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Induced seismicity associated with geothermal energy applications is a threat to feasibility and social acceptance. Thermo-Hydro-Mechanical models that predict changes in the criticality of the rock help to mitigate induced seismicity. One of the key challenges in these models is the knowledge of the initial stress state. It can be predicted throughout a reservoir using 3D geomechanical-numerical models. However, their model results are subject to high uncertainties. Here, a novel modelling approach is presented that both quantifies the uncertainties and reduces them. Various model scenarios are set up that are possible options of the subsurface stress state based on data records. To limit the range to realistic stress states only, additional and more widely available constraints on stress magnitudes are incorporated. Information from boreholes such as formation integrity tests, borehole breakouts, or drilling induced tensile fractures as well as observed seismicity or distinguished seismological quiescence in connection with a failure criterion are used as constraints. A Bayesian approach is followed in order to weigh the input data and estimate a final weight for each model scenario. A case study in the Bavarian Molasse Basin shows that in the novel approach model uncertainties are reduced.

Stress maps show the orientation of the current maximum horizontal stress (SHmax) in the earth's crust. Assuming that the vertical stress (SV) is a principal stress, SHmax defines the orientation of the 3D stress tensor; the minimum horizontal stress Shmin is than perpendicular to SHmax. In stress maps SHmax orientations are represented as lines of different lengths. The length of the line is a measure of the quality of data and the symbol shows the stress indicator and the color the stress regime. The stress data are freely available and part of the World Stress Map (WSM) project. For more information about the data and criteria of data analysis and quality mapping are plotted along the WSM website at http://www.world-stress-map.org. The stress map of Great Britain and Ireland 2022 is based on the WSM database release 2016. All data records have been checked and we added a number of new data from earthquake focal mechanisms from the national earthquake catalog and borehole data. The number of data records has increased from n=377 in the WSM 2016 to n=474 in this map. Some locations and assigned quality of WSM 2016 data were corrected due to new information. The digital version of the map is a layered pdf generated with GMT (Wessel et al., 2019) using the topography of Tozer et al. (2019). We also provide on a regular 0.1° grid values of the mean SHmax orientation which have a standard deviation < 25°. The mean SHmax orientation is estimated using the tool stress2grid of Ziegler and Heidbach (2019). For this estimation we used only data records with A-C quality and applied weights according to data quality and distance to the grid points. The stress map is available at the landing page of the GFZ Data Services at http://doi.org/10.5880/WSM.GreatBritainIreland2022 where further information is provided.

For around 700 hundred years, the greater Ruhr region has been the heart of the coal mining industry in Germany. In 2018, the last coal mine ceased operation in the country, and the process of abandonment and repurposing of the vast amounts of unused subsurface infrastructure has begun. The operations of mine flooding as well as the recent geothermal exploration campaigns, aiming to utilize old mine infrastructure as well as permeable Massenkalk formations found below mining depths, pose serious questions regarding safety and potential seismic risks in the densely populated greater Ruhr region. To alleviate these concerns, we assess the probability of reactivation of major fault in the region. This study benefits from the astonishing amount of 429 stress magnitude and 38 stress orientation data records derived from hydrofracturing tests and borehole logs carried out in six coal mines and two coal bed methane boreholes between 1986 and 1995. Due to the change in subsurface data regulations, this data has been just recently made available to the public. Our study summarizes the results of this extensive in situ stress test campaign, assigns quality to each data record using the established quality ranking schemes of the World Stress Map project for both stress orientations and magnitudes, and, in combination with already published material, provides the first comprehensive stress database of the region. This unique data set, together with geometries of major faults revealed from coal mining activities and already published results from laboratory studies, serves as a base for the probabilistic assessment of fault reactivation potential, incorporating uncertainty of each Mohr-Coulomb parameter (i.e., stress tensor, pore pressure, frictional properties, and fault geometry). The probabilistic assessment of fault reactivation potential, as presented in this study, aims to de-risk future subsurface operations facilitating the green transition of the greater Ruhr region.

Stress maps show the orientation of the current maximum horizontal stress (SHmax) in the earth's crust. Assuming that the vertical stress (SV) is a principal stress, SHmax defines the orientation of the 3D stress tensor; the minimum horizontal stress Shmin is than perpendicular to SHmax. In stress maps SHmax orientations are represented as lines of different lengths. The length of the line is a measure of the quality of data and the symbol shows the stress indicator and the color the stress regime. The stress data are freely available and part of the World Stress Map (WSM) project. For more information about the data and criteria of data analysis and quality mapping are plotted along the WSM website at http://www.world-stress-map.org. The stress map of Taiwan 2022 is based on the WSM database release 2016. However, all data records have been checked and we added a large number of new data from earthquake focal mechanisms from the national earthquake catalog and from publications. The total number of data records has increased from n=401 in the WSM 2016 to n=6,498 (4,234 with A-C quality) in the stress map of Taiwan 2022 The update with earthquake focal mechanims is even larger since another 1313 earthquake focal mechanism data records beyond the scale of this map have been added to the WSM database. The digital version of the stress map is a layered pdf file generated with GMT (Wessel et al., 2019). It also provide estimates of the mean SHmax orientation on a regular 0.1° grid using the tool stress2grid (Ziegler and Heidbach, 2019). Two mean SHmax orientations are estimated with search radii of r=25 and 50 km, respectively, and with weights according to distance and data quality. The stress map and data are available on the landing page at https://doi.org/10.5880/WSM.Taiwan2022 where further information is provided. The earthquake focal mechanism that are used for this stress map are provided by the Taiwan Earthquake Research Center (TEC) available at the TEC Data Center (https://tec.earth.sinica.edu.tw).

