A GPU-accelerated package for simulation of flow in nanoporous source rocks with many-body dissipative particle dynamics

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

Capacity investigation of brine-bearing sands of the Frio Formation for geologic sequestration of CO2

The capacity of fluvial brine-bearing formations to sequester CO2 is investigated using numerical simulations of CO2 injection and storage. Capacity is defined as the volume fraction of the subsurface available for CO2 storage and is conceptualized as a product of factors that account for two-phase flow and transport processes, formation geometry, formation heterogeneity, and formation porosity. The space and time domains used to define capacity must be chosen with care to obtain meaningful results, especially when comparing different authors’ work. Physical factors that impact capacity include permeability anisotropy and relative permeability to CO2, brine/CO2 density and viscosity ratios, the shape of the trapping structure, formation porosity and the presence of low permeability layering.National Energy Technology LaboratoryBureau of Economic Geolog

Uncertainty quantification for CO2 sequestration and enhanced oil recovery

This study develops a statistical method to perform uncertainty quantification for understanding CO2 storage potential within an enhanced oil recovery (EOR) environment at the Farnsworth Unit of the Anadarko Basin in northern Texas. A set of geostatistical-based Monte Carlo simulations of CO2-oil-water flow and reactive transport in the Morrow formation are conducted for global sensitivity and statistical analysis of the major uncertainty metrics: net CO2 injection, cumulative oil production, cumulative gas (CH4) production, and net water injection. A global sensitivity and response surface analysis indicates that reservoir permeability, porosity, and thickness are the major intrinsic reservoir parameters that control net CO2 injection/storage and oil/gas recovery rates. The well spacing and the initial water saturation also have large impact on the oil/gas recovery rates. Further, this study has revealed key insights into the potential behavior and the operational parameters of CO2 sequestration at CO2-EOR sites, including the impact of reservoir characterization uncertainty; understanding this uncertainty is critical in terms of economic decision making and the cost-effectiveness of CO2 storage through EOR.Comment: 9 pages, 6 figures, in press, Energy Procedia, 201

Numerical Investigation of Two-Phase Flow through a Fault

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