This paper presents a machine learning-based approach for detecting ground deformation patterns from time series indicative of potential sinkholes in the mining district of Lim-burg, the Netherlands. Our research uses large datasets of un-labeled, high-dimensional InSAR time series from Sentinel-1 and RADARSAT-2 satellites to identify anomalies that signal ground subsidence risks. Our methodology involves an anomaly detection process using dimensionality reduction, clustering time series data and cluster labeling. One of the challenges we face in the Limburg mining district is that there are no annotated datasets and no target labels that are required for a supervised learning approach, therefore we label the clusters by expert judgement. By adopting unsupervised learning, we aim to uncover unknown patterns in the time series, grouping similar temporal features into clusters for further analysis.

In this study, we develop a methodology to evaluate and benchmark the European Ground Motion Service (EGMS) products. Our approach integrates Global Navigation Satellite Systems (GNSS) measurements and measurements at and around corner reflectors (CRs), targeting the three product levels of the EGMS. We employ statistical tests to identify significant differences in the comparisons, focusing on time series, velocity estimation, and geopositioning. The study applies this practical methodology to evaluate the first EGMS product from 2015 and 2021 over various European test sites with significant surface deformation. The results consistently demonstrate a solid time series and velocity correlation between EGMS and GNSS at the tested sites, with, e.g., most of the differences between velocities being below 2 mm/year. This methodology, implemented in Python notebooks, ensures reproducible results and allows for validating the EGMS over other locations.

The European Ground Motion Service (EGMS) is part of the Copernicus Land Monitoring Service (CLMS) managed by the EEA (European Environment Agency) [1]. EGMS is based on the full resolution InSAR processing of ESA Sentinel-1 (S1) acquisitions over Europe (Copernicus Participating states) [2]. The first release or baseline includes ground motion time-series between 2015 and 2020. This open data service has yearly updates.The EGMS employs persistent scatterer (PS) and distributed scatterer (DS) in combination with a Global Navigation Satellite System (GNSS) model to calibrate the ground motion products. This public dataset consists of three products levels (L2a/Basic, L2b/Calibrated and L3/Ortho). The Basic and Calibrated product levels are full resolution (20x5m) Line of sight (Los) velocity maps from ascending/descending orbits. The Ortho product offers horizontal (East-West) and vertical (Up-Down) anchored to the reference geodetic model resampled at 100x100m.The objective of this paper is to describe the independent validation of this continental scale ground motion time-series dataset. The goal is to ensure that the EGMS products are consistent with user requirements and product specifications and they cover the expected range of applications. To evaluate the fitness of the EGMS ground motion data service 7 reproducible validation activities (VA) have been developed gathering validation data from 50 sites across 12 European countries. Last but not least, a software environment has been developed to carry out all the validation activities and describe/store the data coming from the validation sites.

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.

Reclaimed coastal plains often experience significant subsidence as a result of phreatic water level lowering, which induces oxidation of organic material, shrinkage of clay, and sediment compaction. A primary example in the center of the Netherlands, is the 'South Flevopolder' which was reclaimed in 1968 and transformed into an area for residential, industrial and agricultural use. The area subsided over 1.5 m since its reclamation and its surface is still lowering.The city of Almere, with roughly 200.000 inhabitants and a surface area of c. 250 km2, is situated in the South Flevopolder. Most buildings in the city are founded in deeper Pleistocene sand, whilst objects such as parking lots, sport fields and playgrounds are often unfounded and are directly situated on the younger Holocene coastal deposits. Currently, the unfounded objects show subsidence rates as high as 5 mm per year for which the different subsidence rates may be related to subsurface heterogeneities. The upper layers in the area are dominated by clay and sand, up to a few meters in thickness, which overly peat and highly organic layers. The lowering of the phreatic surface results in an erratic pattern of subsidence over the area.We present a workflow to disentangle and parameterize the different contributions of shallow subsidence from Interferometric synthetic-aperture radar (InSAR) measurements. InSAR measurements from founded and unfounded scatterers are separated with a dimensionality reduction technique, t-Distributed Stochastic Neighbor Embedding (t-SNE), followed by an automatic detection of clusters with Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN). We have limited ourselves to structures with a construction date of >10 years with respect to the first InSAR measurement date to reduce the effect of construction-related consolidation and isolate the effect of shallow subsidence related to reclamation and phreatic surface level changes. The filtered dataset represents the surface response of unfounded structures in the urbanized reclaimed coastal area.The subsidence processes are disentangled and parameterized with an Ensemble Smoother with Multiple Data Assimilation (ES-MDA). Additional input data for this method is provided by a phreatic groundwater level model and a voxelized lithological model from the surface towards the top of the Pleistocene sand layers.We show that the automated data selection method prevents bias by selecting unfounded objects and the proposed workflow can be of aid when studying shallow subsidence in urbanized areas, where most objects are founded below the level at which shallow subsidence takes place. The results of this study quantify the rate of the different subsidence processes on a spatiotemporal scale and thus provide insights for tailored decision making to mitigate subsidence.

