bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal Mobility Control of Sensors in the Event of a Disaster
Authors: Nakamura Yuichi , Ito Masaki , Sezaki Kaoru ,   Institute of Industrial Science, The University of Tokyo 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan,   Center for Spatial Information Science, The University of Tokyo, Chiba, Japan
Published: March 2019

Disasters have caused serious damage on human beings throughout their long history. In a major natural disaster such as an earthquake, a key to mitigate the damage is evacuation. Evidently, secondary collateral disasters is account for more casualty than the initial one. In order to have citizens to evacuate safely for the sake of saving their lives, collecting information is vital. However at times of a disaster, it is a difficult task to gain environmental information about the area by conventional way. One of the solutions to this problem is crowd-sensing, which regards citizens as sensors nodes and collect information with their help. We considered a way of controlling the mobility of such sensor nodes under limitation of its mobility, caused by road blockage, for example. Aiming to make a mobility control scheme that enables high-quality information collection, our method uses preceding result of the measurement to control the mobility. Here it uses kriging variance to do that. We evaluated this method by simulating some measurements and it showed better accuracy than baseline. This is expected to be a method to enable a higher-quality input to the agent-based evacuation simulation, which helps to guide people to evacuate more safely.
Analysis of Optimal Scale of Tsunami Protection Facility and Associated Residual Risk
Authors: Fujima Koji , Hiwatashi Yasuko ,   Department of Civil and Environmental Engineering, National Defense Academy 1-10-20 Hashirimizu, Yokosuka, Kanaga 239-8686, Japan,   Tokyo University of Marine Science and Technology, Tokyo, Japan
Published: March 2019

It is necessary to identify the role and limitation of a tsunami protection facility in installing the hardware elements and performing damage-reduction activities necessary to mitigate aftermath of the calamity. This paper examines the probabilities of occurrence of earthquakes of various magnitudes based on the earthquake occurrence frequency, estimates the corresponding tsunami damage, and proposes a method to determine the expected damage reduction,B(H), and expected damage,D(H), when a tsunami protection facility of a given scale,H, is built. With the goal of facilitating an agreement with the local government regarding the scale of the tsunami protection facility, promoting damage reduction measures, and reducing the overall social cost, it also proposes a scheme built on the results of the aforementioned method and the cost,C(H). The present method can also be used to identify residual risks, which will allow concerned parties to set concrete damage reduction targets.
Imaging and Characterization of Microporous Carbonates Using Confocal and Electron Microscopy of Epoxy Pore Casts
Authors: Hassan A. , Chandra V. , Yutkin M. P. , Patzek T. W. , Espinoza D. N.
Published: March 2019

Microporous carbonates contain perhaps 50% of the oil left behind in current projects in the giant carbonate fields in the Middle East and elsewhere. Pore geometry, connectivity, and wettability of the micropore systems in these carbonates are of paramount importance in finding new improved-oil-recovery methods. In this study, we present a robust pore-imaging approach that uses confocal laser scanning microscopy (CLSM) to obtain high-resolution 3D images of etched epoxy pore casts of the highly heterogeneous carbonates. In our approach, we have increased the depth of investigation for carbonates 20-fold, from 10 µm reported by Fredrich (1999) and Shah et al. (2013) to 200 µm. In addition, high-resolution 2D images from scanning electron microscopy (SEM) have been correlated with the 3D models from CLSM to develop a multiscale imaging approach that covers a range of scales, from millimeters in three dimensions to micrometers in two dimensions. The developed approach was implemented to identify various pore types [e.g., intercrystalline microporosity (IM), intragranular microporosity (IGM), and interboundary sheet pores (SPs)] in limestone and dolomite samples.
Adjoint-Based Adaptive Convergence Control of the Iterative Finite Volume Multiscale Method
Authors: de Zeeuw W. , de Moraes R. J. , Heemink A. W. , Jansen J. D.
Published: March 2019

We propose a novel adaptive, adjoint-based, iterative multiscale finite volume (i-MSFV) method. The method aims to reduce the computational cost of the smoothing stage of the original i-MSFV method by selectively choosing fine-scale sub-domains (or sub-set of primary variables) to solve for. The selection of fine-scale primary variables is obtained from a goal-oriented adjoint model. An adjoint-based indicator is utilized as a criterion to select the primary variables having the largest errors. The Lagrange multipliers from the adjoint model can be interpreted as sensitivities of the objective function value with respect to deviations from the constraints. In case of adjoining the porous media flow equations with Lagrange multipliers, this implies that the multipliers are the sensitivities of the objective function with respect to the residuals of the flow equations, i.e., to the residual error that remains after approximately solving linear equations with the aid of an iterative solver. This allow us to recognize at which locations the solution contains more errors. More specifically, we propose a modification to the i-MSFV method to adaptively reduce the size of the fine-scale system that must be smoothed. The aim is to make the fine-scale smoothing stage less computationally demanding. To that end, we introduce a goal-oriented, adjoint-based fine-scale system reduction criterion. We demonstrate the performance of our method via single-phase, incompressible flow simulation models with challenging geological settings and using a history-matching like misfit objective function as the goal. The performance of the newly introduced method is compared to the original i-MSFV method. We investigate the adaptivity versus accuracy of the method and demonstrate how the solution accuracy varies by varying the number of unknowns selected to be smoothed. It is shown that the method can provide accurate solutions at reduced computational cost. The proof-of-concept applications indicate that the method deserves further investigations.
A New Framework for the Integrated Reservoir and Surface Facilities Modeling
Authors: Zaydullin Rustem , Cao Hui , Liao Terrence , Obi Eguono
Published: March 2019

