Characterization of Hydraulically Induced Fractures from Monitoring and Production Data Using Ensemble Kalman Filtering

Monday, 15 December 2014
Siavash Hakim Elahi and Behnam Jafarpour, University of Southern California, Los Angeles, CA, United States
Characterization of hydraulically induced fractures in unconventional oil and gas development can significantly improve production efficiency and reduce the related environmental impacts. Microseismic monitoring is the primary technology for imaging the initiation and growth of the induced fractures. While fracture geometric attributes and distribution can be inferred from recorded microseismic measurements, delineating the open fractures that contribute to production and quantifying their hydraulic properties require complementary flow and transport data such as tracer and production measurements. We consider estimating fracture geometric attribute and conductivity from combined microseismic, production, and tracer data. To this end, we use a forward model with geomechanical considerations to predict the microseismic and tracer response for hydraulically fractured formations and apply a hierarchical ensemble Kalman filtering approach to update the fracture geometric and hydraulic properties. We investigate the applicability of our estimation approach by consider several case studies with different number of fracture stages, fracture length scales, and hydraulic conductivity. We first update fracture dimensions using microseismic and tracer data that do not contain any information about flow properties. We then estimate the hydraulic conductivity of the fractures from tracer and production data. The proposed fracture imaging framework can be applied in real-time to guide the fracturing process, to monitor the fracture growth, and to optimize the hydraulic fracturing design and minimize potential environmental impacts. Moreover, calibration of the fracture conductivity can be used to predict future production and identify candidate regions for re-fracturing.