We perform statistical analyses on spatiotemporal patterns in the magnitude distribution of induced earthquakes in the Groningen natural gas field. The seismic catalogue contains 336 earthquakes with (local) magnitudes above, observed in the period between 1 January 1995 and 1 January 2022. An exploratory moving-window analysis of maximum-likelihood b-values in both time and space does not reveal any significant variation in time, but does reveal a spatial variation that exceeds the significance level. In search for improved understanding of the observed spatial variations in physical terms we test five physical reservoir properties as possible b-value predictors. The predictors include two static (spatial, time-independent) properties: The reservoir layer thickness, and the topographic gradient (a measure of the degree of faulting intensity in the reservoir); and three dynamic (spatiotemporal, time-dependent) properties: The pressure drop due to gas extraction, the resulting reservoir compaction, and a measure for the resulting induced stress. The latter property is the one that is currently used in the seismic source models that feed into the state-of-The-Art hazard and risk assessment. We assess the predictive capabilities of the five properties by statistical evaluation of both moving window analysis, and maximum-likelihood parameter estimation for a number of simple functional forms that express the b-value as a function of the predictor. We find significant linear trends of the b-value for both topographic gradient and induced stress, but even more pronouncedly for reservoir thickness. Also for the moving window analysis and the step function fit, the reservoir thickness provides the most significant results. We conclude that reservoir thickness is a strong predictor for spatial b-value variations in the Groningen field. We propose to develop a forecasting model for Groningen magnitude distributions conditioned on reservoir thickness, to be used alongside, or as a replacement, for the current models conditioned on induced stress.

We investigate ground movements induced by the 8 February 2016, Mw=4.2 earthquake at the Los Humeros Geothermal Field (Mexico) using Sentinel-1 radar interferometry. Previous estimated focal mechanism solution based on seismic data with a hypocentral depth of 1900 m could not resolve the measured coseismic surface deformation pattern. In this study, we applied inverse elastic dislocation models to estimate the source parameters of the seismic event. Our models suggest the reverse reactivation of the Los Humeros normal fault at a shallower depth (<1000 m), with a more significant left lateral component below ~400 m depth. The occurrence of such shallow events at Los Humeros pose increased risks for the neighboring communities and infrastructure. Therefore, continuous monitoring of seismicity and cautious planning of field operations are crucial.

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.

After decades of oil, gas, and coal exploitation, we have learned about some of the unpleasant aftereffects of subsurface resource exploration. Adverse long-term impacts, some known during exploration periods, others only afterwards, may include induced seismicity, land subsidence, or even sinkholes. While geothermal is currently seen as a sustainable source of energy, seismicity induced by inappropriate operational procedures or lack of knowledge of the subsurface may incite doubt and public sensitivity about its future use. A problem frequently posed before and during geothermal exploration is the cost of geophysical measurements for resource assessment, subsurface characterization during the prospection phase, and monitoring accompanying production. In this study, we investigate and discuss the potential of two economic geophysical measurement techniques for geothermal reservoir characterization and monitoring: passive seismic interferometry for better subsurface characterization through seismic imaging (static model), and satellite-based radar interferometry for geodetic imaging (dynamic model). Seismic imaging using passive seismic techniques allows for subsurface characterization via Ambient Noise Tomography, and supports the assessment of geothermal resources without requiring the use of shooting, which reduces the cost compared to active seismics. Geodetic imaging, by measuring the surface displacements during and after production, allows for the monitoring of the effects of production and constrains reservoir modelling, and can be achieved through the use of (freely available) satellite imagery. We discuss the results of both techniques over two high enthalpy geothermal sites in Iceland: Reykjanes Peninsula and Torfajökull volcano. While the Reykjanes Peninsula has geothermal fields that have been producing for decades, Torfajökull’s geothermal field, despite being the largest in Iceland, is not producing. For the subsurface characterization, we use S-wave velocity tomographic images derived from ambient noise seismic interferometry over the two geothermal sites. Within the tomographic images, low- and high-velocity anomalies are used to characterize subsurface structures, which complement current geological models with information at greater depths. From the monitoring point of view, radar satellite deformation measurements over both areas show displacements (subsidence) due to production (Reykjanes) and due to natural phenomena (Torfajökull). Finally, we summarize the lessons learnt and discuss outcomes on each technique.

