bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a Thermal Stability Method for Phase Appearance and Disappearance Handling in Thermal Compositional Simulators
Authors: Heidari Mohammad Reza , Stone Terry Wayne 
Published: October 2021

Abstract
Thermal compositional simulators rely heavily on multicomponent, multiphase flash calculations for a variety of reasons, including reservoir and wellbore initialization, phase appearance and disappearance, and property calculation. In a mass variable formulation, an isenthalpic flash is used for phase split computation, phase saturation update, component mole fraction update in different phases, and temperatures. A natural variable formulation utilizes an isothermal flash mainly for phase appearance and disappearance as well as computation of component mole fractions in appearing phases.
Multiphase multicomponent isothermal flash calculations cannot be performed in narrow boiling systems which are very common in the simulation of thermal EOR operations such as Steam-Assisted Gravity Drainage (SAGD) or Steam Flooding (SF). In a narrow boiling point system, pressure and temperature are not linearly independent, and an isothermal flash will fail. In addition, flash calculations are computationally expensive, and reservoir simulators use different techniques to perform them as little as possible.
A new thermal stability check has been developed that can be used in thermal compositional simulators and replaces an isothermal flash calculation. The new stability check quickly determines the phase state of a fluid sample and can be used as an initial guess for mole fraction of a phase appearing in the next simulation cycle. In this method, primary variables of the simulator are used as input for the stability check immediately after the nonlinear solver update so that computation of global mole fractions is not required. The new stability check can also be used in separator and isenthalpic flash calculations to determine the phase state of a fluid. An algorithm is provided, covering all different transitions of phase states in a thermal compositional simulator. The proposed algorithm is significantly faster than a flash calculation and saves simulation time spent in this calculation, hence the overall speed up is case dependent.
The new stability check is simple, computationally inexpensive, and robust. It can be used for multicomponent and single-component systems, and we tested it rigorously against real field and synthetic models. The new thermal stability check always predicts the number of phase states correctly and never fails. In this paper, we demonstrate a thermal compositional simulation that is run without performing a single flash calculation.
A Proxy Peng-Robinson EOS for Efficient Modeling of Phase Behavior
Authors: Zhao Mark , Okuno Ryosuke 
Published: October 2021

Abstract
Equation-of-state (EOS) compositional simulation is commonly used to model the interplay between phase behavior and fluid flow for various reservoir and surface processes. Because of its computational cost, however, there is a critical need for efficient phase-behavior calculations using an EOS. The objective of this research was to develop a proxy model for fugacity coefficient based on the Peng-Robinson EOS for rapid multiphase flash in compositional flow simulation. The proxy model as implemented in this research is to bypass the calculations of fugacity coefficients when the Peng-Robinson EOS has only one root, which is often the case at reservoir conditions.
The proxy fugacity model was trained by artificial neural networks (ANN) with over 30 million fugacity coefficients based on the Peng-Robinson EOS. It accurately predicts the Peng- Robinson fugacity coefficient by using four parameters: Am, Bm, Bi, and ΣxiAij. Since these scalar parameters are general, not specific to particular compositions, pressures, and temperatures, the proxy model is applicable to petroleum engineering applications as equally as the original Peng-Robinson EOS. The proxy model is applied to multiphase flash calculations (phase-split and stability), where the cubic equation solutions and fugacity coefficient calculations are bypassed when the Peng-Robinson EOS has one root. The original fugacity coefficient is analytically calculated when the EOS has more than one root, but this occurs only occasionally at reservoir conditions.
A case study shows the proxy fugacity model gave a speed-up factor of 3.4% in comparison to the conventional EOS calculation. Case studies also demonstrate accurate multiphase flash results (stability and phase split) and interchangeable proxy models for different fluid cases with different (numbers of) components. This is possible because it predicts the Peng-Robinson fugacity in the variable space that is not specific to composition, temperature, and pressure. For the same reason, non-zero binary iteration parameters do not impair the applicability, accuracy, robustness, and efficiency of the model. As the proxy models are specific to individual components, a combination of proxy models can be used to model for any mixture of components. Tuning of training hyperparameters and training data sampling method helped reduce the mean absolute percent error to less than 0.1% in the ANN modeling.
To the best of our knowledge, this is the first generalized proxy model of the Peng-Robinson fugacity that is applicable to any mixture. The proposed model retains the conventional flash iteration, the convergence robustness, and the option of manual parameter tuning for fluid characterization.
A GPU-Based, Industrial Grade Compositional Reservoir Simulator
Authors: Esler K. , Gandham R. , Patacchini L. , Garipov T. , Panfili P. , Caresani F. , Pizzolato A. , Cominelli A. 
Published: October 2021

