GB2600293A - AI/ML, distributed computing, and blockchained based reservoir management platform - Google Patents
AI/ML, distributed computing, and blockchained based reservoir management platform Download PDFInfo
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- GB2600293A GB2600293A GB2200668.8A GB202200668A GB2600293A GB 2600293 A GB2600293 A GB 2600293A GB 202200668 A GB202200668 A GB 202200668A GB 2600293 A GB2600293 A GB 2600293A
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- 238000000034 method Methods 0.000 claims abstract 15
- 238000005192 partition Methods 0.000 claims abstract 11
- 238000013473 artificial intelligence Methods 0.000 claims abstract 8
- 238000005457 optimization Methods 0.000 claims 17
- 239000002245 particle Substances 0.000 claims 6
- 238000005553 drilling Methods 0.000 claims 3
- 230000002068 genetic effect Effects 0.000 claims 3
- 238000005070 sampling Methods 0.000 claims 3
- 230000008878 coupling Effects 0.000 claims 2
- 238000010168 coupling process Methods 0.000 claims 2
- 238000005859 coupling reaction Methods 0.000 claims 2
- 238000004140 cleaning Methods 0.000 claims 1
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B44/00—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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
- H04L9/3236—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using cryptographic hash functions
- H04L9/3239—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using cryptographic hash functions involving non-keyed hash functions, e.g. modification detection codes [MDCs], MD5, SHA or RIPEMD
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
- H04L9/3297—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials involving time stamps, e.g. generation of time stamps
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/50—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols using hash chains, e.g. blockchains or hash trees
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B2200/00—Special features related to earth drilling for obtaining oil, gas or water
- E21B2200/22—Fuzzy logic, artificial intelligence, neural networks or the like
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/40—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/004—Artificial life, i.e. computing arrangements simulating life
- G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computing arrangements based on specific mathematical models
- G06N7/01—Probabilistic graphical models, e.g. probabilistic networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q2220/00—Business processing using cryptography
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Abstract
A system for managing well site operations, the system comprising executable partitions, predictive engines, node system stacks, and a blockchain. The predictive engines comprise an Artificial Intelligence (AI) algorithm to generate earth model variables using a physics model, well log data variables, and seismic data variables. The node system stacks are coupled to the blockchain, sensors, and machine controllers. Each node system stack comprises a Robot Operating System (ROS) based middleware controller, with each coupled to each partition, each node system stack, each predictive engine, and an AI process or processes. The blockchain comprises chained blocks of a distributed network. The distributed network comprises a genesis block and a plurality of subsequent blocks, each subsequent block comprising a well site entry and a hash value of a previous well site entry. The well site entry comprises operation control variables. The operation control variables are based on the earth model variables.
Claims (20)
1. A system for managing well site operations, the system comprising: at least one predictive engine having at least one selected from a group comprising an artificial intelligence algorithm and a trained artificial intelligence algorithm, the at least one predictive engine generates earth model variables using a physics model and at least one selected from a group comprising well log data variables and seismic data variables; at least one node system stack communicable coupled to the at least one predictive engine, a distributed network, a plurality of sensors, and at least one machine controller; and at least one chained block of a distributed network, the distributed network comprising a genesis block and a plurality of subsequent blocks, each subsequent block comprising a well site entry and a cryptographic hash value of a previous well site entry, wherein the well site entry comprises at least one transacted operation control variable; wherein the at least one transacted operation control variable is, at least in part, based on at least one of the generated earth model variables.
2. The system of claim 1, further comprising at least one partition, wherein each partition comprises the at least one node system stack and at least one selected from a group comprising the least one predictive engine and at least one process of the at least one predictive engine.
3. The system of claim 2, wherein the at least one node system stack comprises a middleware controller, the middleware controller communicable coupled to each partition, each node system stack, each predictive engine, and the at least one process.
4. The system of claim 3, wherein the middleware controller is a Robot Operating System (ROS) based controller.
5. The system of claim 1, further comprising an optimization engine, the optimization engine optimizes the generated earth model variables by sampling the generated earth model variables based on at least one drilling model and an optimization tool.
6. The system of claim 5, wherein the optimization tool is one of a Bayesian optimization, genetic algorithm optimization, and particle swarm optimization.
7. The system of claim 1, further comprising: a deep particle filter to clean the well log data variables and seismic data variables; and a forward modeling component to compare predicted variables in the generated earth model to the cleaned well log data variables and seismic data variables.
8. An apparatus for managing well site operations, the apparatus comprising: at least one predictive engine having at least one selected from a group comprising an artificial intelligence algorithm and a trained artificial intelligence algorithm, the at least one predictive engine generates earth model variables using a physics model and at least one selected from a group comprising well log data variables and seismic data variables; and at least one node system stack communicable coupled to the at least one predictive engine, a distributed network, a plurality of sensors, and at least one machine controller; wherein the at least one transacted operation control variable is, at least in part, based on at least one of the generated earth model variables.
