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Satellite Radar Interferometry
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Subsidence Monitoring Techniques
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Remote Sensing and Digital Immage Processing
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VOLUME 14
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Series Editor:
EARSeL Series Editor:
Freek D. van der Meer
André Marçal
Department of Earth Systems Analysis, International Institute for Geo-Information Science and Earth Observation (ITC), Enchede, The Netherlands & Department of Physical Geography, Faculty of Geosciences, Utrecht University, The Netherlands
Faculty of Sciences, University of Porto, Porto, Portugal
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Editorial Advisory Board:
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Michael Abrams
Helsinki University of Technology, Finland
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NASA Jet Propulsion Laboratory, Pasadena, CA, U.S.A.
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Paul Curran University of Bournemouth, U.K.
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EARSeL Editorial Advisory Board:
Mario Gomarasca CNR - IREA Milan, Italy
Martti Hallikainen
Håkan Olsson Swedish University of Agricultural Sciences, Sweden
Eberhard Parlow
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Arnold Dekker
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CSIRO, Land and Water Division, Canberra, Australia
Rainer Reuter
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Steven M. de Jong
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Department of Applied Mathematics, Faculty of Geosciences, Utrecht University, The Netherlands
University of Oldenburg, Germany
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Michael Schaepman
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Centre for Geo-Information, Wageningen UR, The Netherlands
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University of Basel, Switzerland
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For other volumes published in this series go to www.springer.com/series/6447
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Satellite Radar Interferometry Subsidence Monitoring Techniques
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V.B.H. Ketelaar
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Delft University of Technology, Delft, The Netherlands
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V.B.H. Ketelaar Delft University of Technology, Delft, and Nederlandse Aardolie Maatschappij, Assen, The Netherlands
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Remote Sensing and Digital Image Processing
ISSN 1567-3200
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ISBN 978-1-4020-9427-9
e-ISBN 978-1-4020-9428-6
Library of Congress Control Number: 2008944289
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© 2009 Springer Science + Business Media B.V. No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work.
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Preface
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Since the start of hydrocarbon production in the Netherlands, measurement campaigns have been performed to measure the resulting subsidence, to which gas and oil companies in the Netherlands are legally obliged. The majority of the gas fields in the Netherlands, including the Groningen gas field, are operated by Nederlandse Aardolie Maatschappij B.V. (NAM). Different subsidence measurement techniques (leveling, GPS) have been utilized since the 1960s. Synchronously, geodetic estimation methodologies have been developed to estimate subsidence due to hydrocarbon production from the measurements, in which the Delft Institute of Earth Observation and Space Systems (DEOS) has been closely involved. Since the 1990s, satellite radar interferometry (InSAR) as a deformation monitoring technique has developed. However, the situation in the Groningen area is not favorable (temporal decorrelation, rural areas, atmospheric disturbances, small deformation rates— several mm/year—over a large spatial extent). In 2003, the project ‘Fundamenteel Onderzoek Radar Interferometrie’ was approved (Regeling Technologische Samenwerking), which enabled a four year PhD research to investigate the feasibility of InSAR for monitoring subsidence due to hydrocarbon production.
