| Abstract |
Knowledge of the petrophysical and mineralogical parameters of a geothermal reservoir is essential for the estimation of rock mechanical behavior during hydraulic stimulation. The strength of a rock is determined by manifold petrophysical parameters. Clay bearing zones, which form during hydrothermal alteration, can affect not only the mechanical reservoir properties, but also the hydraulic properties, the stress parameters and the occurrence of induced seismicity. We describe in this manuscript a neural network based method to identify clay bearing fracture zones from spectral gamma logs of the geothermal site at Soultz-sous-Forêts. With this method, synthetic clay content logs (SCCL) are obtained, which can be used as a basis for the interpretation of hydraulic, mechanical and seismic data in order to investigate the effects of hydrothermal alteration on the reservoir behavior. By comparing SCCL logs of the five geothermal wells with hydro-mechanical and seismic data, it is shown that the precipitation of clay minerals locally lowers the frictional strength of the reservoir rock. Such weak zones can affect the orientation and magnitude of the principal stress components. In terms of hydraulic properties of the reservoir, the formation of secondary minerals as fracture fillings can increase, but also reduce fracture permeability. Fractures with high clay content seem to affect the evolution of induced seismicity during hydraulic stimulation and to promote the occurrence of aseismic movements. Thus, secondary mineral precipitation during hydrothermal alteration might have a great effect on the performance, the behavior and the evolution of a geothermal reservoir. The identification of hydrothermally altered zones is a first step towards understanding the relation between different processes determining the character of a geothermal reservoir. |