Seismic Reflections of Rock Properties

Similar documents
Integrated Reservoir Asset Management

Stanford Rock Physics Laboratory - Gary Mavko. Basic Geophysical Concepts

Because rock is heterogeneous at all scales, it is often invalid

RESERVOIR GEOSCIENCE AND ENGINEERING

7.2.4 Seismic velocity, attenuation and rock properties

Integration of Geological, Geophysical, and Historical Production Data in Geostatistical Reservoir Modelling

DecisionSpace. Prestack Calibration and Analysis Software. DecisionSpace Geosciences DATA SHEET

Graduate Courses in Petroleum Engineering

Figure 2-10: Seismic Well Ties for Correlation and Modelling. Table 2-2: Taglu Mapped Seismic Horizons

Reservoir Modelling and Interpretation with Lamé s Parameters: A Grand Banks Case Study

Integration of reservoir simulation with time-lapse seismic modelling

Hydrocarbon reservoir modeling: comparison between theoretical and real petrophysical properties from the Namorado Field (Brazil) case study.

Nautilus Global Schedule 2016

BS PROGRAM IN PETROLEUM ENGINEERING (VERSION 2010) Course Descriptions

Pore Radius and Permeability Prediction from Sonic Velocity

WELL LOGGING TECHNIQUES WELL LOGGING DEPARTMENT OIL INDIA LIMITED

Frio Formation of the Gulf Coast* By Michael D. Burnett 1 and John P. Castagna 2

Travel Time Modelling using Gamma Ray and Resistivity Log in Sand Shale Sequence of Gandhar Field

DecisionSpace Earth Modeling Software

RESERVOIR EVALUATION. The volume of hydrocarbons in a reservoir can be calculated:

Developing integrated amplitude driven solutions for pore content prediction through effective collaboration

EarthStudy 360. Full-Azimuth Angle Domain Imaging and Analysis

Guidelines: Reporting & Requirements for Geoscience Programs & Operations

Collecting and Analyzing Big Data for O&G Exploration and Production Applications October 15, 2013 G&G Technology Seminar

TABLE OF CONTENTS PREFACE INTRODUCTION

MILLER AND LENTS, LTD.

The successful integration of 3D seismic into the mining process: Practical examples from Bowen Basin underground coal mines

Unconventional Challenges: Integrated Analysis for Unconventional Resource Development Robert Gales VP Resource Development

Broadband seismic to support hydrocarbon exploration on the UK Continental Shelf

Appendix 25. Content of a Competent Person s Report for Petroleum Reserves and Resources

Shuey s Two-Term Approximation

Certificate Programs in. Program Requirements

Marine broadband seismic: Is the earth response helping the resolution revolution? N. Woodburn*, A. Hardwick, and R. Herring, TGS

CIM DEFINITION STANDARDS - For Mineral Resources and Mineral Reserves

Periodical meeting CO2Monitor. Leakage characterization at the Sleipner injection site

Figure 1. The only information we have between wells is the seismic velocity.

Management Across Cultures

Abstract. 1. Introduction

14TH INTERNATIONAL CONGRESS OF THE BRAZILIAN GEOPHYSICAL SOCIETY AND EXPOGEF

PROHITECH WP3 (Leader A. IBEN BRAHIM) A short Note on the Seismic Hazard in Israel

DEPARTMENT OF PETROLEUM ENGINEERING Graduate Program (Version 2002)

Introduction to Petroleum Geology and Geophysics

Waterflooding identification of continental clastic reservoirs based on neural network

I N T E L L I G E N T S O L U T I O N S, I N C. DATA MINING IMPLEMENTING THE PARADIGM SHIFT IN ANALYSIS & MODELING OF THE OILFIELD

Module 1 : Site Exploration and Geotechnical Investigation. Lecture 5 : Geophysical Exploration [ Section 5.1 : Methods of Geophysical Exploration ]

Parameters That Influence Seismic Velocity Conceptual Overview of Rock and Fluid Factors that Impact Seismic Velocity and Impedance

