Satellite InSAR data : reservoir monitoring from space

178 Pages·2014·11.674 MB·English

by  Ferretti, Alessandro

Satellite InSAR Data
Reservoir Monitoring from Space

Alessandro Ferretti
© 2014 EAGE Publications bv

All rights reserved. This publication or part hereof may not be reproduced or transmitted in any form
or by any means, electronic or mechanical, including photocopy, recording, or any information storage
and retrieval system, without the prior written permission of the publisher.

ISBN 978-90-73834-71-2

EAGE Publications bv
PO Box 59
3990 DB HOUTEN
The Netherlands
General disclaimer
The purpose of this book is to educate and the text is written to complement a training class given by
the author, on behalf of EAGE. The author and EAGE shall have neither liability nor responsibility to
any person or entity with respect to any loss or damage caused, or alleged to have been caused,
directly or indirectly, by the information contained in this book or from written or oral information
provided in the complementary training classes.
This book is designed to provide information on satellite InSAR and its applications. It includes
reviews of existing published materials and contains references to a number of technical papers,
expanded abstracts and text books. The intent has not been to produce a reprint of this material but
instead to use it combined with the author’s own experience to illustrate the practical use of satellite
InSAR data.
We recommend complementing the book by reading the referenced articles, to ensure readers have
the best possible context and to help tailor the information to specific needs. Readers are urged to
consult with experts on all aspects about which you are in doubt, prior to utilizing any of the ideas and
concepts referred to in the textbook and the associated lecture.
Every effort has been made to make this work as accurate as possible. However, there may be
mistakes, both typographical and in content. Therefore, this text should be used only as a general guide
and reference and not used as the ultimate source for commercial work.
Contents