Abstract
Recently, graphics processing units (GPUs) have been demonstrated to provide a significant performance benefit for black-oil reservoir simulation, as well as flash calculations that serve an important role in compositional simulation. A comprehensive approach to compositional simulation based on GPUs had yet to emerge, and some questions remained as to whether the benefits observed in black-oil simulation would persist with a more complex fluid description. We present our positive answer to this question through the extension of a commercial GPU-based black-oil simulator to include a compositional description based on standard cubic equations of state. We describe the motivations for the formulation we select to make optimal use of GPU characteristics, including choice of primary variables and iteration scheme. We then describe performance results on an example sector model and simplified synthetic case designed to allow a detailed examination of scaling with respect to the number of hydrocarbon components and model size, as well as number of processors. We finally show results from two complex asset models (synthetic and real) and examine performance scaling with respect to GPU generation, demonstrating that performance correlates strongly with GPU memory bandwidth.
INSIM-FPT-3D: A Data-Driven Model for History Matching, Water-Breakthrough Prediction and Well-Connectivity Characterization in Three-Dimensional Reservoirs
Authors: Zhao Hui , Liu Wei , Rao Xiang , Sheng Guanglong , Li Huazhou Andy , Guo Zhenyu , Liu Deng , Cao Lin 
Published: October 2021

Abstract
The data-driven interwell simulation model (INSIM) has been recognized as an effective tool for history matching and interwell-connectivity characterization of waterflooding reservoirs. INSIM-FT-3D (FT: front tracking) was recently developed to upgrade the applicationdimension of INSIM series data-driven models from two-dimensional (2D) to three-dimensional (3D). However, INSIM-FT-3D cannot accurately infer the dynamic change of well-connectivity and predict well's bottom-hole pressure (BHP). The main purpose of this study intends to expand the capability of INSIM-FT-3D to empower for the assimilation of BHPs, the reliable prediction of water breakthrough and the characterization of dynamic interwell-connectivities.
The default setting of well index (WI) in INSIM-FT-3D based on Peaceman's equation does not yield accurate BHP estimates. We derive a WI that can honor the BHPs of a reference model composed of a set of 1D connections. When history matching BHPs of a 3D reservoir, we show that the derived WI is a better initial guess than that obtained from Peaceman's equation. We also develop a flow-path-tracking (FPT) algorithm to calculate the dynamic interwell properties (allocation factors and pore volumes (PVs)). Besides, we discuss the relationship between the INSIM-family methods and the traditional grid-based methods, which indicates that the INSIM-family methods can calculate the transmissibility of the connection between coarse-scale cells in a more accurate manner. As an improvement of INSIM-FT-3D, the newly proposed data-driven model is denoted as INSIM-FPT-3D.
To verify the correctness of the derived WI, we present a 1D problem and a T-shaped synthetic reservoir simulation model as the reference models. BHPs and oil production rates are obtained as the observed data by running these two reference models with total injection/production-rate controls. An INSIM-FPT-3D model is created by specifying the transmissibilities and PVs that are the same as those in the reference model. By applying the derived WIs in INSIM-FPT-3D, the resulting BHPs and oil rates obtained agree well with the reference model without further model calibration. Applying INSIM-FPT-3D to a synthetic multi-layered reservoir shows that we obtain a reasonable match of both BHPs and oil rates with INSIM-FPT-3D. Compared with the FrontSim model, the INSIM-FPT-3D model after history matching is shown to match the dynamic PVs from FrontSim reasonably well and can correctly predict the timing of water breakthrough.
By allowing for the assimilation of BHP data, we enable INSIM-FPT-3D to history match a green field with limited production history and forecast the timing of water breakthrough. The improved INSIM-FPT-3D leads to more accurate characterization of the interwell connectivities.
GEOSX: A Multiphysics, Multilevel Simulator Designed for Exascale Computing
Authors: Gross Herve , Mazuyer Antoine 
Published: October 2021

