## Search

Now showing items 1-10 of 21

JavaScript is disabled for your browser. Some features of this site may not work without it.

AuthorSun, Shuyu (19)Li, Yiteng (4)Chen, Huangxin (3)Kou, Jisheng (3)Yang, Haijian (3)View MoreDepartmentEarth Science and Engineering Program (21)Physical Sciences and Engineering (PSE) Division (21)Computational Transport Phenomena Lab (12)Earth Science and Engineering (3)Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division (2)View MoreJournalJournal of Computational Physics (5)Journal of Computational and Applied Mathematics (2)Journal of Natural Gas Science and Engineering (2)Advances in Mechanical Engineering (1)Applied Mathematical Modelling (1)View MoreKAUST Grant Number

BAS/1/1351-01-01 (21)

BAS/1/1624-01-01 (1)PublisherElsevier BV (13)Springer Nature (3)American Chemical Society (ACS) (1)American Geophysical Union (AGU) (1)SAGE Publications (1)View MoreSubjectEnergy stability (3)Fully implicit method (3)Parallel computing (3)Adsorption (2)Reservoir simulation (2)View MoreTypeArticle (21)Year (Issue Date)2019 (7)2018 (7)2017 (4)2016 (3)Item AvailabilityEmbargoed (12)Open Access (5)Metadata Only (4)

Now showing items 1-10 of 21

- List view
- Grid view
- Sort Options:
- Relevance
- Title Asc
- Title Desc
- Issue Date Asc
- Issue Date Desc
- Submit Date Asc
- Submit Date Desc
- Results Per Page:
- 5
- 10
- 20
- 40
- 60
- 80
- 100

Darcy-scale phase equilibrium modeling with gravity and capillarity

Sun, Shuyu (Journal of Computational Physics, Elsevier BV, 2019-09-05) [Article]

The modeling of multiphase fluid mixture and its flow in porous media is of great interest in the field of reservoir simulation. In this paper, we formulate a novel energy-based framework to model multi-component two-phase fluid systems at equilibrium. Peng-Robinson equation of state (EOS) is used to model the bulk properties of each phase, though our framework works well also with other equations of state. Our model reduces to the conventional compositional grading if restricted to one spatial vertical dimension together with the assumption of monodisperse pore-size distribution (all pores being one size). However, our model can be combined with a general distribution of pore size, which can generate interesting behaviors of capillarity in porous media. In particular, the model can be used to predict the capillary pressure of two-phase fluid as a function of saturation, with a given pore-size distribution. This model is the quantitative study of the first time in the literature for the capillarity of a two-phase fluid with partial miscibility. We proposed an unconditional-stable energy-decay numerical algorithm based on convex-concave splitting, which has been demonstrated to be both robust and efficient using numerical examples. To verify our model, we simulate the compositional grading of a binary fluid mixture consisting of carbon dioxide and normal decane. To demonstrate powerful features of our model, we provide an interesting example of fluid mixture in a porous medium with wide pore size distribution, where the competition of capillarity and gravity is observed. This work represents the first effort in the literature that rigorously incorporates capillarity and gravity effects into EOS-based phase equilibrium modeling.

Advances in Gaussian random field generation: a review

Liu, Yang; Li, Jingfa; Sun, Shuyu; Yu, Bo (Computational Geosciences, Springer Science and Business Media LLC, 2019-08-05) [Article]

Gaussian (normal) distribution is a basic continuous probability distribution in statistics, it plays a substantial role in scientific and engineering problems that related to stochastic phenomena. This paper aims to review state-of-the-art of Gaussian random field generation methods, their applications in scientific and engineering issues of interest, and open-source software/packages for Gaussian random field generation. To this end, first, we briefly introduce basic mathematical concepts and theories in the Gaussian random field, then seven commonly used Gaussian random field generation methods are systematically presented. The basic idea, mathematical framework of each generation method are introduced in detail and comparisons of these methods are summarized. Then, representative applications of the Gaussian random field in various areas, especially of engineering interest in recent two decades, are reviewed. For readers’ convenience, four representative example codes are provided, and several relevant up-to-date open-source software and packages that freely available from the Internet are introduced.

A fully implicit constraint-preserving simulator for the black oil model of petroleum reservoirs

Yang, Haijian; Sun, Shuyu; Li, Yiteng; Yang, Chao (Journal of Computational Physics, Elsevier BV, 2019-07-05) [Article]

Due to the rapid advancement of supercomputing resource, there is a growing interest in developing parallel algorithms for the large-scale reservoir simulation. In this paper, we present a parallel and fully implicit simulator for the black oil model based on the variational inequality (VI) framework, which can be used to enforce important mathematical and physical properties to obtain accurate constraint-preserving solutions. In other words, this framework ensures the predicted solution to stay within the physical range. In the proposed approach, the black oil model is reformulated as a variational inequality system that naturally satisfies the basic boundedness requirement of the solution, and then a fully implicit finite volume method is applied to discretize the model equations. In addition to that, a number of nonlinear and linear fast solver technologies, including a variant of inexact Newton methods and the domain decomposition based preconditioners, are employed to guarantee the robustness and parallel scalability of the simulator. A particular emphasis of the proposed framework is placed on the parallel and algorithmic performance of the variational inequality approach across large-scale and heterogeneous problems. Several numerical results pertaining to the problems in one, two and three dimensions are presented to illustrate the efficiency, robustness, and the overall performance of the fully implicit constraint-preserving simulator.