INDIRECT METHODS SOUNDING OR PENETRATION TESTS. Dr. K. M. Kouzer, Associate Professor in Civil Engineering, GEC Kozhikode

Guidelines for the Estimation and Reporting of Australian Black Coal Resources and Reserves

Securing the future of decom

Tu-P07-02 Workaround to Build Robust Facies Model with Limited Input Data - A Case Study from North West Kuwait

Well-logging Correlation Analysis and correlation of well logs in Rio Grande do Norte basin wells

University of Cyprus

College of Science and Health ENVIRONMENTAL SCIENCE & GEOGRAPHY Course Outline

Which physics for full-wavefield seismic inversion?

Uncertainty Study on In-Place Volumes in Statoil

Data Mining and Exploratory Statistics to Visualize Fractures and Migration Paths in the WCBS*

Shale Field Development Workflow. Ron Dusterhoft

An Integrated Rock Catalog for E&P Geotechnologists

Geothermal. . To reduce the CO 2 emissions a lot of effort is put in the development of large scale application of sustainable energy.

Tight Gas Reservoir Characterization

Full azimuth angle domain decomposition and imaging: A comprehensive solution for anisotropic velocity model determination and fracture detection

Search and Discovery Article #40256 (2007) Posted September 5, Abstract

FAN group includes NAMVARAN UPSTREAM,

Value Addition Using Cement Evaluation by Ultra Sonic Imaging Tool In Upper Assam Oil Fields

Search and Discovery Article #40356 (2008) Posted October 24, Abstract

Petrel TIPS&TRICKS from SCM

P-83 Lawrence Berkeley National Laboratory High-Resolution Reservoir Characterization Using Seismic, Well, and Dynamic Data

Name: Date: Class: Finding Epicenters and Measuring Magnitudes Worksheet

GROUND RESPONSE OF KATHMANDU VALLEY ON THE BASIS OF MICROTREMORS

FINDING MEANINGFUL PERFORMANCE MEASURES FOR HIGHER EDUCATION A REPORT FOR EXECUTIVES

Decomposition of Marine Electromagnetic Fields Into TE and TM Modes for Enhanced Interpretation

Petrophysical Well Log Analysis for Hydrocarbon exploration in parts of Assam Arakan Basin, India

Deep Geothermal energy and groundwater in

Operations in the Arctic areas? New challenges: Exploration Development Production

Application of Nuclear Magnetic Resonance in Petroleum Exploration

Paradigm High Tech and Innovative Software Solutions for the Oil and Gas Industry

SECURITY AND QUALITY OF SERVICE IN AD HOC WIRELESS NETWORKS

Development of EM simulator for sea bed logging applications using MATLAB

technical article Pål T. Gabrielsen, 1* Peter Abrahamson, 2 Martin Panzner, 1 Stein Fanavoll 1 and Svein Ellingsrud 1

sufilter was applied to the original data and the entire NB attribute volume was output to segy format and imported to SMT for further analysis.

Frequently Asked Questions on the Alberta Tier 1 and Tier 2 Soil and Groundwater Remediation Guidelines. February 2008

Italy - Porto Tolle: storage in offshore saline aquifer

Geology. Administered by the Department of Physical Sciences within the College of Arts and Sciences.

Understanding Porosity and Permeability using High-Pressure MICP Data: Insights into Hydrocarbon Recovery*

RPSEA Project Management Plan

Analysis of GS-11 Low-Resistivity Pay in Main Gandhar Field, Cambay Basin, India A Case Study

UPSTREAM OIL AND GAS INDUSTRY IN KENYA

Calibration of Uncertainty (P10/P90) in Exploration Prospects*

Digital core flow simulations accelerate evaluation of multiple recovery scenarios

Statistical Rules of Thumb

When to Use Immediate Settlement in Settle 3D

EnerCom The Oil & Gas Conference. An Integrated Workflow for Unconventional Reservoirs

Primary Mathematics. Capitalising on ICT for today and tomorrow

Eagle Ford Shale Exploration Regional Geology meets Geophysical Technology. Galen Treadgold Bruce Campbell Bill McLain

