Long-term monitoring of geodynamic surface deformation using SAR interferometry

Thesis (Ph.D.) University of Alaska Fairbanks, 2014Synthetic Aperture Radar Interferometry (InSAR) is a powerful tool to measure surface deformation and is well suited for surveying active volcanoes using historical and existing satellites. However, the value and applicability of InSAR for geodynamic monitoring problems is limited by the influence of temporal decorrelation and electromagnetic path delay variations in the atmosphere, both of which reduce the sensitivity and accuracy of the technique. The aim of this PhD thesis research is: how to optimize the quantity and quality of deformation signals extracted from InSAR stacks that contain only a low number of images in order to facilitate volcano monitoring and the study of their geophysical signatures. In particular, the focus is on methods of mitigating atmospheric artifacts in interferograms by combining time-series InSAR techniques and external atmospheric delay maps derived by Numerical Weather Prediction (NWP) models. In the first chapter of the thesis, the potential of the NWP Weather Research & Forecasting (WRF) model for InSAR data correction has been studied extensively. Forecasted atmospheric delays derived from operational High Resolution Rapid Refresh for the Alaska region (HRRRAK) products have been compared to radiosonding measurements in the first chapter. The result suggests that the HRRR-AK operational products are a good data source for correcting atmospheric delays in spaceborne geodetic radar observations, if the geophysical signal to be observed is larger than 20 mm. In the second chapter, an advanced method for integrating NWP products into the time series InSAR workflow is developed. The efficiency of the algorithm is tested via simulated data experiments, which demonstrate the method outperforms other more conventional methods. In Chapter 3, a geophysical case study is performed by applying the developed algorithm to the active volcanoes of Unimak Island Alaska (Westdahl, Fisher and Shishaldin) for long term volcano deformation monitoring. The volcano source location at Westdahl is determined to be approx. 7 km below sea level and approx. 3.5 km north of the Westdahl peak. This study demonstrates that Fisher caldera has had continuous subsidence over more than 10 years and there is no evident deformation signal around Shishaldin peak.Chapter 1. Performance of the High Resolution Atmospheric Model HRRR-AK for Correcting Geodetic Observations from Spaceborne Radars -- Chapter 2. Robust atmospheric filtering of InSAR data based on numerical weather prediction models -- Chapter 3. Subtle motion long term monitoring of Unimak Island from 2003 to 2010 by advanced time series SAR interferometry -- Chapter 4. Conclusion and future work

Repeated magmatic intrusions at El Hierro Island following the 2011–2012 submarine eruption

After more than 200 years of quiescence, in July 2011 an intense seismic swarm was detected beneath the center of El Hierro Island (Canary Islands), culminating on 10 October 2011 in a submarine eruption, 2 km off the southern coast. Although the eruption officially ended on 5 March 2012, magmatic activity continued in the area. From June 2012 to March 2014, six earthquake swarms, indicative of magmatic intrusions, were detected underneath the island. We have studied these post-eruption intrusive events using GPS and InSAR techniques to characterize the ground surface deformation produced by each of these intrusions, and to determine the optimal source parameters (geometry, location, depth, volume change). Source inversions provide insight into the depth of the intrusions (~ 11–16 km) and the volume change associated with each of them (between 0.02 and 0.13 km3). During this period, > 20 cm of uplift was detected in the central-western part of the island, corresponding to approximately 0.32–0.38 km3 of magma intruded beneath the volcano. We suggest that these intrusions result from deep magma migrating from the mantle, trapped at the mantle/lower crust discontinuity in the form of sill-like bodies. This study, using joint inversion of GPS and InSAR data in a post-eruption period, provides important insight into the characteristics of the magmatic plumbing system of El Hierro, an oceanic intraplate volcanic island

Generic interferometric synthetic aperture radar atmospheric correction model and its application to co- and post-seismic motions

PhD ThesisThe tremendous development of Interferometric Synthetic Aperture Radar (InSAR) missions in recent years facilitates the study of smaller amplitude ground deformation over greater spatial scales using longer time series. However, this poses more challenges for correcting atmospheric effects due to the spatial-temporal variability of atmospheric delays. Previous attempts have used observations from Global Positioning System (GPS) and Numerical Weather Models (NWMs) to separate the atmospheric delays, but they are limited by (i) the availability (and distribution) of GPS stations; (ii) the time difference between NWM and radar observations; and (iii) the difficulties in quantifying their performance. To overcome the abovementioned limitations, we have developed the Iterative Tropospheric Decomposition (ITD) model to reduce the coupling effects of the troposphere turbulence and stratification and hence achieve similar performances over flat and mountainous terrains. Highresolution European Centre for Medium-Range Weather Forecasts (ECMWF) and GPS-derived tropospheric delays were properly integrated by investigating the GPS network geometry and topography variations. These led to a generic atmospheric correction model with a range of notable features: (i) global coverage, (ii) all-weather, all-time usability, (iii) available with a maximum of two-day latency, and (iv) indicators available to assess the model’s performance and feasibility. The generic atmospheric correction model enables the investigation of the small magnitude coseismic deformation of the 2017 Mw-6.4 Nyingchi earthquake from InSAR observations in spite of substantial atmospheric contamination. It can also minimize the temporal correlations of InSAR atmospheric delays so that reliable velocity maps over large spatial extents can be achieved. Its application to the post-seismic motion following the 2016 Kaikoura earthquake shows a success to recover the time-dependent afterslip distribution, which in turn evidences the deep inactive subduction slip mechanism. This procedure can be used to map surface deformation in other scenarios including volcanic eruptions, tectonic rifting, cracking, and city subsidence.This work was supported by a Chinese Scholarship Council studentship. Part of this work was also supported by the UK NERC through the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET)