Acceleration of the NVT Flash Calculation for Multicomponent Mixtures Using Deep Neural Network Models

Li, Yiteng; Zhang, Tao; Sun, Shuyu (Industrial & Engineering Chemistry Research, American Chemical Society (ACS), 2019-06-24) [Article]

Phase equilibrium calculation, also known as flash calculation, has been extensively applied in petroleum engineering, not only as a standalone application for a separation process but also as an integral component of compositional reservoir simulation. Previous research devoted numerous efforts to improve the accuracy of phase equilibrium calculations, which place more importance on safety than speed. However, the equation-of-state-based flash calculation consumes an enormous amount of computational time in compositional simulation and thus becomes a bottleneck to the broad application of compositional simulators. Therefore, it is of vital importance to accelerate flash calculation without much compromise in accuracy and reliability, turning it into an active research topic in the past two decades. With the rapid development of computational techniques, machine learning brings another wave of technology innovation. As a subfield of machine learning, the deep neural network becomes a promising computational technique due to its great capacity to deal with complicated nonlinear functions, and it thus attracts increasing attention from academia and industry. In this study, we establish a deep neural network model to approximate the iterative flash calculation at given moles, volume, and temperature, known as the NVT flash. A dynamic model designed for NVT flash problems is iteratively solved to generate data for training the neural network. In order to test the model’s capacity to handle complex fluid mixtures, three real reservoir fluids are investigated, including one Bakken oil and two Eagle Ford oils. Compared to previous studies that follow the conventional flash framework in which stability testing precedes phase splitting calculation, we incorporate stability test and phase split calculation together and accomplish two steps by a single deep learning model. The trained model is able to identify the single vapor, single liquid, and vapor–liquid states under the subcritical region of the hydrocarbon mixtures. A number of examples are presented to show the accuracy and efficiency of the proposed deep neural network. It is found that the trained model makes predictions at most 244 times faster than the iterative NVT flash calculation for the given cases and meanwhile preserves high accuracy.

Accelerating flash calculation through deep learning methods

Li, Yu; Zhang, Tao; Sun, Shuyu; Gao, Xin (Journal of Computational Physics, Elsevier BV, 2019-05-29) [Article]

In the past two decades, researchers have made remarkable progress in accelerating flash calculation, which is very useful in a variety of engineering processes. In this paper, general phase splitting problem statements and flash calculation procedures using the Successive Substitution Method are reviewed, while the main shortages are pointed out. Two acceleration methods, Newton's method and the Sparse Grids Method are presented afterwards as a comparison with the deep learning model proposed in this paper. A detailed introduction from artificial neural networks to deep learning methods is provided here with the authors' own remarks. Factors in the deep learning model are investigated to show their effect on the final result. A selected model based on that has been used in a flash calculation predictor with comparison with other methods mentioned above. It is shown that results from the optimized deep learning model meet the experimental data well with the shortest CPU time. More comparison with experimental data has been conducted to show the robustness of our model.

Numerical Approximation of a Phase-Field Surfactant Model with Fluid Flow

Zhu, Guangpu; Kou, Jisheng; Sun, Shuyu; Yao, Jun; Li, Aifen (Journal of Scientific Computing, Springer Nature, 2019-03-07) [Article]

Modeling interfacial dynamics with soluble surfactants in a multiphase system is a challenging task. Here, we consider the numerical approximation of a phase-field surfactant model with fluid flow. The nonlinearly coupled model consists of two Cahn–Hilliard-type equations and incompressible Navier–Stokes equation. With the introduction of two auxiliary variables, the governing system is transformed into an equivalent form, which allows the nonlinear potentials to be treated efficiently and semi-explicitly. By certain subtle explicit-implicit treatments to stress and convective terms, we construct first and second-order time marching schemes, which are extremely efficient and easy-to-implement, for the transformed governing system. At each time step, the schemes involve solving only a sequence of linear elliptic equations, and computations of phase-field variables, velocity and pressure are fully decoupled. We further establish a rigorous proof of unconditional energy stability for the first-order scheme. Numerical results in both two and three dimensions are obtained, which demonstrate that the proposed schemes are accurate, efficient and unconditionally energy stable. Using our schemes, we investigate the effect of surfactants on droplet deformation and collision under a shear flow, where the increase of surfactant concentration can enhance droplet deformation and inhibit droplet coalescence.

