The state of the art of modeling fluid flow in shale gas reservoirs is dominated by dual porosity models that divide the reservoirs into matrix blocks that significantly contribute to fluid storage and fracture networks which principally control flow capacity. However, recent extensive microscopic studies reveal that there exist massive micro- and nano- pore systems in shale matrices. Because of this, the actual flow mechanisms in shale reservoirs are considerably more complex than can be simulated by the conventional dual porosity models and Darcy’s Law. Therefore, a model capturing multiple pore scales and flow can provide a better understanding of complex flow mechanisms occurring in these reservoirs.
Through the use of a unique simulator, this research work establishes a micro-scale multiple-porosity model for fluid flow in shale reservoirs by capturing the dynamics occurring in three separate porosity systems: organic matter (mainly kerogen); inorganic matter; and natural fractures. Inorganic and organic portions of shale matrix are treated as sub-blocks with different attributes, such as wettability and pore structures. In the organic matter or kerogen, gas desorption and diffusion are the dominant physics. Since the flow regimes are sensitive to pore size, the effects of smaller pores (mainly nanopores and picopores) and larger pores (mainly micropores and nanopores) in kerogen are incorporated in the simulator. The separate inorganic sub-blocks mainly contribute to the ability to better model dynamic water behavior. The multiple porosity model is built upon a unique tool for simulating general multiple porosity systems in which several porosity systems may be tied to each other through arbitrary transfer functions and connectivities. This new model will allow us to better understand complex flow mechanisms and in turn to extend simulation to the reservoir scale including hydraulic fractures through upscaling techniques
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/151163 |
| Date | 16 December 2013 |
| Creators | Yan, Bicheng |
| Contributors | Killough, John E, Ayers, Walter B, Sun, Yuefeng |
| Source Sets | Texas A and M University |
| Language | English |
| Detected Language | English |
| Type | Thesis, text |
| Format | application/pdf |
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