On the use of deep learning for phase recovery

Phase recovery (PR) refers to calculating the phase of the light field from its intensity measurements. As exemplified from quantitative phase imaging and coherent diffraction imaging to adaptive optics, PR is essential for reconstructing the refractive index distribution or topography of an object and correcting the aberration of an imaging system. In recent years, deep learning (DL), often implemented through deep neural networks, has provided unprecedented support for computational imaging, leading to more efficient solutions for various PR problems. In this review, we first briefly introduce conventional methods for PR. Then, we review how DL provides support for PR from the following three stages, namely, pre-processing, in-processing, and post-processing. We also review how DL is used in phase image processing. Finally, we summarize the work in DL for PR and outlook on how to better use DL to improve the reliability and efficiency in PR. Furthermore, we present a live-updating resource (https://github.com/kqwang/phase-recovery) for readers to learn more about PR.Comment: 82 pages, 32 figure

Synthetic Aperture Radar (SAR) Meets Deep Learning

This reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology. A synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications. In recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications. This reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports

The 2008 Eruptive Unrest at Cerro Azul Volcano (Galápagos) Revealed by InSAR Data and a Novel Method for Geodetic Modelling

Cerro Azul is one of the most active volcanoes in the western Galápagos Islands, but its unrest episodes are poorly studied. Unrest, which started in 2007, culminated in two eruptive phases from 29 May to 11 June 2008. We investigate this unrest and the associated eruptions using interferometric synthetic aperture radar (InSAR) data and geodetic modelling. To overcome the unwrapping errors affecting some of our InSAR data, we invert the wrapped phase directly by estimating the integer ambiguities simultaneously with the geophysical parameters. Our results highlight how the eruption was preceded by long‐term pre‐eruptive inflation (October 2007–April 2008). During the first eruptive phase, most of the magma responsible for the inflation fed the lateral propagation of a radial dike, which caused a first deflation of the magmatic reservoir. During the second eruptive phase, the further lateral propagation of the dike fed a radial eruptive fissure at the base of the edifice, causing further deflation of the magmatic reservoir. From the first to the second eruptive phase, the radial dike changed its strike propagating toward a topographic low between Cerro Azul and Sierra Negra

Advances in Methane Production from Coal, Shale and Other Tight Rocks

This collection reports on the state of the art in fundamental discipline application in hydrocarbon production and associated challenges in geoengineering activities. Zheng et al. (2022) report an NMR-based method for multiphase methane characterization in coals. Wang et al. (2022) studied the genesis of bedding fractures in Ordovician to Silurian marine shale in the Sichuan basin. Kang et al. (2022) proposed research focusing on the prediction of shale gas production from horizontal wells. Liang et al. (2022) studied the pore structure of marine shale by adsorption method in terms of molecular interaction. Zhang et al. (2022) focus on the coal measures sandstones in the Xishanyao Formation, southern Junggar Basin, and the sandstone diagenetic characteristics are fully revealed. Yao et al. (2022) report the source-to-sink system in the Ledong submarine channel and the Dongfang submarine fan in the Yinggehai Basin, South China Sea. There are four papers focusing on the technologies associated with hydrocarbon productions. Wang et al. (2022) reported the analysis of pre-stack inversion in a carbonate karst reservoir. Chen et al. (2022) conducted an inversion study on the parameters of cascade coexisting gas-bearing reservoirs in coal measures in Huainan. To ensure the safety CCS, Zhang et al (2022) report their analysis of available conditions for InSAR surface deformation monitoring. Additionally, to ensure production safety in coal mines, Zhang et al. (2022) report the properties and application of gel materials for coal gangue control

Improved modeling of segmented earthquake rupture informed by enhanced signal analysis of seismic and geodetic observations

