TS1.4

In nation-wide radar satellite time series data of Germany, a linear subsidence motion of several kilometer spatial wavelength shows up south-east of Kiel, northern Germany. The center region of this signal, showing line-of-sight displacement velocities of about 2 mm/a, coincides with the facilities of a gas storage site managing two in-service and one out-of-service caverns in the salt dome beneath. The three caverns have been water-drilled only a few hundred meters apart in 1971, 1996 and 2014 into a large halite salt dome, which has risen up there to depths of around 1000 m. Their sizes range within a couple of 100.000 m³. Above the salt body thick deposits of mainly chalk, silk and claystone below layers of clays, silts, sands and glacial marls in the upper 200 m form a relatively strong roof layer.

We hypothesize that despite a thick and competent cover layer, the long-term ductile behavior of halite, which evidently causes shrinking of the cavern volumes through time, results in the observed continuous surface subsidence across several square kilometers. We present an attempt to test the hypothesis by optimizing a simple kinematic model to fit the surface subsidence signal. Using equivalent body forces to represent an isotropic volume point source embedded in a viscoelastic host medium below a horizontally layered elastic roof medium, we estimate the horizontal position of a single cavern, its depth and the corresponding volume change at the cavern. The medium properties at the cavern sites are well known from borehole geophysical analyses, but likely vary strongly laterally. We use InSAR time series data from two ascending look directions and two descending.

Our results show that a cavern at about 1200 m depth and in very close proximity to above-ground facilities of the storage site can indeed be associated with the observed ground motion. The best-fit models pin the location to the known positions, also in depth. The estimated volume loss is slightly larger than 20.000 m³ per year and is in the same order of volume loss estimated from volume measurements inside the actual caverns.

The model approach we present, a single kinematic point source for three caverns and a one-dimensional medium model, is simple, the signal-to-noise ratio of the satellite data is rather small and furthermore there are considerable spatial gaps in the InSAR time series data in areas of agriculture and forests. However, with a computationally fast forward calculation of surface displacements we can afford to propagate data error statistics that account for spatially correlated errors to model parameter uncertainty estimates in a Bayesian way through model ensembles. We plan to add modeling errors of the medium to better grasp their potential influence on the volume loss estimations. The optimization code we use, Grond, is part of the seismological open-source software toolbox Pyrocko (pyrocko.org). The data is openly available at bodenbewegungsdienst.bgr.de.

How to cite: Sudhaus, H., Seidel, A. L., and Schulze-Glanert, N.: A kinematic model for observed surface subsidence above a salt cavern gas storage site in Northern Germany, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11827, https://doi.org/10.5194/egusphere-egu22-11827, 2022.

The Arabian Peninsula is part of a small tectonic plate that is characterized by active and appreciable deformations along its boundaries. Knowledge of the present-day in situ stress field in the Arabian plate and its variability is critical for earth science disciplines that require an understanding of geodynamic processes. In addition, it is essential for a range of practical applications that include the production of hydrocarbons and geothermal energy, mine safety, seismic hazard assessment, underground storage of CO2, and more.

This project aims at modeling the stress orientation field in the Arabian Plate using advanced computational tools together with a plate velocity model. We built a three-layer 3D model of the Arabian crust using digital elevation, basement depth, and Moho depth maps. Based on these data, we built a 3D unstructured finite element mesh for the whole Arabian plate, including the offshore area, with finer resolution at critical locations. The latter is a novel approach to this work.  To capture the deformation caused by the water bodies in the Red Sea, Gulf of Aden, and the Arabian Sea areas, we set a hydrostatic boundary condition as a function of bathymetry. Along the Zagros fold and thrust belt, we pinned the plate boundary to capture continental collision. Finally, the partial differential equation of force equilibrium (a linear static analysis) is solved using plate displacements (inferred from plate velocities) as boundary conditions for several displacement conditions.

The modeling results suggest NE-SW S_Hmax azimuths in northeastern Saudi Arabia and Kuwait while the Dead Sea transform areas show NW-SE to NNW-SSE azimuths, and the rest of the plate is characterized by predominant N-S S_Hmax azimuth. Due to pinned boundary conditions at the Zagros Mountains, S_Hmax azimuth changes from N-S at the Red Sea basin to NE-SW at the Zagros fold and thrust belt. We also notice significant stress concentrations in the transition from the Arabian shield to the sedimentary basins in the Eastern parts of the plate. This is in response to associated changes in rock properties. Hence, the simulated stress orientations corroborate the ongoing tectonic process and deepen our understanding of regional and local in situ stress variation drivers as well as the current elastic deformation in the Arabian plate.

