Machine Learning in the Oil and Gas Industry: Including Geosciences, Reservoir Engineering, and Production Engineering with Python
暫譯: 石油與天然氣產業中的機器學習：涵蓋地球科學、油藏工程及生產工程，並使用 Python

應用機器學習和深度學習來解決石油和天然氣行業中的一些挑戰。本書首先簡要討論了石油和天然氣勘探及生產的生命週期，並在行業運作的不同階段中探討數據流的情況。接著，介紹了一些有趣的問題，這些問題非常適合應用機器學習和深度學習方法。最初的章節提供了用於實現算法的 Python 程式語言的入門知識；隨後概述了監督式和非監督式機器學習的概念。作者使用開源數據集提供行業範例，並對算法進行實用解釋，而不深入探討所使用算法的理論方面。《Machine Learning in the Oil and Gas Industry》涵蓋了多樣的行業主題，包括地球物理學（地震解釋）、地質建模、油藏工程和生產工程。

在整本書中，重點在於提供實用的方法，並逐步解釋和提供代碼範例，以實現機器學習和深度學習算法來解決石油和天然氣行業中的現實問題。

您將學到的內容：

- 理解石油和天然氣行業的端到端生命週期及其工業運作中的數據流
- 獲得實現所使用算法所需的計算機程式設計和機器學習、深度學習的基本概念
- 研究適合用機器學習和深度學習解決的有趣行業問題
- 發現執行石油和天然氣行業機器學習和深度學習項目的實際考量和挑戰

本書適合對象：

石油和天然氣行業的專業人士，他們可以從對機器學習和深度學習方法解決現實問題的實用理解中受益。

Yogendra Pandey is a senior product manager at Oracle Cloud Infrastructure. He has more than 14 years of experience in orchestrating intelligent systems for the oil and gas, utilities, and chemical industries. He has worked in different capacities with oil and gas, and utilities companies, including Halliburton, ExxonMobil, and ADNOC. Yogendra holds a bachelor's degree in chemical engineering from the Indian Institute of Technology (BHU), and a PhD from the University of Houston, with specialization in high-performance computing applications to complex engineering problems. He served as an executive editor for the Journal of Natural Gas Science and Engineering. Also, he has authored/co-authored more than 25 peer-reviewed journal articles, conference publications, and patent applications. He is a member of the Society of Petroleum Engineers.

Ayush Rastogi is a data scientist at BPX Energy, Denver CO. His research interests are based on multi-phase fluid flow modeling and integrating physics-based and data-driven algorithms to develop robust predictive models. He has published his work in the field of machine learning and data-driven predictive modeling in the oil and gas industry. He has previously worked with Liberty Oilfield Services in the technology team in Denver, prior to which he worked as a field engineer in TX, ND, and CO as a part of his internship. He also has experience working as a petroleum engineering consultant in Houston, TX. Ayush holds a PhD in petroleum engineering with a minor in computer science from Colorado School of Mines, and is an active member of the Society of Petroleum Engineers.

Sribharath Kainkaryam leads a team of data scientists and data engineers at TGS. Prior to joining TGS in 2018, he was a research scientist working on imaging and velocity model building challenges at Schlumberger. He graduated with a masters in computational geophysics from Purdue University and has an undergraduate degree from the Indian Institute of Technology, Kharagpur.

Srimoyee Bhattacharya is a reservoir engineer in the Permian asset team in the Shell Exploration and Production Company. She has over 11 years of combined academic and professional experience in the oil and gas industry. She has worked in reservoir modeling, enhanced oil recovery, history matching, fracture design, production optimization, proxy modelling, and applications of multivariate analysis methods. She also worked with Halliburton as a research intern on digitalization of oil fields and field-wide data analysis using statistical methods. Srimoyee holds a PhD in chemical engineering from the University of Houston, and a bachelor's degree from the Indian Institute of Technology, Kharagpur. She has served as a technical reviewer for the SPE Journal, Journal of Natural Gas Science and Engineering, and Journal of Sustainable Energy Engineering. She has authored/co-authored more than 25 peer-reviewed journal articles, conference publications, technical reports, and patent application.