The 3D geomechanical-numerical modelling aims at a continuous description of the stress state in a subsurface volume. The model is fitted to the model-independent stress data records by adaptation of the displacement boundary conditions. This process is herein referred to as model calibration. Depending on the amount of available stress data records and the complexity of the model the calibration can be a lengthy process of trial-and-error to estimate the best-fit boundary conditions. The tool FAST Calibration (Fast Automatic Stress Tensor Calibration) is a Matlab script that facilitates and speeds up this calibration process. By using a linear regression it requires only three test model scenarios with different displacement boundary conditions to calibrate a geomechanical-numerical model on available stress data records. The differences between the modelled and observed stresses are used for the linear regression that allows to compute the displacement boundary conditions required for the best-fit estimation. The influence of observed stress data records on the best-fit displacement boundary conditions can be weighted. Furthermore, FAST Calibration provides a cross checking of the best-fit estimate against indirect stress information that cannot be used for the calibration process, such as the observation of borehole breakouts or drilling induced fractures. The script files are provided for download at http://github.com/MorZieg/FAST_Calibration. Tab. 0-1 gives an overview of the folder structure and input files with a short explanation.

The 3D geomechanical-numerical modelling of the in-situ stress state aims at a continuous description of the stress state in a subsurface volume. It requires observed stress information within the model volume that are used as a reference. Once the modelled stress state is in agreement with the observed reference stress data the model is assumed to provide the continuous stress state in its entire volume. The modelled stress state is fitted to the reference stress data records by adaptation of the displacement boundary conditions. This process is herein referred to as calibration. Depending on the amount of available stress data records and the complexity of the model the manual calibration is a lengthy process of trial-and-error modelling and analysis until best-fit boundary conditions are found. The Fast Automatic Stress Tensor Calibration (FAST Calibration) is a Python function that facilitates and speeds up this calibration process. By using a linear regression it requires only three model scenarios with different boundary conditions. The stress states from the three model scenarios at the locations of the reference stress data records are extracted. The differences between the modelled and observed stress states are used for a linear regression that allows to compute the displacement boundary conditions required for the best-fit modelled stress state. If more than one reference stress state is provided, the influence of the individual observed stress data records on the best-fit boundary conditions can be weighted. The script files are provided for download at: http://github.com/MorZieg/PyFAST_Calibration

These data are supplementary material to Ziegler & Heidbach (2020) and present the results of a 3D geomechanical-numerical model of the stress state with quantified uncertainties. The average modelled stress state is provided for each of the six components of the full stress tensor. In addition, the associated standard deviation for each component is provided. The modelling approach uses a published lithological model and the used data is described in the publication Ziegler & Heidbach (2020). The reduced stress tensor is derived using the Tecplot Addon GeoStress (Stromeyer & Heidbach, 2017).The model results are provided in a comma-separated ascii file. Each line in the file represents one of the approx. 3 million finite elements that comprise the model.

GFZ, German Research Centre for Geosciences, Potsdam, Germany (1); MIT, Massachussets Institute of Technology, Cambridge, MA, USA (2); RWTH Aachen University, Aachen, Germany (3) In this study, we carry out an evaluation of the potential for induced seismicity arising from hydraulic stimulation of low to intermediate enthalpy porous reservoirs, by taking the geothermal reservoir of Groß Schönebeck (northern Germany) as study case. The aim is to evaluate the spatial and temporal distribution of 26 events, which were triggered by hydraulic stimulations in the volcanic section of the reservoir. The results from the THM simulations of this hydraulic stimulation are in agreement with the calculated overpressure and indicate that an increase in the reservoir fluid pressure is most likely responsible for the recorded micro-seismicity. Our current evaluation shows an increase of slip and dilation during the treatment on the seismic plane, of magnitudes close to the failure level as based on Mohr-Coulomb friction concept which would have led to a reactivation of the fault plane and related seismic activity. We conclude this contribution by presenting a thermodynamically consistent framework to describe the deformation dynamics at the semi-brittle semi-ductile transition, thereby extending the classical mechanical analysis to faulting processes. We will focus on (i) the role of damage weakening and its impact on the evolution of localized deformation and (ii) the role of porosity evolution as precursor to dilatant brittle deformation. We will demonstrate how such a framework can bridge the gap between the microstructural evolution, expressed in terms of a damage intensity variable, and the macroscopic response of porous rocks subject to differential loading and in the presence of fluids.

Dataset

The present-day stress state is a key parameter in numerous geoscientific research fields including geodynamics, seismic hazard assessment, and geomechanics of georeservoirs. The Taranaki Basin of New Zealand is located on the Australian Plate and forms the western boundary of tectonic deformation due to Pacific Plate subduction along the Hikurangi margin. This paper presents the first comprehensive wellbore-derived basin-scale in situ stress analysis in New Zealand. We analyze borehole image and oriented caliper data from 129 petroleum wells in the Taranaki Basin to interpret the shape of boreholes and determine the orientation of maximum horizontal stress (S-Hmax). We combine these data (151 S-Hmax data records) with 40 stress data records derived from individual earthquake focal mechanism solutions, 6 from stress inversions of focal mechanisms, and 1 data record using the average of several focal mechanism solutions. The resulting data set has 198 data records for the Taranaki Basin and suggests a regional S-Hmax orientation of N068 degrees E (22 degrees), which is in agreement with NW-SE extension suggested by geological data. Furthermore, this ENE-WSW average S-Hmax orientation is subparallel to the subduction trench and strike of the subducting slab (N50 degrees E) beneath the central western North Island. Hence, we suggest that the slab geometry and the associated forces due to slab rollback are the key control of crustal stress in the Taranaki Basin. In addition, we find stress perturbations with depth in the vicinity of faults in some of the studied wells, which highlight the impact of local stress sources on the present-day stress rotation.