Quantitative Seismic Interpretation: Applying Rock Physics Tools to Reduce Interpretation Risk

by Per Avseth , Tapan Mukerji , Gary Mavko

• ISBN13: 9780521151351
• ISBN10: 052115135X
• Format: Paperback
• Copyright: 2010-07-30
• Publisher: Cambridge University Press

Summary

Demonstrating how rock physics can be applied to predict reservoir parameters, such as lithologies and pore fluids, from seismically derived attributes, this volume provides an integrated methodology and practical tools for quantitative interpretation, uncertainty assessment, and characterization of subsurface reservoirs. Including problem sets and a case-study for which seismic and well-log data and Matlab codes are provided on the Internet (http://publishing.cambridge.org/resources/0521816017), the book is intended for students of petroleum geoscience as well as professionals in the field.

Table of Contents

Preface	p. xi
Introduction to rock physics	p. 1
Introduction	p. 1
Velocity-porosity relations for mapping porosity and facies	p. 2
Fluid substitution analysis	p. 15
Pressure effects on velocity	p. 24
The special role of share wave information	p. 30
Rock physics ôWhat ifs?ö: fluid and lithology substitution	p. 42
All models are wrong…some are useful	p. 43
Rock physics interpretation of texture, llithology and compaction	p. 48
Introduction	p. 48
The link between rock physics properties and sedimentary microstructure: theory and models	p. 51
Example: rock physics interpretation of microstructure in North Sea turbidite systems	p. 70
Relating rock physics to lithofacies and depositional environments	p. 81
Example: seismic lithofacies in a North Sea turbidite system	p. 83
Rock physics depth trends	p. 90
Example: rock physics depth trends and anomalies in a North Sea field	p. 96
Rock physics templates: a tool for lilthology and fluid prediction	p. 101
Discussion	p. 107
Conclusions	p. 109
Statistical rock physics: Combining rock physics, information theory, and statistics to reduce uncertainty	p. 111
Introduction	p. 111
Why quantify uncertainty?	p. 112
Statistical rock physics workflow	p. 123
Information entropy: some simple examples	p. 132
More Carlo simulation	p. 136
Statistical classification and pattern recongniition	p. 138
Discussion and summary	p. 165
Common techniques for Quantitative seismic interpretation	p. 168
Introduction	p. 168
Qualitative seismic amplitude interpretation	p. 168
AVO analysis	p. 180
Impedance inveersion	p. 230
Forward seismic modeling	p. 252
Future directions in quantitative seismic interpreetation	p. 256
Case studies: Lithology and pore-fluid prediction from seismic data	p. 258
Case 1: Seismic reservoir mapping from 3D AVO in a North Sea turbidite system	p. 258
Case 2: Mapping lithofacies and pore-fluid probabilities in a North Sea reservoir using seismic impedance inversions and statistical rock physics	p. 278
Case 3: Sesimic lithology prediction and reservoir delineation using statistical AVO in the Grane field, North Sea	p. 295
Case 4: AVO depth trends for lithology and pore fluid classification in unconsolidated deep-water systems, offshore West Africa	p. 306
Case 5: Sesimic reservoir mapping using rock physics templates. Example from a North Sea turbidite system	p. 312
Workflows and Guidelines	p. 317
AVO reconnaissance	p. 318
Rock physics ôWhat ifsö and AVO feasibility studies	p. 320
RPT analysis	p. 322
AVO classification constrained by rock physics depth trends	p. 323
Seismic reservoir characterization constrained by lithofacies analysis and statistical rock physics	p. 325
Why and when should we do quantitative seismic interpretation?	p. 328
Hands-on	p. 332
Introduction	p. 332
Problems	p. 332
Project	p. 336
References	p. 340
Index	p. 356
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