputting the total loss probability to be used in a drilling operation in the wellbore.

IPC Classes  ?

  • E21B 21/08 - Controlling or monitoring pressure or flow of drilling fluid, e.g. automatic filling of boreholes, automatic control of bottom pressure
  • E21B 21/00 - Methods or apparatus for flushing boreholes, e.g. by use of exhaust air from motor
  • E21B 47/117 - Detecting leaks, e.g. from tubing, by pressure testing
  • E21B 43/26 - Methods for stimulating production by forming crevices or fractures

72.

Active reinforcement learning for drilling optimization and automation

      
Application Number 17047109
Grant Number 11982171
Status In Force
Filing Date 2020-06-05
First Publication Date 2023-04-13
Grant Date 2024-05-14
Owner Landmark Graphics Corporation (USA)
Inventor
  • Saidutta, Yashas Malur
  • Pandya, Raja Vikram R
  • Madasu, Srinath
  • Dande, Shashi
  • Rangarajan, Keshava

Abstract

Systems and methods for automated drilling control and optimization are disclosed. Training data, including values of drilling parameters, for a current stage of a drilling operation are acquired. A reinforcement learning model is trained to estimate values of the drilling parameters for a subsequent stage of the drilling operation to be performed, based on the acquired training data and a reward policy mapping inputs and outputs of the model. The subsequent stage of the drilling operation is performed based on the values of the drilling parameters estimated using the trained model. A difference between the estimated and actual values of the drilling parameters is calculated, based on real-time data acquired during the subsequent stage of the drilling operation. The reinforcement learning model is retrained to refine the reward policy, based on the calculated difference. At least one additional stage of the drilling operation is performed using the retrained model.

IPC Classes  ?

  • E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
  • G06N 3/092 - Reinforcement learning

73.

DETERMINING CHARACTERISTICS OF FLUID LOSS IN A WELLBORE

      
Application Number US2021057085
Publication Number 2023/059345
Status In Force
Filing Date 2021-10-28
Publication Date 2023-04-13
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Samuel, Robello
  • Adari, Rishi

Abstract

A system can provide for determining characteristics loss in a wellbore. The system can include a processor and a non-transitory memory with instructions that are executable by the processor for causing the processor to execute operations. The operations can include receiving, from sensors in a wellbore, data corresponding to loss indicators. The operations can include determining a loss probability for each loss indicator. The operations can include determining a total loss probability of fluid loss in the wellbore based on the loss probabilities. The operations can include outputting the total loss probability to be used in a drilling operation in the wellbore.

IPC Classes  ?

  • E21B 47/10 - Locating fluid leaks, intrusions or movements
  • E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
  • E21B 43/26 - Methods for stimulating production by forming crevices or fractures
  • E21B 47/06 - Measuring temperature or pressure

74.

COMBINED SOFT AND STIFF-STRING TORQUE AND DRAG MODEL

      
Application Number 17054432
Status Pending
Filing Date 2020-01-02
First Publication Date 2023-03-30
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Samuel, Robello
  • Zhang, Yuan

Abstract

Aspects of the disclosed technology provide techniques for determining frictional forces bearing on a downhole drill string. In some implementations, a method of the disclosed technology can include steps for segmenting a plurality of continuous nodes of the drilling string into a first segment and a second segment, computing a first set of values corresponding with one or more nodes in the first segment using a first model, computing a second set of values corresponding with one or more nodes in the second segment using a second model, and determining a torque of the drill string based on the first set of values and the second set of values. In some aspects, the method can further include steps for determining a drag force on the drill string based on the first set of values and the second set of values. Systems and machine-readable media are also provided.

IPC Classes  ?

  • E21B 47/007 - Measuring stresses in a pipe string or casing
  • E21B 44/04 - Automatic control of the tool feed in response to the torque of the drive
  • E21B 7/06 - Deflecting the direction of boreholes

75.

