A many-body dissipative particle dynamics model, namely, MDPD, is applied for simulation of pore-scale, multi-component, multi-phase fluid flows in fine-grained, nanoporous shales. Since this model is able to simultaneously capture the discrete features of fluid molecules in nanometer size pores and continuum fluid dynamics in larger pores, and is relatively easy to parameterize, it has been recognized as being particularly suitable for simulating complex fluid flow in multi-length-scale nanopore networks of shales. A remarkable feature of this work is the integration of a high-resolution FIB-SEM (focused ion beam scanning electron microscopy) digital imaging technique to the MDPD model for providing 3D voxel data that contain the invaluable geometrical and compositional information of shale samples. This is the first time that FIB-SEM is seamlessly linked to a Lagrangian model like MDPD for fluid flow simulation, which offers a robust approach to bridging gaps between the molecular- and continuum-scales, since the relevant spatial and temporal scales are too big for molecular dynamics, and too small for computational fluid dynamics with known constitutive models. Simulations ranging from a number of benchmark problems to a forced two-fluid flow in a Woodford shale sample are presented. Results indicate that this model can be used to deliver reasonable simulations for multi-component, multi-phase fluid flows in arbitrarily complex pore networks in shales.

Mesoscopic simulations of hydrocarbon flow in source shales are challenging, in part due to the heterogeneous shale pores with sizes ranging from a few nanometers to a few micrometers. Additionally, the sub-continuum fluid-fluid and fluid-solid interactions in nano-to micro-scale shale pores, which are physically and chemically sophisticated, must be captured. To address those challenges, we present a GPU-accelerated package for simulation of flow in nano-to micro-pore networks with a many-body dissipative particle dynamics (mDPD) mesoscale model. Based on a fully distributed parallel paradigm, the code offloads all intensive workloads on GPUs. Other advancements, such as smart particle packing and no-slip boundary condition in complex pore geometries, are also implemented for the construction and the simulation of the realistic shale pores from 3D nanometer-resolution stack images. Our code is validated for accuracy and compared against the CPU counterpart for speedup. In our benchmark tests, the code delivers nearly perfect strong scaling and weak scaling (with up to 512 million particles) on up to 512 K20X GPUs on Oak Ridge National Laboratory's (ORNL) Titan supercomputer. Moreover, a single-GPU benchmark on ORNL's SummitDev and IBM's AC922 suggests that the host-to-device NVLink can boost performance over PCIe by a remarkable 40%. Lastly, we demonstrate, through a flow simulation in realistic shale pores, that the CPU counterpart requires 840 Power9 cores to rival the performance delivered by our package with four V100 GPUs on ORNL's Summit architecture. This simulation package enables quick-turnaround and high-throughput mesoscopic numerical simulations for investigating complex flow phenomena in nano-to micro-porous rocks with realistic pore geometries. Program summaryProgram title: USER MESO 2.5 Licensing provisions: GNU General Public License 3 Programming language: CUDA C/C++ with MPI and OpenMP Nature of problem: Particle-based simulation of multiphase flow and fluid-solid interaction in nano-to micro-scale pore networks of arbitrary pore geometries. Solution method: Fluid particles and solid wall particles are modeled with a many-body dissipative particle dynamics (mDPD) model -a mesoscopic model for coarse-grained fluid and solid molecules. The pore surface wall boundary for arbitrary surface geometries is modeled with a no-slip boundary condition for fluid particles that prevents fluid particles from indefinitely penetrating in the walls. The time evolution of the system is integrated using the Velocity-Verlet algorithm. Restrictions: The code is compatible with NVIDIA GPUs with compute capability 3.0 and above. Unusual features: The code is implemented on GPGPUs with significantly improved speed.Recently we developed an mDPD based nano to micro-scale pore flow model and applied it for multiphase flow simulations in source shale [58]. In that model, realistic shale pore geometries are constructed based on 3D voxel 2/21

Porosity and permeability are the key factors in assessing the hydrocarbon productivity of unconventional (shale) reservoirs, which are complex in nature due to their heterogeneous mineralogy and poorly connected nano-and micro-pore systems. Experimental efforts to measure these petrophysical properties posse many limitations, because they often take weeks to complete and are difficult to reproduce. Alternatively, numerical simulations can be conducted in digital rock 3D models reconstructed from image datasets acquired via e.g., nanoscale-resolution focused ion beam-scanning electron microscopy (FIB-SEM) nano-tomography. In this study, impact of reservoir confinement (stress) on porosity and permeability of shales was investigated using two digital rock 3D models, which represented nanoporous organic/mineral microstructure of the Marcellus Shale. Five stress scenarios were simulated for different depths (2,000-6,000 feet) within the production interval of a typical oil/gas reservoir within the Marcellus Shale play. Porosity and permeability of the pre-and post-compression digital rock 3D models were calculated and compared. A minimal effect of stress on porosity and permeability was observed in both 3D models. These results have direct implications in determining the oil-/gas-in-place and assessing the production potential of a shale reservoir under various stress conditions.

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