In this work, a 3D diffusion equation is considered to model induced seismicity due to fluid injections in a geological reservoir. A robust tracking control is then designed to force the seismicity rate to follow a desired reference, minimize induced seismicity and assure fluid circulation. The designed regulator ensures the control task despite system uncertainties and external perturbations. Simulations of the process are presented to show the reliability and performance of the control approach.

In the Rhine Ruhr area of western Germany, where Europe's largest district heating network is located, up to 1,300 m thick carbonates of Devonian age are available in ≥ 4,000 m depth. At reservoir depth, abundant karstification may significantly increase the geothermal reservoir potential. This study aims at the geological characterization of deep seated (hydrothermal) karst cavities in Steltenberg Quarry (western Germany) where Middle/Upper Devonian carbonates (Massenkalk limestone) are present in the vicinity of two regional fault zones. We applied state of the art petrographical, geochemical, palaeothermometrical methods, and U-Pb dating.

Forecasting the occurrence of slip behaviors, either aseismic creep or dynamic slip, relies heavily on understanding the evolution of friction controls during the interseismic creep, particularly those significantly modified from the previous slip events. Here we collected the experimental data from a series of fluid injection experiments and built a dual-stage attention-based recurrent neural network model to uncover the contributions of controlling factors. The results reveal that the shear stress becomes the dominant control of slip behaviors after the first dynamic slip event, promoting the propagation of rupture front and the occurrence of dynamic slip.