Shale-gas plays are the current rage in the US energy industry and have started a new era for hydrocarbon production, worldwide. Drilling is expanding; shale-gas wells are not hard to drill, but difficult to complete. The challenge is to release gas from rock as impermeable as concrete. Horizontal drilling and stimulation are enabling technologies that make development of unconventional shale-formations economically viable. Rocks around wellbores must be fractured before wells can produce significantly. Multistage hydraulic-fracturing treatments create complex conductive networks, represented by stimulated reservoir volumes (SRV) which have been effectively contacted and contribute to higher production profiles.
Reservoir characterization/modeling and simulation offer the best techniques to evaluate well performance and estimate the ultimate recovery. History matching or replicating past well behavior is the first, crucial step in simulation and is very difficult; however, as complex as it is, history matching, which calibrates the simulation-model is required to generate convincing forecasts. Main challenges to simulate past/future production include accurately describing the SRV, its geometry and position; fractures intensities and characterizing matrix/fracture attributes.
This paper presents innovative techniques, which previously were impossible to perform, in order to history-match horizontal wellbores by focusing on the mentioned matrix/fracture challenges to sensitize the complex growth and attributes of hydraulic-fractures. The techniques played an important role in understanding the stimulated shale volumes. Key conclusions of achievements include the capability to generate more reliable forecasts/predictions that are highly critical if it is aimed to understand well performance and optimize its productivity.
This research has led to a game-changing methodology for the global E&P industry that enables operators to develop an early understanding of shale-gas wells performance where such detailed knowledge is vital to optimizing exploitation economics and estimation of reserves and resource potential.