Login
Maximum Magnitude Forecast in Hydraulic Stimulation Based on Clustering and Size Distribution of Early Microseismicity

Mohammad Javad Afshari Moein, Thessa Tormann, Benoît Valley & Stefan Wiemer

Résumé We interpreted the spatial clustering and size distribution of induced microseismicity observed during the stimulation of an enhanced geothermal system beneath Basel by comparison with scale-invariant synthetic data derived from discrete fracture network models. We evaluated microseimic specific influential factors including the effect of hypocentral location uncertainties, existence of a fractured zone and repeating events on the observed spatial organization. Using a dual power-law model originally developed in the context of discrete fracture network modeling, we developed theoretically the relationships among spatial clustering and magnitude distributions. We applied this model to the Basel data set and showed that the spatial clustering characteristics presented stationary properties during the hydraulic stimulation. Based on this observation, we proposed a statistical seismicity model calibrated on the scaling of early stimulation spatial patterns that is capable of forecasting the maximum magnitude of induced events with increasing injection time and stimulated volume.
   
Mots-clés
   
Citation Afshari Moein, M. J., Tormann, T., Valley, B., & Wiemer, S. (2018). Maximum Magnitude Forecast in Hydraulic Stimulation Based on Clustering and Size Distribution of Early Microseismicity. Geophysical Research Letters, 45(0), 6907-6917.
   
Type Article de périodique (Anglais)
Date de publication 6-7-2018
Nom du périodique Geophysical Research Letters
Volume 45
Numéro 0
Pages 6907-6917
URL http://dx.doi.org/10.1029/2018GL077609
Liée au projet Stress heterogenities and fracture network