Evaluation of Singular Value Decomposition (SVD) Enhanced Upscaling in Reservoir Simulation

2020 ◽  
Author(s):  
Xu Zhou ◽  
Mayank Tyagi
Keyword(s):  
Reservoir Simulation ◽  
Homogeneous Model ◽  
Flow Simulation ◽  
Reservoir Modeling ◽  
Base Case ◽  
Fine Grid ◽  
Heterogeneous Model ◽  
Grid Model ◽  
Simulation Results ◽  
Simulation Time

Abstract Reservoir upscaling is an important step in reservoir modeling for converting highly detailed geological models to simulation grids. It substitutes a heterogeneous model that consists of high-resolution fine grid cells with a lower resolution reduced-dimension homogeneous model using averaging schemes. Its objective is to use a coarse grid model to represent a fine grid model, thus to reduce simulation time. The benefit of upscaling in reservoir simulation is that it efficiently saves simulation time, and effectively preserves key features of data for flow simulation. Singular Vector Decomposition (SVD) is a matrix decomposition method. It has been used for image processing and compressing. It has been proved to be capable of providing a good compression ratio, and effectively saves digital image storage space. SVD also has been used in noise suppression and signal enhancement. It has been shown to be effective in reducing noise components arising from both the sound sampling and delivery system. This study evaluates the effect of SVD in parameterization and upscaling for reservoir simulation. A two-phase flow reservoir model was created using data from the SPE tenth comparative solution project [1]. Simulation results show that SVD is valid in the parameterization of permeability values. The reconstructed permeability matrices using certain amount of singular values are good approximations of the original permeability values. Simulation results from SVD processed permeability values are similar to that using the original values. SVD is then applied on the upscaled permeability value to evaluate the effectiveness on upscaling. Simulation results were compared between the base case, upscaled case, and SVD upscaled case. The simulation results did not show a significant improvement in the accuracy of predicting oil production by applying SVD on the upscaled permeability values. It could be because the reconstructed permeability matrix has the same dimension before and after the SVD processing, thus the model accuracy and efficiency are not significantly improved. Future work includes adding more cases to further explore the effect of SVD on upscaling. The number of grid blocks may be increased, and more layers can be added to investigate whether SVD enhance upscaling for larger scale reservoir simulation models.

Hybrid Fluid Flow Simulation Combining Full Physics Simulation and Artificial Intelligence

2021 ◽  
Author(s):  
Mokhles Mezghani ◽  
Mustafa AlIbrahim ◽  
Majdi Baddourah
Keyword(s):  
Artificial Intelligence ◽  
Reservoir Simulation ◽  
History Matching ◽  
Hybrid Approach ◽  
Flow Simulation ◽  
Latin Hypercube Sampling ◽  
Simulation Models ◽  
Fine Scale ◽  
Simulation Results ◽  
Optimization Loop

Abstract Reservoir simulation is a key tool for predicting the dynamic behavior of the reservoir and optimizing its development. Fine scale CPU demanding simulation grids are necessary to improve the accuracy of the simulation results. We propose a hybrid modeling approach to minimize the weight of the full physics model by dynamically building and updating an artificial intelligence (AI) based model. The AI model can be used to quickly mimic the full physics (FP) model. The methodology that we propose consists of starting with running the FP model, an associated AI model is systematically updated using the newly performed FP runs. Once the mismatch between the two models is below a predefined cutoff the FP model is switch off and only the AI model is used. The FP model is switched on at the end of the exercise either to confirm the AI model decision and stop the study or to reject this decision (high mismatch between FP and AI model) and upgrade the AI model. The proposed workflow was applied to a synthetic reservoir model, where the objective is to match the average reservoir pressure. For this study, to better account for reservoir heterogeneity, fine scale simulation grid (approximately 50 million cells) is necessary to improve the accuracy of the reservoir simulation results. Reservoir simulation using FP model and 1024 CPUs requires approximately 14 hours. During this history matching exercise, six parameters have been selected to be part of the optimization loop. Therefore, a Latin Hypercube Sampling (LHS) using seven FP runs is used to initiate the hybrid approach and build the first AI model. During history matching, only the AI model is used. At the convergence of the optimization loop, a final FP model run is performed either to confirm the convergence for the FP model or to re iterate the same approach starting from the LHS around the converged solution. The following AI model will be updated using all the FP simulations done in the study. This approach allows the achievement of the history matching with very acceptable quality match, however with much less computational resources and CPU time. CPU intensive, multimillion-cell simulation models are commonly utilized in reservoir development. Completing a reservoir study in acceptable timeframe is a real challenge for such a situation. The development of new concepts/techniques is a real need to successfully complete a reservoir study. The hybrid approach that we are proposing is showing very promising results to handle such a challenge.