Integrated simulation of reservoirs, wells, and surface facilities is becoming increasingly popular for modeling hydrocarbon production from deep offshore assets. Currently, there exist two common approaches for the integration. The first approach employs separate reservoir and facility simulators; whereas, the second approach combines the two within one reservoir simulation framework. Both approaches have advantages and drawbacks. For example, the first approach can be more accurate for the facility modeling, but overall it suffers from stability issues and long running times. On the other hand, the second approach is always numerically stable and typically provides better runtime performance, but requires additional inputs, e.g., Vertical Lift Performance (VLP) tables. Preparation of these additional inputs can be time consuming and often error-prone. Moreover, the VLP tables used in the second approach are typically constructed with the averaged values of "auxiliary" parameters, such as inlet temperature, water salinity, etc. This averaging can potentially lead to inaccuracies during simulation.

In this paper, we propose a new framework for integrated asset modeling which combines the benefits of the two approaches and hence significantly improves the efficiencies in both workflow construction and simulation accuracy. Our framework is based on the previously presented fully coupled network approach implemented as an in-house extension to a reservoir simulator. Here we extend the approach by introduction of an additional coupling step with a separate pipe flow (network) simulator. However, instead of using the pipe flow simulator to solve the network, it is used only to dynamically generate the VLP tables for the simulator's internal network module. Comparing to the previous fully coupled network approach, our new approach streamlines the simulation workflow by avoiding the necessity of the additional manually created network input. Furthermore this new approach also improves the modeling accuracy by using a generalization of the VLP description (e.g. with temperature as additional dimension) and by avoiding tables extrapolations. In this paper we discuss the new workflow and the new dynamic generalized VLP table construction in details.
Modeling Hydraulically Fractured Shale Wells Using the Fast Marching Method with Local Grid Refinements LGRs and Embedded Discrete Fracture Model EDFM
Authors: Xue Xu , Yang Changdong , Onishi Tsubasa , King Michael J. , Datta-Gupta Akhil
Published: March 2019

Recently the Fast Marching Method (FMM) based flow simulation has shown great promise for rapid modeling of unconventional oil and gas reservoirs. Currently, the application of FMM-based simulation has been limited to the use of tartan grid to model the hydraulic fractures (HFs). The use of tartan grids adversely impacts the computational efficiency, particularly for field-scale applications with hundreds of HFs. This paper is aimed at extending the FMM-based simulation to incorporate local grid refinements (LGRs) and embedded discrete fracture model (EDFM) to simulate HFs with natural fractures and validating the accuracy and efficiency of the methodologies.

The FMM-based simulation is extended to LGRs and EDFM. This requires novel gridding through introduction of triangles (in 2D) and tetrahedrons (in 2.5D) to link the local and global domain and solution of the Eikonal equation in unstructured grids to compute the ‘diffusive time of flight'. The FMM-based flow simulation reduces 3D simulation to an equivalent 1D simulation using the ‘diffusive time of flight (DTOF)’ as a spatial coordinate. The 1D simulation can be carried out using standard finite-difference method leading to orders of magnitude savings in computation time compared to full 3D simulation for high-resolution models.

We first validate the accuracy and computational efficiency of the FMM-based simulation with LGRs by comparing with tartan grids. The results show good agreements and the FMM-based simulation with LGRs shows significant improvement in computational efficiency. Then, we apply the FMM based simulation with LGRs to a multi-stage hydraulically fractured horizontal well with multiphase flow case to demonstrate the practical feasibility of our proposed approach. After that, we investigate various discretization schemes for the transition between local and global domain in the FMM-based flow simulation. The results are used to identify optimal gridding schemes to maintain accuracy while improving computational efficiency. Finally, we demonstrate the workflow of the FMM-based simulation with EDFM, including grid generation, comparison with FMM with unstructured grid and validation of the results. The FMM with EDFM can simulate arbitrary fracture patterns without simplification and shows good accuracy and efficiency.