Tomographic imaging based on ambient seismic noise measurements has shown to be a powerful tool, especially in areas like Iceland, where the microseism illumination is excellent. In this paper, we produce a 3D S-wave tomographic image over the western Reykjanes Peninsula high-enthalpy geothermal fields and evaluate the reliability of the tomographic results for different resolutions through simulated and real data. We use 30 broadband stations operating for approximately one-and-a-half year and apply ambient noise seismic interferometry for each station-pair. This results in empirical Green's functions in which especially the ballistic surface waves (BSW) are well resolved. The retrieved BSW exhibit a high signal-to-noise ratio between 0.1 and 0.5 Hz, and the beamforming analysis indicates an apparent surface-wave velocity of 3 km/s over a broad azimuthal range. For the tomographic inversion, we invert the estimated phase velocities between all station pairs to frequency-dependent phase velocity maps in four different resolutions (1, 2, 3, and 4 km) using a Tikhonov regularisation. With the estimated regularisation parameter per frequency per resolution, we invert simulated data for checkerboard sensitivity tests per frequency for different combinations of velocity anomaly sizes and resolutions.

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.

Integration of results from active seismic, passive seismic and well data reduces the uncertainties of several subsurface parameters that are of interest for cost-effective geothermal production operations in Los Humeros. In this study, we present results from the application of ambient noise seismic interferometry (ANSI) to retrieve zero-offset reflected P-waves from continuous seismic data recorded at the Los Humeros geothermal field, Mexico. This study is inspired by encouraging results from the application of ANSI for body wave reflection retrieval that was reported in 2016 for a geothermal field located at Reykjanes peninsula, Iceland (Verdel et al., 2016). Continuous broadband and short-period seismic recordings provided insightful reflection information that corresponded well, in relevant depth intervals, with reflectivity retrieved from the correlation of coda waves from a distant but very strong earthquake. That work was carried out within the context of EU’s Seventh Framework research and innovation program IMAGE. Encouraged by these findings, it was decided to conduct a new study following a similar approach within the context of the GEMex project, a European-Mexican collaboration. The purpose of GEMex is to gain an improved understanding of the geological structure and geothermal reservoir behaviour for two geothermal fields: Los Humeros and Acoculco. In the following, we address data selection and processing aspects related to the retrieval of reflected P-waves from Los Humeros seismic noise recordings. The retrieved reflections are compared with modelled reflectivities at two station locations at a close distance from the location where the seismic interval velocities that are used in the modelling were available from the literature. The reflected P-wave information provides structural detail about the field at locations directly underneath the employed seismic stations.

Torfajökull volcano, Iceland, has not erupted since 1477. However, intense geothermal activity, deformation, and seismicity suggest a long‐lasting magmatic system. In this paper, we use ambient noise tomography to image the magmatic system beneath Torfajökull volcano. One hundred days of ambient noise data from 23 broadband seismometers show the consistent presence of double‐frequency microseism noise with significant power between ∼0.1 and 0.5 Hz. Beamforming results indicate microseism noise with persistent higher energy propagating from west and SE directions and apparent velocities below 3 km/s. We use ambient noise seismic interferometry to retrieve Rayleigh waves, and we introduce a method to estimate the reliability of the retrieved surface waves. We find stable estimation of surface wave phase velocities between 0.16 and 0.38 Hz. Azimuthal velocity variations show a trend of higher velocities in the NE/SW direction, the strike of the rift zone intersecting Torfajökull, and orientation of erupted lavas on a NE‐SW fissure swarm. Tomographic results indicate low‐velocity anomalies beneath the volcano caldera (between −5% and −10%) and even lower velocity variations in the southeast and southwest study area (below −10%), outside the volcano caldera. Low anomalies may indicate the existence of hot material, more prominent outside the caldera outskirts. High‐velocity variations (between 5% and 10%) outline the volcano caldera between 4‐ and 5‐km depth and more pronounced velocities (between 10% and 15%) up to 5‐km depth in the north of the volcano caldera. We interpret the former as possible caldera collapse structure and the latest as solidified intrusive magma from the old preferred magma paths.

