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Abstract

Abstract

Shale gas has changed the energy equation around the world, and its impact has been especially profound in the United States. It is now generally agreed that the fabric of shale systems comprise primarily of organic matter, inorganic material and natural fractures. However, the underlying flow mechanisms through these multi-porosity, multi-permeability systems are poorly understood. For instance, debate still exists about the predominant transport mechanism (diffusion, convection and desorption) as well as the flow interactions between organic matter, inorganic matter and fractures. Furthermore balancing the computational burden of precisely modeling the gas transport through the pores versus running full reservoir scale simulation is also contested. To that end, commercial reservoir simulators are developing new shale gas options but some, for expediency, rely on simplification of existing data structures and/or flow mechanisms.

We present here the development of a comprehensive multi-mechanistic (desorption, diffusion and convection) multi-porosity (organic materials, inorganic materials and fractures), multi-permeability model that uses experimentally determined shale organic and inorganic material properties to predict shale gas reservoir performance. Our multi-mechanistic model takes into account gas transport due to both pressure-driven convection and concentration-driven diffusion. The model accounts for all the important processes occurring in shale systems, including desorption of multi-component gas from the organics surface, multi-mechanistic organic-inorganic material mass transfer, multi-mechanistic inorganic material-fracture network mass transfer, and production from a hydraulically fractured wellbore.

Our results show that Dual-porosity Dual-permeability (DPDP) with Knudsen diffusion is generally adequate to model shale gas reservoir production. By comparing Triple-porosity Dual-permeability (TPDP), DPDP and Single-porosity Single-permeability (SPSP) formulations under similar conditions, we show that Knudsen diffusion is a key mechanism and should not be ignored. We also guide the fractures design by analyzing flow rate limiting steps. This work provides a basis for long-term shale gas production analysis and also helps define value-adding laboratory measurements.

© EAGE Publications BV
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2014-02-25
2024-04-23

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Understanding Shale Gas Production Mechanisms Through Reservoir Simulation
Conference Proceedings 2014, 1 (2014); https://doi.org/10.2118/167753-MS
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