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Acknowledgements This research has been performed in cooperation between Delft University of Technology and NAM, between the radar remote sensing group of Prof. Hanssen (DEOS, DUT) and the onshore surveys team of Lammert Zeijlmaker (NAM). The project has been supported by SenterNovem, agency of the Dutch Ministry of Economic Affairs. The SAR data were kindly provided by the European Space Agency (ESA) for Category 1 project 2724. I am very grateful to my promotors Prof. Hanssen and Prof. Teunissen, and Lammert Zeijlmaker of NAM for giving me the opportunity to perform this scientific research with such direct practical implementations. I have experienced a very pleasant and open working environment both at Delft University of Technology and at NAM. In particular, I would like to thank Prof. Hanssen for the support during the entire research period, the detailed review of this book and many valuable suggestions. I also greatly appreciate the feedback and critical comments I have received from Prof. Teunissen and the members of the examination committee. Furthermore, I would like to thank all (former) members of the radar remote sensing group at Delft University of Technology for the pleasant working environment: Joaquin Munoz Sabater, Freek van Leijen, Petar Marinkovic, Yue Huanyin, Swati Gehlot, Rossen Grebenitcharsky, Zbigniew Perski, Ayman Elawar, Liu Guang, Miguel Caro Cuenca, Mahmut Arikan, Jia Youliang, Frank Kleijer, Gert Jan van Zwieten and Shizhuo Liu, and Bianca Cassee during her MSc graduation project. Special thanks go to Freek van Leijen and Petar Marinkovic, whose work has definitely speeded up the obtained results for subsidence monitoring in the Groningen
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region, for the open attitude during my entire PhD research period, and the inspiring discussions. I would also like to thank Bert Kampes for his quick response to many questions. Thanks go as well to Alireza Amiri-Simkooei for assistance with Variance Component Estimation, Roderik Lindenbergh for assistance with geostatistics, Ria Scholtes for the administrative support, and to all other members of the Mathematical Geodesy and Positioning (MGP) department of Delft University of Technology for the nice working environment. I would like to thank Hans Garlich and Joop Gravesteijn for the assistance with leveling the corner reflectors. Furthermore, I would like to thank Adriaan Houtenbos for the useful hints he has given me. Going back to the initial contact at the start of my PhD research, I would like to thank Frank Kenselaar for reacting enthusiastically when contacting him after spending four and a half years working in the industry. At NAM, I have received a lot of useful feedback from the subsidence monitoring team of Lammert Zeijlmaker and the geomechanics team of Dirk Doornhof. I have appreciated the cooperation with Simon Schoustra, Wilfred Veldwisch and Stefan Kampshoff, and would like to thank Onno van der Wal for all subsidence prognoses. Finally, I would like to thank my parents Gert and Marijke and brother Joris (the cover designer) for their patience and support.
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Audience The research described in this book investigates the applicability of satellite radar interferometry (InSAR) for deformation monitoring, in particular subsidence due to hydrocarbon extraction. It covers the subject in a generic way, from the precision and reliability of InSAR as a measurement technique to the estimation of the deformation signal of interest in the potential presence of multiple deformation causes. It provides an overview of the Persistent Scatterer InSAR (PSI) theory, and subsequently focuses on the accuracy of the parameter estimates. For the reliability assessment of InSAR deformation estimates, which is essential for operational use, the multi-track datum connection procedure is introduced. The presented methodologies are demonstrated in an integrated way for the entire northern part of the Netherlands and a part of Germany (covering ∼15.000 km2 ) using time series of ERS and Envisat acquisitions. The capabilities of PSI for wide-scale monitoring of subsidence rates of several millimeters per year in rural areas are shown. Furthermore, it is demonstrated that the temporal observation density of PSI improves the insight in hydrocarbon reservoir behavior. The reader is assumed to have a background in geosciences and to be familiar with basic radar interferometry concepts. The book is designed for both researchers and the industry, since it translates the research results into the consequences for the operational use of InSAR for subsidence monitoring. Readers who are interested in a geological background of the Groningen gas reservoir and the prediction of subsidence at ground level are referred to Chap. 2. For the theoretical background of PSI and its precision and reliability, the reader is recommended to focus on the Chaps. 3, 4, and 5. If one has a background in PSI
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and is looking for the specific application for subsidence monitoring due to gas extraction in the Netherlands, the reader is referred to Chap. 6, preceded by Chap. 5, which addresses the reliability assessment methodology for PSI deformation estimates. Readers who are most interested in the operational use of PSI for monitoring subsidence due to hydrocarbon production are referred to Chapt. 7. To conclude, Chap. 8 addresses the potential of PSI for improving knowledge on reservoir behavior.
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Contents
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Introduction . . . . . . . 1.1 Background . . . . 1.2 Research Objectives 1.3 Outline . . . . . . .
