GB2600294A - AI/ML, distributed computing, and blockchained based reservoir management platform - Google Patents

AI/ML, distributed computing, and blockchained based reservoir management platform Download PDF

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Publication number
GB2600294A
GB2600294A GB2200669.6A GB202200669A GB2600294A GB 2600294 A GB2600294 A GB 2600294A GB 202200669 A GB202200669 A GB 202200669A GB 2600294 A GB2600294 A GB 2600294A
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United Kingdom
Prior art keywords
engine
variables
machine learning
artificial intelligence
algorithm
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GB2200669.6A
Inventor
Prasad Rangarajan Keshava
Vikram R Pandya Raja
Madasu Srinath
Dande Shashi
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Landmark Graphics Corp
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Landmark Graphics Corp
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Priority claimed from PCT/US2019/064655 external-priority patent/WO2021040764A1/en
Application filed by Landmark Graphics Corp filed Critical Landmark Graphics Corp
Publication of GB2600294A publication Critical patent/GB2600294A/en
Pending legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP 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
    • 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
    • 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
    • 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
    • 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/02—Agriculture; Fishing; 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
    • 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
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP 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
    • 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
    • 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
    • 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
    • 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

Abstract

A system, for controlling well site operations, comprising a machine learning engine, a predictive engine, a node system stack, and a blockchain. The learning engine includes a machine learning algorithm, an algorithmically generated earth model, and control variables. The learning algorithm generates a trained data model using the algorithmically generated earth model. The predictive engine includes an Artificial Intelligence (AI) algorithm. The AI algorithm generates a trained AI algorithm using the trained data model and earth model variables using the trained AI algorithm. The system stack is communicable coupled to the predictive engine, the learning engine, the blockchain, sensors, and a machine controller. The blockchain having a genesis block and a plurality of subsequent blocks. Each subsequent block comprising a well site entry and a hash of a previous entry. The well site entry comprises transacted operation control variables. The transacted variables are based on the generated earth model variables.

Claims (20)

What is claimed is:
1. A system for managing well site operations, the system comprising: at least one machine learning engine having at least one machine learning algorithm, at least one algorithmically generated earth model, at least one control variable; at least one trained data model generated using the at least one machine learning engine; at least one predictive engine having an artificial intelligence algorithm, the at least one predictive engine generates a trained artificial intelligence algorithm using the artificial intelligence algorithm and the at least one trained data model, the trained artificial intelligence algorithm having a parameter set less than the artificial intelligence algorithm; earth model variables generated using the trained artificial intelligence algorithm; at least one node system stack communicable coupled to the at least one predictive engine, the at least one machine learning algorithm, a distributed network, a plurality of sensors, and at least one machine controller; 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; and the machine controller communicable coupled to the at least one transacted operation control variable and at least one well site operation; 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, 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, and at least one selected from a group comprising the least one machine learning engine and at least one process of the at least one machine learning 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, each process of the predictive engine, each machine learning engine, and each process of the machine learning engine.
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 machine learning engine having at least one machine learning algorithm, at least one algorithmically generated earth model, and at least one control variable; at least one trained data model generated using the at least one machine learning engine; at least one predictive engine having an artificial intelligence algorithm, the at least one predictive engine generates a trained artificial intelligence algorithm using the artificial intelligence algorithm and the at least one trained data model, the trained artificial intelligence algorithm having a parameter set less than the artificial intelligence algorithm; earth model variables generated using the trained artificial intelligence algorithm; at least one node system stack communicable coupled to the at least one predictive engine, the at least one machine learning algorithm, a distributed network, a plurality of sensors, and at least one machine controller; and the machine controller communicable coupled to the at least one transacted operation control variable and at least one well site operation; 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, 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, and at least one selected from a group comprising the least one machine learning engine and at least one process of the at least one machine learning 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, each process of the predictive engine, each machine learning engine, and each process of the machine learning engine.
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 at least one trained data model generated using at least one machine learning algorithm, at least one algorithmically generated earth model, at least one control variable; training an artificial intelligence algorithm using an artificial intelligence algorithm, the at least one trained data model, the trained artificial intelligence algorithm having a parameter set less than the artificial intelligence algorithm; generating earth model variables using the trained artificial intelligence algorithm; 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; controlling at least one well site operation using the 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, 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, and at least one selected from a group comprising the least one machine learning engine and at least one process of the at least one machine learning engine.
17. The method of claim 16, communicable coupling a middleware controller to each partition, each node system stack, each predictive engine, each process of the predictive engine, each machine learning engine, and each process of the machine learning engine.
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.
GB2200669.6A 2019-08-23 2020-08-21 AI/ML, distributed computing, and blockchained based reservoir management platform Pending GB2600294A (en)

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/US2020/047502 WO2021041254A1 (en) 2019-08-23 2020-08-21 Ai/ml, distributed computing, and blockchained based reservoir management platform

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Also Published As

Publication number Publication date
WO2021041251A1 (en) 2021-03-04
GB2600293B (en) 2023-03-22
NO20220092A1 (en) 2022-01-21
WO2021041252A1 (en) 2021-03-04
NO20220097A1 (en) 2022-01-21
WO2021041254A1 (en) 2021-03-04
GB2600296A (en) 2022-04-27
GB2600293A (en) 2022-04-27

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