This is the first study to apply the FMM-based flow simulation with LGRs and EDFM. The three main contributions of the proposed methodology are: (i) unique mesh generation schemes to link fracture and matrix flow domains (ii) diffusive time of flight calculations in locally refined grids (iii) sensitivity studies to identify optimal discretization schemes for the FMM-based simulation.
A Bayesian Sampling Framework With Seismic Priors for Data Assimilation and Uncertainty Quantification
Authors: Nejadi Siavash , Kazemi Nasser , Hubbard Stephen M. , Gates Ian D.
Published: March 2019

We present a novel sampling algorithm for characterization and uncertainty quantification of heterogeneous multiple facies reservoirs. The method implements a Bayesian inversion framework to estimate physically plausible porosity distributions. This inversion process incorporates data matching at the well locations and constrains the model space by adding a priori information about the sub-surface structure using a seismic impedance volume. The new framework improves predictive performance and the geological realism of the assimilated ensemble through an efficient parameter estimation. The new parameter estimation process enables conditioning data assimilation to characterize the main features of geological uncertainty such as structural, stratigraphic, facies, and petrophysical properties.

The proposed workflow uses an ensemble-based Markov Chain Monte Carlo approach combined with sampling probability distributions that are physically meaningful. Moreover, the method targets geostatistical modeling to specific zones in the reservoir. Accordingly, it improves fulfilling the inherent stationarity assumption in geostatistical simulation techniques. Parameter sampling and geostatistical simulations are calculated through an inversion process. In other words, the models fit the known porosity field at the well locations and are structurally consistent within main reservoir compartments, zones, and layers obtained from the seismic impedance volume. The new sampling algorithm ensures that the automated history matching algorithm maintains diversity among ensemble members avoiding underestimation of the uncertainty in the posterior probability distribution.

We evaluate the efficiency of the sampling methodology on a synthetic model of a waterflooding field. The predictive capability of the assimilated ensemble is assessed by using production data and dynamic measurements. Also, the qualities of the results are examined by comparing the geological realism of the assimilated ensemble with the reference probability distribution of the model parameters and computing the predicted dynamic data mismatch. Our numerical examples show that incorporating the seismically constrained models as prior information results in an efficient model update scheme and favorable history matching.
Efficient and Robust Solver for Multiphase Rachford-Rice Equations in Compositional and Thermal Simulations
Authors: Pan Huanquan , Imai Motonao , Connolly Michael , Tchelepi Hamdi
Published: March 2019

Robust and efficient multiphase flash calculations are crucial in compositional and thermal simulations for complex fluid systems in which three or four phase may co-exist. Solution of the Richford-Rice (RR) equations is an important operation in the multiphase flash. The Newton method generally does not converge during solution of the RR equations unless very good initial values are provided. In this paper, the solution of the RR equations is formulated as a minimization of a convex function problem. For the first time, we use a trust-region (TR) method to solve the RR equations through minimization of the convex function. The Hessian matrix of the convex function is always positive-definite, and the TR-based solver guarantees convergence. The key to successful implementation is to determine the relaxation parameter in the Newton update. We select this relaxation parameter to meet the boundary of the objective function and to ensure an adequate step length. We tested the RR solver for three and four phase RR problems in the construction of phase diagrams. The test cases are representative of complex fluid systems encountered in enhanced oil recovery, including injection of CO2 into low temperature reservoirs and steam injection into heavy oil reservoirs at elevated temperatures. We performed tens of millions of multiphase flash computations, the results of which reveal our RR solver to be robust, efficient, insensitive to initial values, and capable of handling negative phase amounts. We also evaluated the effect of the initial values on convergence and recommend methods to estimate the initial values in our RR solver. In summary, our RR solver greatly improves the multiphase flash calculations and strengthens the coupling of phase equilibrium calculations to the governing equations in multiphase compositional and thermal simulation.
History Matching and Optimal Design of Chemically Enhanced Oil Recovery Using Multi-Objective Optimization
Authors: Zhang Zheng , Jung Hye Young , Datta-Gupta Akhil , Delshad Mojdeh
Published: March 2019

Chemical enhanced oil recovery (EOR) methods have received increased attention in recent years since they have the ability to recover the capillary trapped oil. Successful chemical flooding application requires accurate numerical models and reliable forecast across multiple scales: core scale, pilot scale, and field scale. History matching and optimization are two key steps to achieve this goal.

For history matching chemical floods, we propose a general workflow for multi-stage model calibration using an Evolutionary Algorithm. A comprehensive chemical flooding simulator is used to model important physical mechanisms including phase behavior, cation exchange, chemical and polymer adsorption and capillary desaturation. First, we identify dominant reservoir and process parameters based on a sensitivity analysis. The history matching is then carried out in a stage-wise manner whereby the most dominant parameters are calibrated first and additional parameters are incorporated sequentially until a satisfactory data misfit is achieved. Next, a diverse subset of history matched models is selected for optimization using a Pareto-based multi-objective optimization approach. Based on the concept of dominance, Pareto optimal solutions are generated representing the trade-off between increasing oil recovery while improving the efficiency of chemical usage. These solutions are searched using a Non-dominated Sorting Genetic Algorithm (NSGA-II). Finally we implement a History Matching Quality Index (HMQI) with Moving Linear Regression Analysis to evaluate simulation results from history matching process. The HMQI provides normalized values for all objective functions having different magnitude and leads to a more consistent and robust approach to evaluate the updated models through model calibration.
A Calibrated Model for the Carbonate-Brine-Crude Oil Surface Chemistry and its Effect on the Rock Wettability, Dissolution, and Mechanical Properties
Authors: Bonto Maria , Eftekhari Ali Akbar , Nick Hamid
Published: March 2019

We suggest two new thermodynamic models for the adsorption of ions to the brine/carbonate and brine/crude oil interface. We calibrate the model parameters to the ionic adsorption and zeta potential data. We then investigate the effect of the rock and oil surface charges on the dissolution, wettability alteration, and mechanical properties of the carbonates in the context of modified-salinity water flooding in the North Sea chalk reservoirs.