Diffusion flux inclusion for a reservoir simulation for hydrocarbon recovery

      
Application Number 18070227
Grant Number 11775708
Status In Force
Filing Date 2022-11-28
First Publication Date 2023-03-30
Grant Date 2023-10-03
Owner Landmark Graphics Corporation (USA)
Inventor
  • Mohebbinia, Saeedeh
  • Wong, Terry Wayne

Abstract

A method includes selecting a model for a simulation of hydrocarbon recovery from a reservoir having a plurality of fractures during injection of an injected gas into the plurality of fractures. Selecting the model includes determining a flux ratio of a convection rate to a diffusion rate for the reservoir, determining whether the flux ratio is less than a threshold, and in response to the flux ratio being less than the threshold, selecting the model that includes diffusion. Selecting the model includes performing the simulation of the hydrocarbon recovery from the reservoir based on the model.

IPC Classes  ?

  • G06F 30/20 - Design optimisation, verification or simulation
  • E21B 49/00 - Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
  • G06F 9/455 - Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
  • E21B 43/16 - Enhanced recovery methods for obtaining hydrocarbons
  • E21B 41/00 - Equipment or details not covered by groups
  • G06F 111/10 - Numerical modelling
  • E21B 43/26 - Methods for stimulating production by forming crevices or fractures

76.

Physical parameter projection for wellbore drilling

      
Application Number 17054629
Grant Number 12018555
Status In Force
Filing Date 2020-03-26
First Publication Date 2023-03-30
Grant Date 2024-06-25
Owner Landmark Graphics Corporation (USA)
Inventor
  • Wesley, Avinash
  • Samuel, Robello
  • Mittal, Manish K.

Abstract

Aspects and features of this disclosure relate to projecting physical drilling parameters to control a drilling operation. A computing system applies Bayesian optimization to a model incorporating the input data using varying values for an adverse drilling factor to produce a target function. The computing system determines a minimum value for the target function. The computing system provides a projected value for the physical drilling parameters based on the minimum value. The computing system generates an alert responsive to determining that the projected value for the physical drilling parameters exceeds a prescribed limit.

IPC Classes  ?

  • E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
  • E21B 47/007 - Measuring stresses in a pipe string or casing
  • G06F 30/20 - Design optimisation, verification or simulation

77.

FORMATION EVALUATION BASED ON SEISMIC HORIZON MAPPING WITH MULTI-SCALE OPTIMIZATION

      
Application Number US2021071473
Publication Number 2023/043476
Status In Force
Filing Date 2021-09-15
Publication Date 2023-03-23
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Possee, Daniel James
  • Liu, Yikuo
  • Baines, Graham

Abstract

A least one seismic attribute is determined for each voxel of the seismic volume. A first horizon is selected for mapping and a sparse global grid is generated which includes the horizon, at least one constraint point identifying the horizon, and a number of points having a depth in the seismic volume. A value of at least one seismic attribute is determined for each point and their depths are adjusted based on the value of the seismic attribute. A map of the horizon can be generated based on the adjusted depths. Multiple local grids can be generated based on the sparse global grid, and the depths of the local grid points adjusted to generate a map of the horizon at voxel level resolution. The seismic volume can be mapped into multiple horizons, where previously mapped horizons can function as constraints on the sparse global grid.

IPC Classes  ?

  • G01V 1/30 - Analysis
  • G01V 1/36 - Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy

78.

Formation evaluation based on seismic horizon mapping with multi-scale optimization

      
Application Number 17447604
Grant Number 11630226
Status In Force
Filing Date 2021-09-14
First Publication Date 2023-03-16
Grant Date 2023-04-18
Owner Landmark Graphics Corporation (USA)
Inventor
  • Possee, Daniel James
  • Liu, Yikuo
  • Baines, Graham

Abstract

A least one seismic attribute is determined for each voxel of the seismic volume. A first horizon is selected for mapping and a sparse global grid is generated which includes the horizon, at least one constraint point identifying the horizon, and a number of points having a depth in the seismic volume. A value of at least one seismic attribute is determined for each point and their depths are adjusted based on the value of the seismic attribute. A map of the horizon can be generated based on the adjusted depths. Multiple local grids can be generated based on the sparse global grid, and the depths of the local grid points adjusted to generate a map of the horizon at voxel level resolution. The seismic volume can be mapped into multiple horizons, where previously mapped horizons can function as constraints on the sparse global grid.