scholarly journals Dynamic effects of fault modeling on stair-step and corner-point grids

2021 ◽  
Vol 11 (3) ◽  
pp. 1323-1338
Author(s):  
Faruk O. Alpak ◽  
Tianhong Chen
Keyword(s):  
Reservoir Simulation ◽  
Corner Point ◽  
Flow Simulation ◽  
Fault Modeling ◽  
Added Value ◽  
Dynamic Effects ◽  
Flux Approximation ◽  
Grid Convergence ◽  
Simulation Results ◽  
Similar Accuracy

AbstractFault modeling has become an integral element of reservoir simulation for structurally complex reservoirs. Modeling of faults in general has major implications for the simulation grid. In turn, the grid quality control is very important in order to attain accurate simulation results. We investigate the dynamic effects of using stair-step grid (SSG) and corner-point grid (CPG) approaches for fault modeling from the perspective of dynamic reservoir performance forecasting. We have performed a number of grid convergence and grid-type sensitivity studies for a variety of simple, yet intuitive faulted flow simulation problems with gradually increasing complexity. We have also explored the added value of the multipoint flux approximation (MPFA) method over the conventional two-point flux approximation (TPFA) to increase the accuracy of reservoir simulation results obtained on CPGs. Effects of fault seal modeling on grid-resolution convergence and grid-type sensitivity have also been briefly examined. For simple geometries, both SSG and CPG can be used for fault modeling with similar accuracy in conjunction with the pillar-grid approach. This is evidenced by the fact that simulation results from SSG and CPG converge to identical solutions. SSG and CPG yield different results for more complex geometries. Simulation results approach to a converged solution for relatively fine SSGs. However, a SSG only provides an approximation to the fault geometry and reservoir volumes when the grid is coarse. On the other hand, non-orthogonality errors are increasingly evident in relatively more complex faulted models on CPGs and such errors cannot be addressed by grid refinement. It has been observed that MPFA partially addresses the discretization errors on non-orthogonal grids but only from the total flux accuracy perspective. However, transport related errors are still evident. Grid convergence behaviors and grid effects are quite similar with or without fault seal modeling (i.e., dedicated fault-zone modeling by use of scaled-up seal factors) for simple geometries. However, in more complex test cases, we have observed that it is more difficult to achieve converged results in conjunction with fault seal modeling due to increased heterogeneity of the underlying problem.

Reservoir Modeling for Flow Simulation by Use of Surfaces, Adaptive Unstructured Meshes, and an Overlapping-Control-Volume Finite-Element Method

2015 ◽  
Vol 18 (02) ◽  
pp. 115-132 ◽  
Author(s):  
M.D.. D. Jackson ◽  
J.R.. R. Percival ◽  
P.. Mostaghimi ◽  
B.S.. S. Tollit ◽  
D.. Pavlidis ◽  
...  
Keyword(s):  
Finite Element ◽  
Reservoir Simulation ◽  
Flow Simulation ◽  
Unstructured Meshes ◽  
Tetrahedral Mesh ◽  
Reservoir Modeling ◽  
Element Formulation ◽  
Surface Geometry ◽  
Flow Features ◽  
Geologic Heterogeneity