Acknowledgements                        iii 
General Disclaimer                        Iv 
1. Motivation                          1 
2. Satellite Radar Images                      4 
  2.1 Key Features of Satellite Radar Systems                4 
  2.2 Amplitude and Phase Information: The Magic of Complex Numbers          5 
   2.2.1  The Basic Idea                    6 
   2.2.2  Modulo‐2 p Values:  Knowing Som ethi ng, but  Not Ev erythi ng        8 
   2 .2.3 Demodulation, Sampling and Analog to Digital Conversion       10 
  2.3 Ran ge  Re solution, Sign al Compression and  Formation of a  Range Li ne    12 
  2.4 Acquisition Geometry and Synthetic Aperture           17 
   2.4.1  Azimuth Focusing                 19  
  2.5 SAR Images                     20 
   2.5.1  Signal Statistics                  21 
   2.5.2  Back sca tter Measurements            24  
  2.6 Geometric Distortions and Satellite Orbit             24  
   2.6.1  Ascending and Descending Orbits              26 
  2.7 Scattering Mechanisms                  28 
  2.8 What We Have Learned So Far               33  
3. SAR Interferometry                     35 
  3.1 Measuring Phase Variations                 35 
  3.2 Modelling the Interferometric Phase              37  
   3.2.1  Linear Approximation of the Interferometric Phase         40 
   3.2.2  Metres or Millimetres?               44  
  3.3 SAR Interferograms                   46 
   3.3.1  Differential Interferograms: DInSAR Analyses         47  
  3.4 Phase Decorrelation and Coherence Maps              51 
   3.4.1  Geometrical and Volume Decorrelation           54 
   3.4.2  Temporal Decorrelation               57
3.5 Atmospheric Effects                     59 
   3.5.1  Atmospheric Turbulence                  61 
   3.5.2  Atmospheric Stratification                 63 
   3.5.3  Modelling the Atmospheric Phase Screen              64 
  3.6 Phase Unwrapping                      65 
  3.7 What We Have Learned So Far                  68 
4. Multi‐Interferogram Techniques                    70 
  4.1 Some History                      70 
   4.1.1  First Steps Towards a Solution                71 
  4.2 The Permanent Scatterer (PS) Technique: PSInSAR              73 
   4.2.1  Basic Blocks                    75 
   4.2.2  Results of the PS Technique                79 
   4.2.3  Permanent or Persistent?                  81 
  4.3 SBAS and other Multi‐Interferogram Techniques              82 
  4.4 SqueeSAR                        86 
   4.4.1  Deterministic and Stochastic Scatterers              87 
   4.4.2  Processing Chain and Results                90 
   4.4.3  A Note on Master Image and Reference Point Selection          91 
  4.5 Estimation of 2‐Dimensional Displacement Fields              93 
   4.5.1 Pseudo ‐ PS                   95 
  4.6 Precision Assessment and Validation                 96 
   4.6.1  Precision Assessment of Phase Values              99 
   4.6.2  Validation                   101 
  4.7 What We Have Learned So Far                103 
5. Oil and Gas Applications                    104 
  5.1 Surface Expression of Reservoir Dynamics: An Opportunity More Than a Problem    104 
   5.1.1  Tools for Surface Deformation Monitoring          106 
   5.1.2  Compaction and Subsidence              109 
  5.2 Inversion of Surface Deformation Data             111 
   5.2.1  Distributed Subsurface Deformation Sources         112 
   5.2.2  Estimation of Compaction and Subsidence          114 
   5.2.3  Fault Dislocation                 116 
   5.2.4  Inversion Methods                 117
5.3 A Case Study in Middle East                 120 
  5.4 Carbon Capture and Storage (CCS)               124 
   5.4.1  First Evidence of Sub‐Millimetre Accuracy           127 
   5.4.2  Permeability Estimation                129 
  5.5 Underground Gas Storage (UGS)               130 
  5.6 Off‐Shore Applications                  134 
  5.7 What We Have Learned So Far               136 
6. Conclusions and Future Trends                  137 
  6.1 InSAR Applications                    137 
  6.2 Artificial Reflectors                    144 
  6.3 Satellite Archives, Historical Analyses and Monitoring Projects       147  
  6.4 New Trends and Why We Should Care              153 
References                        155 
Index                          165
1 Motivation
Do we need another book on InSAR? That’s the question I asked myself when I started working on
this manuscript. Is there anything a reader cannot find in hundreds of papers now available on the
internet, excellent tutorials published by international journals, books, conference proceedings and
even some nice videos on Youtube? After all, many years have passed since the pioneering works of
Graham (1974), Gabriel (1989), Massonnet (1993), Goldstein (1994) and the launch of SEASAT in
1978, the first satellite platform mounting a Synthetic Aperture Radar (SAR) sensor on board
(interestingly the same year as the launch of the first GPS satellite).
Still, satellite radar interferometry is often seen as a “new technology” for surface deformation
monitoring and the potentials of InSAR are largely non-diffused, even within the scientific
community. This book starts from this one fact. While GPS has become a standard tool for geodesy,
InSAR is gaining recognition at a much slower pace. Why?
The reasons behind this slow uptake are numerous and complex. If we look at the history of GPS
and compare it to that of InSAR applications, we observe three main differences: (1) the space
segment; (2) the “sponsor” and (3) the industry.
The diffusion of any space technology is strongly related to the availability of a reliable and robust
space segment, providing proper and adequate infrastructure and data sources. For InSAR, despite the