On the 8th of February 2016, a Mw 4.2 earthquake was detected inside the Los Humeros caldera, located in the eastern sector of the Trans-Mexican Volcanic Belt. The event occurred after a sharp increase in the injection rate at the Los Humeros Geothermal Field and it was recorded by the seismic monitoring network of the power plant. The earthquake was felt by the local population and it caused damage in the power plant infrastructure. The focal mechanism solution of a previous study based on seismological data shows a reverse movement with a minor left-lateral component: Mw=4.2, depth=1500m, strike=169°, dip=61°, rake=42°. We have performed a geodetic and geomechanical analysis of the seismic source event based on ground deformation inferred from DInSAR. We used ascending and descending Sentinel-1 differential interferograms to retrieve the horizontal and vertical components of the co-seismic deformation. Subsequently, we inverted the estimated deformation to obtain the solution of an activated fault using the Okada model. These results shed light on the geomechanical aspects of the event and can help to understand the effects of field operations interacting with pre-existing structural features and active tectonic processes in the Los Humeros caldera.

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.

Variations of b-values in Gutenberg-Richter’s law has been proven to provide insights on earthquake triggering mechanisms. These b-value variations express changes in the rate of occurrence of small earthquakes relative to large ones. Geophysical processes correlated with b-value variations have been identified using earthquake catalogues over natural tectonically active environments. Not so much is known over anthropogenic exploration sites due to the lack of dedicated seismometers in place and therefore the reduced number of recorded events. In the early 1990's, nearly after 30 years of gas production, small seismic events started to be detected at the Groningen gas field. Several efforts to measure these seismic events let to a unique seismic network and an earthquake catalogue available through KNMI’s website. We perform a temporal, spatial and spatiotemporal b-value analysis for which we use 800 events from early 90’s up to now with a magnitude lower limit of 1.1 (magnitude of completeness).

Tomographic studies based on passive seismic measurements have proven to be a powerful tool to image the subsurface. This especially holds in areas like Iceland, where the microseism coverage arriving from the ocean is excellent. In this study, we apply Ambient Noise Seismic Interferometry (ANSI) to generate a tomographic image of Rayleigh-waves velocity anomalies to further invert for S-wave anomalies at two Icelandic locations. We derive a tomographic image over Reykjanes Peninsula geothermal system using 30 Broad-Band (BB) stations deployed under the IMAGE (Integrated Methods for Advanced Geothermal Exploration) project framework and operated for approximately one year and a half. In the other case study, we derive a tomographic image of Torfajökull volcano using 23 BB seismometers that recorded ambient noise for 100 days. The later data were acquired in 2005 by Cambridge University. We retrieve the surface-wave part of the Green’s functions by cross-correlation between station pairs and consecutive stacking of the cross-correlations to obtain coherent ballistic surface waves (BSW). We pick the arrival times of the BSW, which are the input for the tomographic analysis. Both datasets show remarkably high signal-to-noise ratio of surface-wave arrivals between 0.1 and 0.5 Hz, even with only 100 days of recorded ambient noise. A beamforming analysis indicates a broad azimuthal coverage with persistent ambient noise arrivals within three azimuthal quadrants - between 90 and 360 degrees. The highly coherent surface-wave retrieval and the wide azimuthal coverage of the microseisms explain the success of ANSI techniques in Iceland. For the tomographic inversion, we use a Tikhonov and a statistical regularisation to invert the ballistic surface-wave time-arrival to 3D frequency-dependent velocity variations. After further inversion to S-wave velocity variations, we detect low- and high-velocity anomalies with changes between -15% and 15% from an estimated average velocity, we interpret these anomalies as possible old dyke intrusions and heat sources.

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.