Description

Book Synopsis
Use big data analytics to efficiently drive oil and gas exploration and production

Harness Oil and Gas Big Data with Analytics provides 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. This spans exploration, development, production and rejuvenation of oil and gas assets.

The book serves as a guide for fully leveraging data, statistical, and quantitative analysis, exploratory and predictive modeling, and fact-based management to drive decision making in oil and gas operations. This comprehensive resource delves into the three major issues that face the oil and gas industry during the exploration and production stages:

  • Data management, including storing massive quantities of data in a m

    Table of Contents

    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

Petroleum Big Data SAS

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    A Hardback by Keith R. Holdaway

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      Publisher: John Wiley & Sons Inc
      Publication Date: Publication Date: 11/07/2014
      ISBN13: 9781118779316, 978-1118779316
      ISBN10: 1118779312
      Also in:
      Economics

      Description

      Book Synopsis
      Use big data analytics to efficiently drive oil and gas exploration and production

      Harness Oil and Gas Big Data with Analytics provides 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. This spans exploration, development, production and rejuvenation of oil and gas assets.

      The book serves as a guide for fully leveraging data, statistical, and quantitative analysis, exploratory and predictive modeling, and fact-based management to drive decision making in oil and gas operations. This comprehensive resource delves into the three major issues that face the oil and gas industry during the exploration and production stages:

      • Data management, including storing massive quantities of data in a m

        Table of Contents

        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

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