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Subsidence Due to Hydrocarbon Production in the Netherlands . . . 2.1 Geological Background . . . . . . . . . . . . . . . . . . . . . . . 2.1.1 Hydrocarbon Reservoirs . . . . . . . . . . . . . . . . . . . 2.1.2 The Groningen Reservoir . . . . . . . . . . . . . . . . . . 2.1.3 Reservoir Properties . . . . . . . . . . . . . . . . . . . . . 2.1.4 Subsidence Prediction Methodologies . . . . . . . . . . . . 2.2 Subsidence Monitoring Using Leveling Measurements . . . . . . . 2.2.1 Leveling Campaigns . . . . . . . . . . . . . . . . . . . . . 2.2.2 Legal Guidelines . . . . . . . . . . . . . . . . . . . . . . . 2.3 Geodetic Deformation Monitoring . . . . . . . . . . . . . . . . . 2.3.1 Adjustment and Testing Procedure . . . . . . . . . . . . . 2.3.2 Point-wise Multi-epoch Deformation Analysis . . . . . . . 2.3.3 Continuous Spatio-temporal Deformation Analysis . . . . . 2.3.4 Deformation Analysis of Subsidence Due to Gas Extraction 2.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Persistent Scatterer InSAR . . . . . . . . . . . . . 3.1 Interferometric Processing . . . . . . . . . . . . 3.1.1 Oversampling . . . . . . . . . . . . . . 3.1.2 Coregistration . . . . . . . . . . . . . . 3.1.3 Interferogram Computation . . . . . . . 3.2 Persistent Scatterer Selection . . . . . . . . . . 3.2.1 Identification Methods of PS Candidates 3.2.2 Pseudo-calibration . . . . . . . . . . . . 3.3 Persistent Scatterer Phase Observations . . . . . 3.3.1 Master Selection . . . . . . . . . . . . . 3.3.2 Double-difference Observations . . . . . 3.4 PSI Estimation . . . . . . . . . . . . . . . . . . 3.4.1 Functional Model . . . . . . . . . . . . 3.4.2 Integer Least-Squares Estimation . . . . 3.4.3 Stochastic Model . . . . . . . . . . . . 3.4.4 DePSI Estimation Strategy . . . . . . . 3.5 Conclusions . . . . . . . . . . . . . . . . . . .
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Quality Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Precision and Reliability in PSI . . . . . . . . . . . . . . . . . . . 4.2 Influence of Imperfections in the Functional Model . . . . . . . . . 4.2.1 Sub-pixel Position . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Sidelobe Observations . . . . . . . . . . . . . . . . . . . . 4.2.3 Orbital Inaccuracies . . . . . . . . . . . . . . . . . . . . . 4.2.4 Phase Unwrapping in the Presence of Atmospheric Disturbances . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Imperfections in the Stochastic Model . . . . . . . . . . . . . . . 4.3.1 Measurement Precision . . . . . . . . . . . . . . . . . . . 4.3.2 Separation of Unmodeled Deformation and Atmospheric Signal . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.3 Possibilities and Limitations of Variance Component Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.4 Dilution of Precision . . . . . . . . . . . . . . . . . . . . . 4.4 Measurement Precision . . . . . . . . . . . . . . . . . . . . . . . 4.4.1 Leveling Precision . . . . . . . . . . . . . . . . . . . . . . 4.4.2 InSAR A-priori Measurement Precision . . . . . . . . . . 4.4.3 InSAR and Leveling Double-Difference Displacements . . 4.4.4 Validation of the Stochastic Model . . . . . . . . . . . . . 4.4.5 InSAR A-posteriori Precision . . . . . . . . . . . . . . . . 4.5 Idealization Precision for Deformation Monitoring . . . . . . . . . 4.5.1 Deformation Regimes . . . . . . . . . . . . . . . . . . . . 4.5.2 PS Characterization . . . . . . . . . . . . . . . . . . . . . 4.5.3 The Use of A-priori Knowledge on the Deformation Signal 4.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Multi-track PSI . . . . . . . . . . . . . . . . . . 5.1 Single-Track Datum Connection . . . . . . 5.2 Multi-track Datum Connection . . . . . . . 5.2.1 Unified Radar Datum . . . . . . . . 5.2.2 Connection of PSI Estimates . . . . 5.2.3 Spatial Trends . . . . . . . . . . . . 5.3 Decomposition of Line of Sight Deformation 5.3.1 System of Equations . . . . . . . . . 5.3.2 Quadtree Decomposition . . . . . . 5.4 Conclusions . . . . . . . . . . . . . . . . .
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PSI Subsidence Monitoring in Groningen . . . 6.1 InSAR Processing Strategy . . . . . . . . . 6.1.1 Data Coverage and Master Selection 6.1.2 Generation of Interferograms . . . . 6.1.3 DePSI . . . . . . . . . . . . . . . . 6.2 ERS and Envisat PSI Results . . . . . . . . 6.2.1 ERS Deformation Estimates . . . . . 6.2.2 Envisat Deformation Estimates . . .