IPC Classes  ?

  • G01V 1/34 - Displaying seismic recordings
  • G01V 1/28 - Processing seismic data, e.g. analysis, for interpretation, for correction

79.

CONTEXTUALIZATION OF GEOSCIENTIFIC DATA USING GEOLOGICAL AGE FRAMEWORK

      
Application Number US2021049756
Publication Number 2023/038627
Status In Force
Filing Date 2021-09-10
Publication Date 2023-03-16
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Booker, Matthew
  • Carroll, Gareth
  • Wright, Georgina

Abstract

The disclosure presents processes to improve the ability to analyze geological information for an area or region of interest. A user can specify one or more input files, such as from public, private, or proprietary sources. The user can specify a geological or geographic framework to utilize. The process can then perform a matching between the data in the input files and the data in the framework. The matching process can utilize a geological matching using a specified range of depths or a geographical matching followed by the geological matching. Other parameters can be utilized such as a radius to define an area of interest around a central location of interest. Matched data elements can have geological attributes from the geological framework data linked to data elements in the input files. The input files can be downloaded, displayed, printed, or communicated to another computing system or program for further analysis

IPC Classes  ?

  • E21B 49/00 - Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
  • E21B 41/00 - Equipment or details not covered by groups
  • G01V 1/46 - Data acquisition
  • G01V 1/50 - Analysing data

80.

CONTEXTUALIZATION OF GEOSCIENTIFIC DATA USING GEOLOGICAL AGE FRAMEWORK

      
Application Number 17470758
Status Pending
Filing Date 2021-09-09
First Publication Date 2023-03-09
Owner Landmark Graphics Corporation (USA)
Inventor
  • Booker, Matthew
  • Carroll, Gareth
  • Wright, Georgina

Abstract

The disclosure presents processes to improve the ability to analyze geological information for an area or region of interest. A user can specify one or more input files, such as from public, private, or proprietary sources. The user can specify a geological or geographic framework to utilize. The process can then perform a matching between the data in the input files and the data in the framework. The matching process can utilize a geological matching using a specified range of depths or a geographical matching followed by the geological matching. Other parameters can be utilized such as a radius to define an area of interest around a central location of interest. Matched data elements can have geological attributes from the geological framework data linked to data elements in the input files. The input files can be downloaded, displayed, printed, or communicated to another computing system or program for further analysis.

IPC Classes  ?

81.

DETERMINING PARAMETERS FOR A WELLBORE PLUG AND ABANDONMENT OPERATION

      
Application Number US2021048271
Publication Number 2023/033788
Status In Force
Filing Date 2021-08-30
Publication Date 2023-03-09
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Samuel, Robello
  • Samec, William Wade
  • Hebert, Roddy
  • Gales, Robert H.
  • Eyuboglu, Abbas Sami

Abstract

A location of a cut and an amount of force to be used in a pull operation for a plug & abandonment (P&A) operation can be determined. Measurements of at least one characteristic of fluids and solids disposed in an annulus defined between a casing and a wall of a wellbore can be received. A total fluid and solid friction force drag can be determined using hydrostatic force that is determined from the measurements. A mechanical friction force drag can be determined based on a weight of the casing. The mechanical friction force drag and the total fluid and solid friction force drag can be used to determine a friction factor. The friction factor can be used to determine a depth location at which to cut the casing and a pull force for pulling the casing from the wellbore in the P&A operation.

IPC Classes  ?

  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
  • E21B 47/04 - Measuring depth or liquid level
  • E21B 44/04 - Automatic control of the tool feed in response to the torque of the drive

82.

