bluuebunny/crossref_metadata_2025_split huggingface dataset:
Localized Solvers for General Full-Resolution Implicit Reservoir Simulation
Authors: Sheth Soham M. , Younis Rami M. 
Published: February 2017

Abstract
In the solution of implicit reservoir simulation timesteps, the Newton iteration updates are often very sparse; this sparsity can be as high as 95% and can vary dramatically from one iteration to the next. We develop, implement and demonstrate a mathematically sound adaptive framework to predict this sparsity pattern before the system is solved. The development first mathematically relates the Newton update in functional space to that of the discrete system. Next, the Newton update formula in functional space is homogenized and solved in such a way that it results in conservative estimates of the numerical Newton update. The cost of evaluating the estimates is linear in the number of nonzero components. The estimates are used to label the components of the solution vector that will be nonzero, and the corresponding submatrix is solved. The computed result is guaranteed to be identical to the one obtained by solving the entire system.
When applied to various simulations of three-phase flow recovery processes in the SPE 10 geological model, the observed reduction in computational effort ranges between four to tenfold depending on the level of total compressibility in the system, the time step size and on the degree of complexity in the underlying physics. We show the extensions to the case of flow and multicomponent transport where the reduction in computation effort ranges between four to tenfold. The improvement in computational speed scales strongly with the number of transport components, and to a lesser degree with problem size. The results of the localized and full simulations are identical, as is the nonlinear convergence behavior.
A Multi-Porosity, Multi-Physics Model to Simulate Fluid Flow in Unconventional Reservoirs
Authors: Wang Cong , Xiong Yi , Huang Zhaoqin , Winterfeld Philip , Ding Didier , Wu Yu-Shu 
Published: February 2017

Abstract
Gas flow in shales is complicated by the highly heterogeneous and hierarchical rock structures (i.e., ranging from organic nanopores, inorganic nanopores, less permeable micro-fractures, more permeable macro-fractures, to hydraulic fractures). The dominant fluid flow mechanism varies in these different flow regimes, and properties of these rock structures are sensitive to stress changes with different levels. Although traditional single-porosity and double-porosity models can simulate certain time range of reservoir performance with acceptable accuracy, they are not generally applicable for the prediction of long-term performance and have limitations to improve our understandings of enhanced hydrocarbon recovery. In this paper, we present a multi-domain, multi-physics model, aiming to accurately simulate the fluid flow in shale gas reservoirs with more physics-based formulations.
An idealized model has been developed for the purpose of studying the characteristic behavior of a fractured nanopore medium, which contains five regions: organic nanopores, inorganic nanopores, local micro-fractures, global natural fractures, and hydraulic fractures. Fluid flow governing equations in this model vary according to the different dominant fluid flow mechanisms in different regions. For example, the apparent permeability, which is the intrinsic permeability multiplied by a correction factor, is used to account for the gas slippage through nanopores of shale matrix; while the organic and inorganic nanopores in this matrix have different capacities for gas adsorption. On the other hand, for fluids flow in natural fractures and hydraulic fractures with high velocity, the non-Darcy flow model is used to capture the strong inertia when is comparable to viscous force.
Numerical studies with practical interests are discussed. Several synthetic, but realistic test cases are simulated. Input parameters in these cases are evaluated using either the laboratory or theoretical work. Our results demonstrate that this model is able to capture the typical production behavior of unconventional reservoirs: a great initial peak, the sharp decline in the first few months, followed by a long flat production tail. A series of sensitivity analyses, which address the organic matter content, organic matter connectivity, natural fracture density, and hydraulic fracture spacing, will also be conducted.
Pressure Coupling for Geomechanical Multi-Phase Flow Simulation Using Vertex Centered Flow Elements and Unstructured Grids
Authors: SAMIER Pierre 
Published: February 2017