9. The apparatus of claim 8, further comprising at least one partition, wherein each partition comprises the at least one node system stack and at least one selected from a group comprising the least one predictive engine and at least one process of the at least one predictive engine.
10. The apparatus of claim 9, wherein the at least one node system stack comprises a middleware controller, the middleware controller communicable coupled to each partition, each node system stack, each predictive engine, and the at least one process.
11. The apparatus of claim 10, wherein the middleware controller is a Robot Operating System (ROS) based controller.
12. The apparatus of claim 8, further comprising an optimization engine, the optimization engine optimizes the generated earth model variables by sampling the generated earth model variables based on at least one drilling model and an optimization tool.
13. The apparatus of claim 12, wherein the optimization tool is one of a Bayesian optimization, genetic algorithm optimization, and particle swarm optimization.
14. The apparatus of claim 8, further comprising: a deep particle filter to clean the well log data variables and seismic data variables; and a forward modeling component to compare predicted variables in the generated earth model to the cleaned well log data variables and seismic data variables.
15. A method for managing well site operations, the method comprising: generating earth model variables using an artificial intelligence algorithm or a trained artificial intelligence algorithm, a physics model, and at least one selected from a group comprising well log data variables and seismic data variables; communicable coupling at least one node system stack to the at least one predictive engine, a distributed network, a plurality of sensors, and at least one machine controller; and creating at least one chained block in a distributed network, the distributed network comprising a genesis block and a plurality of subsequent blocks, each subsequent block comprising a well site entry and a cryptographic hash value of a previous well site entry, wherein the well site entry comprises at least one transacted operation control variable; wherein the at least one transacted operation control variable is, at least in part, based on at least one of the generated earth model variables.
16. The method of claim 15, further comprising creating at least one partition, wherein each partition comprises the at least one node system stack and at least one selected from a group comprising the least one predictive engine and at least one process of the at least one predictive engine.
17. The method of claim 16, communicable coupling a middleware controller to each partition, each node system stack, each predictive engine, and the at least one process.
18. The method of claim 17, wherein the middleware controller is a Robot Operating System (ROS) based controller.
19. The method of claim 15, further comprising optimizing the generated earth model variables by sampling the generated earth model variables based on at least one drilling model and one of a Bayesian optimization, genetic algorithm optimization, and particle swarm optimization.
20. The method of claim 15, further comprising cleaning the well log data variables and seismic data variables using a deep particle filter; and comparing predicted variables in the generated earth model to the cleaned well log data variables and seismic data variables using a forward modeling component.
Applications Claiming Priority (4)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201962891223P | 2019-08-23 | 2019-08-23 | |
PCT/US2019/064655 WO2021040764A1 (en) | 2019-08-23 | 2019-12-05 | Ai/ml based drilling and production platform |
US202016651859A | 2020-03-27 | 2020-03-27 | |
PCT/US2020/047499 WO2021041252A1 (en) | 2019-08-23 | 2020-08-21 | Ai/ml, distributed computing, and blockchained based reservoir management platform |
Publications (2)
Publication Number | Publication Date |
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GB2600293A true GB2600293A (en) | 2022-04-27 |
GB2600293B GB2600293B (en) | 2023-03-22 |
Family
ID=74684267
Family Applications (3)
Application Number | Title | Priority Date | Filing Date |
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GB2200679.5A Active GB2600296B (en) | 2019-08-23 | 2020-08-21 | AI/ML and blockchained based automated reservoir management platform |
GB2200669.6A Pending GB2600294A (en) | 2019-08-23 | 2020-08-21 | AI/ML, distributed computing, and blockchained based reservoir management platform |
GB2200668.8A Active GB2600293B (en) | 2019-08-23 | 2020-08-21 | AI/ML, distributed computing, and blockchained based reservoir management platform |
Family Applications Before (2)
Application Number | Title | Priority Date | Filing Date |
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GB2200679.5A Active GB2600296B (en) | 2019-08-23 | 2020-08-21 | AI/ML and blockchained based automated reservoir management platform |
GB2200669.6A Pending GB2600294A (en) | 2019-08-23 | 2020-08-21 | AI/ML, distributed computing, and blockchained based reservoir management platform |