MACHINE LEARNING MODEL SELECTION BASED ON FEATURE MERGING FOR A SPATIAL LOCATION ACROSS MULTIPLE TIME WINDOWS

      
Application Number US2021071335
Publication Number 2023/033857
Status In Force
Filing Date 2021-09-01
Publication Date 2023-03-09
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor Zhang, Jiazuo

Abstract

A method comprises receiving a current dataset for a current time window from at least one sensor in a wellbore created in a subsurface formation, wherein the current dataset comprises values of a number of current features of the subsurface formation at a spatial location in the wellbore. The method includes selecting at least one previous time window from a number of previous time windows that includes a previously cached dataset that was detected by the at least one sensor or a different sensor in the wellbore and that spatially overlaps with the spatial location for the current dataset. The method includes merging the current dataset with the previously cached dataset to create a merged dataset. The method includes selecting a machine learning model from a plurality of machine learning models for the spatial location in the wellbore based on the merged dataset.

IPC Classes  ?

  • G06N 20/20 - Ensemble learning
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling

83.

MACHINE LEARNING MODEL SELECTION BASED ON FEATURE MERGING FOR A SPATIAL LOCATION ACROSS MULTIPLE TIME WINDOWS

      
Application Number 17446537
Status Pending
Filing Date 2021-08-31
First Publication Date 2023-03-02
Owner Landmark Graphics Corporation (USA)
Inventor Zhang, Jiazuo

Abstract

A method comprises receiving a current dataset for a current time window from at least one sensor in a wellbore created in a subsurface formation, wherein the current dataset comprises values of a number of current features of the subsurface formation at a spatial location in the wellbore. The method includes selecting at least one previous time window from a number of previous time windows that includes a previously cached dataset that was detected by the at least one sensor or a different sensor in the wellbore and that spatially overlaps with the spatial location for the current dataset. The method includes merging the current dataset with the previously cached dataset to create a merged dataset. The method includes selecting a machine learning model from a plurality of machine learning models for the spatial location in the wellbore based on the merged dataset.

IPC Classes  ?

  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06N 20/00 - Machine learning

84.

Determining parameters for a wellbore plug and abandonment operation

      
Application Number 17461294
Grant Number 11761298
Status In Force
Filing Date 2021-08-30
First Publication Date 2023-03-02
Grant Date 2023-09-19
Owner Landmark Graphics Corporation (USA)
Inventor
  • Samuel, Robello
  • Samec, William Wade
  • Hebert, Roddy
  • Gales, Robert H.
  • Eyuboglu, Abbas Sami

Abstract

A location of a cut and an amount of force to be used in a pull operation for a plug & abandonment (P&A) operation can be determined. Measurements of at least one characteristic of fluids and solids disposed in an annulus defined between a casing and a wall of a wellbore can be received. A total fluid and solid friction force drag can be determined using hydrostatic force that is determined from the measurements. A mechanical friction force drag can be determined based on a weight of the casing. The mechanical friction force drag and the total fluid and solid friction force drag can be used to determine a friction factor. The friction factor can be used to determine a depth location at which to cut the casing and a pull force for pulling the casing from the wellbore in the P&A operation.

IPC Classes  ?

  • E21B 29/00 - Cutting or destroying pipes, packers, plugs, or wire lines, located in boreholes or wells, e.g. cutting of damaged pipes, of windows; Deforming of pipes in boreholes or wells; Reconditioning of well casings while in the ground
  • E21B 47/09 - Locating or determining the position of objects in boreholes or wells; Identifying the free or blocked portions of pipes
  • E21B 33/14 - Methods or devices for cementing, for plugging holes, crevices, or the like for cementing casings into boreholes
  • E21B 33/134 - Bridging plugs

85.

