CA3076887A1 - Method for cost effective thermo-dynamic fluid property predictions using machine-learning based models - Google Patents

Method for cost effective thermo-dynamic fluid property predictions using machine-learning based models Download PDF

Info

Publication number
CA3076887A1
CA3076887A1 CA3076887A CA3076887A CA3076887A1 CA 3076887 A1 CA3076887 A1 CA 3076887A1 CA 3076887 A CA3076887 A CA 3076887A CA 3076887 A CA3076887 A CA 3076887A CA 3076887 A1 CA3076887 A1 CA 3076887A1
Authority
CA
Canada
Prior art keywords
phase
computer
machine learning
learning algorithm
algorithm
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CA3076887A
Other languages
English (en)
French (fr)
Inventor
Abishek Kashinath
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Saudi Arabian Oil Co
Original Assignee
Saudi Arabian Oil Co
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Saudi Arabian Oil Co filed Critical Saudi Arabian Oil Co
Publication of CA3076887A1 publication Critical patent/CA3076887A1/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00Machine learning
    • G06N20/10Machine learning using kernel methods, e.g. support vector machines [SVM]
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00Machine learning
    • G06N20/20Ensemble learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/0499Feedforward networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/09Supervised learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computing arrangements based on specific mathematical models
    • G06N7/01Probabilistic graphical models, e.g. probabilistic networks
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/30Prediction of properties of chemical compounds, compositions or mixtures
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/70Machine learning, data mining or chemometrics
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • Artificial Intelligence (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • General Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Medical Informatics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Crystallography & Structural Chemistry (AREA)
  • Chemical & Material Sciences (AREA)
  • Computational Linguistics (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Molecular Biology (AREA)
  • Databases & Information Systems (AREA)
  • Algebra (AREA)
  • Mathematical Optimization (AREA)
  • Mathematical Analysis (AREA)
  • Pure & Applied Mathematics (AREA)
  • Computational Mathematics (AREA)
  • Probability & Statistics with Applications (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
CA3076887A 2017-09-26 2018-09-19 Method for cost effective thermo-dynamic fluid property predictions using machine-learning based models Pending CA3076887A1 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201762563460P 2017-09-26 2017-09-26
US62/563,460 2017-09-26
PCT/US2018/051684 WO2019067282A1 (en) 2017-09-26 2018-09-19 METHOD FOR PREDICTING ECONOMIC FLUID THERMODYNAMIC PROPERTIES USING MODELS BASED ON AUTOMATIC LEARNING

Publications (1)

Publication Number Publication Date
CA3076887A1 true CA3076887A1 (en) 2019-04-04

Family

ID=63794679

Family Applications (1)

Application Number Title Priority Date Filing Date
CA3076887A Pending CA3076887A1 (en) 2017-09-26 2018-09-19 Method for cost effective thermo-dynamic fluid property predictions using machine-learning based models

Country Status (6)

Country Link
US (1) US11449747B2 (https=)
EP (1) EP3688683A1 (https=)
JP (1) JP7229233B2 (https=)
CN (1) CN111344710A (https=)
CA (1) CA3076887A1 (https=)
WO (1) WO2019067282A1 (https=)

Families Citing this family (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110096785B (zh) * 2019-04-25 2020-09-01 华北电力大学 一种应用于超超临界机组的堆叠自编码器建模方法
EP3872038A1 (en) * 2020-02-27 2021-09-01 Grundfos Holding A/S Reinforcement learning for h2s abatement
CA3175274A1 (en) * 2020-03-09 2021-09-16 Schlumberger Canada Limited Fast front tracking in eor flooding simulation on coarse grids
CN115087995A (zh) * 2020-03-31 2022-09-20 Abb瑞士股份有限公司 用于工业车间的特定生产过程的迁移学习方法
CN111546035B (zh) * 2020-04-07 2021-07-02 大连理工大学 一种基于学习与预测的齿轮在线快速装配方法
US11815650B2 (en) 2020-04-09 2023-11-14 Saudi Arabian Oil Company Optimization of well-planning process for identifying hydrocarbon reserves using an integrated multi-dimensional geological model
US11486230B2 (en) 2020-04-09 2022-11-01 Saudi Arabian Oil Company Allocating resources for implementing a well-planning process
US11693140B2 (en) 2020-04-09 2023-07-04 Saudi Arabian Oil Company Identifying hydrocarbon reserves of a subterranean region using a reservoir earth model that models characteristics of the region
AU2021255730B2 (en) * 2020-04-17 2024-08-08 Chevron U.S.A. Inc. Compositional reservoir simulation
US20210390424A1 (en) * 2020-06-10 2021-12-16 At&T Intellectual Property I, L.P. Categorical inference for training a machine learning model
CN114139432B (zh) * 2020-09-04 2025-06-27 中国石油化工股份有限公司 利用神经网络技术的裂缝性油藏co2驱流动模拟方法
WO2022061331A1 (en) * 2020-09-18 2022-03-24 Schlumberger Technology Corporation Generalizable machine learning algorithms for flash calculations
US12019059B2 (en) * 2020-10-16 2024-06-25 Saudi Arabian Oil Company Detecting equipment defects using lubricant analysis
CN112668607B (zh) * 2020-12-04 2024-09-13 深圳先进技术研究院 一种用于目标物体触觉属性识别的多标签学习方法
CN112632787B (zh) * 2020-12-25 2023-11-28 浙江中控技术股份有限公司 多解闪蒸优化策略的仿真测试方法
CN113539387A (zh) * 2021-07-09 2021-10-22 西南石油大学 一种基于CPA状态方程预测NaCl水溶液中CO2溶解度的方法
US12271445B2 (en) * 2022-10-28 2025-04-08 Yahoo Assets Llc Electronic information extraction using a machine-learned model architecture method and apparatus
CN115688592B (zh) * 2022-11-09 2023-05-09 福建德尔科技股份有限公司 用于电子级四氟化碳制备的精馏控制系统及其方法
CN116992296A (zh) * 2023-09-27 2023-11-03 广东电网有限责任公司珠海供电局 电子敏感设备发生暂降的中断概率评估方法、装置和设备
CN119849340B (zh) * 2025-03-20 2025-07-15 中国石油大学(华东) 一种基于机器学习相识别模型的三相闪蒸计算方法

