J.C. Esteves Martins
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Microbial Biomineralisation in Living Artefacts for Regenerative Ecologies
An Overview and Design Pathways
Despite its importance, directly measuring the Earth’s subsurface remains a challenge. Deformation measurements from Interferometric Synthetic Aperture Radar (InSAR) and subsequent geophysical modelling offer potential solutions, but have limitations related to resolution and uncertainties in estimating the geometry, depth, and volume change of magma sources. In addition, estimates of elastic and rheological properties are often lacking and rely on unverified assumptions.
To overcome these challenges, this study introduces an interdisciplinary approach, leveraging the integrated strengths of seismic and geodetic space-time metrics and using Icelandic volcanoes as case studies. The objectives of this study are as follows: (i) derive phase velocities from seismic ambient noise using seismic interferometry to enhance 3D shear-wave tomography of volcanic structures; (ii) estimate InSAR-derived time series to model surface deformation and provide estimates for the geometry, depth, and volumechanges ofmagmatic plumbing systems, incorporating seismic or other geodetic constraints whenever possible; and (iii) assess the effectiveness of the above-mentioned methods using real and simulated…
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Despite its importance, directly measuring the Earth’s subsurface remains a challenge. Deformation measurements from Interferometric Synthetic Aperture Radar (InSAR) and subsequent geophysical modelling offer potential solutions, but have limitations related to resolution and uncertainties in estimating the geometry, depth, and volume change of magma sources. In addition, estimates of elastic and rheological properties are often lacking and rely on unverified assumptions.
To overcome these challenges, this study introduces an interdisciplinary approach, leveraging the integrated strengths of seismic and geodetic space-time metrics and using Icelandic volcanoes as case studies. The objectives of this study are as follows: (i) derive phase velocities from seismic ambient noise using seismic interferometry to enhance 3D shear-wave tomography of volcanic structures; (ii) estimate InSAR-derived time series to model surface deformation and provide estimates for the geometry, depth, and volumechanges ofmagmatic plumbing systems, incorporating seismic or other geodetic constraints whenever possible; and (iii) assess the effectiveness of the above-mentioned methods using real and simulated…
In autumn 2017 a network of 14 broadband seismic stations was deployed at the Theistareykir high temperature geothermal field (NE Iceland). This experiment was conducted as part of the current efforts to characterize the field's main structures, and possible short and long term stress variations due to the ongoing fluid injection and extraction operations which started in autumn 2017. In this work, we use two years of continuous seismic records (October 2017–October 2019) to compute a 3D shear wave velocity model of the geothermal field and to detect possible crustal stress changes related to the injection and production activities. From phase cross-correlations of the vertical component recordings, we measure the Rayleigh wave group velocity dispersion curves to obtain 2D group velocity maps between 1 and 5 s. Subsequently, we use a neighborhood algorithm to retrieve the 3D shear wave velocity model of Theistareykir. Mainly, two sets of elongated high and low velocity anomalies can be observed oriented in a NW/WNW direction, parallel to the lineaments of the active Tjörnes fracture zone. Velocity reductions west of Ketilfjall and at Baerjafjall could indicate the location of upflow zones of the magmatic reservoir or hydrothermal system. We analyzed the temporal evolution of phase and amplitude of phase auto-correlations using the stretching technique and discuss their behavior in relation to the geothermal field operations. We notice a slightly stronger long-term velocity decrease in the reservoir region compared to outer regions. This could be related to the mass depletion in that area (higher fluid extraction compared to the water reinjection). In summary, our findings show how a monitoring network can be set up to enable a detailed imaging and monitoring of reservoir behavior in general.
A NNW-SSE striking fault swarm, including the Los Humeros fault, acts as a major boundary of the subsiding area observed by InSAR time-series between February 2016 and May 2019. A potential explanation of the reverse reactivation of the Los Humeros fault and following downward movement of the eastern fault block is the depressurization of the whole hydrothermal system. Such depressurization can occur due to the exploitation of the geothermal field and/or due to natural pressure/temperature changes related to magmatic activity. ...
