Abstract
Successful design of enhanced geothermal systems (EGSs) requires accurate numerical simulation of hydraulic stimulation processes in the subsurface. To ensure correct prediction, the underlying model assumptions and constitutive relationships of simulators need to be verified against experimental datasets. With the aim of generating laboratory-scale benchmark datasets, a state-of-the-art testing facility was developed, allowing for experiments under controlled conditions. Samples of size 30 cm × 30 cm × 45 cm were subjected to confining stresses while high-pressure fluid was injected into the sample through a pre-drilled borehole, where a saw-cut notch was used to initiate a penny-shaped fracture. Fracture growth and propagation was monitored by measuring pressure data and acoustic emissions detected using 32 seismic sensors. Subsequently, samples were split along the fracture plane to outline the created fracture marked by a red-dyed injection fluid. Finally, a 2D fracture contour was generated using photogrammetry. Presented datasets, accessible via a public repository, include experiments on granite and marble samples. They can be used for verifying and improving numerical codes for field stimulation designs.
Highlights
Background & SummaryEngineering a successful stimulation system in the subsurface requires understanding rock response to different pressure conditions
Due to the lack of analytical solutions for these coupled, non-linear processes, the accuracy of these simulation tools in solving hydro-mechanical processes can only be assessed by comparing the simulated results against laboratory-scale or field-scale datasets
A code comparison study investigating the capabilities of numerical codes and the quality of the numerical solutions to specific enhanced geothermal systems (EGSs) problems is reported in[1], where real field data was used to benchmark a number of simulators under specific assumptions
Summary
Engineering a successful stimulation system in the subsurface requires understanding rock response to different pressure conditions. To obtain meaningful results from laboratory tests, it is necessary to perform experiments on sufficiently large samples so that a stable fracture propagation can be achieved. Experiments of this scale are rather expensive and relatively rare in the geothermal energy sector, especially when performed under true triaxial conditions, i.e. with confining stresses along all the three axes. Most of these facilities are often commissioned by oil and gas companies, and their results are not publicly available to the broad scientific community. We provide a Python-based code which can be used for processing the seismic data and visualizing of the experimental results
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