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Reliable and detailed information about the Earth's subsurface is of crucial importance throughout the geosciences. Quantitative integration of all available geophysical and geological data helps to make Earth models more robust and reliable. The aim of this book is to summarize and synthesize the growing literature on combining various types of geophysical and other geoscientific data. The approaches that have been developed to date encompass joint inversion, cooperative inversion, and statistical post-inversion analysis methods, each with different benefits and assumptions. Starting with the foundations of inverse theory, this book systematically describes the mathematical and theoretical aspects of how to best integrate different geophysical datasets with geological prior understanding and other complimentary data. This foundational basis is followed by chapters that demonstrate the diverse range of applications for which integrated methods have been used to date. These range from imaging the hydrogeological properties of the near-surface to natural resource exploration and probing the composition of the lithosphere and the deep Earth. Each chapter is written by leading experts in the field, which makes this book the definitive reference on integrated imaging of the Earth. Highlights of this volume include: * Complete coverage of the theoretical foundations of integrated imaging approaches from inverse theory to different coupling methods and quantitative evaluation of the resulting models * Comprehensive overview of current applications of integrated imaging including hydrological investigations, natural resource exploration, and imaging the deep Earth * Detailed case studies of integrated approaches providing valuable guidance for both experienced users and researchers new to joint inversion. This volume will be a valuable resource for graduate students, academics, industry practitioners, and researchers who are interested in using or developing integrated imaging approaches.

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Geophysical Monograph 218

Integrated Imaging of the Earth

Theory and Applications

Max Moorkamp

Peter G. Lelièvre

Niklas Linde

Amir Khan

Editors

This Work is a co-publication between the American Geophysical Union and John Wiley and Sons, Inc.

This Work is a co-publication between the American Geophysical Union and John Wiley & Sons, Inc.

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Brooks Hanson, Director of PublicationsRobert van der Hilst, Chair, Publications Committee

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Library of Congress Cataloging-in-Publication Data

ISBN: 978-1-118-92905-6

Cover image: Gravity anomalies (left), magnetic anomalies (middle) and snapshot of global seismic waves travelling through the Earth (right). The wavefield calculations were performed using AxiSEM; the source is a strike-slip earthquake located in the Apennines, Italy; image courtesy of Martin van Driel. The magnetic and gravity anomalies were plotted using the data and scripts described in Bezdk, A., and J. Sebera (2013), Matlab script for 3D visualizing geodata on a rotating globe, Computers & Geosciences, 56, 127–130, doi:10.1016/j.cageo.2013.03.007.

CONTRIBUTORS

Juan Carlos AfonsoCCFS—Department of Earth and Planetary Sciences Macquarie UniversitySydney, New South Wales, Australia

Miguel BoschApplied Physics Department, Engineering Faculty Universidad Central de VenezuelaCaracas, Venezuela

Knud Skou CorduaSolid Earth PhysicsNiels Bohr InstituteUniversity of CopenhagenCopenhagen, Denmark

Paul CupillardLaboratoire GeoRessourcesUniversité de Lorraine, CNRSVandoeuvre-lès-Nancy, France

Joseph DoetschSwiss Competence Center for Energy Research Supply of Electricity (SCCER-SoE), ETH ZurichZurich, Switzerland

Colin G. FarquharsonDepartment of Earth SciencesMemorial University of NewfoundlandSt. John's, Newfoundland and LabradorCanada

Javier FulleaInstitute of Geosciences (CSIC, UCM)Madrid, Spain andDublin Institute for Advanced StudiesDublin, Ireland

Luis A. GallardoEarth Science DivisionCICESEEnsenada, Mexico

Björn HeinckeGeomar, Helmholtz Centre for Ocean SciencesKiel, GermanyPresent address: Geological Survey of Denmark and GreenlandCopenhagen, Denmark

Richard W. HobbsDepartment of Earth SciencesDurham University, Science LabsDurham, United Kingdom

Marion JegenGeomar, Helmholtz Centre for Ocean SciencesKiel, Germany

Amir KhanInstitute of GeophysicsSwiss Federal Institute of TechnologyZürich, Switzerland