Transcription:

Seismic Reflections of Rock Properties Key global geophysical applications, such as prospecting for oil and gas, require interpretation of the seismic response from the subsurface to assess rock properties and conditions behind the observed seismic reflection (amplitude), and to create an accurate geological subsurface model. This book now provides an accessible guide to using the rock-physics-based forward modeling approach, systematically linking the properties and conditions of rock to the seismic amplitude. Providing a number of practical workflows, the book shows how to methodically vary lithology, porosity, and rock type, as well as pore fluids and reservoir geometry; calculate the corresponding elastic properties; and then generate synthetic seismic traces. These synthetic traces can then be compared to actual seismic traces from the field: the practical implication being that, if the actual seismic response is similar, the rock properties in the subsurface are similar as well. The book catalogues various cases, such as siliclastic and carbonate natural rocks, and time-lapse seismic monitoring, and also discusses the effect of attenuation on seismic reflections. It shows how to build earth models (pseudo-wells) using deterministic as well as statistical approaches, and includes case studies based on real well data. This is a vital guide for researchers and petroleum geoscientists in industry and academia, providing sample catalogues of synthetic seismic reflections from a variety of realistic reservoir models with direct application to oil and gas exploration and reservoir characterization and monitoring. Jack Dvorkin is a Senior Research Scientist in the Department of Geophysics at Stanford University. His primary research interests are theoretical rock physics and its practical applications as well as computational rock physics, and he has delivered dozens of industrial rock physics short-courses and lectures worldwide (USA, Canada, Colombia, Brazil, India, China, Japan, Norway, Germany, Italy). Dr. Dvorkin has published around 150 professional papers and has also co-authored two books including The Rock Physics Handbook (Cambridge, 2009). Mario A. Gutierrez is a Principal Geophysicist at Shell International Exploration and Production Inc., working primarily on the application of seismic- and rock physics-based methods for evaluating and risking the presence of reservoir rocks and hydrocarbons to support business decisions and recommendations on oil and gas exploration projects worldwide. Dr. Gutierrez holds a Ph.D. in Geophysics from Stanford University, and has previously held leading applied research and operations positions at Shell, BHP Billiton Petroleum, Ecopetrol, and various seismic contractors, working on rock physics and seismic attributes modeling, reservoir characterization, shallow geo-hazards, and pore pressure prediction. Dario Grana is an Assistant Professor at the University of Wyoming. He has worked for four years on seismic reservoir characterization at Eni Exploration and Production in Milan, and then moved to Stanford where he received his Ph.D. in geophysics in 2013 during which time he also published six peer-reviewed journal papers and presented at several international conferences. Dr. Grana s main research interests are rock physics, seismic reservoir characterization, geostatistics, and inverse problems for reservoir modeling.

Seismic Reflections of Rock Properties Jack Dvorkin Stanford University, California Mario A. Gutierrez Shell International Exploration and Production, Inc. Texas Dario Grana University of Wyoming

University Printing House, Cambridge CB2 8BS, United Kingdom Published in the United States of America by Cambridge University Press, New York Cambridge University Press is part of the University of Cambridge. It furthers the University s mission by disseminating knowledge in the pursuit of education, learning and research at the highest international levels of excellence. Information on this title: /9780521899192 2014 This publication is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published 2014 Printed in the United Kingdom by TJ International Ltd, Padstow, Cornwall A catalogue record for this publication is available from the British Library ISBN 978-0-521-89919-2 Hardback Cambridge University Press has no responsibility for the persistence or accuracy of URLs for external or third-party internet websites referred to in this publication, and does not guarantee that any content on such websites is, or will remain, accurate or appropriate.