We modify a charge-distribution multi-site complexation (CD-MUSIC) model and optimize its parameters by fitting the model to a large data set of calcite surface zeta potential in presence of different brine compositions. We also modify and optimize a diffuse layer model for the oil/brine interface. We then use the optimized surface complexation models with a finite-volume solver to model the two phase reactive transport of oil and brine in a chalk reservoir, including the impact of dissolution, polar-group adsorption, and compaction on the relative permeability of chalk to water and oil. We compare the simulation results with the published experimental data.
Application of Algebraic Smoothing Aggregation Two Level Preconditioner to Multiphysical Fluid Flow Simulations in Porous Media
Authors: Wang Shihao , Lukyanov Alexander , Wu Yu-Shu
Published: March 2019

Traditionally, preconditioners are used to damp slowly varying error modes in the linear solver stage. State-of-the-art multilevel preconditioners use a sequence of aggressive restriction, coarse-grid correction and prolongation operators to handle low-frequency modes on the coarse grid. High-frequency errors are then resolved by employing a smoother on fine grid. In this paper, the algebraic smoothing aggregation two level preconditioner is implemented to solve different coupled problems.

The proposed method generalizes the existing MsRSB and smoothing aggregation AMG methods. This method does not require any coarse partitioning and, hence, can be applied to general unstructured topology of the fine scale. Inspired by smoothing aggregation algebraic multigrid solver, the algebraic smoothing aggregation preconditioner constructs basis functions which allow mapping of some high-frequency modes from fine scale to low-frequency modes on the coarse scale. These basis functions are also used to reconstruct unknown primary variables at the fine scale using their approximations at the coarse level.

The proposed preconditioner has been adopted to challenging multiphysical problems, including fully coupled simulation of filtration and geomechanics processes including non-isothermal fluid flow problems. The preconditioner provides a reasonably good approximation to the coupled physical processes and speeds up the convergence. Compared to traditional ILU0+GMRES linear solvers, our preconditioner with GMRES solver reduces the number of iterations by about 3 times. In addition, the proposed method obeys a good theoretical scalability essential for parallel simulations.
Compact Stacked Contour Applied to Full Field Simulation Lifecycle
Authors: Middya Usuf , Crumpton Paul
Published: March 2019

The objective is to enable a full simulation lifecycle of multi-billion cell reservoir models for gigantic Middle Eastern reservoirs utilizing parallel hardware. Debugging, building and developing models with this resolution is not possible without seamlessly changing the scale of the reservoir model and applying a portfolio of boundary conditions to fit the current workflow.

Throughout the lifecycle of the full-field reservoir model a variety of simulations are needed, including small, single and multiple well sensitivity studies (O(108) cells), regional models (O(107) cells), and ultimately full-field modeling (O(109) cells). It is crucial this can be achieved in a way to exploit the current hardware, with a minimum memory and computational overhead, and have a quick and seamless way to maintain the integrity of the full-field model, without the need for complex pre- and post-processing tools. This is achieved here by the definition of a compact stacked contour; this is cheap enough to be read by every processor in the current run, and by exploiting advanced parallel IO techniques; only the portion of the full-field grid to be simulated needs be imported to core memory. This definition easily lends itself as a natural way to apply boundary conditions to model aquifers, fluxes derived from larger models, and pressure boundary conditions.

The techniques described here will be demonstrated on a number of workflows. Firstly, in aquifer modelling, to exclude the large number of aquifer cells that often arises from simulating on a geological level model, and replace these cells with an analytical model. An external program takes the area of interest, and using the convex hull of the area of interest generates a stacked contour, which is subsequently used to define a Fetkovich aquifer. Secondly, a pressure boundary condition is applied to an area of interest within a full-field model to mimic the decline.