Peter G. LelièvreDepartment of Earth SciencesMemorial University of NewfoundlandSt. John's, Newfoundland and Labrador, Canada

Niklas LindeApplied and Environmental Geophysics GroupInstitute of Earth SciencesUniversity of LausanneLausanne, Switzerland

Thomas Mejer HansenSolid Earth PhysicsNiels Bohr InstituteUniversity of CopenhagenCopenhagen, Denmark

Max A. MejuExploration Technical Services DivisionPetronas UpstreamKuala Lumpur, Malaysia

Max MoorkampDepartment of GeologyUniversity of LeicesterLeicester, United Kingdom

Klaus MosegaardSolid Earth PhysicsNiels Bohr InstituteUniversity of CopenhagenCopenhagen, Denmark

Hendrik PaascheUFZ-Helmholtz Centre for Environmental Research Department Monitoring and Exploration TechnologiesLeipzig, Germany

Alan W. RobertsDepartment of Earth SciencesDurham University, Science LabsDurham, United KingdomPresent address: Geospatial Research LimitedDurham, United Kingdom

Andrea ZuninoSolid Earth PhysicsNiels Bohr InstituteUniversity of CopenhagenCopenhagen, Denmark

FOREWORD

Geophysics is all about being able to see the unseen and to make the subsurface as transparent as the atmosphere. With this goal in mind, integrated imaging of the Earth and the monitoring of its processes occupy a central position in the field of geophysics. Geophysical inversion has rapidly evolved in the last three decades, and especially in the last few years, to include more and more information in the inverse problem. Although classic Tikhonov regularization is still used a lot, more physically based regularization operators are currently employed in deterministic inverse problems. The use of stochastic methods is another avenue to merging various types of information while respecting the physics of the processes and their uncertainties. It is important to remember that the subsurface is not a random structure. It obeys rules governed by sedimentation processes and erosion and is shaped by tectonic forces and mineralogical transformations. Incorporating these “geological” and “geochemical” data in the geophysical inverse problem is currently a hot topic. The joint inversion of geophysical data, especially with different sensitivities to subsurface properties, is also a new frontier. This can be done using petrophysics-based approaches, structural approaches such as the cross-gradient technique, and geostatistical methods. Finally, time-lapse imaging (e.g., dynamic tomography), which can be used to monitor subsurface processes, is an area of fertile research where a variety of approaches are currently being developed. Among them is the fully coupled inversion approach where the geophysical observables are directly tied to the processes we try to image. This brings me to the role of petrophysics and mineralogy in geophysical imaging. Historically, petrophysics has been loosely used to interpret geophysical models in terms of parameters of interest. Nowadays, petrophysics is more and more used upfront, integrated directly in the inversion process. This can be done, for instance, through petrophysical clustering (in a deterministic way or by including some randomness in the petrophysical relationships for each facies of the subsurface) or by filling the gap between the variables describing a given process and the geophysical observables. Finally, some novelties include the way we parameterize the inverse problem. Geophysical images exhibit usually some sparsity, which one can take advantage of. This is often crucial when using stochastic methods because of their high computational cost.

Geophysical inversion has been treated in a number of books, so we may wonder why another book on the topic is needed. The originality of “Integrated Imaging of the Earth” is that it covers, perhaps for the first time, the topics of joint and cooperative inversion of geophysical data. In a fast growing field, this book summarizes in a very didactic way the current state-of-knowledge in combining different types of geophysical data and information to better image the subsurface. In this quest for information, to paraphrase Tarantola and Valette, the readers will find an extensive discussion of the joint inversion problem together with innovative solution strategies. In addition to developing the background theory, as expected for such a book, the authors have paid special attention to providing many detailed examples covering a broad spectrum of applications, from the shallow subsurface to the Earth's mantle. At each scale and for each application, different amounts of information may be integrated in the inverse problem, and this book illustrates exciting strategies to do so. It will propel the readers to what geophysics should be in the twenty-first century.