WELL CONSTRUCTION OPTIMIZATION TECHNIQUES

      
Application Number 17404446
Status Pending
Filing Date 2021-08-17
First Publication Date 2023-02-23
Owner Landmark Graphics Corporation (USA)
Inventor
  • Braz, Paulo Alves
  • Marin Martinez, Roger David
  • Tirado, Gabriel
  • De Souza, Marcelo Gomes
  • Martinez, Damian
  • Araujo, Henrique De Azevedo
  • Fattori, Cristian

Abstract

A method includes acquiring historical well construction data associated with a set of historical wells. The method also includes developing a well construction model using the corpus of historical well construction data. Additionally, the method includes acquiring real-time well construction data during a well construction operation and applying the well construction model to the real-time well construction data to identify changes to a well construction parameter. Further, the method includes outputting a command to update the well construction operation using the changes to the well construction parameter.

IPC Classes  ?

  • E21B 44/00 - Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
  • G06Q 10/06 - Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

86.

CALIBRATION OF DRILLSTRING WEIGHT WITH DRAG FOR FRICTION FACTOR ESTIMATION

      
Application Number 17445582
Status Pending
Filing Date 2021-08-20
First Publication Date 2023-02-23
Owner Landmark Graphics Corporation (USA)
Inventor Samuel, Robello

Abstract

A method comprises determining a value of at least one oppositional force for a drillstring at multiple depths in the wellbore, determining a value of a drag force for the drillstring at the multiple depths, determining a value of hook load for the drillstring at the multiple depths based on the value of the at least one opposition force and the value of the drag force at the multiple depths, and determining a calibrated drillstring weight based on a change in the value of the hook load over the multiple depths. From the calibrated drillstring weight, an adjusted estimated hook load can be determined. The drag force can be calculated based on a drag per centralizer and the number of centralizers in the wellbore. A centralizer friction factor can be determined and used to calibrate the value of the drag per centralizer.

IPC Classes  ?

  • E21B 47/007 - Measuring stresses in a pipe string or casing
  • G01N 19/02 - Measuring coefficient of friction between materials
  • E21B 12/00 - Accessories for drilling tools

87.

CALIBRATION OF DRILLSTRING WEIGHT FOR FRICTION FACTOR ESTIMATION

      
Application Number US2021071257
Publication Number 2023/022746
Status In Force
Filing Date 2021-08-23
Publication Date 2023-02-23
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor Samuel, Robello

Abstract

A method comprises determining a value of at least one oppositional force for a drillstring at multiple depths in the wellbore, determining a value of hook load for the drillstring at the multiple depths based on the value of the at least one opposition force at the multiple depths, and determining a calibrated drillstring weight based on a change in the value of the hook load over the multiple depths of the wellbore. The change in the value of the hook load can be determined based on a change in a measured hook load and/or a change in an estimated hook load. From the calibrated drillstring weight, an adjusted estimated hook load can be determined.

IPC Classes  ?

  • E21B 47/04 - Measuring depth or liquid level
  • E21B 44/02 - Automatic control of the tool feed
  • E21B 41/00 - Equipment or details not covered by groups

88.

CALIBRATION OF DRILLSTRING WEIGHT FOR FRICTION FACTOR ESTIMATION

      
Application Number 17445578
Status Pending
Filing Date 2021-08-20
First Publication Date 2023-02-23
Owner Landmark Graphics Corporation (USA)
Inventor Samuel, Robello

Abstract

A method comprises determining a value of at least one oppositional force for a drillstring at multiple depths in the wellbore, determining a value of hook load for the drillstring at the multiple depths based on the value of the at least one opposition force at the multiple depths, and determining a calibrated drillstring weight based on a change in the value of the hook load over the multiple depths of the wellbore. The change in the value of the hook load can be determined based on a change in a measured hook load and/or a change in an estimated hook load. From the calibrated drillstring weight, an adjusted estimated hook load can be determined.

IPC Classes  ?

  • E21B 47/007 - Measuring stresses in a pipe string or casing
  • G01N 19/02 - Measuring coefficient of friction between materials
  • E21B 12/00 - Accessories for drilling tools

89.