Abstract
Significant work has been done for generating unstructured grids. Coupled geomechanics simulation and hydraulic fracture flow for gas shale simulation have given a new impulse for unstructured gridding.
The objective of the paper is to couple flow and geomechanics using unstructured grid models, to demonstrate the ability to apply a more efficient pressure coupling using discretization at vertices on both sides (mechanical and flow equations).
Coupled equations are discretized and solved on an unstructured flow grid and a geomechanical finite element grid which are composed of various types of elements such as tetrahedrons and hexahedrons. On the flow side, a recent multi-point flux method, the Vertex Approximate Gradient (VAG) (Eymard 2012) is investigated for solving the reservoir equations on such unstructured grid. SPE paper 173309 (Samier, Masson 2015) presented the implementation of VAG scheme inside a next generation reservoir simulator designed for handling unstructured grids. This paper proposes an iterative coupling scheme with full pressure coupling at vertices. The geo-mechanics equations fully coupled to a single phase flow are solved using global pressure.
Then the resulting deformations are iteratively coupled to the multi-phase flow simulator.
Since most geo-mechanic simulators propose fully coupled single phase flow features, the main advantage of this method is the ability to use a full pressure coupling method with industrial simulators.
The convergence of this new scheme is discussed and results are presented for two cases described below. The two cases are validation cases used by other SPE papers. Faults are modeled using specific cohesive elements. Results are compared with standard loose iterative coupling method using TPFA cell centered elements.
SPE paper 173232 (RSS 2015, Doster et al) presented a full pressure coupling method using cell centered elements. The aim of the paper is to extend the method to unstructured grids and to vertex centered elements which are more adequate for a coupled problem since the multi-phase flow pressures, component masses and displacements unknowns are now discretized at the same location.
Optimization Based Isenthalpic Flash for Thermal Reservoir Simulations
Authors: Chempath Shaji , Sun Huafei , Haugen Kjetil 
Published: February 2017

Abstract
We present an algorithm for multiphase isenthalpic phase-equilibrium calculations. The algorithm addresses issues related to robustness and performance of isenthalpic flash, which sometimes get aggravated due to narrow boiling conditions. The isenthalpic flash is posed as an optimization of total system entropy for the given input conditions: pressure, system enthalpy, and composition of the mixture. We use a second-order optimization method to maximize entropy, with the individual phase-compositions and phase-enthalpies as the independent variables. At any point during the iterative solution procedure, the direction of the iterative step can be checked by ensuring an increase in entropy. During the iterations we allow phases to be split further into sub-phases to tackle the issue of a phase having multiple roots for the specified enthalpy (the phase is at boiling point temperature). We successfully apply the method to calculate the phase diagrams for many hydrocarbon mixtures. We have shown that the isenthalpic flash with entropy maximization works robustly in all the cases tested, including the narrow-boiling examples. Result of applying the flash to fluids with two hydrocarbon phases and a simplified water and rock phase is also presented.
A Mixed Natural and Concentration Variable Formulation for Chemical Flood Simulation
Authors: Shi Xundan , Han Choongyong , Wolfsteiner Christian , Chang Yih-Bor , Schrader Mark 
Published: February 2017

Abstract
Correlations for PVT properties used in chemical flood simulation are frequently written in concentration variables. Therefore, a mixed variable formulation has been proposed to implement chemical flooding option in an existing natural variable simulator. The new formulation results in a straightforward and efficient implementation of published PVT correlations as well as fast convergence.
A new three-layer pseudo component framework (i.e., phase – pseudo component – pure component) has been adopted to effectively model a group of pure components that can have the same composition and properties in each phase where it exists while allowing the flexibility of using different variable types on the pure component level, such as phase mole fraction and molar concentration. This ensures the same composition for pseudo component in different phases without introducing extra constraint equations.
In our implementation, we use a symmetric binodal curve and tie lines to describe the liquid phase behavior based on the pseudo-component concept. Phase densities and viscosities are computed using correlations with corresponding pseudo-component values and volumetric concentrations. A Corey-type relative permeability model and shear thinning effect on viscosity are also implemented. Furthermore, both cation exchange on surfactant/clay and adsorption of polymer/surfactant on rock are efficiently implemented.
Our algorithms have been validated against other state-of-the-art chemical flood simulators with both small conceptual test cases and large scale models. A very good agreement in results and a high nonlinear performance have been observed.
Mixed natural and concentration variable formulation proposed in this paper is a novel method to implement chemical flood capability in an existing natural variable simulator. The combination of mass and natural variables for surfactant flood simulation into a single formulation is an industry first. Its extensibility and robustness give us confidence for further extensions along these lines.
New Formulations for Isothermal Multiphase Flash
Authors: Paterson D. , Michelsen M. L. , Stenby E. H. , Yan W. 
Published: February 2017