How to cite: Pena Clavijo, S., Finkbeiner, T., and Afifi, A. M.: Modeling principal stress orientations in the Arabian plate using plate velocities, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4738, https://doi.org/10.5194/egusphere-egu22-4738, 2022.

Machine learning algorithms (MLAs) are emerging as a powerful tool for forecasting complex and nuanced rock mass behaviour, particularly when large, multivariate datasets are available. In engineering practice, it is often difficult for geomechanical professionals to investigate all available data in detail, and simplifications are necessary to streamline the engineering design process. An MLA is capable of processing large volumes of data quickly and may uncover relationships that are not immediately evident when manually processing data. This research compares two algorithms developed for two mines representing end member behaviours of rock failure mechanisms: squeezing ground with high radial convergence, and spalling ground with high in situ stresses and seismicity. For the squeezing ground case study, a Convolutional Neural Network is used to forecast the yield of the tunnel liner elements using tunnel mapping images as the input. For the high stress case study, a Long Short Term Memory network is used to forecast the in-situ stresses that takes time series microseismic events and geomechanical properties as inputs. The two case studies are used to compare input data requirements and pre-processing techniques. Ensemble modelling techniques used to quantify MLA uncertainty for both case studies are presented. The development of the two MLAs is discussed in terms of their complexity, generalizability, performance evaluation, verification, and practical applications to underground rock engineering. Finally, best practices for MLA development are proposed based on the two case studies to ensure model interpretability and use in engineering applications.

How to cite: Morgenroth, J., Khan, U. T., and Perras, M. A.: Machine Learning and Underground Geomechanics – data needs, algorithm development, uncertainty, and engineering verification, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-799, https://doi.org/10.5194/egusphere-egu22-799, 2022.

NE-SW stress compression in the Western Canadian Sedimentary Basin was discovered in the pioneering borehole breakout observations of Bell and Gough (1979). However, all of these and subsequent stress direction indicators are from the Phanerozoic sediment veneer, while the state of stress in the underlying craton remains unexplored. With the emergent demands on geothermal energy and wastewater and CO₂ disposal, however, the state of stress in the cratons can no longer be safely ignored. To address this problem, we analyze various vintages of geophysical logs obtained from a serendipitous wellbore-of-opportunity drilled to 2.4 km in NE Alberta.  The profile of breakout orientations inferred from image and caliper logs exhibits a distinct rotation in breakout orientations changing from N100°E at 1650-2000m to N173°E at 2000-2210m and, finally, to N145°E at the bottom from 2210-2315m. The deepest measurement is consistent with the many observations in the overlying sediments. The heterogeneous breakout orientations at different depth intervals possibly indicate a heterogeneous in-situ stress field in the Precambrian craton. In addition, however, there is a strong correlation between the metamorphic textures and the breakout orientations suggesting that anisotropic strength may play an important role.  Using a recently developed algorithm we show that these observations can indeed be explained by foliation-controlled failure patterns in such anisotropic metamorphic rocks (Wang & Schmitt, accepted).  Models demonstrate that the observed breakout rotations can be produced under uniform stress orientations with failure slip planes controlled by the textured metamorphic rocks with anisotropic strength. This modeled stress field indicates that the stress field in the Canadian Shield where the far-field S_H azimuth is at N50°E and the region is under normal/strike-slip faulting regime, is coupled with that in the overlying sedimentary basin.

How to cite: Wang, W. and Schmitt, D.: Stress characterization in the Canadian Shield: Complexity in stress rotation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5494, https://doi.org/10.5194/egusphere-egu22-5494, 2022.

Deformation rate analysis (DRA) and Acoustic Emission (AE) are popular methods of in-situ stress measurements from oriented cored rocks which take advantage of the rock stress memory also known as the Kaiser effect. These methods rely on the accurate measurement of a point of inflection in the characteristic DRA and AE curves, however, due to the complex geological stress history in rocks, locating point of inflection can be problematic. In order to better understand the stress memory experiments were performed on a combination of six different types of soft, and hard crystalline rocks including concrete with no stress history. The effect of loading modes, strain rates, and time delay were studied on preloaded rock specimens to investigate their influence on the stress memory. A fading effect was observed when the number of the cycles in the test were increased which led to the development of a new method of quantifying the preloads. Results show that the type of loading and the loading rate has little to no influence on the Kaiser effect, however, under faster loading rates the Kaiser effect is more distinct. Likewise, no time dependency was observed for time delays up to seven months.