WELL CONSTRUCTION OPTIMIZATION TECHNIQUES

      
Application Number US2021046880
Publication Number 2023/022730
Status In Force
Filing Date 2021-08-20
Publication Date 2023-02-23
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Braz, Paulo Alves
  • Marin Martinez, Roger David
  • Tirado, Gabriel
  • De Souza, Marcelo Gomes
  • Martinez, Damian
  • Araujo, Henrique De Azevedo
  • Fattori, Cristian

Abstract

A method includes acquiring historical well construction data associated with a set of historical wells. The method also includes developing a well construction model using the corpus of historical well construction data. Additionally, the method includes acquiring real-time well construction data during a well construction operation and applying the well construction model to the real-time well construction data to identify changes to a well construction parameter. Further, the method includes outputting a command to update the well construction operation using the changes to the well construction parameter.

IPC Classes  ?

  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
  • G01V 1/40 - Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging

90.

CALIBRATION OF DRILLSTRING WEIGHT WITH DRAG FOR FRICTION FACTOR ESTIMATION

      
Application Number US2021071258
Publication Number 2023/022747
Status In Force
Filing Date 2021-08-23
Publication Date 2023-02-23
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor Samuel, Robello

Abstract

A method comprises determining a value of at least one oppositional force for a drillstring at multiple depths in the wellbore, determining a value of a drag force for the drillstring at the multiple depths, determining a value of hook load for the drillstring at the multiple depths based on the value of the at least one opposition force and the value of the drag force at the multiple depths, and determining a calibrated drillstring weight based on a change in the value of the hook load over the multiple depths. From the calibrated drillstring weight, an adjusted estimated hook load can be determined. The drag force can be calculated based on a drag per centralizer and the number of centralizers in the wellbore. A centralizer friction factor can be determined and used to calibrate the value of the drag per centralizer.

IPC Classes  ?

  • E21B 47/10 - Locating fluid leaks, intrusions or movements
  • E21B 44/02 - Automatic control of the tool feed

91.

Multiple swivels and rotation motor system

      
Application Number 17388869
Grant Number 12006777
Status In Force
Filing Date 2021-07-29
First Publication Date 2023-02-02
Grant Date 2024-06-11
Owner Landmark Graphics Corporation (USA)
Inventor
  • Zhang, Yuan
  • Samuel, Robello

Abstract

The disclosure presents apparatuses and systems to reduce drag and friction forces on a drill string located downhole a borehole. The drill string can have two or more movement isolators to allow a movement sensitive tool to be movement isolated from other portions of the drill string that have powered movement. The other drill string portions can be powered by a surface equipment or by a downhole movement motor attached to the drill string, such as a rotational mud motor, an agitator, a jar motor, or a rotary steerable. Portions of the drill string located further downhole than the movement sensitive tool can utilize a movement motor attached to the drill string to provide movement to reduce drag and friction force where the movement isolators can reduce the movement force experienced by the movement sensitive tool.

IPC Classes  ?

  • E21B 17/05 - Swivel joints
  • E21B 4/16 - Plural down-hole drives, e.g. for combined percussion and rotary drilling; Drives for multi-bit drilling units

92.

MULTIPLE SWIVELS AND ROTATION MOTOR SYSTEM

      
Application Number US2021043825
Publication Number 2023/009131
Status In Force
Filing Date 2021-07-30
Publication Date 2023-02-02
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Zhang, Yuan
  • Samuel, Robello

Abstract

The disclosure presents apparatuses and systems to reduce drag and friction forces on a drill string located downhole a borehole. The drill string can have two or more movement isolators to allow a movement sensitive tool to be movement isolated from other portions of the drill string that have powered movement. The other drill string portions can be powered by a surface equipment or by a downhole movement motor attached to the drill string, such as a rotational mud motor, an agitator, a jar motor, or a rotary steerable. Portions of the drill string located further downhole than the movement sensitive tool can utilize a movement motor attached to the drill string to provide movement to reduce drag and friction force where the movement isolators can reduce the movement force experienced by the movement sensitive tool.

IPC Classes  ?

93.