A NNW-SSE striking fault swarm, including the Los Humeros fault, acts as a major boundary of the subsiding area observed by InSAR time-series between February 2016 and May 2019. A potential explanation of the reverse reactivation of the Los Humeros fault and following downward movement of the eastern fault block is the depressurization of the whole hydrothermal system. Such depressurization can occur due to the exploitation of the geothermal field and/or due to natural pressure/temperature changes related to magmatic activity.
Surface deformation due to fluid extraction can be detected by satellite-based geodetic sensors, providing important insights on subsurface geomechanical properties. In this study, we use Differential Interferometric Synthetic Aperture Radar (DInSAR) observations to measure ground deformation due to fluid extraction at the Los Humeros Geothermal Field (Puebla, Mexico). Our main goal is to reveal the pressure distribution in the reservoir and to identify reservoir compartmentalization, which can be important aspects for optimizing the production of the field. The result of the PS-InSAR (Persistent Scatterer by Synthetic Aperture Radar Interferometry) analysis shows that the subsidence at the LHGF was up to 8 mm/year between April 2003 and March 2007, which is small relative to the produced volume of 5×106 m3/year. The subsidence pattern indicates that the geothermal field is controlled by sealing faults separating the reservoir into several blocks. To assess if this is the case, we relate surface movements with volume changes in the reservoir through analytical solutions for different types of nuclei of strain. We constrain our models with the movements of the PS points as target observations. Our models imply small volume changes in the reservoir, and the different nuclei of strain solutions differ only slightly. These findings suggest that the pressure within the reservoir is well supported and that reservoir recharge is taking place.
Finally, after the inversion to depth, we detect S-wave velocity anomalies with variations between −15% and 15% with reference to an estimated average velocity using 1 km and 3 km of lateral resolutions and 1 km of vertical resolution. This study shows the potential of ambient noise tomography as complementary seismological tool for reservoir characterization. ...
Finally, after the inversion to depth, we detect S-wave velocity anomalies with variations between −15% and 15% with reference to an estimated average velocity using 1 km and 3 km of lateral resolutions and 1 km of vertical resolution. This study shows the potential of ambient noise tomography as complementary seismological tool for reservoir characterization.
In recent years, new algorithms have been proposed to retrieve maximum available information in synthetic aperture radar (SAR) interferometric stacks with focus on distributed scatterers. The key step in these algorithms is to optimally estimate single-master (SM) wrapped phases for each pixel from all possible interferometric combinations, preserving useful information and filtering noise. In this paper, we propose a new method for SM-phase estimation based on the integer least squares principle. We model the SM-phase estimation problem in a linear form by introducing additional integer ambiguities and use a bootstrap estimator for joint estimation of SM-phases and the integer unknowns. In addition, a full error propagation scheme is introduced in order to evaluate the precision of the final SM-phase estimates. The main advantages of the proposed method are the flexibility to be applied on any (connected) subset of interferograms and the quality description via the provision of a full covariance matrix of the estimates. Results from both synthetic experiments and a case study over the Torfajökull volcano in Iceland demonstrate that the proposed method can efficiently filter noise from wrapped multibaseline interferometric stacks, resulting in doubling the number of detected coherent pixels with respect to conventional persistent scatterer interferometry.
Previously we modelled individual interferograms that showed that there was a large uplift signal. We modelled this as a series of sills and a dike with a total volume of ~0.05 km3. During the flank eruption, beginning on 20 March, no significant deformation is detected, but coinciding with the start of the explosive eruption on April 14, we detected subsidence centred on the caldera. What we modelled showed us that Eyjafjallajökull was an unusual which we modelled …. This deformation does not relate to pressure changes within a single magma chamber.
Here we extend our analysis InSAR time series covering full eruptive period. After correcting for DEM errors and reduction of atmospheric signal, we have found a number of signals that we interpreted in terms of magma movement. These magma movements are separately analysed in 3 phases: pre-eruptive (inflation), co-eruptive (no deformation) and post-eruptive (deflation).