How to cite: Ali, Z., Karakus, M., Nguyen, G. D., and Amrouch, K.: The stress memory in rocks: insight from the deformation rate analysis (DRA) and acoustic emission (AE), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3272, https://doi.org/10.5194/egusphere-egu22-3272, 2022.

Hydrocarbon production may cause subsidence as a result of the pressure reduction in the gas-producing layer and reservoir compaction. To analyze the process of subsidence and estimate reservoir parameters, we use a particle method to assimilate Interferometric synthetic-aperture radar (InSAR) observations of surface deformation with a conceptual model of reservoir. As example, we use an analytical model of the Groningen gas reservoir based on a geometry representing the compartmentalized structure of the subsurface at the reservoir depth.

The efficacy of the particle method becomes less when the degree of freedom is large compared to the ensemble size. This degree of freedom, in turn, varies because of spatial correlation in the observed field. The resolution of the InSAR data and the number of observations affect the performance of the particle method.

In this study, we quantify the information in a Sentinel-1 SAR dataset using the concept of Shannon entropy from information theory. We investigate how to best capture the level of detail in model resolved by the InSAR data while maximizing their information content for a data assimilation use. We show that incorrect representation of the existing correlations leads to weight collapse when the number of observation increases, unless the ensemble size growths. However, simulations of mutual information show that we could optimize data reduction by choosing an adequate mesh given the spatial correlation in the observed subsidence. Our approach provides a means to achieve a better information use from available InSAR data reducing weight collapse without additional computational cost.

How to cite: Kim, S. S. R., Vossepoel, F. C., Wouters, M. C., Govers, R., Brouwer, W. S., and Hanssen, R. F.: Optimizing the use of InSAR observations in data assimilation problems to estimate reservoir compaction, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11879, https://doi.org/10.5194/egusphere-egu22-11879, 2022.

Quantifying the contemporary stress state of the Earth’s crust is critical for developing a geomechanical understanding of the behavior of brittle deformation (fractures and faults).In this study we characterize the shallow contemporary stress state of the active Hikurangi Subduction Margin (HSM), New Zealand, to better understand how it affects and responds to variable deformation and slip behavior documented along this plate boundary. The HSM is characterized by along-strike variations in megathrust slip behavior, ranging from shallow slow slip events (SSEs) and creep at the northern and central HSM to interseismic locking and stress accumulation in the southern HSM. We estimate the state of stress across the HSM utilizing rock strength estimates from empirical relationships, leak-off test data, wireline logs and borehole geology, and measurement of borehole wall failures such as borehole breakouts and drilling‐induced tensile fractures from eight boreholes. Stress magnitude constraints at depth intervals where BOs are observed indicate that the maximum principal stress (σ₁) is horizontal along the shallow (<3 km) HSM and the stress state is predominantly strike-slip or contractional (barring localized areas where an extensional stress state is determined). Our results reveal a NE-SW (margin-parallel) S_Hmax orientation in the shallow central HSM, which rotates to a WNW- ESE/NW-SE (margin-perpendicular) S_Hmax orientation in the shallow southern HSM. The central NE-SW S_Hmax orientation is inconsistent with active, km-scale, NE-SW striking contractional faults observed across the central HSM. Considering both stress magnitude and orientation patterns at the central HSM, we suggest that long-term clockwise rotation of the Hikurangi forearc, over time, may transform motion on these km-scale central HSM faults from contractional dip-slip to a more contemporary strike/oblique-slip. The southern shallow WNW- ESE/NW-SE S_Hmax orientation is nearly perpendicular to focal-mechanisms derived NE-SW S_Hmax orientations within the subducting slab. This, combined with observed strike-slip and contractional faulting in the region and the NW-SE convergence direction, implies the overriding plate in the southern HSM is in a contractional stress state, potentially as deep as the plate interface, which is decoupled from that experienced in the subducting slab. Observed localized extensional stress states across the HSM may occur as a result of local extensions or reflect uncertainties in our estimations of S_Hmax magnitude which are sensitive to the UCS values used (unconstrained by laboratory testing). This UCS uncertainty and the potential errors it can introduce into a stress model highlights the importance of developing robust empirical relationships for UCS in regions where stress is a critical geological consideration for hazard and resource management.

How to cite: Behboudi, E., McNamara, D., and Lokmer, I.: Stress state and patterns at the upper plate of Hikurangi Subduction Margin, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8802, https://doi.org/10.5194/egusphere-egu22-8802, 2022.