Family Cites Families (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6633857B1 (en) * 1999-09-04 2003-10-14 Microsoft Corporation Relevance vector machine
FR2848320B1 (fr) * 2002-12-10 2005-01-28 Inst Francais Du Petrole Methode pour modeliser des caracteristiques hydrodynamiques d'ecoulements polyphasiques par reseaux de neurones
US7490071B2 (en) * 2003-08-29 2009-02-10 Oracle Corporation Support vector machines processing system
JP2008221146A (ja) * 2007-03-13 2008-09-25 Sumitomo Chemical Co Ltd 計算装置、計算方法、計算装置制御プログラム、及び該計算装置制御プログラムを記録したコンピュータ読み取り可能な記録媒体
CA2805446C (en) 2010-07-29 2016-08-16 Exxonmobil Upstream Research Company Methods and systems for machine-learning based simulation of flow
CN102147807A (zh) * 2011-03-10 2011-08-10 南京信息工程大学 基于gis的海量雷电数据时空分析方法
EP2729051B1 (en) * 2011-07-05 2018-06-06 Saudi Arabian Oil Company Systems, computer medium and computer-implemented methods for coaching employees based upon monitored health conditions using an avatar
US10119374B2 (en) 2012-03-12 2018-11-06 Total Sa Method for simulating fluid flows, a computer program and a computer readable medium
US10289962B2 (en) * 2014-06-06 2019-05-14 Google Llc Training distilled machine learning models
SG10201403287VA (en) * 2014-06-16 2016-01-28 Ats Group Ip Holdings Ltd Flash flooding detection system
US20150377667A1 (en) * 2014-06-30 2015-12-31 Saudi Arabian Oil Company Virtual multiphase flow metering and sand detection
CN106526708B (zh) * 2016-09-21 2018-10-30 广东奥博信息产业股份有限公司 一种基于机器学习的气象强对流天气的智能预警分析方法
WO2018117890A1 (en) 2016-12-21 2018-06-28 Schlumberger Technology Corporation A method and a cognitive system for predicting a hydraulic fracture performance
CN106920544A (zh) * 2017-03-17 2017-07-04 深圳市唯特视科技有限公司 一种基于深度神经网络特征训练的语音识别方法

Also Published As

Publication number Publication date
US20190095792A1 (en) 2019-03-28
US11449747B2 (en) 2022-09-20
CN111344710A (zh) 2020-06-26
WO2019067282A1 (en) 2019-04-04
EP3688683A1 (en) 2020-08-05
JP7229233B2 (ja) 2023-02-27
JP2020537221A (ja) 2020-12-17

Similar Documents

Publication Publication Date Title
US11449747B2 (en) Algorithm for cost effective thermodynamic fluid property predictions using machine-learning based models
US11727311B2 (en) Classifying user behavior as anomalous
US11087201B2 (en) Neural architecture search using a performance prediction neural network
CN112100312B (zh) 从数据源中智能提取因果知识
US10430315B2 (en) Classifying warning messages generated by software developer tools
Kashinath et al. A fast algorithm for calculating isothermal phase behavior using machine learning
US20210117627A1 (en) Automated Testing of Dialog Systems
WO2021026425A1 (en) Representation learning in massive petroleum network systems
CN109313720A (zh) 具有稀疏访问的外部存储器的增强神经网络
Zhen et al. An interpretable and augmented machine-learning approach for causation analysis of major accident risk indicators in the offshore petroleum industry
WO2021026423A1 (en) Aggregation functions for nodes in ontological frameworks in representation learning for massive petroleum network systems
US12481895B2 (en) Training individually fair machine learning algorithms via distributionally robust optimization
Chen et al. Did the model change? efficiently assessing machine learning api shifts
CN104885101A (zh) 包括表征选择的不确定度的基于不完备描述对新总体成员的相似成员的自动选择
Ucherek et al. Auto-Suggestive Real-Time Classification of Driller Memos into Activity Codes Using Natural Language Processing
US20160217393A1 (en) Information extraction
Aulia et al. A new history matching sensitivity analysis framework with random forests and Plackett-Burman design
CN117151247B (zh) 机器学习任务建模的方法、装置、计算机设备和存储介质
US20250037036A1 (en) Supervised and multivariate continuous attributes discretization
US20240070658A1 (en) Parsing event data for clustering and classification
US20220156604A1 (en) Identification of compartments in gas reservoirs
Fisher et al. Marginal Bayesian posterior inference using recurrent neural networks with application to sequential models
US12560739B2 (en) Machine learning of geology by probabilistic integration of local constraints
US20250028907A1 (en) Forming a hypothesis set from sentences across documents representative of different stances taken across the documents
Gao et al. Software defect prediction based on geometric mean for subspace learning