To our families

Contents Preface Acknowledgments page xiii xvii Part I The basics 1 1 Forward modeling of seismic reflections for rock characterization 3 1.1 Introduction 3 1.2 Quantifying elastic properties of earth by forward modeling: a primer 4 1.3 Quantifying rock properties by forward modeling: a primer 9 1.4 Rock physics transforms: a primer 9 1.5 Synthetic seismic catalogues 10 2 Rock physics models and transforms 13 2.1 Rock physics transforms 13 2.2 Elastic constants 13 2.3 Solid phase 14 2.4 Fluid phase 16 2.5 Fluid substitution 18 2.6 The Raymer Hunt Gardner transform 22 2.7 Other S-wave velocity predictors 24 2.8 Contact-cement model 26 2.9 Soft-sand model 28 2.10 Stiff-sand model 29 2.11 Constant-cement model 30 2.12 Inclusion models 31 2.13 Summary of the models 34 2.14 Properties of the pore fluid phases 35 2.15 A note on effective and total porosity and fluid substitution 35 2.16 Example of applying rock physics models to simulate seismic amplitude 41 vii

viii Contents 3 Rock physics diagnostics 43 3.1 Quantitative diagnostics 43 3.2 Qualitative diagnostics: staring at the data 47 3.3 Word of caution when using well data 49 Part II Synthetic seismic amplitude 51 4 Modeling at an interface: quick-look approach 53 4.1 Reflection modeling at an interface: the concept 53 4.2 Normal reflectivity and reflectivity at an angle 53 4.3 Forward modeling using elastic constants 56 4.4 Forward modeling directly from rock properties 60 5 Pseudo-wells: principles and examples 68 5.1 Sandwich (three-layer) model 68 5.2 Geologically consistent inputs 72 5.3 Depth and compaction 83 6 Pseudo-wells: statistics-based generation 90 6.1 Introduction 90 6.2 Monte Carlo simulation 91 6.3 Monte Carlo simulation with spatial correlation 92 6.4 Monte Carlo simulation within facies 97 6.5 Stochastic simulation of related variables 98 6.6 Examples and sensitivity analysis 100 6.7 Pseudo-logs of facies 102 6.8 Spatial simulation of rock properties and reflections 106 Part III From well data and geology to earth models and reflections 113 7 Clastic sequences: diagnostics and V s prediction 115 7.1 Unconsolidated gas sand 115 7.2 Consolidated cemented gas sand 125 8 Log shapes at the well scale and seismic reflections in clastic sequences 132 8.1 Examples of shapes encountered in clastic sequences 132 8.2 Typical shapes and pseudo-wells in clastic sequences 137 9 Synthetic modeling in carbonates 153 9.1 Background and models 153

ix Contents 9.2 Laboratory and well data 157 9.3 Pseudo-wells and reflections 159 10 Time lapse (4D) reservoir monitoring 165 10.1 Background 165 10.2 Fluid substitution on velocity pressure data 169 10.3 Synthetic seismic gathers 172 10.4 Conclusion 175 Part IV Frontier exploration 177 11 Rock-physics-based workflow in oil and gas exploration 179 11.1 Introduction 179 11.2 Rock physics modeling for amplitude calibration 180 11.3 Log and seismic quality control and conditioning 181 11.4 Velocity in exploration seismology 182 11.5 Time-to-depth calibration 183 11.6 Rock typing 185 11.7 Seismic forward modeling 185 11.8 Rock property upscaling 186 11.9 Depth trends, rock physics diagnostics, and model formulation 187 11.10 Using trends at prospect location 194 12 DHI validation and prospect risking 197 12.1 Introduction 197 12.2 Feasibility studies 197 12.3 Recognition of seismic anomalies 198 12.4 DHI validation and prospect risking 199 Part V Advanced rock physics: diagenetic trends, self-similarity, permeability, Poisson s ratio in gas sand, seismic wave attenuation, gas hydrates 205 13 Rock physics case studies 207 13.1 Universality of diagenetic trends 207 13.2 Self-similarity in rock physics 212 13.3 Elastic properties of rock and its permeability 218 13.4 Stratigraphy-constrained rock physics modeling 220

