CN111344710A - 使用基于机器学习的模型进行成本有效的热力学流体特性预测的方法 - Google Patents

使用基于机器学习的模型进行成本有效的热力学流体特性预测的方法 Download PDF

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CN111344710A
CN111344710A CN201880073266.5A CN201880073266A CN111344710A CN 111344710 A CN111344710 A CN 111344710A CN 201880073266 A CN201880073266 A CN 201880073266A CN 111344710 A CN111344710 A CN 111344710A
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阿比舍克·卡希纳特
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Saudi Arabian Oil Co
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CN201880073266.5A 2017-09-26 2018-09-19 使用基于机器学习的模型进行成本有效的热力学流体特性预测的方法 Pending CN111344710A (zh)

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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

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US (1) US11449747B2 (https=)
EP (1) EP3688683A1 (https=)
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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112668607A (zh) * 2020-12-04 2021-04-16 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
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
CN115688592A (zh) * 2022-11-09 2023-02-03 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
CN119849340A (zh) * 2025-03-20 2025-04-18 中国石油大学(华东) 一种基于机器学习相识别模型的高效三相闪蒸计算方法

Families Citing this family (16)

* 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
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
US12271445B2 (en) * 2022-10-28 2025-04-08 Yahoo Assets Llc Electronic information extraction using a machine-learned model architecture method and apparatus
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

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050049990A1 (en) * 2003-08-29 2005-03-03 Milenova Boriana L. Support vector machines processing system
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
CN103781407A (zh) * 2011-07-05 2014-05-07 沙特阿拉伯石油公司 用于利用虚拟形象来基于监测的健康状况训练雇员的系统、计算机介质和计算机实现方法
CN105160397A (zh) * 2014-06-06 2015-12-16 谷歌公司 训练精炼的机器学习模型
CN106526708A (zh) * 2016-09-21 2017-03-22 广东奥博信息产业有限公司 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
CN106537136A (zh) * 2014-06-30 2017-03-22 沙特阿拉伯石油公司 虚拟多相流计量和砂检测
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
US20170193305A1 (en) * 2014-06-16 2017-07-06 Agt International Gmbh Flash flooding detection system

Family Cites Families (6)

* 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
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
US10119374B2 (en) 2012-03-12 2018-11-06 Total Sa Method for simulating fluid flows, a computer program and a computer readable medium
WO2018117890A1 (en) 2016-12-21 2018-06-28 Schlumberger Technology Corporation A method and a cognitive system for predicting a hydraulic fracture performance

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050049990A1 (en) * 2003-08-29 2005-03-03 Milenova Boriana L. Support vector machines processing system
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
CN103781407A (zh) * 2011-07-05 2014-05-07 沙特阿拉伯石油公司 用于利用虚拟形象来基于监测的健康状况训练雇员的系统、计算机介质和计算机实现方法
CN105160397A (zh) * 2014-06-06 2015-12-16 谷歌公司 训练精炼的机器学习模型
US20170193305A1 (en) * 2014-06-16 2017-07-06 Agt International Gmbh Flash flooding detection system
CN106537136A (zh) * 2014-06-30 2017-03-22 沙特阿拉伯石油公司 虚拟多相流计量和砂检测
CN106526708A (zh) * 2016-09-21 2017-03-22 广东奥博信息产业有限公司 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
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

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
VASSILIS GAGANIS: "An integrated approach for rapid phase behavior calculations in compositional modeling", 《JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING》, vol. 118, 3 April 2014 (2014-04-03), pages 74 - 87, XP055528353, DOI: 10.1016/j.petrol.2014.03.011 *
王飞;张义军;赵均壮;吕伟涛;孟青;: "雷达资料在孤立单体雷电预警中的初步应用", 应用气象学报, no. 02, 15 April 2008 (2008-04-15) *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112668607A (zh) * 2020-12-04 2021-04-16 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
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
CN115688592A (zh) * 2022-11-09 2023-02-03 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
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
CN119849340A (zh) * 2025-03-20 2025-04-18 中国石油大学(华东) 一种基于机器学习相识别模型的高效三相闪蒸计算方法

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US11449747B2 (en) 2022-09-20
WO2019067282A1 (en) 2019-04-04
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JP7229233B2 (ja) 2023-02-27
JP2020537221A (ja) 2020-12-17
CA3076887A1 (en) 2019-04-04

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