Search for: All records

Abstract Gas extraction from the Groningen gas reservoir, located in the northeastern Netherlands, has led to a drop in pressure and drove compaction and induced seismicity. Stress-based models have shown success in forecasting induced seismicity in this particular context and elsewhere, but they generally assume that earthquake clustering is negligible. To assess earthquake clustering at Groningen, we generate an enhanced seismicity catalog using a deep-learning-based workflow. We identify and locate 1369 events between 2015 and 2022, including 660 newly detected events not previously identified by the standard catalog from the Royal Netherlands Meteorological Institute. Using the nearest-neighbor distance approach, we find that 72% of events are background independent events, whereas the remaining 28% belong to clusters. The 55% of the clustered events are swarm-like, whereas the rest are aftershock-like. Among the swarms include five newly identified sequences propagating at high velocities between 3 and 50 km/day along directions that do not follow mapped faults or existing structures and frequently exhibit a sharp turn in the middle of the sequence. The swarms occurred around the time of the maximum compaction rate between November 2016 and May 2017 in the Zechstein layer, above the anhydrite caprock, and well-above the directly induced earthquakes that occur within the reservoir and caprock. We suggest that these swarms are related to the aseismic deformation within the salt formation rather than fluids. This study suggests that the propagating swarms do not always signify fluid migration. 

Abstract A variety of geo‐energy operations involve extraction or injections of fluids, including hydrocarbon production or storage, hydrogen storage, CO₂sequestration, and geothermal energy production. The surface deformation resulting from such operations can be a source of information on reservoir geomechanical properties as we show in this study. We analyze the time‐dependent surface deformation in the Groningen region in northeastern Netherlands using a comprehensive geodetic data set, which includes InSAR (Radarsat2, TerraSAR‐X, Sentinel‐1), GNSS, and optical leveling spanning several decades. We resort to an Independent Component Analysis (ICA) to isolate deformation signals of various origins. The signals related to gas production from the Groningen gas field and from seasonal storage at Norg Underground Gas Storage are clearly revealed. Surface deformation associated to the Groningen reservoir show decadal subsidence, with spatially variable subsidence rates dictated by local compressibility. The ICA reveals distinct seasonal fluctuations at Norg, closely mirroring the variations of gas storage. By comparing the observed long‐term subsidence within the Groningen reservoir and seasonal oscillations at Norg from a linear poroelastic compaction model, we quantify the fraction of inelastic deformation of the reservoir in space and time and constrain the reservoir compressibility. In Groningen, increased compressibility indicates inelastic compaction that has built over time and might account for as much as 20% of the total compaction cumulated until 2021, while Norg shows no signs of inelastic deformation and a constant compressibility. This study provides a methodology to monitor and calibrate models of the subsurface deformation induced by geo‐energy operations or aquifer management. 

Abstract Deterministic earthquake prediction remains elusive, but time‐dependent probabilistic seismicity forecasting seems within reach thanks to the development of physics‐based models relating seismicity to stress changes. Difficulties include constraining the earthquake nucleation model and fault initial stress state. Here, we analyze induced earthquakes from the Groningen gas field, where production is strongly seasonal, and seismicity began 3 decades after production started. We use the seismicity response to stress variations to constrain the earthquake nucleation process and calibrate models for time‐dependent forecasting of induced earthquakes. Remarkable agreements of modeled and observed seismicity are obtained when we consider (a) the initial strength excess, (b) the finite duration of earthquake nucleation, and (c) the seasonal variations of gas production. We propose a novel metric to quantify the nucleation model's ability to capture the damped amplitude and the phase of the seismicity response to short‐timescale (seasonal) stress variations which allows further tightening the model's parameters.