Geomechanical Reservoir Characterization with Microseismic Data

Abstract

AbstractBulk fluid injection into low permeability geologic formations been observed to trigger microearthquakes (MEQs). Triggering of MEQ events has been linked to pore pressure, temperature, and in-situ stress variations. The resulting clouds of micro-seismic events are believed to carry information about the underlying coupled flow, geomechanics, and thermal processes and, hence, rock hydraulic and mechanical properties. We develop a framework for integrating injection-induced microseismic events as monitoring data to infer reservoir property distributions. To model the reservoir stimulation and induced microseismicity, we use a fully coupled thermo-poroelastic model with coupled heat transport, fluid flow, and rock deformation capabilities as forward model and apply the ensemble Kalman filter (EnKF) data assimilation algorithm invert MEQ measurements. Because discrete MEQ events are not amenable to continuous estimation methods, we first use a kernel density estimation (KDE) method to convert the observed cloud of MEQ events into a continuous seismicity density map. We then apply a variant of the EnKF to integrate the resulting continuous seismicity density map to estimate, individually and jointly, heterogeneous hydraulic and geomechanical rock property distributions such as permeability, Young's modulus, tensile strength and Cohesion. We apply a spectral projection approach to decorrelate the spatially correlated observation of MEQ for improved EnKF implementation. We use numerical experiments to evaluate the performance of the developed methods.