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6.3 Quality Control . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.1 Precision of PSI Estimates . . . . . . . . . . . . . . . . 6.3.2 Unmodeled Residual Components . . . . . . . . . . . 6.4 Multi-track Analysis . . . . . . . . . . . . . . . . . . . . . . . 6.4.1 Datum Connection . . . . . . . . . . . . . . . . . . . . 6.4.2 Displacement Vector Decomposition . . . . . . . . . . 6.5 Idealization Precision for Deformation Monitoring . . . . . . . 6.5.1 Identification of Deformation Regimes . . . . . . . . . 6.5.2 Shallow and Deep Subsurface Movements in Groningen 6.5.3 PS Characterization . . . . . . . . . . . . . . . . . . . 6.5.4 On the Use of A-priori Knowledge on the Deformation Signal . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Cross-Validation and Operational Implementation . . . . . . . 7.1 Precision and Spatio-Temporal Observation Frequency . . . . 7.1.1 PSI and Leveling Deformation Estimates . . . . . . . 7.1.2 Setup for the Evaluation of Spatio-Temporal Sampling 7.1.3 Temporal Sampling . . . . . . . . . . . . . . . . . . 7.1.4 Spatial Sampling . . . . . . . . . . . . . . . . . . . . 7.2 Comparison of PSI and Leveling Deformation Estimates . . . 7.2.1 Parameterization of the Agreement between PSI and Leveling . . . . . . . . . . . . . . . . . . . . . . . . 7.2.2 PSI and Leveling Displacement Rates . . . . . . . . . 7.2.3 PSI and Leveling Displacements . . . . . . . . . . . 7.3 The Integration of Geodetic Measurement Techniques . . . . 7.3.1 Mathematical Model . . . . . . . . . . . . . . . . . . 7.3.2 The Integration of Leveling and PSI . . . . . . . . . . 7.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . .
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Discussion and Future Subsidence Monitoring . . . . . . . . . . . . 8.1 Precision and Reliability . . . . . . . . . . . . . . . . . . . . . . 8.2 Separation of Deformation Regimes . . . . . . . . . . . . . . . . 8.3 PSI and Reservoir Behavior . . . . . . . . . . . . . . . . . . . . 8.3.1 Temporal Behavior of Subsidence Due to Gas Extraction 8.3.2 Spatial Behavior of Subsidence Due to Gas Extraction . . 8.4 Future Subsidence Monitoring . . . . . . . . . . . . . . . . . . .
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Conclusions and Recommendations . . . . . . 9.1 Conclusions . . . . . . . . . . . . . . . . 9.1.1 PS Density . . . . . . . . . . . . . 9.1.2 Precision . . . . . . . . . . . . . . 9.1.3 Reliability . . . . . . . . . . . . . 9.1.4 Deformation Regimes . . . . . . . 9.1.5 Cross-Validation PSI and Leveling
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9.1.6 Hydrocarbon Reservoir Behavior 9.1.7 Outlook . . . . . . . . . . . . . 9.2 Contributions . . . . . . . . . . . . . . . 9.3 Recommendations . . . . . . . . . . . .
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Appendix 1 Location of Research Areas . . . . . . . . . . . . . . . . 219
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Appendix 2 PSI and Leveling Displacement Profiles . . . . . . . . . . 221 A2.1 PSI (Track 380,487) and Leveling (Free Network Adjustments) . . 221 A2.2 PSI (Track 380,487) and Leveling (SuMo Analysis) . . . . . . . . 223 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
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Summary
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Monitoring Surface Deformation Induced by Hydrocarbon Production Using Satellite Radar Interferometry The start of hydrocarbon production in the 1960s in the northeastern part of the Netherlands has resulted in subsidence of the ground level, which has been estimated from periodic leveling campaigns. Although leveling is a precise and reliable technique for subsidence monitoring, it is labor intensive, expensive and poses a safety risk since measurements are taken along roads. Hence, the application of satellite radar interferometry (InSAR) is investigated for subsidence monitoring, coupled with the potential improvement of reservoir behavior monitoring due to the InSAR observation frequency. The main focus lies on the Groningen gas field, which has a diameter of ∼30 kilometers, at ∼3 kilometers below surface. Complicating factors for the application of InSAR for subsidence monitoring in the Groningen area are surface changes in time due to its agricultural character (temporal decorrelation), atmospheric disturbances, and the low subsidence rates (