A coupled Lattice Boltzmann approach to simulate gas flow and transport in shale reservoirs with dynamic sorption

Zhang, Tao; Sun, Shuyu (Fuel, Elsevier BV, 2019-03-01) [Article]

Gas flow in a shale reservoir is hard to model and simulate as certain complex mechanisms should be included, for example, diffusion and sorption. As a mesoscopic approach, Lattice Boltzmann Methods can capture the flow behavior in both scales: free flow through the conventional pore channels and gas transport with sorption in the tight matrix with very small pores. In this paper, two Lattice Boltzmann (LB) schemes are presented to recover the Navier-Stokes equations and advection diffusion equation respectively, to model the flow and transport in the two scales. The Navier-Stokes type LB scheme is constructed to model the free flow in fractures and conventional pore channels in matrix, and the convection diffusion type LB scheme is constructed to model the transport in tight matrix with very small pores. Chapman-Enskog expansions are derived to show the equivalence of the two LB schemes with the two macroscopic equations. Dynamic sorption is included in the advection diffusion with the dependance of gas concentration and free flow velocities, and the absorbed amount can affect the free flow velocity as well. In our simulation of gas flow and transport in shale reservoirs, the media is generated through two methods, reading a realistic media image and generating using a pore-network model. The rock characteristics are preserved in our generated porous media, with the method we proposed to link the LB scheme with the pore network modeling method. The simulation results are reasonable to prove that our schemes are robust and efficient, and the effect of porosity and sorption parameters are presented. Furthermore, the interaction of the two-scale gas flow and transport is analyzed, and we show that the increasing adsorbed gas amount in matrix may not slow down the free flow velocity as this increase may be resulted from changes in the rock characteristics. The scheme is simple to understand and implement, because only a few modifications are needed to construct the LB schemes on the two scales.

Homogenization of two-phase fluid flow in porous media via volume averaging

Chen, Jie; Sun, Shuyu; Wang, Xiaoping (Journal of Computational and Applied Mathematics, Elsevier BV, 2018-12-30) [Article]

A technique of local volume averaging is employed to obtain general equations which depict mass and momentum transport of incompressible two-phase flow in porous media. Starting from coupled Navier–Stokes–Cahn–Hilliard equations for incompressible two-phase fluid flow, the averaging is performed without oversimplifying either the porous media or the fluid mechanical relations. The resulting equations are Darcy's law for two-phase flow with medium parameters which could be evaluated by experiment. The Richards’ equation of the mixed form can be deduced from the resulting equations.The differences between the resulting equations and the empirical two-phase fluid flow model adopted in oil industry are discussed by several numerical examples.

Efficient energy stable schemes for the hydrodynamics coupled phase-field model

Zhu, Guangpu; Chen, Huangxin; Yao, Jun; Sun, Shuyu (Applied Mathematical Modelling, Elsevier BV, 2018-12-28) [Article]

In this paper, several efficient and energy stable semi-implicit schemes are presented for Cahn-Hilliard phase-field model of two-phase incompressible flows. A scalar auxiliary variable (SAV) approach is implemented to solve the Cahn-Hilliard equation while a splitting method based on pressure stabilization is used to solve Navier-Stokes equation. At each time step, the schemes involve solving only a sequence of linear elliptic equations and computations of phase-field variable, velocity and pressure are totally decoupled. A finite difference method on staggered grids is adopted to spatially discretize the proposed time marching schemes. We rigorously prove the unconditional energy stability for the semi-implicit schemes and fully discrete scheme. Numerical results in both two and three dimensions are obtained, which demonstrate accuracy and effectiveness of the proposed schemes. Using our numerical scheme, we compare the SAV, invariant energy quadratization (IEQ) and stabilization approaches. Bubble rising dynamics and coarsening dynamics are also investigated in detail. The results demonstrate that the SAV approach can be more accurate than the IEQ approach, and the stabilization approach is the least accurate among the three approaches. The energy stability of SAV approach appears better than other approaches at large time steps.

The transport of nanoparticles in subsurface with fractured, anisotropic porous media: Numerical simulations and parallelization

Chen, Meng-Huo; Salama, Amgad; Sun, Shuyu (Journal of Computational and Applied Mathematics, Elsevier BV, 2018-10-05) [Article]

The flow of fluids through fractured porous media has been an important topic in the research of subsurface flow. The several orders of magnitude in size between the fractures and the rock matrix causes difficulties for simulating such flow scenario. The fluid velocities in fractures are also several orders of magnitude higher than that in the rock matrix due to high permeability and porosity. If there exists pollutant such as nanoparticles in the fluids, the pollutant may be transported rapidly and the rock matrix’s properties near the fractures are hence changed. In this research, we simulate the transport phenomena of nanoparticles in the fluid flow through fractured porous media. The permeability fields which contain different anisotropy angles are considered in the simulation. Fractures are represented explicitly by volumetric grid cells and the numerical algorithm is parallelized in order to reduce the simulation time. We investigate the effect of the appearance of fractures and rotated anisotropy on the transport of nanoparticles, particles deposition, entrapment and detachment. The results show that flow directions are affected by the direction of anisotropy and the transport of nanoparticles in the fractures is significantly faster than that in rock matrix due to high fluid velocities. The direction of anisotropy distorted the pressure field and changed the fluid flow directions, which determined the time needed for the pollutant front to reach the fractures. The parallel efficiency of the overall algorithm is also discussed and the experimental results show that it is deeply affected by the performance of the multigrid solver.

The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

By default, clicking on the export buttons will result in a download of the allowed maximum amount of items. For anonymous users the allowed maximum amount is 50 search results.

To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.