Summary We present new approaches to reservoir modeling and flow simulation that dispose of the pillar-grid concept that has persisted since reservoir simulation began. This results in significant improvements to the representation of multiscale geologic heterogeneity and the prediction of flow through that heterogeneity. The research builds on more than 20 years of development of innovative numerical methods in geophysical fluid mechanics, refined and modified to deal with the unique challenges associated with reservoir simulation. Geologic heterogeneities, whether structural, stratigraphic, sedimentologic, or diagenetic in origin, are represented as discrete volumes bounded by surfaces, without reference to a predefined grid. Petrophysical properties are uniform within the geologically defined rock volumes, rather than within grid cells. The resulting model is discretized for flow simulation by use of an unstructured, tetrahedral mesh that honors the architecture of the surfaces. This approach allows heterogeneity over multiple length-scales to be explicitly captured by use of fewer cells than conventional corner-point or unstructured grids. Multiphase flow is simulated by use of a novel mixed finite-element formulation centered on a new family of tetrahedral element types, PN(DG)–PN+1, which has a discontinuous Nth-order polynomial representation for velocity and a continuous (order N +1) representation for pressure. This method exactly represents Darcy-force balances on unstructured meshes and thus accurately calculates pressure, velocity, and saturation fields throughout the domain. Computational costs are reduced through dynamic adaptive-mesh optimization and efficient parallelization. Within each rock volume, the mesh coarsens and refines to capture key flow processes during a simulation, and also preserves the surface-based representation of geologic heterogeneity. Computational effort is thus focused on regions of the model where it is most required. After validating the approach against a set of benchmark problems, we demonstrate its capabilities by use of a number of test models that capture aspects of geologic heterogeneity that are difficult or impossible to simulate conventionally, without introducing unacceptably large numbers of cells or highly nonorthogonal grids with associated numerical errors. Our approach preserves key flow features associated with realistic geologic features that are typically lost. The approach may also be used to capture near-wellbore flow features such as coning, changes in surface geometry across multiple stochastic realizations, and, in future applications, geomechanical models with fracture propagation, opening, and closing.

Aquifer Acceleration in Parallel Implicit Field-Scale Reservoir Simulation

SPE Journal ◽  
2018 ◽  
Vol 23 (02) ◽  
pp. 614-624 ◽  
Author(s):  
Shouhong Du ◽  
Larry S. Fung ◽  
Ali H. Dogru
Keyword(s):  
Reservoir Simulation ◽  
Computational Cost ◽  
Coarse Grid ◽  
New Method ◽  
Fine Scale ◽  
Fine Grid ◽  
Water Influx ◽  
Grid Coarsening ◽  
Grid Solution ◽  
Simulation Results