SUPERVISED MACHINE LEARNING-BASED WELLBORE CORRELATION

      
Application Number 17305861
Status Pending
Filing Date 2021-07-15
First Publication Date 2023-01-19
Owner Landmark Graphics Corporation (USA)
Inventor
  • Servais, Marc Paul
  • Baines, Graham

Abstract

A method for performing wellbore correlation across multiple wellbores includes predicting a depth alignment across the wellbores based on a geological feature of the wellbores. Predicting a depth alignment includes selecting a reference wellbore, defining a control point in a reference signal of a reference well log for the reference wellbore, and generating an input tile from the reference signal, the control points, and a number of non-reference well logs corresponding to non-reference wellbores. The well logs include changes in a geological feature over a depth of a wellbore. The input tile is input into a machine-learning model to output a corresponding control point for each non-reference well log. The corresponding control point corresponds to the control point of the reference log. Based on the corresponding control points output from the machine-learning model, the non-reference well logs are aligned with the reference well log to correlate the multiple wellbores.

IPC Classes  ?

  • E21B 47/04 - Measuring depth or liquid level
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
  • G06N 3/08 - Learning methods

94.

SUPERVISED MACHINE LEARNING-BASED WELLBORE CORRELATION

      
Application Number US2021070891
Publication Number 2023/287454
Status In Force
Filing Date 2021-07-16
Publication Date 2023-01-19
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Servais, Marc Paul
  • Baines, Graham

Abstract

A method for performing wellbore correlation across multiple wellbores includes predicting a depth alignment across the wellbores based on a geological feature of the wellbores. Predicting a depth alignment includes selecting a reference wellbore, defining a control point in a reference signal of a reference well log for the reference wellbore, and generating an input tile from the reference signal, the control points, and a number of non-reference well logs corresponding to non-reference wellbores. The well logs include changes in a geological feature over a depth of a wellbore. The input tile is input into a machine-learning model to output a corresponding control point for each non-reference well log. The corresponding control point corresponds to the control point of the reference log. Based on the corresponding control points output from the machine-learning model, the non-reference well logs are aligned with the reference well log to correlate the multiple wellbores.

IPC Classes  ?

  • E21B 41/00 - Equipment or details not covered by groups
  • E21B 47/04 - Measuring depth or liquid level
  • E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
  • G06N 20/00 - Machine learning

95.

CASING WEAR AND PIPE DEFECT DETERMINATION USING DIGITAL IMAGES

      
Application Number US2021039482
Publication Number 2023/277868
Status In Force
Filing Date 2021-06-29
Publication Date 2023-01-05
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Samuel, Robello
  • Adari, Rishi

Abstract

The disclosure presents solutions for determining a casing wear parameter. Image collecting or capturing devices can be used to capture visual frames of a section of drilling pipe during a trip out operation. The visual frames can be oriented to how the drilling pipe was oriented within the borehole during a drilling operation. The visual frames can be analyzed for wear, e.g., surface changes, of the drilling pipe. The surface changes can be classified as to the type, depth, volume, length, shape, and other characteristics. The section of drilling pipe can be correlated to a depth range where the drilling pipe was located during drilling operations. The surface changes, with the depth range, can be correlated to an estimated casing wear to generate the casing wear parameter. An analysis of multiple sections of drilling pipe can be used to improve the locating of sections of casing where wear is likely.

IPC Classes  ?

96.

MACHINE LEARNING BASED RANKING OF HYDROCARBON PROSPECTS FOR FIELD EXPLORATION

      
Application Number US2021039792
Publication Number 2023/277894
Status In Force
Filing Date 2021-06-30
Publication Date 2023-01-05
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Roy, Samiran
  • Chaki, Soumi

Abstract

An ensemble of machine learning models is trained to evaluate seismic and risk -related data in order to evaluate, value, or otherwise rank various prospective hydrocarbon reservoir ("prospects") of a field. A classification machine learning model is trained to classify a prospect or region of a prospect based on the exploration risk level. From the seismic data, a frequency-filtered volume (FFV) for each prospect is calculated, where the FFV is a measure of reservoir volume which takes into account seismic resolution limits. Based on the risk classification and FFV, prospects of the field are ranked based on their economic value which is a combination of the risk associated with drilling and their potential reservoir volume.