x Contents 14 Poisson s ratio and seismic reflections 225 14.1 The high Poisson s ratio issue in gas sand 225 14.2 Physics-based explanations 229 14.3 But how much does it really matter? 237 15 Seismic wave attenuation 239 15.1 Background and definitions 239 15.2 Attenuation and modulus (velocity) dispersion 241 15.3 Q data 243 15.4 Modulus dispersion and attenuation at partial saturation 244 15.5 Modulus dispersion and attenuation in wet rock 252 15.6 Examples 254 15.7 Effect of attenuation on seismic traces 255 15.8 Approximate theory of S-wave attenuation 256 16 Gas hydrates 262 16.1 Background 262 16.2 Rock physics models for sediment with gas hydrate 264 16.3 Attenuation in sediment with gas hydrate 269 16.4 Pseudo-wells and synthetic seismic in gas hydrates 273 Part VI Rock physics operations directly applied to seismic amplitude and impedance 275 17 Fluid substitution on seismic amplitude 277 17.1 Background 277 17.2 Primer: model-based reflection between two half-spaces 278 17.3 Model-based effect of thickness 279 17.4 Applying a model-based approach to a case study 285 17.5 Lessons and conclusions 289 17.6 Practical application 291 18 Rock physics and seismically derived impedance 292 Part VII Evolving methods 297 19 Computational rock physics 299 19.1 Third source of controlled experimental data 299 19.2 Scale of experiment and trends 301 19.3 More examples 304

xi Contents 19.4 Multiphase flow 305 19.5 Conclusion 307 Appendix: Direct hydrocarbon indicator checklist 308 References 312 Index 323 Color plates appear between pages 126 and 127.

Preface xiii Rock physics is the part of geophysics concerned with establishing relations between various properties of rocks. Because the elastic radiation is the main agent that allows us to illuminate the subsurface, the primary emphasis of rock physics has been to relate the elastic properties of rock, including the P- and S-wave velocity, P- and S-wave impedance, and Poisson s ratio to porosity, lithology, and pore fluid. A significant number of such rock physics models (transforms) have been developed based on experimental data or physical theories or both. These models enable us to forward model the elastic properties of rock as a function of porosity, rock texture (arrangement of grains or cavities at the pore-scale level), mineralogy, and the compressibility of the pore fluid. Because the seismic reflection depends on the contrast of the elastic properties in the subsurface, rock physics helps generate synthetic seismic reflections at an interface between two different rock types, such as a non-reservoir rock cap and petroleum reservoir, as well as at a fluid contact within a reservoir itself (e.g., gas/oil contact and oil/water contact). However, in field applications, we face an inverse problem whose solution is not unique: how to interpret a seismic event, which is manifested by a reflection amplitude that stands out of the background, in terms of reservoir properties and conditions. The inherent difficulty of this problem is that the number of variables required to produce the elastic properties of porous rock is larger than the number of seismic observables. Various approaches have been developed to tackle this uncertainty; most of them based on statistical techniques that help assess the probability of the occurrence of a certain object (e.g., high-porosity sand filled with oil) at a given location in a 3D subsurface. Even when using statistical techniques, forward modeling of seismic reflections based on either well log data or theoretical rock physics is a key element of interpreting seismic data. This book concentrates on such rock-physics-based modeling. The main idea is to create an earth model consistent with the geological understanding at the location, compute the respective elastic properties, and generate synthetic seismic traces. Rock physics enables us to systematically perturb this earth model by varying porosity, mineralogy, and pore fluid, as well as the thickness of the target and the properties of the bounding non-reservoir rock. Systematically conducted perturbational modeling leads

