Table of Contents

1. Introduction to Digital Oil and Gas Field Systems2. Instrumentation and Measurement3. Data Filtering and Conditioning4. Components of Artificial Intelligence and Data Analytics5. Workflow Automation and Intelligent Control6. Integrated Asset Management and Optimization Workflows7. Smart Wells and Techniques for Reservoir Monitoring8. Transitioning to Effective DOF Enabled by Collaboration and Management of Change9. The Future Digital Oil Field

Promotional Information

A one-stop guide to transforming engineering workflows and data analytics into successfully delivered oil and gas projects

About the Author

Gustavo is a Sr. Reservoir Engineer at BP America conducting automated workflows to evaluate unconventional assets and deploys data analytics for production optimization. He is developing full field reservoir simulation models for unconventional reservoirs using history matching in complex geologic systems containing rock matrix, hydraulic fractures, and natural fractures. Prior to his current position, he worked for Halliburton delivering Digital Oil Field intelligent strategies and operations. Gustavo has more than 20 years of experience with IOC, NOC and services companies, and he has published more than 60 technical papers on the subject of reservoir studies and DOF applications, developed more than 40 complex automated workflows that include classic reservoir and production engineering tools combined with artificial intelligence components, and has 15 patents for improving real-time model-based operations. He holds a BSc in Petroleum Engineering from the Universidad de Oriente (Venezuela), a MEng in Project Management from the U.C. Andres Bello (Venezuela), and an MSc and MPhil, both in Reservoir Engineering from Heriot-Watt University, Scotland, UK. Marko Maucec is a Petroleum Engineering Specialist, responsible for the development and implementation of advanced workflows for uncertainty quantification, assisted history matching, and production optimization of oil and gas fields. In 2015, Marko served as a Data Scientist with Blue River Analytics in Denver, CO. Formerly, he served as Principal Consultant, Chief Technical Advisor/Scientist, and Technology Research Fellow Associate at several positions in Halliburton/Landmark in the US and Malaysia. There, he was working in the areas technology development for assisted history matching and forecasting under uncertainty, integrated DOF workflows, predictive data-driven analytics, advanced geo-modeling, and subsurface imaging of conventional and unconventional assets. Previously, Marko had been a research geoscientist with Shell International E&P in Houston, TX, where he worked in quantitative reservoir management and developed methods for dynamic stochastic model inversion. Prior to entering the oil and gas industry, Marko had worked internationally in the areas of nuclear engineering and nuclear geophysics, specializing in the development of techniques for Monte Carlo simulations of nuclear radiation transport for nuclear safety and medical physics applications. Marko has published more than 80 professional technical and peer-reviewed scientific publications, has been awarded 7 patents, and is a (co)inventor on 14 pending patent applications. Marko is an active member of SPE, where he has served extensively as an invited presenter and a steering committee (co)chair at conferences, technical workshops and Forum series events. He is also currently affiliated as the technical reviewer with several professional journals. Marko holds a BSc in electrical engineering from the University of Ljubljana, a MSc in nuclear engineering from the University of Maribor, and a PhD in nuclear engineering from the University of Ljubljana (all in Slovenia). Stan is an independent consultant and Engineering Advisor with RARE PETRO Inc. which offers specialized oil field mobile applications, well sensors, and engineering services. In 2015 he formed Greenway Energy Transformations to advise oil and gas operators for which he consulted on Digital Oil Field (DOF) and unconventional development projects for clients in North America and the Middle East. From 2012-2015, he was Director, Corporate Technology in LINN Energy and VP Technology for Berry Petroleum Corp for which he initiated and implemented DOF projects in their North American assets. He had been Chief Advisor and Director for Global Petroleum Engineering for Halliburton Consulting and Project Management, and he was technical manager for a large Middle East DOF implementation in 2010-2011. From 2003 to 2010, Stan was a Halliburton Technology Fellow, focusing on field development planning, well placement, decision management and uncertainty, smart wells, and improved recovery. Previously in Mobil Oil he led projects on field development planning, project evaluation and decision management, production performance optimization, and subsurface characterization. Stan has more than 75 technical articles with about 20 directly related to DOF and 22 awarded patents, including 8 on DOF (3 applications pending). He has a PhD from The Ohio State University, a MBA from University of Texas at Dallas, and a BS from Tulane University.

Reviews

"Chapters are pitched at a very accessible level and should be useful for giving students and domain specialists a good (if uncritical) view of the big picture. Coverage includes a fairly extensive top-level treatment of AI and machine learning in predictive analysis of equipment failure. A must-read for all practitioners." --Oil IT Journal

"A comprehensive guide to the digital oilfield from well-qualified specialists."

Intelligent Digital Oil and Gas Fields (IDOF) by Gustavo Carvajal (BP America), Marco Maucec (Saudi Aramco) and Stan Cullick (Rare Petro) is a 350-page, information-packed resumé of the digital oilfield movement. The authors experience of the DOF began in the mid 2000s when, as specialists from Halliburton, they worked on Kuwait Oil’s flagship KwIDF project.

An introductory chapter sets out the essential technological and business underpinnings of the DOF and provides a brief outline of major industry initiatives, Shell’s Smart Fields, BP’s Field of the Future, Integrated Operations initiatives from ConocoPhillips and Statoil and I-Fields from Aramco and Chevron.

Other chapters cover instrumentation, data conditioning (but not data management – see below), analytics, workflow automation and smart wells. These are pitched at a very accessible level and should be useful for giving students and domain specialists a good (if uncritical) view of the big picture. Coverage includes a fairly extensive top-level treatment of AI and machine learning in predictive analysis of equipment failure.

The workflow automation chapter covers all bases but suffers from an issue that permeates IDOF. The authors share the Society of Petroleum Engineers’ reluctance to name to a piece of software. This misguided avoidance of ‘commerciality’ is curious. Is all software ‘commodity?’ Can a book about the digital oilfield be written without mentioning the PI System?

The topic of data management is touched on in the introduction but poorly developed elsewhere in IDOF which may well reflect the state of the art! The introduction has it that in the early days, oils though that the DOF was ‘simply IT or data management,’ while ‘it is so much more.’ It is indeed, as Oil IT Journal has demonstrated since well before the DOF was dreamed-up. Shame you forgot to mention that guys! No hard feelings though, IDOF is a major undertaking and significant contribution to the DOF literature. A must-read for all practitioners." --Intelligent Digital Oil and Gas Fields by Neil McNaughton, Editor, Oil IT Journal