The definition of a stacked compact contour enables the large reservoir model to be analyzed at local, regional and full-field scale while maintaining the integrity of the full-field model. A variety of boundary conditions are applied to the stacked compact contour.
Three-Dimensional Geological Boundary Aligned Unstructured Grid Generation, and CVD-MPFA Flow Computation
Authors: Manzoor Shahid , Edwards Michael G. , Dogru Ali H.
Published: March 2019

Three-dimensional unstructured grid generation for reservoirs with geological layers, faults, pinchouts, fractures and wells is presented. Grids are generated for example cases, and pressure fields and flow fields computed by the cell-centered and vertex-centered control-volume distributed multi-point flux approximation (CVD-MPFA) schemes are compared and contrasted together with the methods. Grid generation for reservoir simulation, must honour classical key geological features and multilateral wells. The geological features are classified into two groups; 1) involving layers, faults, pinchouts and fractures, and 2) involving well distributions. In the former, control-volume boundary aligned grids (BAGs) are required, while in the latter, control-point well aligned grids (WAGs) are required. In reservoir simulation a choice of grid type and consequent control-volume type is made, i.e. either primal or dual-cells are selected as control-volumes. The control-point is defined as the centroid of the control-volume for any grid type. Three-dimensional unstructured grid generation methods are proposed that automate control-volume boundary alignment to geological features and control point alignment to wells, yielding essentially perpendicular bisector (PEBI) meshes either with respect to primal or dual-cells depending on grid type. Both primal and dual-cell boundary aligned grid generators use primal-cells (tetrahedra, pyramids, prisms and hexahedra) as grid elements. Dual-cell feature aligned grids are derived from underlying primal-meshes, such that features are recovered, with control-volume faces aligned with interior feature boundaries. The grids generated enable a comparative performance study of cell- vertex versus cell-centered CVD-MPFA finite-volume formulations using equivalent degrees of freedom. The benefits of both types of approximation are presented in terms of flow resolution relative to the respective degrees of freedom employed. Stability limits of the methods are also explored. For a given mesh the cell-vertex method uses approximately a fifth of the unknowns used by a cell-centered method and proves to be the most beneficial with respect to accuracy and efficiency, which is verified by flow computation. Novel techniques for generating three-dimensional unstructured hybrid essentially PEBI-grids, honouring geological features are presented. Geological boundary aligned grid generation is performed for primal and dual-cell grid types. Flow results show that vertex-centered CVD-MPFA methods outperform cell-centered CVD-MPFA methods.
A Massively Parallel Algebraic Multiscale Solver for Reservoir Simulation on the GPU Architecture
Authors: Manea A. M. , Almani T.
Published: March 2019

In this work, the scalability of the Algebraic Multiscale Solver (AMS) (Wang et al. 2014) for the pressure equation arising from incompressible flow in heterogeneous porous media is investigated on the GPU massively parallel architecture. The solvers robustness and scalability is compared against its carefully optimized implementation on the shared-memory multi-core architecture (Manea et al. 2016), which this work is directly extending. Although several components in the AMS algorithm are directly parallelizable, its scalability on GPU's depends heavily on the underlying algorithmic details and data-structures design of each step, where one needs to ensure favorable control- and data-flow on the GPU, while extracting enough parallel work for a massively parallel environment. In addition, the type of the algorithm chosen for each step greatly influences the overall robustness of the solver. Taking all these constraints into account, we have developed a GPU-based AMS that exploits the parallelism in every module of the solver, including both the setup phase and the solution phase. The performance of AMS—with our carefully optimized algorithmic choices on the GPU for both the setup phase and the solution phase, is demonstrated using highly heterogeneous 3D problems derived from the SPE10 Benchmark (Christie et al. 2001). Those problems range in size from millions to tens of millions of cells. The GPU implementation is benchmarked on a massively parallel architecture consisting of NVIDIA Kepler K80 GPU's, where its performance is compared to the multi-core CPU architecture using an optimized multi-core AMS implementation (Manea et al. 2016) running on a shared memory multi-core architecture consisting of two packages of Intel's Haswell-EP Xeon(R) CPU E5-2667. While the GPU-based AMS parallel implementation shows good scalability for the solution stage, its setup stage is less efficient compared to the CPU, mainly due to the dependence on a QR-based basis functions solver.
Unstructured CVD-MPFA Reduced-Dimensional DFM Models for Two-Phase Flow, Coupled with Higher Resolution Hybrid Upwind Methods
Authors: Xie Yawei , Edwards Michael G.
Published: March 2019

A novel discrete fracture model (DFM) approximation is presented and coupled with the control-volume distributed multi-point flux approximation (CVD-MPFA) formulation. The reduced-dimensional discrete discontinuous pressure model for intersecting fractures is extended to two-phase flow, including gravity and discontinuous capillary pressure. A novel higher resolution hybrid upwind method provides improved flow resolution on unstructured grids.

Novel discontinuous fracture models together with appropriate interface conditions, essential for application to cases involving continuous and discontinuous capillary pressure, and for fractures with permeability barrier effects are presented. The CVD-MPFA based discontinuous DFM models are coupled with higher resolution methods on unstructured grids, including an extended higher resolution hybrid upwind method for gravity driven flow and a novel higher resolution capillary flux approximation. A special DFM approximation is presented for fracture intersection cells located in flow fields where viscous and gravity forces interact.

Performance comparisons are presented for tracer and two-phase flow and fracture problems involving discontinuous capillary pressure and gravity on unstructured meshes. The results demonstrate the importance of the discontinuous DFM model to resolve flow problems including oil trapping in fractures. In addition comparison between the standard lower order method and the higher resolution hybrid upwind scheme shows that the higher resolution method yields significantly improved flow resolution in gravity driven flow fields.