Luigi Saputelli is a reservoir management expert advisor to ADNOC and Frontender Corporation with over 28 years of experience. He worked in various operators and services companies around the world including PDVSA, Hess, and Halliburton. He is a founding member of the Real-time Optimization TIG and Petroleum Data-driven Analytics technical section of the Society of Petroleum Engineers, and recipient of the 2015 Society of Petroleum Engineers international production and operations award. He also received the 2007 employee of the year award from Halliburton. He has published more than 90 industry papers on applied technologies related to reservoir management, real-time optimization, and production operations. Saputelli is an electronic engineer with a masters in petroleum engineering, and a PhD in chemical engineering. He also serves as managing partner in Frontender Corporation, a petroleum engineering services firm based in Houston.

Yogendra Pandey 是 Oracle Cloud Infrastructure 的資深產品經理。他在石油和天然氣、公用事業及化學工業的智能系統協調方面擁有超過 14 年的經驗。他曾在不同職位上與石油和天然氣及公用事業公司合作，包括 Halliburton、ExxonMobil 和 ADNOC。Yogendra 擁有印度理工學院（BHU）的化學工程學士學位，以及休斯頓大學的博士學位，專攻高效能計算在複雜工程問題中的應用。他曾擔任《天然氣科學與工程期刊》的執行編輯。此外，他已發表或共同發表超過 25 篇經過同行評審的期刊文章、會議出版物和專利申請。他是石油工程師學會的成員。

Ayush Rastogi 是 BPX Energy 的數據科學家，位於科羅拉多州丹佛市。他的研究興趣基於多相流體流動建模，並整合基於物理的和數據驅動的算法以開發穩健的預測模型。他在石油和天然氣行業的機器學習和數據驅動預測建模領域發表了他的研究成果。他曾在丹佛的 Liberty Oilfield Services 的技術團隊工作，之前作為實習生在德克薩斯州、北達科他州和科羅拉多州擔任現場工程師。他還在德克薩斯州休斯頓擔任石油工程顧問。Ayush 擁有科羅拉多礦業學院的石油工程博士學位，並輔修計算機科學，是石油工程師學會的活躍成員。

Sribharath Kainkaryam 在 TGS 領導一支數據科學家和數據工程師的團隊。在 2018 年加入 TGS 之前，他曾在 Schlumberger 擔任研究科學家，專注於成像和速度模型構建的挑戰。他擁有普渡大學的計算地球物理學碩士學位，並擁有印度理工學院卡哈拉古爾的學士學位。

Srimoyee Bhattacharya 是 Shell Exploration and Production Company 的 Permian 資產團隊的油藏工程師。她在石油和天然氣行業擁有超過 11 年的學術和專業經驗。她的工作涵蓋油藏建模、增產技術、歷史匹配、裂縫設計、生產優化、代理建模及多變量分析方法的應用。她還曾在 Halliburton 擔任研究實習生，專注於油田數位化和使用統計方法進行全場數據分析。Srimoyee 擁有休斯頓大學的化學工程博士學位，以及印度理工學院卡哈拉古爾的學士學位。她曾擔任 SPE Journal、《天然氣科學與工程期刊》和《可持續能源工程期刊》的技術審稿人。她已發表或共同發表超過 25 篇經過同行評審的期刊文章、會議出版物、技術報告和專利申請。

Luigi Saputelli 是 ADNOC 和 Frontender Corporation 的油藏管理專家顧問，擁有超過 28 年的經驗。他曾在全球多家運營商和服務公司工作，包括 PDVSA、Hess 和 Halliburton。他是石油工程師學會即時優化技術小組和基於數據的石油分析技術小組的創始成員，並獲得 2015 年石油工程師學會國際生產與運營獎。他還於 2007 年獲得 Halliburton 的年度員工獎。他已發表超過 90 篇有關油藏管理、即時優化和生產運營的應用技術行業論文。Saputelli 是電子工程師，擁有石油工程碩士學位和化學工程博士學位。他還擔任位於休斯頓的石油工程服務公司 Frontender Corporation 的管理合夥人。