André Revil

Directeur de Recherche CNRS, Le Bourget-du-Lac

PREFACE

The idea for this volume emerged from a successful session on integrated imaging approaches at the AGU Fall meeting in 2012 that was organized by three contributors of this book. This session showcased a variety of different methods to unify geophysical data and demonstrated how such approaches can be applied successfully in a variety of settings. Thus when one of us was subsequently contacted by Wiley with the proposal to work on an edited volume on this topic, it was easy to see the potential content for such a book. Furthermore, we were not aware of any similar efforts that compile the current state-of-the-art in integrated Earth imaging in a concise and comprehensive manner.

Now, three years later, we are happy to see the shape that this project has taken. The chapters cover all important aspects of integrated imaging from basic theory to current areas of application. This broad view on the topic should provide newcomers with a good introduction and provide experienced practitioners with new ideas on how to advance the field. We hope that this volume becomes a valuable resource to you, as it has become to us.

Max Moorkamp

Peter G. Lelièvre

Niklas Linde

Amir Khan

Leicester, St. John's, Lausanne, and Zürich

ACKNOWLEDGMENTS

The editors would like to thank the contributing authors for their efforts in writing the individual chapters. Without their expertise and knowledge, this volume would not be what it is now. The reviewers of the various chapters helped to ensure that each contribution adheres to the highest scientific standards.

1Introduction

Max Moorkamp,1 Peter G. Lelièvre,2 Niklas Linde,3 and Amir Khan4

1 Department of Geology, University of Leicester, Leicester, United Kingdom

2 Department of Earth Sciences, Memorial University of Newfoundland, Canada

3 Applied and Environmental Geophysics Group, Institute of Earth Sciences, University of Lausanne, Lausanne, Switzerland

4 Institute of Geophysics, Swiss Federal Institute of Technology, Zürich, Switzerland

Reliable and detailed information about the Earth’s subsurface is of crucial importance throughout the geosciences. Improved descriptions of the Earth’s internal structure and composition are fundamental to better understand and predict physical processes within the Earth. Earth models are generally more reliable and practical if they unify multiple sources of information. This unification of geophysical, petrophysical, geological, and geochemical aspects ranging from theory, field measurements, and laboratory experiments forms a truly multidisciplinary challenge. In this volume, we consider primarily the combination of complementary, yet possibly disparate, types of geophysical data in presence of geological and petrophysical constraints. The literature on this subject encompasses a wide variety of analysis methods from joint inversion, cooperative inversion, and statistical post-inversion analysis methods, which come with different assumptions, advantages, and challenges. We use the term integrated imaging of the Earth to not only designate this broad range of different approaches, but also as a possible name for this emerging branch of solid-Earth geophysics that has recently gained considerable attention within the geosciences.

This book reviews and synthesizes a variety of approaches, successes, and challenges related to integrated imaging of the Earth. The aim is to promote further understanding of the science involved, provide a coherent framework for practitioners and students, and outline promising avenues for future research. The book covers the fundamental theory and a broad range of applications at spatial scales that range from meters to hundreds of kilometers. In the remainder of this chapter we discuss some of the issues common to all integrated approaches and provide definitions of key terms. We then give a short overview of the content of the different chapters in this book and conclude with a brief look to the future. Given the already extensive literature on integrated approaches, we will not provide references for all aspects discussed in this introductory chapter. Instead we refer to individual chapters in this book which provide extensive references to the current literature.

1.1. SOME DEFINITIONS

A key question in integrated Earth imaging is how to best combine various geophysical methods and data to produce robust and consistent Earth models. Presently, there exists no consistent and widely adopted terminology to describe and classify different methodologies designed for this task. Here we provide a set of definitions that we hope will enable a more consistent usage in the literature. We have chosen these definitions to best fit with the usages preferred by the contributing authors. In some cases, these choices represent a trade-off between historical and current usage trends.

Joint inversion, sometimes also termed simultaneous inversion (although we prefer the former), refers to approaches where different data types are inverted within a single algorithm, with a single objective function, and where all model parameters describing the property fields are adjusted concurrently throughout the inversion process. This stands in contrast to cooperative inversion