A novel DFM approximation is presented and coupled with the CVD-MPFA formulation on unstructured grids. The method includes a discontinuous discrete fracture model with appropriate interface conditions for application to discontinuous capillary pressure fields, and a new method for treatment of intersecting fractures is also introduced for viscous-gravity driven flow. The method is also coupled with a higher resolution hybrid upwind scheme which yields improved flow resolution.
Thermodaynamic Stability Analysis for Multi-Component Mixtures with Capillary Pressure
Authors: Neshat Sajjad Sadeghi , Okuno Ryosuke , Pope Gary Arnold
Published: March 2019

Despite the great interest and importance of modeling hydrocarbon production from tight oil reservoirs, the thermodynamic stability of multicomponent mixtures with capillary pressure has not been studied sufficiently. This paper introduces a practical algorithm for phase stability analysis of multi-component mixtures with capillary pressure. The capillary pressure is determined from a realistic saturation-dependent function which is representative of pore size distributions as well as other petrophysical properties such as wettability and water saturation in tight oil reservoirs. The new stability procedure is coupled with calculations of the phase behavior. The significance and robustness of the new method is shown in several examples with realistic tight oil and gas-condensate mixtures.
A Geomechanically-Constrained Dynamic Fractal Wormhole Growth Model for Simulating Cold Heavy Oil Production with Sand
Authors: Yu Haisheng , Leung Juliana Y.
Published: March 2019

Cold heavy oil production with sand (CHOPS) is a non-thermal primary process that is widely adopted in many weakly consolidated heavy oil deposits around the world. However, only 5 to 15% of the initial oil in place is typically recovered. Several solvent-assisted schemes are proposed as follow-up strategies to increase the recovery factor in post-CHOPS operations. The development of complex, heterogeneous, high-permeability channels or wormholes during CHOPS renders the analysis and scalability of these processes challenging. One of the key issues is how to properly estimate the dynamic growth of wormholes during CHOPS. Existing growth models generally offer a simplified representation of the wormhole network, which, in many cases, is denoted as an extended wellbore. Despite it is commonly acknowledged that wormhole growth due to sand failure is likely to follow fractal statistics, there are no established workflows to incorporate geomechanical constraints into the construction of these fractal wormhole patterns.

A novel dynamic wormhole growth model is developed to generate a set of realistic fractal wormhole networks during the CHOPS operations. It offers an improvement to the Diffusion Limited Aggregation (DLA) algorithm with a sand-arch-stability criterion. The outcome is a fractal pattern that mimics a realistic wormhole growth path, with sand failure and fluidization being controlled by geomechanical constraints. The fractal pattern is updated dynamically by coupling compositional flow simulation on a locally-refined grid and a stability criterion for the sand arch: the wormhole would continue expanding following the fractal pattern, provided that the pressure gradient at the tip exceeds the limit corresponding to a sand-arch-stability criterion. Important transport mechanisms including foamy oil (non-equilibrium dissolution of gas) and sand failure are integrated.

Public field data for several CHOPS fields in Canada is used to examine the results of the dynamic wormhole growth model and flow simulations. For example, sand production history is used to estimate a practical range for the critical pressure gradient representative of the sand-arch-stability criterion. The oil and sand production histories show good agreement with the modeling results.

In many CHOPS or post-CHOPS modeling studies, constant wormhole intensity is commonly assigned uniformly throughout the entire domain; as a result, the ensuing models are unlikely to capture the complex heterogeneous distribution of wormholes encountered in realistic reservoir settings. This work, however, proposes a novel model to integrate a set of statistical fractal patterns with realistic geomechanical constraints. The entire workflow has been readily integrated with commercial reservoir simulators, enabling it to be incorporated in practical field-scale operations design.
A Numerical Method for Hydraulic Fracture Propagation Using Embedded Meshes
Authors: Ren Guotong , Younis Rami M.
Published: March 2019

Fracture propagation (FP) occurs in extensive applications including hydraulic fracturing, underground disposal of liquid waste, CO2 sequestration etc. It is crucial to develop a simulator that is able to reflect physics behind FP and capture the FP path. This work is an extension of the previous developed model (Ren et al. (2018), Ren & Younis (2018)) to the simulation of FP. One of the remarkable benefits using the coupled XFEM-EDFM scheme allows FP free of the remeshing. In this work, the onset of FP is controlled by a single parameter, the equivalent stress intensity factor (SIF). A domain integral method, J integral is applied to extract the SIF information. A time marching scheme is performed to ensure the SIF criterion satisfied everytime fracture propagates. The developed simulator is verified by the analytical solutions and shows the capability of FP simulation in poroelastic materials.
Modelling of Electromagnetic Heating Process and its Applications in Oil Sands Reservoirs
Authors: Ji Dongqi , Harding Thomas , Chen Zhangxin , Dong Mingzhe , Liu Hui
Published: March 2019