results from SEASAT, the first (civilian) sensor specifically designed for surface deformation
monitoring over large areas will be SENTINEL-1A, a SAR satellite operated by the European Space
Agency (ESA) that is expected to be launched in 2014. So far, all SAR sensors have been multi-
purpose, where repeat-pass InSAR was just one of a long list of possible applications from iceberg
monitoring and oil-spill detection to soil moisture estimation and biomass mapping.
The first InSAR results from satellite sensors were a somewhat unexpected, although extremely
welcome, outcome. However, after obtaining proof of concept with SEASAT and the success of the
ERS missions operated by ESA, InSAR technology still did not take off as fast as expected. The space
segment did not aid its evolution either. The specifications of satellites being developed in the new
millennium were not in the direction required for systematic and repeatable InSAR observations. As
we will see, interferometry needs a simple acquisition scheme, with radar sensors acquiring data
regularly over a particular area using the very same acquisition mode and geometry. SAR technicians
and aerospace industries, on the contrary, were focused on a different goal: on offering many
sophisticated imaging options, in terms of polarization of the electromagnetic signal wave, image
resolution, incidence angle of the radar beam, etc., and not on simple, single-mode radar sensors. Even
considering the most recent SAR missions, the requirement to task the satellite to acquire an image,
while selecting the correct acquisition mode (from a long list of options), to create a homogeneous
multi-temporal data-set over an area, does not facilitate the diffusion of InSAR as a standard geodetic
tool.
On the contrary, GPS technology was application-driven. Plan and target was clear, from the very
beginning, as well as the financier of the project, i.e. the US Department of Defense. In other words,
while InSAR data were somewhat opportunistic measurements obtained by sensors designed primarily
for other applications, the development of GPS applications could rely on ad hoc space and ground
segments, and a significant amount of public money.
The third factor is related to the Earth observation industry: companies providing products and
services based on a certain space technology. So far, no large corporations within the aerospace
1
segment have invested a significant amount of resources into the development of InSAR products and
services. Certainly nothing compared to GPS. Today, InSAR teams within large corporations are
typically manned by less than a dozen engineers, while the largest InSAR groups are found within
small or medium enterprises, often spin-off companies of universities or research centers.
Without a “sponsor” and the involvement of large corporations, any new technology takes more
time to gain traction. Whenever large corporations and important players invest in new technologies
they can increase their awareness relatively quickly. Thinking about Apple or Google, it is easy to
understand what we are talking about. Both a lack of public (or private) sponsorship and a lack of
investment by large corporations have certainly not fostered the use of InSAR data, nor its integration
with other in situ measurement techniques.
Even within the geodetic community, this scenario has been interpreted as evidence of the fact that
InSAR is still not a mature technology (“if it were so, it would have attracted similar investments to
GPS,” it has been said). InSAR analyses are thought to provide interesting but qualitative data, great to
write scientific papers on, but with a limited impact on real-life applications.
In our opinion, this interpretation is not correct and overlooks an important point that we have
already mentioned: contrary to GPS, for InSAR there was no push towards a large-scale application of
the technology by any government, space agency or international organization. That doesn’t mean
space agencies did not play a role at all or did not foster InSAR, in fact they did a lot, particularly
ESA, and during the last decade they have been endorsing InSAR applications more and more.
Simply, surface deformation monitoring was not immediately recognized as an application deserving a
dedicated sensor. A lack of “big projects” with challenging targets, for example the systematic
monitoring of all seismic and volcanic areas all over the world, translated into a lack of “sizable
funding” for the space and ground segment and hence a limited interest in InSAR from multi-national
corporations in the aerospace sector.
The aim of this book is to demonstrate that despite the slow uptake, InSAR is a mature technology.
InSAR does work and can provide quantitative and reliable information whenever enough radar
acquisitions are available over an area of interest, suitable for a number of geosciences and geo-
engineering applications.
Strange as it may seem, another reason for the slow uptake of InSAR for surface deformation
monitoring is related to the large number of applications and market sectors where this technology can
have impact. InSAR data can be used for fault characterization and calibration of geo-mechanical
models in the oil and gas sector, for monitoring landslides, volcanoes and seismic faults, areas prone to
sinkholes, terrain compaction phenomena induced by tunneling works, and even for monitoring the
stability of individual buildings. Each of these applications requires specific knowledge and
understanding of the needs and requirements of the people involved, as well as a strong understanding
of competitor technologies: too much for a small group of radar specialists, as in the ones involved in