Abstract
Two algorithms are proposed for isothermal multiphase flash. These are referred to as modified RAND and vol-RAND. The former uses the chemical potentials and phase amounts as the iteration variables while the latter uses chemical potentials and phase volumes to co-solve a pressure explicit equation of state with the equilibrium equations. When compared to the conventional approach of treating a single phase as dependent, these methods are more structured with all components in all phases treated in the same way. Both have been derived to include chemical reactions for any number of phases along with the possible simplifications for purely phase equilibria.
Numerical Modelling of Hybrid Steam and In-Situ Combustion Performance for Oil Sands
Authors: Yang Min , Harding Thomas G. , Chen Zhangxin , Yu Kuizheng , Liu Hui , Yang Bo , He Ruijian 
Published: February 2017

Abstract
Steam injection is a widely used thermal technology to recover heavy oil and oil sands resources, while high operating costs have made it vulnerable to low crude oil prices. In-Situ Combustion (ISC) provides an alternative to steam injection with the advantage of low operating costs and high energy efficiency. Hybrid steam and ISC has great potential in oil sands recovery because it combines the advantages of both steam injection and ISC. Before design of this hybrid process, it is important to understand the displacement mechanisms during this hybrid process.
In this study, numerical simulation has been performed to investigate the performance of co-injection of an air and steam process at the experimental scale. A three-dimensional radial numerical model has been developed using CMG STARS to simulate a steam flood test and a combustion tube test. The co-injection of enriched air and steam was performed after a period of hot water flooding in the combustion tube test. Simulated temperature profiles and combustion front velocities were matched with experimental measured results, indicating that the high temeprautre oxidation (HTO) reactions were captured in the simulation. In order to understand displacement mechnisms, simulation results obtained from both tests have been compared and analyzed, including temperature profiles, a steam front velocity, residual oil saturation, and oil recovery.
It is found that co-injection of steam and enriched air has the potential to improve oil recovery. An ultimate recovery factor of around 90% is achieved for the co-injection of the steam and enriched air process, while the recovery factor is around 60% for the steam flooding test. This is because ISC is able to recover residual oil left behind by the steam flooding. However, steam still plays a dominant role in displacement of bitumen. The steam front propagates faster than the combustion front. Also, the steam front travels faster with the presence of the combustion front, indicating that the combustion front behaves as a heat source for steam front propagation. This work greatly increases the understanding of displacement mechanisms in a hybrid steam and combustion process.
Integrated Static and Dynamic Uncertainties Modeling Big-Loop Workflow Enhances Performance Prediction and Optimization
Authors: Kumar Sarwesh , Wen Xian-Huan , He Jincong , Lin Wenjuan , Yardumian Hrant , Fahruri Irvan , Zhang Yanfen , Orribo Jose M. , Ghomian Yousef , Marchiano Iryna Petrovska , Babafemi Ayanbule 
Published: February 2017