xiv Preface to a catalogue of seismic reflections that can serve as a field guide to interpreting a seismic event observed in the field under the assumption that if a synthetic reflection matches the real one, the rock properties and conditions behind the real event may be the same as used to produce the matching synthetic event. Because of the flexibility of existing rock physics models, we can even bracket the interpretation of an event by finding the extreme cases outside which such an event is impossible under sitespecific geologic conditions. Here we systematically explore this deterministic as well as statistics-based synthetic forward-modeling approach to generate seismic reflections of rock properties. All examples are based on seismic traces computed for a 1D earth model with the reflecting waves generated by the incidence waves traveling at a varying angle of incidence to an interface between rock types. This book includes 7 parts, 19 chapters, and an appendix. Part I deals with the basics needed in rock-physics-based forward modeling. In Chapter 1, we introduce the concept of rock-physics-based forward modeling, discuss the non-uniqueness of this approach, revisit the concept of rock physics transforms, and give an example of a synthetic seismic catalogue. Chapter 2 reviews theoretical and empirical rock physics models, including the velocity porosity mineralogy models as well as methods of fluid substitution, that is, computing the elastic properties of a sample filled with a hypothetical fluid if such properties are measured on the same sample filled with a different fluid. Chapter 3 discusses rock physics diagnostics, a technique that uses well or laboratory data to find an appropriate theoretical model that mimics and explains these data. This process includes two basic steps: bringing all the samples to the common fluid denominator via fluid substitution and then matching the data points with the model curves. Part II is dedicated to the principles of synthetic seismic modeling. Chapter 4 introduces quick-look rock physics modeling applets, rock-physics-based displays where the user can quickly generate a synthetic gather at an interface depending on the porosity and mineralogy of the reservoir and non-reservoir rock located above it, as well as fluid type and saturation in the reservoir. Such applets can be fairly easily coded in most programming environments. Chapter 5 discusses the principles of building a pseudo-well relevant to local geology. Special attention is paid to depositionally consistent inputs and the resulting relations between these inputs, such as relations between clay content and porosity and clay content and irreducible water saturation. Compaction trends examined in this chapter also serve as constraints for the porosity range at a given depth. Chapter 6 discusses the principles of statistics-based perturbations for pseudo-well generation based on existing well data, including interdependence of basic rock properties, such as porosity, clay content, and water saturation. We also describe a procedure to create pseudo-logs of porosity and other rock properties that honor the vertical trends and the vertical continuity present in the input well data. An example is also

xv Preface given of generating these rock properties in 3D, populating a 3D earth model with the elastic properties and generating the normal and offset reflections. Part III discusses how to use well data and geology to arrive at earth models and respective seismic amplitude. In Chapter 7, we examine two well datasets, both from clastic sedimentary environments, one where the reservoir sand is unconsolidated and soft and the other where the sand is cemented. We systematically conduct the rock physics diagnostics, establish relevant rock physics models, create rock-physics-based modeling applets for both cases, and provide synthetic seismic gathers for various perturbations of the original well data curves. Chapter 8 discusses vertical log shapes of lithology and porosity associated with various depositional sequences and events in clastic sediments. We construct relevant pseudo-wells and select appropriate rock physics models to translate the sedimentology-driven variables into the elastic properties. Synthetic seismic gathers generated based on such depositional scenarios can serve as a quick-look catalogue for identifying real seismic events. Chapter 9 discusses rock physics models and laboratory data for carbonate reservoirs. We construct several pseudo-wells to analyze the effects of the pore fluid, porosity, and mineralogy of the seismic gathers as well as generate pseudo-wells and synthetic seismic traces for two concrete depositional scenarios. In Chapter 10, we address the changes in seismic reflections due to hydrocarbon production (the time-lapse of 4D seismic). The two main factors that affect the elastic properties of the reservoir are the changes in the pore pressure and hydrocarbon saturation. We show how these two factors interact to contribute to discernible temporal amplitude variations or cancel each other and leave the amplitude practically unchanged. Part IV is dedicated to practical approaches to frontier exploration. Chapter 11 describes a rock-physics-based practical workflow used in hydrocarbon exploration, including selection of a rock physics model, time-to-depth calibration, and depth compaction curves. These results are then used in synthetic seismic gather generation and hydrocarbon- and depth-driven AVO classification for potential hydrocarbon detection. The following Chapter 12, continues the practical workflow topic and discusses methods of validation of apparent hydrocarbon indicators and assesses the probability of success in actually tapping into a hydrocarbon reservoir after drilling a wildcat well. The direct hydrocarbon indicator check list described in this chapter is placed in the appendix. Part V deals with advanced rock physics applications. In Chapter 13 we discuss four rock physics diagnostics case studies that reveal the universality of diagenetic trends, meaning that the same theoretical model can be used at different geographical locations and depth intervals; the self-similarity in rock physics, showing that although the porosity and clay content affect the elastic moduli of the rock in separate ways, a

