Mechanistic simulation workflow in shale gas reservoirs Conference Paper uri icon

abstract

  • © Copyright 2017, Society of Petroleum Engineers Shale gas reservoir is comprised of highly heterogeneous porosity systems including hydraulic/secondary fractures, inorganic and organic matrix. Multiple non-Darcy flow mechanisms in the shale matrix further bring challenges for modeling. In this paper, we developed a framework combining a multi-physics compositional simulator with Multi-Porosity Modeling preprocessor for gas storage and transport in shale. A Triple-Porosity Model is used to characterize the three porosity systems in shale gas reservoirs. In the fracture porosity the heterogeneous impact of secondary fractures distribution on matrix-to-fracture fluid transfer is revealed by shape factor distribution. They are upscaled with superior accuracy from a detailed Discrete Fracture Network Model (DFN) sector model, where orthogonal hydraulic fractures are explicitly discretized. With the occurrence of nano-pores in shale matrix, the interaction between pore-wall and gas molecules is considered via Knudsen diffusion and gas slippage. Gas adsorption on the pore-wall of organic matrix is modeled by extended Langmuir isotherm. The inter-porosity and intra-porosity connectivities in the Triple-Porosity Model are flexibly controlled by arbitrary connections. Our results show that gas production in the Triple-Porosity Model with shape factor upscaled from DFN exhibits different production performance from models with uniform shape factor distribution. The deviations are caused by the dominance of different regions at different production periods. Moreover, different combinations of flow and storage mechanisms are investigated. We show that Langmuir desorption maintains reservoir pressure, but gas slippage and Knudsen diffusion accelerate the pressure drop. Both mechanisms contribute to improve the gas production and the consideration of them simultaneously improve gas production most.

author list (cited authors)

  • Yan, B., Mi, L., Wang, Y., Tang, H., An, C., & Killough, J. E.

publication date

  • January 2017