Jitendra Kikani
312 pp.; Adobe® Digital Edition
167 KB
ISBN: 978-1-61399-336-1
Society of Petroleum Engineers
(1 review)
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Generating economic producing opportunities in a new or an existing field is key to the success of an oil and gas company. These opportunities arise from a systematic assessment of key value drivers through relevant and appropriate measurements and by performing vigorous analysis that creates intelligence for the field.


Interwoven in this evident and simple construct is the understanding of reservoir surveillance technologies. This book will help the reader not only clearly understand the broad spectrum of issues to consider for surveillance but also provide tools, techniques and templates to adapt to his or her specific needs. The theory behind some of the equipment as well as data analytics is illustrated with examples. It is essential reading for reservoir, production, operations engineers and earth scientists. Theoretical background and concepts discussed will be valuable for the university student to gain fluency in this integrated subject.


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by Bhavadip N. Vaidya
on 10/21/2013
Senior PE - Specialist Scale in Kuwait Oil Company
Everybody knows that precaution is better than cure. "Precaution for what" is a question to all which can be known by Surveillance. Constant Surveillance is missing in our majority of Industries. With present available technology like Digital Field applications, we can get all required information continuously which needs to be analyse & evaluated by qualified people for creating DATA Bank for proper evaluation of reservoir situation. If you understand Reservoir very well the way it is mentioned in the book, it will not only simplify the operations by reducing uncertainties as well as increase the overall oil & Gas recovery. Excellent material.
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Jitendra Kikani is currently the General Manager of Reservoir Management at Chevron’s Africa and Latin America E&P Company. He has worked with Chevron for more than 17 years in various capacities, including managing their R&D in Reservoir Modeling and Simulation and leading the Well Performance team. In addition, he has been a member of Chevron’s Reserves Advisory Committee and served on various internal committees on reservoir management. Prior to Chevron, he worked for Shell Research and Schlumberger. Kikani was twice a Distinguished Lecturer for SPE (in 1999 and 2005) in the areas of Permanent Downhole Monitoring Systems and Reservoir Surveillance, respectively. He has published and written extensively and was awarded the Technical Achievement Award for the SPE Golden Gate Section in 2002. He has served on various committees for SPE and was Chairman of the Annual Technical Conference and Exhibition Program Committee in 1997. Kikani holds a BS degree in petroleum engineering from the Indian School of Mines, an MS degree in mechanical engineering from the University of California, Berkeley, and an MS degree in mathematics and a PhD degree in petroleum engineering from Stanford University.




1. Introduction

1.1 Monitoring in Industrial Systems

1.2 Military Surveillance

1.3 Reservoir Surveillance

1.4 Global Perspective

1.5 Surveillance and Decision Making

1.6 Objectives of Surveillance

1.7 How To Use the Book Effectively

2. Planning

2.1 Asset-Management Planning

2.2 Uncertainty Management

2.3 Reservoir Surveillance Plans

2.4 Developing Surveillance Plans

2.5 Other Considerations

3. Value of Information

3.1 Introduction

3.2 Decision Making

3.3 Tools and Processes

3.4 Data-Gathering Objectives and Alternatives

3.5 Fundamentals of VOI

3.6 Decision-Tree Methodology

3.7 Summary

4. Well and Production Systems

Production Systems

4.1 Surface Facility

4.2 Surface Production Monitoring

Well Systems

4.3 Well Drilling

4.4 Well Construction

4.5 Well Completions

5. Subsurface Measurement Principles

5.1 Introduction

5.2 Measurement Characteristics

5.3 Measurement Types

5.4 Measurement Quality

5.5 Instrument Reliability

5.6 Measurement Frequency

5.7 Hardware Characteristics

5.8 Measurement Principles

5.9 Fiber-Optic Measurement Principles

5.10 Calibration Principles

6. Measurement Equipment and Procedures

6.1 Introduction

6.2 Data Collection Considerations

6.3 Tool Conveyance and Positioning

6.4 Telemetry Conveyance

6.5 Measurement Equipment

6.6 Choice of Equipment

6.7 Running Procedures and Best Practices

7. Data Assessment and Quality Control
7.1 Data Analysis Model
7.2 Data-Handling Steps
7.3 Impact of Data Frequency on Analysis
7.4 Data-Quality Assessment Framework
7.5 Data Preparation
7.6 Data Errors
7.7 Treatment of Inconsistent Data
7.8 Denoising
7.9 Data Filtering
7.10 Data Smoothing
7.11 Data Correction
7.12 Production-Logging Tool Survey Good Practices
8. Data Analytics
8.1 Introduction
8.2 Data Mining
8.3 Plotting
8.4 Field Analytics
8.5 Single-Well Analytics
8.6 Interwell Analytics
8.7 Pattern Performance
8.8 Water-Alternating-Gas (WAG) Surveillance Analytics
9. Special Techniques
9.1 Introduction
9.2 Considerations for EOR Processes
9.3 Tracer Techniques
9.4 Geochemical Surveillance
9.5 4D Seismic
10. Unconventional Reservoirs
10.1 Introduction
10.2 Resource Characteristics
10.3 Appraisal Program
10.4 Production Mechanisms
10.5 Laboratory Core Measurements
10.6 Measurements To Determine Quality of Completions
11. Case Studies
11.1 Introduction
11.2 Planning
11.3 Integration
11.4 Space-Time Surveillance
11.5 Steamflood Surveillance
11.6 Workflow Automation and Collaborative Environment
Appendix A—Field Surveillance Plan
Appendix B—Uncertainty-Based Allocation 
      Method for Commingled Supply
Appendix C—Thompson’s Significance Test
Author Index
Subject Index


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