Harness Oil and Gas Big Data with Analytics: Optimize Exploration and Production with Data–Driven Models

Praise for Harness Oil and Gas Big Data with Analytics: Optimize Exploration and Production with Data–Driven Models This is a time of great change in the oil and gas industry, and even before embracing real time systems, we were struggling to extract meaningful insights from a large accumulation of data that was right under our noses. Based on his years of global experience, Keith has developed a deep technical understanding of these issues, and in his book Harness Oil and Gas Big Data with Analytics , he combines this understanding with his unique talent for communicating complex issues in a straightforward manner. Reading this book you will begin to see your data as the insight it was intended to be, and not the burden it has become. Dennis Seemann, Supervisor, Reservoir Management Analytical Division, Saudi Aramco Keith Holdaway has written an important and timely book addressing the significance of data–driven analytics in our industry. Keith is highly knowledgeable in this area and has a strong command of the important aspects of this subject. This book is a testimony to his dedication to, and depth of understanding of, data–driven analytics as they relate to the exploration and production industry. This is a must–read for anyone interested in this subject. Shahab D. Mohaghegh, PhD, CEO, Intelligent Solutions, Inc.; Professor of Petroleum Natural Gas Engineering, West Virginia University EXPLOIT NEW EFFICIENCIES THAT BIG DATA ANALYTICS CAN BRING TO OIL AND GAS EXPLORATION AND PRODUCTION From an expert in the field of oil and gas data analytics comes Harness Oil and Gas Big Data with Analytics , a complete view of big data and analytics techniques as they are applied to the oil and gas industry. Including a compendium of specific case studies, the book underscores the acute need for optimization in the oil and gas exploration and production stages and shows how data analytics can provide such optimization. With a unique focus on applying big data analytics to the oil and gas industry, this book provides a roadmap for leveraging data, statistical, and quantitative analysis, exploratory and predictive modeling, and fact–based management to drive decision making in oil and gas operations. Starting out with a complete overview of data analysis and oilfield analytics, this resource hits all the high points of big data analytics best practices and challenges before delving into the specifics of oil and gas exploration. Featuring ten chapters of in–depth information, readers will get a full view of the most important issues for oil and gas data analytics, including seismic attribute analysis, reservoir characterization and simulation, drilling optimization, reservoir management, and production forecasting and optimization. For oil and gas engineers and IT professionals working in the field, this is the resource for making the most of data to forge efficiencies and increase profits from the processes of exploration and production.

Preface xi Chapter 1 Fundamentals of Soft Computing 1 Current Landscape in Upstream Data Analysis 2 Evolution from Plato to Aristotle 9 Descriptive and Predictive Models 10 The SEMMA Process 13 High–Performance Analytics 14 Three Tenets of Upstream Data 18 Exploration and Production Value Propositions 20 Oilfield Analytics 22 I am a. . . 27 Notes 31 Chapter 2 Data Management 33 Exploration and Production Value Proposition 34 Data Management Platform 36 Array of Data Repositories 45 Structured Data and Unstructured Data 49 Extraction, Transformation, and Loading Processes 50 Big Data Big Analytics 52 Standard Data Sources 54 Case Study: Production Data Quality Control Framework 55 Best Practices 57 Notes 62 Chapter 3 Seismic Attribute Analysis 63 Exploration and Production Value Propositions 63 Time–Lapse Seismic Exploration 64 Seismic Attributes 65 Reservoir Characterization 68 Reservoir Management 69 Seismic Trace Analysis 69 Case Study: Reservoir Properties Defined by Seismic Attributes 90 Notes 106 Chapter 4 Reservoir Characterization and Simulation 107 Exploration and Production Value Propositions 108 Exploratory Data Analysis 111 Reservoir Characterization Cycle 114 Traditional Data Analysis 114 Reservoir Simulation Models 116 Case Studies 122 Notes 138 Chapter 5 Drilling and Completion Optimization 139 Exploration and Production Value Propositions 140 Workflow One: Mitigation of Nonproductive Time 142 Workflow Two: Drilling Parameter Optimization 151 Case Studies 154 Notes 173 Chapter 6 Reservoir Management 175 Exploration and Production Value Propositions 177 Digital Oilfield of the Future 179 Analytical Center of Excellence 185 Analytical Workflows: Best Practices 188 Case Studies 192 Notes 212 Chapter 7 Production Forecasting 213 Exploration and Production Value Propositions 214 Web–Based Decline Curve Analysis Solution 216 Unconventional Reserves Estimation 235 Case Study: Oil Production Prediction for Infill Well 237 Notes 242 Chapter 8 Production Optimization 243 Exploration and Production Value Propositions 245 Case Studies 246 Notes 273 Chapter 9 Exploratory and Predictive Data Analysis 275 Exploration and Production Value Propositions 276 EDA Components 278 EDA Statistical Graphs and Plots 284 Ensemble Segmentations 290 Data Visualization 292 Case Studies 296 Notes 308 Chapter 10 Big Data: Structured and Unstructured 309 Exploration and Production Value Propositions 312 Hybrid Expert and Data–Driven System 315 Case Studies 321 Multivariate Geostatistics 330 Big Data Workflows 332 Integration of Soft Computing Techniques 336 Notes 341 Glossary 343 About the Author 349 Index 351

KEITH R. HOLDAWAY is Principal Industry Consultant and Principal Solutions Architect at SAS, where he helps drive implementation of innovative oil and gas solutions and products. He also develops business opportunities for the SAS global oil and gas business unit that align SAS advanced analytics from Exploratory Data Analysis and predictive models to subsurface reservoir characterization and drilling/production optimization in conventional and unconventional fields. Prior to joining SAS, Holdaway was a senior geophysicist with Shell Oil, where he conducted seismic processing and interpretation and determined seismic attributes in 3D cubes for soft computing statistical data mining.