A Validated Digital Rock Workflow to Accurately Predict Apparent Permeability in Tight Rocks Available to Purchase

Core analysis of tight rocks is a challenging task. In terms of fluid flow analysis, conventional techniques to determine absolute permeability commonly do not match field observations and provide a wide range of results. The low permeability of tight rocks makes the time to perform flow-through experiments impractical. Additionally, fluid flow in tight pores occurs at different flow regimes as determined by the Knudsen number. To calculate the apparent rock permeability, we use a lattice Boltzmann solver that accounts for high Knudsen number effects and validate the results against experimental data. Simulations for a range of Knudsen numbers up to 30 are performed on 3D microtubes for comparison to experiments. Overall, we observe that the apparent permeability can be up to two orders of magnitude higher than Darcy permeability in these cases. With the numerical solver validated for simple geometries, simulations on the complex pore space as obtained from FIB-SEM image stacks of clay rich sands and a shale sample are performed. Simulations on the shale sample with a calcite mineral matrix, kerogen, pores within the kerogen, and intergranular pores, show absolute permeability values of up to an order of magnitude higher than Darcy values. For the tight sands containing significant amounts of illite and chlorite clay between quartz grains, variations in absolute permeability by a factor of 5 were predicted at relevant conditions. While the accuracy of the numerical solver has been demonstrated, some uncertainty is still tied to the accuracy of the pore space representation from FIB-SEM images and subsequent pore structure extraction. Accurate assessment of permeability in unconventional reservoirs is needed for reservoir modeling and simulation and is critically dependent on the Knudsen number, especially for gas flow. Accurate modelling of fluid flow in unconventional reservoirs is essential for proper prediction of drainage patterns, which can impact decision such as well spacing, optimal lateral length, and completions style. The digital rock approach provides a significant amount of data in a very short time but must include high Knudsen number effects to provide reliability in low permeability rocks typical of unconventional reservoirs.