Data-driven Monte Carlo Simulations in Estimating the Stimulated Reservoir Volume (SRV) by Hydraulic Fracturing Treatments (SPE 154537)

Hydraulic fracturing treatment has been proven to be the key factor for shale gas to flow at economic rate. Micro-seismic mapping has shown the extreme complexity of the hydraulic fracture network after the stimulation due to the geological complexity of shale formations. It becomes vitally important to understand the impact of the hydraulic fracture treatment, especially the massive multistage, multi-cluster hydraulic fracturing stimulations, to optimize stimulation and development plans of shale gas reservoirs. Recent advances in micro-seismic mapping enable realistic modeling of hydraulic fracture network, though with significant uncertainty. Consequently, it is possible, to certain extent, to represent actual large-scale fracture distribution in reservoir modeling and simulation of shale gas development. In this paper, we propose a simulation method that is able to generate highly likely realizations of fracture network based on micro-seismic data, taking into account of data and shale formation uncertainty. The simulated realizations are then used to construct highly constrained unstructured gridding and a connection list of all neighboring cells (SPE 143590), using the Discrete Fracture Modeling (DFM) approach. DFM enables the prediction of production yield curve. With real production data, statistical analysis is done to calibrate and refine the simulation attributes. Based on a well calibrated simulation system, and linking initial hydraulic stimulation, induced fracture network and production data, we predict future stimulated reservoir volume and production yield curve, hence enabling the optimization of stimulation and development. The proposed approach is extremely computational intensive. Approximations, efficient implementation and parallelization are used to make the approach practical. The approach was tested with success on real field experiments and data and the numerical results have shown great potential of the proposed approach to better understand the impact of hydraulic fracturing treatment.