xvi Preface certain combination of these two variables can uniquely define that elastic property; a study that reveals that sometimes there is a relation between porosity, stiffness of the rock, and its permeability; and stratigraphy-constrained rock physics modeling based on a dataset from a Tertiary fluvial oil field. In Chapter 14, we explore the issue of the S-wave velocity and Poisson s ratio prediction using rock physics models. The problem addressed is that many effectivemedium-based models predict fairly small Poisson s ratio in gas-saturated sand while the actual well data may sometimes comply with this prediction but also show a much larger Poisson s ratio. We discuss the physical reasons for such disparities and, in the end, show how discrepancies in Poisson s ratio prediction affect synthetic seismic gathers and whether such variations affect the interpretation of a seismic anomaly. Chapter 15 presents theoretical methods for predicting attenuation from rock properties measured in the well and elaborates on the basics of attenuation theory and experimental results. Example synthetic seismic gathers are generated based on well data with and without including attenuation and are compared to each other. Chapter 16 is dedicated to the rock physics of gas hydrates and discusses real data collected in gas hydrate wells as well as theoretical models that relate the elastic moduli in sediment with gas hydrates to the hydrate fraction in the pore space. It has been observed that the presence of hydrates often results in significant attenuation of seismic energy traveling through the sediment. This effect is theoretically explained and synthetic seismograms are generated with the attenuation taken into account. In Part VI we discuss how rock physics operations can be applied directly to seismic amplitude and seismically derived impedance. Chapter 17 presents an example of a rock physics operation, fluid substitution, performed directly on the seismic amplitude. We show, by generating synthetic seismic reflections, that in some cases there are fairly straightforward transforms between the amplitude measured at a wet reservoir and that measured at the same reservoir but filled with gas. Such relations may hold in a range of porosity, mineralogy, and thickness variations. Synthetic modeling is followed by a field example where the original full seismic stack was obtained at a wet reservoir and then transformed into that at a hypothetical gas reservoir. The elements of rock physics analysis behind this transform are discussed in detail. Chapter 18 shows how simple rock physics analysis can serve to delineate the fluid contact and also map porosity based on a seismic impedance inversion section from a North Sea field. Part VII is dedicated to an evolving rock physics technique, computational rock physics. It contains one chapter, Chapter 19, where we discuss how computational (or digital) rock physics can serve as a source of controlled experimental data for designing rock physics models and trends in a range of spatial scales of measurement. We discuss the disparity between the scale of various controlled experiments and show that the transforms obtained between two rock properties, such as porosity and velocity, at one scale may be stable in a range of spatial scales.

Acknowledgments All three authors learned about rock physics and learned rock physics itself at the Stanford Rock Physics Laboratory founded more than three decades ago by Amos Nur. Amos has continuously encouraged advancing rock physics theoretically and experimentally, merging it with geology, and eventually making it a practical instrument in exploration and development. This book would not have happened without Amos. Neither would it have happened without Gary Mavko, one of Nur s first students and a leading rock physics scientist and practitioner, domestically and internationally. His knowledge and advice have contributed to shaping and implementing our ideas. Gary has generously provided the software for generating the synthetic seismic traces used throughout this book. His editorial comments have served to improve the manuscript. We also acknowledge our Stanford colleague Tapan Mukerji for help and support, as well as numerous colleagues in the industry for critically discussing ideas and approaches. The computational rock physics chapter has benefited from help of our colleagues at Ingrain, Inc. We thank Elizabeth Diaz for encouragement and help. We also thank Dawn Burgess for crucial editorial help. The authors thank the Society of Exploration Geophysicists for permission to repurpose material from a number of the authors papers originally published in Geophysics and The Leading Edge. xvii