Particle methods for simulation of subsurface multiphase fluid flow and biogeochemical processes

Meakin, Paul; Tartakovsky, Alexandre M.; Scheibe, T. D.; Tartakovsky, Daniel M.; Redden, G. D.; Long, Philip E.; Brooks, Scott C.; Xu, Zhijie

doi:10.1088/1742-6596/78/1/012047

Cited by 5 publications

(4 citation statements)

References 35 publications

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“…To construct bounding walls in DPD based fluid flow simulations, most researchers (e.g. Chen et al [8], Li et al [33], Meakin et al [39]) have followed a particle packing approach proposed in Liu et al [36]. Using this packing approach, the whole simulation system will be first filled with DPD particles at a particle number density (e.g.…”

Section: Particle Packing For Pore Surface Geometriesmentioning

confidence: 99%

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

Xia

Blumers

et al. 2020

Computer Physics Communications

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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

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Section: Particle Packing For Pore Surface Geometriesmentioning

confidence: 99%

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

Xia

Blumers

et al. 2020

Computer Physics Communications

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“…Four stages in a two‐dimensional dissipative particle dynamics simulation of the penetration of a wetting fluid through a fracture junction [ Meakin et al , 2007]. …”

Section: Dissipative Particle Dynamicsmentioning

confidence: 99%

Modeling and simulation of pore‐scale multiphase fluid flow and reactive transport in fractured and porous media

Meakin

Tartakovsky

2009

Reviews of Geophysics

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332

206

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[1] In the subsurface, fluids play a critical role by transporting dissolved minerals, colloids, and contaminants (sometimes over long distances); by mediating dissolution and precipitation processes; and by enabling chemical transformations in solution and at mineral surfaces. Although the complex geometries of fracture apertures, fracture networks, and pore spaces may make it difficult to accurately predict fluid flow in saturated (single-phase) subsurface systems, well-developed methods are available. The simulation of multiphase fluid flow in the subsurface is much more challenging because of the large density and/or viscosity ratios found in important applications (water/air in the vadose zone; water/oil, water/gas, gas/oil, and water/ oil/gas in hydrocarbon reservoirs; water/air/nonaqueous phase liquids (nonaqueous phase liquids/dense nonaqueous phase liquids) in contaminated vadose zone systems; and gas/molten rock in volcanic systems, for example). In addition, the complex behavior of fluid-fluid-solid contact lines and their impact on dynamic contact angles must also be taken into account and coupled with the fluid flow. Here we review the methods that are currently being used to simulate pore-scale multiphase fluid flow and reactive transport in fractured and porous media. After the introduction, the review begins with an overview of the fundamental physics of multiphase fluids flow followed by a more detailed discussion of the complex dynamic behavior of contact lines and contact angles, an important barrier to accurate pore-scale modeling and simulation. The main part of the review focuses on five different approaches: pore network models, lattice gas and lattice Boltzmann methods, Monte Carlo methods, particle methods (molecular dynamics, dissipative particle dynamics, and smoothed particle hydrodynamics), and traditional grid-based computational fluid dynamics coupled with interface tracking and a contact angle model. Finally, the review closes with a discussion of future trends and challenges.Citation: Meakin, P., and A. M. Tartakovsky (2009), Modeling and simulation of pore-scale multiphase fluid flow and reactive transport in fractured and porous media, Rev. Geophys., 47, RG3002,

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“…However, this method is not yet common. Various commercially available fluid analysis software has been developed and is becoming more accurate [8], but there are still no examples of its use in calculating streak lines in mixing vessels.…”

Section: Introductionmentioning

confidence: 99%

Experimental Verification for Numerical Flow Analysis in Mixing Vessel

Kano¹,

Furukawa²,

Kato³

et al. 2022

J. Chem. Eng. Res. Updates.

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Visualization of a streak line pattern in a mixing vessel is quite useful for understanding the mixing mechanism and designing an optimal mixing vessel. However, conventional experimental methods for visualizing streak lines require a lot of time to construct impellers and prepare solutions. Although various commercial fluid analysis software has been developed, there are still no examples of its use for calculating streak lines in mixing vessels. A simulation method was developed to quickly evaluate the streak line pattern in a laminar mixing vessel by numerical analysis with commercial code. A commercial CFD code can calculate streak line patterns in a laminar mixing vessel. It was found that a lattice method was more suitable than a particle method for the simulation of the streak line.

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Particle methods for simulation of subsurface multiphase fluid flow and biogeochemical processes

Cited by 5 publications

References 35 publications

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

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

Modeling and simulation of pore‐scale multiphase fluid flow and reactive transport in fractured and porous media

Experimental Verification for Numerical Flow Analysis in Mixing Vessel

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