Country Status (3)
Country | Link |
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GB (3) | GB2600296B (en) |
NO (2) | NO20220097A1 (en) |
WO (3) | WO2021041252A1 (en) |
Families Citing this family (2)
Publication number | Priority date | Publication date | Assignee | Title |
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CN114352336A (en) * | 2021-12-17 | 2022-04-15 | 北京天玛智控科技股份有限公司 | Fully-mechanized coal mining face intelligent control system and method |
CN116209030B (en) * | 2023-05-06 | 2023-08-18 | 四川中普盈通科技有限公司 | Mobile platform anti-weak network communication gateway access method and system |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140067353A1 (en) * | 2012-09-05 | 2014-03-06 | Stratagen | Wellbore completion and hydraulic fracturing optimization methods and associated systems |
US20140116776A1 (en) * | 2012-10-31 | 2014-05-01 | Resource Energy Solutions Inc. | Methods and systems for improved drilling operations using real-time and historical drilling data |
US20140351183A1 (en) * | 2012-06-11 | 2014-11-27 | Landmark Graphics Corporation | Methods and related systems of building models and predicting operational outcomes of a drilling operation |
US20150148919A1 (en) * | 2013-11-27 | 2015-05-28 | Adept Ai Systems Inc. | Method and apparatus for artificially intelligent model-based control of dynamic processes using probabilistic agents |
US20180171769A1 (en) * | 2015-07-17 | 2018-06-21 | Halliburton Energy Services, Inc. | Structure For Fluid Flowback Control Decision Making And Optimization |
Family Cites Families (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6968909B2 (en) * | 2002-03-06 | 2005-11-29 | Schlumberger Technology Corporation | Realtime control of a drilling system using the output from combination of an earth model and a drilling process model |
US7814989B2 (en) * | 2007-05-21 | 2010-10-19 | Schlumberger Technology Corporation | System and method for performing a drilling operation in an oilfield |
RU2440591C2 (en) * | 2008-04-10 | 2012-01-20 | Шлюмбергер Текнолоджи Б.В. | Method of obtaining characteristics of geological formation intersected by well |
US10345764B2 (en) * | 2015-04-27 | 2019-07-09 | Baker Hughes, A Ge Company, Llc | Integrated modeling and monitoring of formation and well performance |
US10787887B2 (en) * | 2015-08-07 | 2020-09-29 | Schlumberger Technology Corporation | Method of performing integrated fracture and reservoir operations for multiple wellbores at a wellsite |
KR101706245B1 (en) * | 2015-09-14 | 2017-02-14 | 동아대학교 산학협력단 | Method for controlling production rate using artificial neural network in digital oil field |
WO2017188858A1 (en) * | 2016-04-28 | 2017-11-02 | Schlumberger Canada Limited | Reservoir performance system |
US10223482B2 (en) * | 2016-06-29 | 2019-03-05 | International Business Machines Corporation | Machine learning assisted reservoir simulation |
US11574372B2 (en) * | 2017-02-08 | 2023-02-07 | Upstream Data Inc. | Blockchain mine at oil or gas facility |
CN209085657U (en) * | 2017-08-02 | 2019-07-09 | 强力物联网投资组合2016有限公司 | For data gathering system related or industrial environment with chemical production technology |
-
2020
- 2020-08-21 WO PCT/US2020/047499 patent/WO2021041252A1/en active Application Filing
- 2020-08-21 WO PCT/US2020/047498 patent/WO2021041251A1/en active Application Filing
- 2020-08-21 GB GB2200679.5A patent/GB2600296B/en active Active
- 2020-08-21 GB GB2200669.6A patent/GB2600294A/en active Pending
- 2020-08-21 WO PCT/US2020/047502 patent/WO2021041254A1/en active Application Filing
- 2020-08-21 NO NO20220097A patent/NO20220097A1/en unknown
- 2020-08-21 GB GB2200668.8A patent/GB2600293B/en active Active
-
2022
- 2022-01-21 NO NO20220092A patent/NO20220092A1/en unknown
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140351183A1 (en) * | 2012-06-11 | 2014-11-27 | Landmark Graphics Corporation | Methods and related systems of building models and predicting operational outcomes of a drilling operation |
US20140067353A1 (en) * | 2012-09-05 | 2014-03-06 | Stratagen | Wellbore completion and hydraulic fracturing optimization methods and associated systems |
US20140116776A1 (en) * | 2012-10-31 | 2014-05-01 | Resource Energy Solutions Inc. | Methods and systems for improved drilling operations using real-time and historical drilling data |
US20150148919A1 (en) * | 2013-11-27 | 2015-05-28 | Adept Ai Systems Inc. | Method and apparatus for artificially intelligent model-based control of dynamic processes using probabilistic agents |
US20180171769A1 (en) * | 2015-07-17 | 2018-06-21 | Halliburton Energy Services, Inc. | Structure For Fluid Flowback Control Decision Making And Optimization |
Also Published As
Publication number | Publication date |
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NO20220097A1 (en) | 2022-01-21 |
WO2021041252A1 (en) | 2021-03-04 |
NO20220092A1 (en) | 2022-01-21 |
GB2600296B (en) | 2024-06-12 |
GB2600296A (en) | 2022-04-27 |
GB2600294A (en) | 2022-04-27 |
WO2021041251A1 (en) | 2021-03-04 |
GB2600293B (en) | 2023-03-22 |
WO2021041254A1 (en) | 2021-03-04 |
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