the development of InSAR so far, at least.
It takes time to learn new languages and get rid of local jargon and mysterious acronyms. Radar
specialists have had to learn how to speak with geologists, geophysicists, geo-technicians, and
petroleum and civil engineers. It was a time-consuming effort and, thinking about me, I still have to
learn a lot. Finally, after almost 20 years from the first cover page of Nature with InSAR results
(Massonnet et al. 1993), this technology is becoming more and more a standard tool for surface
deformation monitoring. We are getting near to a sort of “domino effect” where the use of InSAR data
in certain applications triggers the use of them in others. Therefore — we think — it is worth spending
some time to get to know what is actually behind the “magic of InSAR”, a technology capable of
measuring displacements of just one millimeter on the ground from satellites orbiting the earth
hundreds of kilometers above us.
This book is intended as a guided tour of InSAR and its applications. It is not a manual for radar
2
specialists, nor a resource for those who want to develop their own software to process SAR images. It
should create curiosity and stimulate ideas about new applications. It is an introduction for people who
have a limited background in satellite radar systems and SAR imagery, but who are interested in new
technologies and in their applications. The mathematics is kept to a minimum, although it is used to
clarify some concepts and help identify the most important variables that affect the results. Special
attention will be paid to the so-called “multi-interferogram techniques”, first of all because they
provide more precise measurements with respect to standard InSAR data and secondly because the
author has been personally involved in the development of the “second generation InSAR analysis”.
The discussion will follow a rather classical path, passing from a short description of satellite SAR
systems, to the analysis of the different phase components in SAR interferograms, to a simplified
description of multi-interferogram techniques and, finally, to a gallery of application examples and an
outlook on the future of InSAR.
Hopefully, you the reader will find this book interesting and not too theoretical. As we already said,
InSAR is a mature technology, and it is now time to use it.
3
2 Satellite radar images
Before introducing the basic concepts of Interferometric Synthetic Aperture Radar (InSAR), it is
necessary to understand what a SAR image is and how it is acquired by a satellite-mounted radar
sensor. In this chapter, we will briefly introduce the most important parameters of modern imaging
radar systems, discuss their acquisition geometries and, perhaps most importantly, introduce the
concept of phase: the key parameter used to understand SAR images and InSAR results.
2.1 Key features of satellite radar systems
Satellite images are now part of everyday life. The use, for example, of Virtual Earth™, Google
Earth™ and Google Maps™ has revolutionized how we access, visualize and search for geographic
information, providing a huge amount of data acquired by satellite platforms mounting optical sensors,
i.e. sophisticated cameras acquiring images in the optical domain (visible wavelengths range from
approximately 0.3 to about 0.7 micrometers) or in neighbouring bands, such as infrared and ultraviolet.
A radar sensor operates in another band of the electromagnetic spectrum: the microwave domain.
Here wavelengths are a few centimetres long, 100,000 times longer than those of the visible spectrum.
Different radar sensors operate at different frequencies (Table 2.1) where, the longer the wavelength
the more effective the ability to penetrate a (dielectric) material. Therefore, unlike an optical camera, a
radar sensor can see through clouds, fog and dust, making it a unique tool for a number of applications.
And it is an active system: images are created by illuminating an area of interest with electromagnetic
pulses and recording the echoes from natural and man-made objects backscattered to the radar antenna.
In monostatic systems the same antenna acts as both the transmitter and the receiver, switching from
one mode to another thousands of times a second.
Their ability to function independently of sun illumination and to generate images no matter what
the weather conditions have made satellite radar platforms an invaluable tool for earth observation and
remote sensing, complementing the information gathered by optical sensors.
The third characteristic is the most important for our discussion: radar is a coherent sensor. It can
carefully record both amplitude and phase information for each ground target. The concept of phase
information deserves a specific section, but to introduce this topic it suffices to say that most of
satellite radar systems available today use “almost monochromatic” signals: that is, the illuminating
beam can be seen as the superposition of a set of sinusoidal signals of similar amplitude and frequency
centred at an operating (or central) frequency of the radar sensor (f ). The difference between the
0
highest and lowest frequencies of this set of signals is called the bandwidth of the radar (BW). In most
of the satellite radar systems available today for civil applications, the ratio between the bandwidth and
the central frequency is a very low figure, ranging from 1/1000 to 1/50. Since BW<<f , the
0
illuminating beam can be considered “almost monochromatic”, i.e. a sinusoidal signal at the central
frequency. The phase of this sinusoid turns out to be a key element in accurately retrieving valuable
information about the sensor-to-target distance, as will be discussed in the next section.
Band Frequencies Wavelengths Sensors
4