Summary Grid coarsening outside of the areas of interest is a common method to reduce computational cost in reservoir simulation. Aquifer regions are candidates for grid coarsening. In this situation, upscaling is applied to the fine grid to generate coarse-grid flow properties. The efficacy of the approach can be judged easily by comparing the simulation results between the coarse-grid model and the fine-grid model. For many reservoirs in the Middle East bordered by active aquifers, transient water influx is an important recovery mechanism that needs to be modeled correctly. Our experience has shown that the standard grid coarsening and upscaling method do not produce correct results in this situation. Therefore, the objective of this work is to build a method that retains the fine-scale heterogeneities to accurately represent the water movement, but to significantly reduce the computational cost of the aquifer grids in the model. The new method can be viewed as a modified two-level multigrid (MTL-MG) or a specialized adaptation of the multiscale method. It makes use of the vertical-equilibrium (VE) concept in the fine-scale pressure reconstruction in which it is applicable. The method differs from the standard grid coarsening and upscaling method in which the coarse-grid properties are computed a priori. Instead, the fine-scale information is restricted to the coarse grid during Newton's iteration to represent the fine-scale flow behavior. Within the aquifer regions, each column of fine cells is coarsened vertically based on fine-scale z-transmissibility. A coarsened column may consist of a single amalgamated aquifer cell or multiple vertically disconnected aquifer cells separated by flow barriers. The pore volume (PV), compressibility, and lateral flow terms of the coarse cell are restricted from the fine-grid cells. The lateral connectivity within the aquifer regions and the one between the aquifer and the reservoir are honored, inclusive of the fine-scale description of faults, pinchouts, and null cells. Reservoir regions are not coarsened. Two alternatives exist for the fine-scale pressure reconstruction from the coarse-grid solution. The first method uses the VE concept. When VE applies, pressure variation can be analytically computed in the solution update step. Otherwise, the second method is to apply a 1D z-line solve for the fine-scale aquifer pressure from the coarse-grid solution. Simulation results for several examples are included to demonstrate the efficacy and efficiency of the method. We have applied the method to several Saudi Arabian complex full-field simulation models in which the transient aquifer water influx has been identified as a key factor. These models include dual-porosity/dual-permeability (DPDP) models, as well as models with faults and pinchouts in corner-point-geometry grids, for both history match and prediction period. The method is flexible and allows for the optional selection of aquifer regions to be coarsened, either only peripheral aquifers or both the peripheral and bottom aquifers. The new method gives nearly identical results compared with the original runs without coarsening, but with significant reduction in computer time or hardware cost. These results will be detailed in the paper.

Computer simulation to evaluate the economics of landfill gas recovery

1998 ◽  
Vol 38 (2) ◽  
pp. 201-208
Author(s):  
M. W. Milke
Keyword(s):  
Computer Simulation ◽  
Computer Program ◽  
Landfill Gas ◽  
Base Case ◽  
Simulation Tool ◽  
Hypothetical Case ◽  
Gas Recovery ◽  
Fixed Set ◽  
Key Variables ◽  
Simulation Results

A need exists for tools to improve evaluations of the economics of landfill gas recovery. A computer simulation tool is presented. It uses a spreadsheet computer program to calculate the economics for a fixed set of inputs, and a simulation program to consider variations in the inputs. The method calculates the methane generated each year, and estimates the costs and incomes associated with the recovery and sale of the gas. Base case results are presented for a city of 500,000. An uncertainty analysis for a hypothetical case is presented. The simulation results can help an analyst see the key variables affecting the economics of a project.

Optimization of RANS Solver Simulation Setup for Propeller Open Water Performance Prediction

2015 ◽  
Author(s):  
Mohammed Islam ◽  
Fatima Jahra ◽  
Michael Doucet
Keyword(s):  
Domain Size ◽  
Open Water ◽  
Fractional Factorial ◽  
Navier Stokes ◽  
Calm Water ◽  
Simulation Results ◽  
Open Water Performance ◽  
Thrust And Torque ◽  
Simulation Time ◽  
Fixed Pitch

Mesh and domain optimization strategies for a RANS solver to accurately estimate the open water propulsive characteristics of fixed pitch propellers are proposed based on examining the effect of different mesh and computation domain parameters. The optimized mesh and domain size parameters were selected using Design of Experiments (DoE) methods enabling simulations to be carried out in a limited memory environment, and in a timely manner; without compromising the accuracy of results. A Reynolds-Averaged Navier Stokes solver is used to predict the propulsive performance of a fixed pitch propeller. The predicted thrust and torque for the propeller were compared to the corresponding measurements. A total of six meshing parameters were selected that could affect the computational results of propeller open water performance. A two-level fractional factorial design was used to screen out parameters that do not significantly contribute to explaining the dependent parameters: namely simulation time, propeller thrust and propeller torque. A total of 32 simulations were carried out only to find out that the selected six meshing parameters were significant in defining the response parameters. Optimum values of each of the input parameters were obtained for the DOE technique and additional simulations were run with those parameters. The simulation results were validated using open water experimental results of the same propeller. It was found that with the optimized meshing arrangement, the propeller opens simulation time was reduced by at least a factor of 6 as compared to the generally popular meshing arrangement. Also, the accuracy of propulsive characteristics was improved by up to 50% as compared to published simulation results. The methodologies presented in this paper can be similarly applied to other simulations such as calm water ship resistance, ship propulsion to systematically derive the optimized meshing arrangement for simulations with minimal simulation time and maximum accuracy. This investigation was carried out using STAR-CCM+, a commercial CFD package; however the findings can be applied to any RANS solver.

