Harness oil and gas big data with analytics : optimize exploration and production with data driven models / Keith R. Holdaway.

Format:

Book

Author/Creator:

Holdaway, Keith R., author.

Series:

Wiley and SAS business series

Wiley & SAS Business Series

Language:

English

Subjects (All):

Petroleum industry and trade--Statistics.

Petroleum industry and trade.

Gas industry--Statistics.

Gas industry.

Big data.

Genre:

Electronic books.

Statistics.

Physical Description:

1 online resource (378 pages) : illustrations.

Place of Publication:

Hoboken, New Jersey : Wiley, 2014.

System Details:

text file

Summary:

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. Book jacket.

Contents:

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.

Notes:

Includes index.

Description based on print version record.

Local Notes:

Electronic reproduction. Palo Alto, Calif. : ebrary, 2015. Available via World Wide Web. Access may be limited to ebrary affiliated libraries.

Other Format:

Print version: Holdaway, Keith R. Harness oil and gas big data with analytics : optimize exploration and production with data driven models.

ISBN:

9781118910955

OCLC:

880425786

Access Restriction:

Restricted for use by site license.