Abstract
Reservoir simulation is a widely accepted tool for assessing the impact of uncertainties on upstream investment decisions. Currently, the most widely used workflow addressing these uncertainties is a traditional two-step approach: 1) geoscientists performing static uncertainty analysis with earth modeling parameters and selecting a few representative geological models (for example, low-mid-high); 2) reservoir simulation engineers conducting dynamic uncertainty analysis with dynamic parameters combined with the pre-selected geological models and performing history matching, forecasting, or optimization. In this workflow, all the geological uncertainties are lumped into one parameter (the grid) for use in the second step. This severely reduces the flexibility for considering a wider range of alternative static realizations, and thus may bias the history match and forecasts. We implemented an integrated workflow, called "big-loop" that unifies the two-step approach into a single step. This allows for simultaneous and explicit analysis of both types of uncertainties and improvement in reservoir management decision quality. It also allows for direct modification of earth model parameters to achieve a history match with geological consistency. Although the concept is not new to the industry, it is rare to find references of field applications of the "big-loop" workflow. We present the applications of this workflow to both green and brown reservoirs to demonstrate its value in improving accuracy and efficiency. In a Gulf of Mexico green field, the workflow is applied for uncertainty analysis of static parameters (for example sand channel width and salt body extension) and dynamic parameters (for example rock-fluid properties) for probabilistic Original Oil in Place (OOIP) assessment and production forecast. The workflow facilitates the design of uncertainty resolution, upside capture and downside mitigation plans. In an onshore fractured reservoir, the workflow is applied for simultaneous history matching using static fracture parameters (fracture length and aperture) and dynamic parameters. The workflow improves the model accuracy and decision quality for the upcoming IOR/EOR development project. In an offshore gas field, the workflow is used to perform experimental design (ED) studies with static and dynamic uncertainties. This systematic & automatic workflow eliminates manual inputs and reduces the need for recycles. Finally, in another field, the workflow is used to perform probabilistic history matching using static and dynamic parameters. This workflow is capable of delivering a full-cycle solution for uncertainty assessment and probabilistic history matching with high efficiency and high quality results.
Nonlinear Safeguarding Strategies for Fully Implicit Timestepping and Complex Processes
Authors: Lutidze Giorgiy , Younis Rami M. 
Published: February 2017

Abstract
This work develops the theoretical basis for a promising safeguarding strategy that is applicable to improving the robustness and efficiency of Newton-like methods for general physics implicit reservoir simulation. The method is demonstrated for a range of models with growing complexity, including thermal compositional problem, and is compared to state-of-the-art alternatives.
The damping algorithm is based on viewing the Newton iteration as a forward Euler discretization of the Newton flow equations. Three alternative a posteriori local discretization error estimates are developed. The first and second is are based on computable estimates of the norm of the derivative of the Newton step with respect to step-length. This estimate provides an accurate measure of the departure from the Newton flow path. The third estimate is based inspired by Richardson extrapolation idea. We propose to control the Newton step length by limiting the estimated local discretization error. The control strategy is conservative far from the solution, and can be shown to result in the standard Newton method otherwise.
Computational results are presented for a series of simulation problems with increasing complexity. First, results for two phase flow simulations demonstrate that the proposed method is competitive with, but not superior to current state-of-the-art strategies. For thermal, reactive, and multicomponent problems the method is compared to line-search methods. Superior robustness and computational efficiency are observed, and the iteration converges for significantly larger time-step sizes. These comparisons show that absent of tailored ad hoc strategies such as those recently proposed for black oil simulation, the proposed strategy is more robust and efficient than the current state-of-the art. This is demonstrated by testing the required number of iterations to convergence for different time-step sizes as well as during the course of full simulations.
While several novel Newton damping strategies and alternative discretization with improved differentiability have been proposed and successfully demonstrated for multiphase flow simulation, this work provides a first step towards tailored robust safeguards for complex physics.
A Massively Parallel Semicoarsening Multigrid Linear Solver on Multi-Core and Multi-GPU Architectures
Authors: Manea A. M. , Tchelepi H. A. 
Published: February 2017

