Petroleum Engineering & Analytics Research Lab

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Shale gas is an increasingly important source of energy in North America and interest in this unconventional gas source is growing worldwide. Natural fractures are the key to production in shale formations. The more fractures in the shale around the wellbore, the faster the gas will be produced. Because of shale's extremely low permeability, the best fracture treatments are those that expose as much of the shale as possible to the pressure drop that allows the gas to flow. The natural formation pressure of a large gas shale reservoir will decline only slightly over decades of production. Accurate predictive modeling and simulation provides the capability for sensitivity analysis in various types of study, to evaluate the economic potential of shale gas regions and to design production wells and stimulation treatments. Our experience with real field data from a large and significant number of shale wells in Pennsylvania shows that data-driven predictive modeling that uses advanced machine learning technology is the most promising technology for analysis and optimization of production from shale assets.

The combination of low permeability matrix rocks with high permeability fractures is a significant challenge for simulation and modeling of naturally fractured shale gas reservoirs. The conventional simulation and modeling of shale gas reservoirs includes geological, geophysical and petrophysical study along with modeling of natural and hydraulically induced fractures. Modeling of the induced hydraulic fractures is the most important but at the same time the most challenging part of this process. Research and development at PEARL is focused on using the the most appropriate technologies for modeling the induced hydraulic fractures using the data that is usually ignored during the development of conventional simulation models. 

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