Pore-network-continuum hybrid modeling of gas flow and storage in isolated kerogen aided by subcritical gas adsorption
Abstract:
The organic matter (OM) or kerogen is the source and storage site for the methane in the gas shale reservoirs. A reliable model for the estimation of the apparent permeability and gas in place (GIP) of the OM is essential for the Representative Elementary Volume (REV) scale modeling of gas flow and storage in shale digital rocks. Due to the interplay between the image field of view and resolution, there are microporosity regions (the pore size is under the resolution of the FIB-SEM image) and macropores (the pore size is above the resolution of the FIB-SEM image) in the OM digital rocks. Building upon our previous work, we further characterized the pore size distribution (PSD) and porosity of the microporosity regions within the OM digital rocks. It is shown that, the permeability of the OM digital rocks with microporosity regions with a non-uniform PSD is close to those with microporosity regions with a uniform volume-weighted mean pore size. The total sorption pore volume (TSPV) can also be calculated from the subcritical adsorption experiments of CO2 and N2, and utilized in the Langmuir equation to parameterize the methane excess isotherms to get the methane absolute isotherms of isolated kerogen. Basing on the methane absolute isotherms and real gas equation of state, FIB-SEM based OM digital rocks can estimate a comparable GIP to that estimated by the measured porosity of isolated kerogen. Utilizing CUDA (Compute Unified Device Architecture), we performed extensive calculations on millions of grid cells to build an apparent permeability equation for the OM digital rocks with microporosity regions with non-uniform PSD. In terms of compressible gas production simulation, we further simplified the implementation process which massively reduced the computational burden and keep the accuracy of the results at the same time. Nine case studies of the OM digital rocks with various macropores porosity indicate that the classification of the OM is crucial to the REV-scale modeling of shale gas flow. Our numerical model balances computational efficiency and accuracy, which will be a valuable tool to predict nonlinear gas flow in shales, but not limited to the OM.
Keywords: pore network modeling, shale organic matter, apparent permeability, gas in place, gas adsorption