IPC Classes  ?

97.

CALCULATING PULL FOR A STUCK DRILL STRING

      
Application Number US2021039494
Publication Number 2023/277873
Status In Force
Filing Date 2021-06-29
Publication Date 2023-01-05
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Samuel, Robello
  • Adari, Rishi

Abstract

The disclosure presents processes and methods for determining an overpull force for a stuck drill string in a borehole system. The fluid composition of a mud in the borehole at a specified depth can be broken down into a percentage of liquid and percentage of solids, as well as adjusting for material sag and settling factors. The fluid composition can be utilized to identify friction factors and drag in respective fluid composition zones. Each friction factor and drag can be summed to determine a total fluid drag on the drill string. In some aspects, the total fluid drag can be adjusted utilizing the relative positioning of casing collars and tool joints. The total fluid drag can be summed with the other force factors, such as a shear force and mechanical drag. The total drag can then be utilized as the overpull force applied to the stuck drill string.

IPC Classes  ?

  • E21B 44/04 - Automatic control of the tool feed in response to the torque of the drive
  • E21B 47/18 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling using acoustic waves through the well fluid
  • E21B 47/007 - Measuring stresses in a pipe string or casing
  • E21B 47/04 - Measuring depth or liquid level

98.

RESERVOIR SIMULATION UTILIZING HYBRID COMPUTING

      
Application Number US2021039978
Publication Number 2023/277915
Status In Force
Filing Date 2021-06-30
Publication Date 2023-01-05
Owner LANDMARK GRAPHICS CORPORATION (USA)
Inventor
  • Wang, Qinghua
  • Erdogan, Hanife Meftun
  • Li, Dong

Abstract

Hybrid computing that utilizes a computer processor coupled to one or more graphical processing units (GPUs) is configured to perform computations that generate outputs related to reservoir simulations associated with formations that may include natural gas and oil reservoirs.

IPC Classes  ?

  • G06F 30/20 - Design optimisation, verification or simulation
  • G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
  • G06F 9/38 - Concurrent instruction execution, e.g. pipeline, look ahead

99.

RESERVOIR SIMULATION UTILIZING HYBRID COMPUTING

      
Application Number 17305041
Status Pending
Filing Date 2021-06-29
First Publication Date 2022-12-29
Owner Landmark Graphics Corporation (USA)
Inventor
  • Wang, Qinghua
  • Erdogan, Hanife Meftun
  • Li, Dong

Abstract

Hybrid computing that utilizes a computer processor coupled to one or more graphical processing units (GPUs) is configured to perform computations that generate outputs related to reservoir simulations associated with formations that may include natural gas and oil reservoirs.

IPC Classes  ?

  • G06F 30/20 - Design optimisation, verification or simulation
  • G01V 99/00 - Subject matter not provided for in other groups of this subclass

100.

MACHINE LEARNING BASED RANKING OF HYDROCARBON PROSPECTS FOR FIELD EXPLORATION

      
Application Number 17304970
Status Pending
Filing Date 2021-06-29
First Publication Date 2022-12-29
Owner Landmark Graphics Corporation (USA)
Inventor
  • Roy, Samiran
  • Chaki, Soumi

Abstract

An ensemble of machine learning models is trained to evaluate seismic and risk-related data in order to evaluate, value, or otherwise rank various prospective hydrocarbon reservoir (“prospects”) of a field. A classification machine learning model is trained to classify a prospect or region of a prospect based on the exploration risk level. From the seismic data, a frequency-filtered volume (FFV) for each prospect is calculated, where the FFV is a measure of reservoir volume which takes into account seismic resolution limits. Based on the risk classification and FFV, prospects of the field are ranked based on their economic value which is a combination of the risk associated with drilling and their potential reservoir volume.

IPC Classes  ?

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