For thermal heavy oil recovery, conventional steam injection processes are generally limited to reservoirs of relatively shallow depth, high permeability, thick pay zone and homogeneity. An alternative approach of applying Electromagnetic (EM) energy may be used to generate heat in reservoirs that are not suitable for steam injection or to improve the economics of the heavy oil recovery compared with steam injection. EM in-situ heating of oil reservoirs, in the form of EM energy absorption by dielectric materials, leads to an increase in temperature, a reduction in oil viscosity and an improvement in oil mobility. Recent studies have shown that EM heating is capable of reducing carbon emissions and water usage. However, the existing EM field simulators are limited to modeling of homogeneous media with respect to dielectric properties, which affects EM wave propagation and in-situ heat generation. For oil sands recovery where reservoir heating by EM energy is promising, it is desirable to simulate reservoirs in inhomogeneous formations, in which dielectric properties vary according to specific location. In this work, important background information regarding the EM wave propagation in inhomogeneous media is provided. A Helmholtz equation for the magnetic field by deformation of Maxwell's equations is presented that makes it feasible to find EM field solutions for such inhomogeneous media. Solution of only the magnetic field makes this work execution faster than the classical methods in which both magnetic and electric fields need to be calculated. By solving the equations of EM wave propagation and fluid flow in oil sands reservoirs simultaneously, this work provides a fully-implicit modelling method for the EM heating process. The feasibility of EM heating in oil sands is examined in two case studies: a) a horizontal well containing an antenna within and b) a horizontal well-pair with an antenna located in the upper well.
Model-Order Reduction of Coupled Flow and Geomechanics in Ultra-Low Permeability ULP Reservoirs
Authors: Florez Horacio , Gildin Eduardo
Published: March 2019

This work focuses on the development of accurate and fast simulation models for Ultra-Low Permeability (ULP) reservoirs, i.e., tight-sands and shales. ULP plays are the main unconventional resources that concentrate the bulk of production activity in the US. ULP challenge conventional simulators because they require multiphysics couplings, e.g., flow and geomechanics couplings, which poses a severe burden regarding computational efforts. We, thus address these challenges by developing accurate reduced-order models for coupled flow and geomechanics.

We rely on projection-based Model-Order Reduction (MOR) and hyper-reduction (POD-DEIM) techniques to reduce the ULPs computational cost. More specifically, we perform the standard offline training stage on displacements as primary variables to create local basis using Proper Orthogonal Decomposition (POD). During the online phase, we project the residual and Jacobian that arise from both poroelasticity and rate-independent poroplasticity into the given basis to reduce one-way coupled flow and geomechanics computations. We approximate the tensors, for the energy equation, to minimize the serial-time. We consider the role of the heterogeneity and material models such as Von Mises and investigate the benefits of hyper-reduction (POD-DEIM) on the non-linear functions.

Preliminary results, that focus on linear and nonlinear thermo-poroelasticity, show that our MOR algorithm provides substantial single and double digits speedups, up to 50X if we combine with multi-threading assembling and perform MOR on both physics. We highlight the remarkable MOR compression ratio above 99.9% for mechanics. The approach is particularly useful to speed up solving the sparse system for the inner iteration in convolution like problems which produces significant time savings compared to the serial full-order model (FOM). The latter is also true for problems that exhibit long serial times, for instance, while assembling the Jacobian and Residual for both physics and post-processing to compute stresses, if the serial-time per iteration is shorter that solving the sparse system of equations. These MOR results are promising in the sense that for most coupled flow and mechanics problems, the above condition holds. We formally compare FOM and reduced-order model (ROM) and provide time data to demonstrate the speedup of the procedure. Examples cover elasticity and rate-independent plasticity one-way coupled with the two-phase flow and the energy equation. We employ continuous Galerkin finite elements for the mechanics.
A Three-Dimensional Symmetric Positive Definite Control-Volume Distributed Multi-Point Flux Approximation for Flow Computation on Tetrahedral Grids
Authors: Ahmed Raheel , Edwards Michael G.
Published: March 2019

A three-dimensional symmetric positive definite (SPD) cell-centred control-volume distributed multi-point flux approximation (CVD-MPFA) is presented for porous media flow simulation on tetrahedral grids. The scheme depends on a single degree of freedom per control-volume and is derived in physical space where the continuous fluxes are resolved directly along the face normals of the tetrahedra. We believe this is the first and possibly only general three-dimensional full-tensor finite-volume scheme that is flux- continuous and SPD in physical space, while depending on a single degree of freedom per control-volume. The equivalent general two-dimensional CVD-MPFA scheme that is SPD in physical space is presented in (Friis et al., 2008).
Optimization Based Well Management for Coupling Giant Reservoir Models
Authors: Middya Usuf , Crumpton Paul , Tariq Qasim
Published: March 2019

The objective is to couple tens of full-field giant reservoirs and apply optimized-based well management system to the all the flowing wells to manage a high level production plateau and injection system.