Earthquake source modeling has emerged from the need to be able to describe and quantifythe mechanism and physical properties of earthquakes. Investigations of earthquake ruptureand fault geometry requires the testing of a large number of such potential sets of earthquakesources models. Earthquakes often rupture across more than one fault segment. If such rupturesegmentation occurs on a significant scale, a simple model may not represent the rupture processwell. This thesis focuses on the data-driven inclusion of earthquake rupture segmentation intoearthquake source modeling. The developed tools and the modeling are based on the jointuse of seismological waveform far-field and geodetic Interferometric Synthetic Aperture Radarnear-field surface displacement maps to characterise earthquake sources robustly with rigorousconsideration of data and modeling errors.A strategy based on information theory is developed to determine the appropriate modelcomplexity to represent the available observations in a data-driven way. This is done inconsideration of the uncertainties in the determined source mechanisms by investigating theinferences of the full Bayesian model ensemble. Application on the datasets of four earthquakesindicated that the inferred source parameters are systematically biased by the choice of modelcomplexity. This might have effects on follow-up analyses, e. g. regional stress field inversionsand seismic hazard assessments.Further, two methods were developed to provide data-driven model-independent constraints toinform a kinematic earthquake source optimization about earthquake source parameter priorestimates. The first method is a time-domain multi-array backprojection of teleseismic datawith empirical traveltime corrections to infer the spatio-temporal evolution of the rupture. Thisenables detection of potential rupture segmentation based on the occurrence of coherent high-frequency sources during the rupture process. The second developed method uses image analysismethods on satellite radar measured surface displacement maps to infer modeling constraints onrupture characteristics (e.g. strike and length) and the number of potential segments. These twomethods provide model-independent constraints on fault location, dimension, orientation andrupture timing. The inferred source parameter constraints are used to constrain an inversion forthe source mechanism of the 2016 Muji Mw 6.6 earthquake, a segmented and bilateral strike-slipearthquake.As a case study to further investigate a depth-segmented fault system and occurrence of co-seismic rupture segmentation in such a system the 2008-2009 Qaidam sequence with co-seismicand post-seismic displacements is investigated. The Qaidam 2008-2009 earthquake sequence innortheast Tibet involved two reverse-thrust earthquakes and a postseismic signal of the 2008earthquake. The 2008 Qaidam earthquake is modeled as a deep shallow dipping earthquakewith no indication of rupture segmentation. The 2009 Qaidam earthquake is modeled on threedistinct south-dipping high-angle thrusts, with a bilateral and segmented rupture process. Agood agreement between co-seismic surface displacement measurements and coherent seismicenergy emission in the backprojection results is determined.Finally, a combined framework is proposed which applies all the developed methods and tools inan informed parallel modeling of several earthquake source model complexities. This frameworkallows for improved routine determination of earthquake source modeling under considerationof rupture segmentation. This thesis provides overall an improvement for earthquake sourceanalyses and the development of modeling standards for robust determination of second-orderearthquake source parameters

Constraining Source Models, Underlying Mechanisms, and Hazards Associated with Slow Slip Events: Insight from Space-Borne Geodesy and Seismology

abstract: The movement between tectonic plates is accommodated through brittle (elastic) displacement on the plate boundary faults and ductile permanent deformation on the fault borderland. The elastic displacement along the fault can occur in the form of either large seismic events or aseismic slip, known as fault creep. Fault creep mainly occurs at the deep ductile portion of the crust, where the temperature is high. Nonetheless, aseismic creep can also occur on the shallow brittle portion of the fault segments that are characterized by frictionally weak material, elevated pore fluid pressure, or geometrical complexity. Creeping segments are assumed to safely release the accumulated strain(Kodaira et al., 2004; Rice, 1992)(Kodaira et al., 2004; Rice, 1992)(Kodaira et al., 2004; Rice, 1992)(Kodaira et al., 2004; Rice, 1992)(Kodaira et al., 2004; Rice, 1992) on the fault and also impede propagation of the seismic rupture. The rate of aseismic slip on creeping faults, however, might not be steady in time and instead consist of successive periods of acceleration and deceleration, known as slow slip events (SSEs). SSEs, which aseismically release the strain energy over a period of days to months, rather than the seconds to minutes characteristic of a typical earthquake, have been interpreted as earthquake precursors and as possible triggering factor for major earthquakes. Therefore, understanding the partitioning of seismic and aseismic fault slip and evolution of creep is fundamental to constraining the fault earthquake potential and improving operational seismic hazard models. Thanks to advances in tectonic geodesy, it is now possible to detect the fault movement in high spatiotemporal resolution and develop kinematic models of the creep evolution on the fault to determine the budget of seismic and aseismic slip. In this dissertation, I measure the decades-long time evolution of fault-related crustal deformation along the San Andrea Fault in California and the northeast Japan subduction zone using space-borne geodetic techniques, such as Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar (InSAR). The surface observation of deformation combined with seismic data set allow constraining the time series of creep distribution on the fault surface at seismogenic depth. The obtained time-dependent kinematic models reveal that creep in both study areas evolves through a series of SSEs, each lasting for several months. Using physics-based models informed by laboratory experiments, I show that the transient elevation of pore fluid pressure is the driving mechanism of SSEs. I further investigate the link between SSEs and evolution of seismicity on neighboring locked segments, which has implications for seismic hazard models and also provides insights into the pattern of microstructure on the fault surface. I conclude that while creeping segments act as seismic rupture barriers, SSEs on these zones might promote seismicity on adjacent seismogenic segments, thus change the short-term earthquake forecast.Dissertation/ThesisDoctoral Dissertation Geological Sciences 201