The displacement time series from June 2009 to 4 February 2010 (pre-eruptive-phase) shows line-of-sight shortening on the southwest flank of about 2 cm. The displacement signal is present in a set of interferograms and it has a consistent behaviour in time, implying that it is not due to atmospheric contamination. We performed atmospheric stratification over the entire Interferogram (4 Feb 2010) to check how much of the signal correlated with the topography would disappear when removed. The correlation coefficient over the southwest flank is very small compared with the signal from the entire interferogram. We can say that in this area not much of the atmospheric effects related with the topography are present, suggesting that the signal could be deformation.
For the co/post-eruptive phases we calculated phase difference between nearby points to check their evolution in time. In the southeast flanks we observe deflation through all analyzed period, while in western flanks of the volcano we observe Inflation during effusive eruption, followed by deflation during explosive eruption, and a new inflation pattern between 05 June and 19 July that we cannot explain. In preliminary modelling we fit this post-eruptive phase with a pressure decrease of an ellipsoidal source, equivalent to a volume reduction of ~0.03 km3.
The limitations when analysing this dataset are mainly concerning the phase unwrapping performance through ice- and ash-covered areas. This is caused by decorrelation owing to ash cover where there is almost complete loss of coherence. We applied new methods to overcome these limitations. To improve point density over the scene, we combined PS (Persistent Scatterers) and SB (Small Baselines) methods. By combining highly coherent interferograms, the increase of distributed scatterers is clear and the phase unwrapping performance improved. To detect and correct non-systematic unwrapping errors, we calculated azimuth and range offsets. Additionally, because of the fact that L band has higher penetration, we processed ALOS images trough single interferogram analysis. By these means we were able to extract more of the deformation signal around decorrelated areas.
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Previously we modelled individual interferograms that showed that there was a large uplift signal. We modelled this as a series of sills and a dike with a total volume of ~0.05 km3. During the flank eruption, beginning on 20 March, no significant deformation is detected, but coinciding with the start of the explosive eruption on April 14, we detected subsidence centred on the caldera. What we modelled showed us that Eyjafjallajökull was an unusual which we modelled …. This deformation does not relate to pressure changes within a single magma chamber.
Here we extend our analysis InSAR time series covering full eruptive period. After correcting for DEM errors and reduction of atmospheric signal, we have found a number of signals that we interpreted in terms of magma movement. These magma movements are separately analysed in 3 phases: pre-eruptive (inflation), co-eruptive (no deformation) and post-eruptive (deflation).
The displacement time series from June 2009 to 4 February 2010 (pre-eruptive-phase) shows line-of-sight shortening on the southwest flank of about 2 cm. The displacement signal is present in a set of interferograms and it has a consistent behaviour in time, implying that it is not due to atmospheric contamination. We performed atmospheric stratification over the entire Interferogram (4 Feb 2010) to check how much of the signal correlated with the topography would disappear when removed. The correlation coefficient over the southwest flank is very small compared with the signal from the entire interferogram. We can say that in this area not much of the atmospheric effects related with the topography are present, suggesting that the signal could be deformation.
For the co/post-eruptive phases we calculated phase difference between nearby points to check their evolution in time. In the southeast flanks we observe deflation through all analyzed period, while in western flanks of the volcano we observe Inflation during effusive eruption, followed by deflation during explosive eruption, and a new inflation pattern between 05 June and 19 July that we cannot explain. In preliminary modelling we fit this post-eruptive phase with a pressure decrease of an ellipsoidal source, equivalent to a volume reduction of ~0.03 km3.
The limitations when analysing this dataset are mainly concerning the phase unwrapping performance through ice- and ash-covered areas. This is caused by decorrelation owing to ash cover where there is almost complete loss of coherence. We applied new methods to overcome these limitations. To improve point density over the scene, we combined PS (Persistent Scatterers) and SB (Small Baselines) methods. By combining highly coherent interferograms, the increase of distributed scatterers is clear and the phase unwrapping performance improved. To detect and correct non-systematic unwrapping errors, we calculated azimuth and range offsets. Additionally, because of the fact that L band has higher penetration, we processed ALOS images trough single interferogram analysis. By these means we were able to extract more of the deformation signal around decorrelated areas.