Abstract
In this work, we have designed and implemented a massively parallel version of the Semicoarsening Multigrid Solver (Schaffer 1998), which is capable of handling highly heterogeneous and anisotropic 3D reservoirs, on a parallel architecture with multiple GPU's. For comparison purposes, the same algorithm was also implemented on a shared-memory multi-core architecture. The implementation exploits the parallelism in every module of the original Multigrid algorithm, including both the setup stage and the solution stage, without modifying the original algorithm basic steps. The benefits of this approach are twofold: maintaining the inherent strong linear convergence of the serial Multigrid algorithm, and making advantage of the shared-memory architecture to minimize the need for communication.
The design of the algorithm uses a combination of plane relaxation and semicoarsening to efficiently handle anisotropies in 3D, (Dendy et al. 1989). Since the z-direction in most reservoir models is a direction of strong-coupling compared to the x- and y- directions, semicoarsening is employed in the z-direction, and plane relaxation is used for relaxation on x-y planes. Besides the need to solve 2D-systems for plane-relaxation, a set of 2D systems must be also solved on each multigrid level during the setup stage to get an approximate representation of the exact prolongation operator described in Schaffer (1998). For handling both types of 2D systems, a massively parallel version of the 2D Black Box Multigrid (Alcouffe et al. 1981) was designed to handle those 2D solves. To be able to handle problems involving high anisotropies in the x- and y- directions, the 2D Black-Box Multigrid uses alternating line-relaxation with zebra ordering to parallelize across multiple line solves. Due to the inherent granularity difference between the GPU threads and the multi-core threads, line-relaxation was designed to use Thomas Algorithm on the multi-core architecture and Parallel Cyclic Reduction (NVIDIA Corporation 2014b) on the GPU architecture. In both the 3D Semicoarsening Multigrid and the 2D Black-Box Multigrid, V-cycling was used to avoid spending more time at coarser levels and thus affecting the parallel efficiency. To minimize the expensive communication between the host and the GPU (and amongst GPU's), every 2D-solve is explicitly handled by a single GPU.
The two versions of the solver were tested using various highly heterogeneous multi-million-cell problems derived from SPE10 Second Dataset Benchmark. For problems with sizes large enough, the GPU implementation, running on KEPLER-Based K40c cards, is found to be always faster than the multi-core implementation running on 12 Intel® Xeon® E5-2620 v2 2.10 GHz cores. In addition, the inherent serial nature of multiplicative multigrid, along with the approach taken to minimize the communication through PCI-e, were found to limit the scalability beyond 3-4 cores/GPU's.
Drill and Learn: A Decision Making Workflow to Quantify Value of Learning
Authors: Hanea R. G. , Casanova P. , Hustoft L. , Bratvold R. B. , Nair R. , Hewson C. , Leeuwenburgh O. , Fonseca R.M. 
Published: February 2017

Abstract
The goal of reservoir management is to make decisions with the objective of maximizing the value creation from the oil or gas production. In order to do this models that preserve geological realism and have predictive capabilities are being developed and used. These models are commonly calibrated by using Assisted History Matching (AHM) methods which, in general, will lead to reduced uncertainty in the predicted production. Although uncertainty assessment and reduction is often an element of high-quality decision making, it is not, in itself, value-creating. Value can only be created through decisions and any decision changes resulting from AHM should be modeled explicitly. Recently there has been a spurt in the application and understanding of Value of Information workflows for reservoir management. In this talk we present a comparison of existing workflows and point out the differences between them. Following this we introduce, a practically driven approach, referred to as Drill and Learn, with elements and concepts from existing workflows to quantify the Value of Learning. The difference and definitions of Value of Information and Value of Learning (VoL) are also presented. Ensemble methods (ES-MDA and StoSAG) are used for the history matching and optimization. The results presented are obtained by applying the proposed Drill and Learn workflow on a realistic synthetic case. Sensitivities to the amount of information obtained before a closed loop exercise is performed are also investigated. We show the benefit of performing the closed loop approach to quantify the value of learning (VoL) to modify field development decisions which leads to a mature robust decision making framework.