In this work each individual reservoir simulation model is a giant field, with a large historical (70y) and prediction (200y) time periods, 10s of millions of cells and thousands of wells, many injection and production constraints and drilling targets. Each of these giant fields requires a parallel supercomputer to run each individual model in a reasonable time. To couple many of these models they are all executed as one combined parallel job, which is subdivided in groups of processes dedicated for individual reservoirs. A layered communication hierarchy is used, which facilitates coordination and synchronization of the individual reservoirs and the optimization and allocation of the production and injection targets of every well and group of wells in the coupled system. Great effort was placed on making the user workflow very simple; having established a history and prediction field-scale model, the coupling can be achieved by a straightforward manipulation of the individual field-scale models, and high-level constraints and targets can be added to the coupled system. To alleviate some run time/resource issues, the level of detail required for each model was chosen by activating a coarsening facility within the reservoir simulator. This reduced the simulation resources needed for individual fields, but exacerbated the potential bottleneck of the optimization engine, as all well and group constraints were preserved in the coupled model.

To stress test this system, up to 15 giant models were coupled, with over 15 thousand wells managed by an optimized based well management system. The single node responsible for allocation of all the wells was not found to be a bottleneck in the system.

The journey from the detailed full-field giant model to a coupled super-giant coupled model has many challenges. Here, these are alleviated by tight and efficient integration of the coupling optimized-based well management system and the massively parallel reservoir simulator. This paper demonstrates a new industry high water mark for the coupling of reservoir models.
Quasi-K-Orthogonal Grid Generation
Authors: Manzoor Shahid , Edwards Michael G. , Dogru Ali H.
Published: March 2019

Quasi K-orthogonal grid generation is presented, to improve grid quality and method stability with respect to flux approximation in the presence of strongly anisotropic full-tensor permeability fields.K-orthogonal grid generation is only possible for low anisotropy ratios. Quasi K-orthogonal grid generation involves satisfying the K-orthogonal condition approximately, resulting in grids that place less demand on an approximation with respect to stability conditions, and therefore improve grid quality with respect to flux approximation in the presence of anisotropic permeability fields. The method employed enables Delaunay grid generation principles to be employed in a locally transformed system according to local permeability tensor variation. The resulting method has great flexibility for handling complex geometries and can handle jumps in permeability tensor principal axes orientation and jumps in coefficients and details will be presented. Results are presented that demonstrate the benefit of a quasi K-orthogonal grid. Highly challenging cases involving strong full-tensor permeability fields where control-volume distributed multi-point flux approximation (CVD-MPFA) schemes exceed their stability limits and yield solutions with spurious oscillations when using conventional grids, are solved using the new grid generation method. CVD-MPFA schemes are still required as the grids are only approximately K-orthogonal in such cases, however the schemes retain a discrete maximum principle on the new quasi-K-orthogonal grids and yield well resolved solutions that are free of spurious oscillations. While the two-point flux approximation (TPFA) requires strict K-orthogonality, results using both CVD-MPFA and TPFA will be presented. New Quasi K-orthogonal grid generation methods are presented that satisfy the K-orthogonal condition approximately, resulting in practical grids that restore a discrete maximum principle (stability) for the CVD-MPFA schemes when applied to cases involving general full-tensor permeability fields. Results are presented for a variety of test cases that confirm the validity of the grids.
Microbiota and Chemical Compounds in Fermented Pinelliae Rhizoma (Banxiaqu) from Different Areas in the Sichuan Province, China
Authors: SHU BO , YING JING , WANG TAO , XIA MENGQIAN , ZHAO WENYU , YOU LING
Published: March 2019

This study focused on the microbiota and chemical compounds of the fermented Pinelliae Rhizoma produced in Longchang (LC), Zizhong (ZZ) and Xindu (XD), in Sichuan Province (China). High-throughput sequencing was used to analyze the microbiota. GC-MS and LC-MS were used to detect the compounds produced during the three different Pinelliae Rhizoma fermentation processes. The bacteria and fungi of the three fermented Pinelliae Rhizoma differed substantially, with the bacterial content mainly composed of the Bacillus genus, while the common fungi were only included in four OTUs, which belong to three species of Eurotiomycetes and Aspergillus cibarius. 51 volatile compounds were detected; they varied between LC, XD, and ZZ fermented Pinelliae Rhizoma. C10 and C15 terpenes were most frequently detected, and only curcumene and β-bisabolene were detected in the three fermented Pinelliae Rhizoma. 65 non-volatile compounds were detected by LC-MS, most were of C16, C18, C20, C21 and C22 structures. Cluster analysis showed more similarity between LC and XD fermented Pinelliae Rhizoma with regards to volatile compound content, but more similarity between the XD and ZZ fermented Pinelliae Rhizoma for non-volatiles. Moreover, no correlation between geographical distance and microflora or compounds of fermented Pinelliae Rhizoma was observed. These results showed that hundreds of compounds are produced by the natural mixed fermentation of Pinelliae Rhizoma, and may mostly relate to the microorganisms of five species.