An improved model on forecasting temperature rise of high-speed angular contact ball bearings considering structural constraints

2018 ◽  
Vol 70 (1) ◽  
pp. 15-22 ◽  
Author(s):  
De-xing Zheng ◽  
Weifang Chen ◽  
Miaomiao Li
Keyword(s):  
Heat Generation ◽  
Temperature Rise ◽  
High Speed ◽  
Structural Constraints ◽  
Ball Bearings ◽  
Content Type ◽  
Grid Model ◽  
Simulation Results ◽  
Operation Parameters ◽  
Improved Model

Purpose Thermal performances are key factors impacting the operation of angular contact ball bearings. Heat generation and transfer about angular contact ball bearings, however, have not been addressed thoroughly. So far, most researchers only considered the convection effect between bearing housings and air, whereas the cooling/lubrication operation parameters and configuration effect were not taken into account when analyzing the thermal behaviors of bearings. This paper aims to analyze the structural constraints of high-speed spindle, structural features of bearing, heat conduction and convection to study the heat generation and transfer of high-speed angular contact ball bearings. Design/methodology/approach Based on the generalized Ohm’s law, the thermal grid model of angular contact ball bearing of high-speed spindle was first established. Next Gauss–Seidel method was used to solve the equations group by Matlab, and the nodes temperature was calculated. Finally, the bearing temperature rise was tested, and the comparative analysis was made with the simulation results. Findings The results indicate that the simulation results of bearing temperature rise for the proposed model are in better agreement with the test values. So, the thermal grid model established is verified. Originality/value This paper shows an improved model on forecasting temperature rise of high-speed angular contact ball bearings. In modeling, the cooling/lubrication operation parameters and structural constraints are integrated. As a result, the bearing temperature variation can be forecasted more accurately, which may be beneficial to improve bearing operating accuracy and bearing service life.

Study on the Cyclic Loading Effects to the Railway Ballast

2013 ◽  
Vol 724-725 ◽  
pp. 1736-1739
Author(s):  
Xue Jun Wang ◽  
Bin Hua ◽  
Yi Lin Chi ◽  
Xue Yu Zhao ◽  
Fu Yu Li
Keyword(s):  
Cyclic Loading ◽  
Research Method ◽  
Flow Simulation ◽  
Railway Ballast ◽  
Compaction Rate ◽  
Simulation Process ◽  
Loading Effects ◽  
Simulation Results ◽  
Frequency Changes ◽  
Particle Flow Simulation

When ballast materials are subjected to cyclic loading, as a result, the change of particles micromechanical properties will lead to ballast degradation, permanent deformations on the railways step by step. In this paper, it presented a coupling discrete particle-flow simulation model of the railway ballast for cyclic tamping loading. Tamping frequency changes from 25HZ to 60HZ in numerical simulation process. Simulation results that the ballast compaction rate increases linearly with frequency up to a characteristic frequency 35HZ and then it declines in inverse proportion to tamping frequency. The aim of this paper is to study on the effects on the railway ballast under cyclic loading. The study shows that the discrete element method is a valid method for investigation of the microscopic properties of railway ballast now, while we have no other better research method.

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