Abstract
Evaluating large basin-scale formations for CO2 sequestration is one of the most important challenges for our industry. The technical complexity and the quantification of risks associated with these operations call for new reservoir engineering and reservoir simulation tools. The impact of multiple coupled physical phenomena, the century timescale, and basin-sized models in these operations force us to completely take apart and revisit the numerical backbone of existing simulation tools. We need a reservoir simulation tool designed for scalability and portability on high-performance computing architectures.
To achieve this, we are proposing a new, open-source, multiphysics, and multilevel physics simulation tool called GEOSX. This tool is jointly created by Lawrence Livermore National Laboratory, Stanford University, and Total. It is designed for scalability on multiple CPUs and multiple GPUs and offers a suite of physical solvers that can be extended easily while achieving a balance between performance and portability. GEOSX is initially targeting multiphysics simulations with coupled geomechanics, flow, and transport mechanics but with its open architecture, it allows access to high-performance physical solvers as building blocks of other multiphysics problems and provides users with a suite of tools for numerical optimization across platforms.
In this paper, we introduce GEOSX, expose its fundamental architecture principles, and show an example of geological sequestration of CO2 modeling on real data. We demonstrate our ability to simulate fluid and rock poromechanical interactions over long periods and basin-scale dimensions. GEOSX demonstrates its usefulness for such complex and large problems and proves to be scalable and portable across multiple high-performance systems.
Cache-Aware and Roofline-Ideal Automatic Differentiation
Authors: Jing Yuxuan , Younis Rami M. 
Published: October 2021

Abstract
Automatic differentiation software libraries augment arithmetic operations with their derivatives, thereby relieving the programmer of deriving, implementing, debugging, and maintaining derivative code. With this encapsulation however, the responsibility of code optimization relies more heavily on the AD system itself (as opposed to the programmer and the compiler). Moreover, given that there are multiple contexts in reservoir simulation software for which derivatives are required (e.g. property package and discrete operator evaluations), the AD infrastructure must also be adaptable. An Operator Overloading AD design is proposed and tested to provide scalability and computational efficiency seemlessly across memory- and compute-bound applications. This is achieved by 1) use of portable and standard programming language constructs (C++17 and OpenMP 4.5 standards), 2) adopting a vectorized programming interface, 3) lazy evaluation via expression templates, and 4) multiple memory alignment and layout policies. Empirical analysis is conducted on various kernels spanning various arithmetic intensity and working set sizes. Cache- aware roofline analysis results show that the performance and scalability attained are reliably ideal. In terms of floapting point operations executed per second, the performance of the AD system matches optimized hand-code. Finally, the implementation is benchmarked using the Automatically Differentiable Expression Templates Library (ADETL).
Bridging the Gap Between Material Balance and Reservoir Simulation for History Matching and Probabilistic Forecasting Using Machine Learning
Authors: Goodwin Nigel H. 
Published: October 2021

Abstract

Objectives/Scope
Methods for efficient probabilistic history matching and forecasting have been available for complex reservoir studies for nearly 20 years. These require a surprisingly small number of reservoir simulation runs (typically less than 200). Nowadays, the bottleneck for reservoir decision support is building and maintaining a reservoir simulation model. This paper describes an approach which does not require a reservoir simulation model, is data driven, and includes a physics model based on material balance. It can be useful where a full simulation model is not economically justified, or where rapid decisions need to be made.

Methods, Procedures, Process
Previous work has described the use of proxy models and Hamiltonian Markov Chain Monte Carlo to produce valid probabilistic forecasts. To generate a data driven model, we take historical measurements of rates and pressures at each well, and apply multi-variate time series to generate a set of differential-algebraic equations (DAE) which can be integrated over time using a fully implicit solver. We combine the time series models with material balance equations, including a simple PVT and Z factor model. The parameters are adjusted in a fully Bayesian manner to generate an ensemble of models and a probabilistic forecast. The use of a DAE distinguishes the approach from normal time-series analysis, where an ARIMA model or state space model is used, and is normally only reliable for short term forecasting.

Results, Observations, Conclusions
We apply these techniques to the Volve reservoir model, and obtain a good history match. Moreover, the effort to build a reservoir model has been removed. We demonstrate the feasibility of simple physics models, and open up the possibility of combinations of physics models and machine learning models, so that the most appropriate approach can be used depending on resources and reservoir complexity. We have bridged the gap between pure machine learning models and full reservoir simulation.

Novel/Additive Information
The approach to use multi-variate time series analysis to generate a set of ordinary differential equations is novel. The extension of previously described probabilistic forecasting to a generalised model has many possible applications within and outside the oil and gas industry, and is not restricted to reservoir simulation.
Comparison of Various Discretization Schemes for Simulation of Large Field Case Reservoirs Using Unstructured Grids
Authors: Pierre Samier , Margaux Raguenel , Gilles Darche 
Published: October 2021

Abstract
Solving the equations governing multiphase flow in geological formations involves the generation of a mesh that faithfully represents the structure of the porous medium. This challenging mesh generation task can be greatly simplified by the use of unstructured (tetrahedral) grids that conform to the complex geometric features present in the subsurface. However, running a million-cell simulation problem using an unstructured grid on a real, faulted field case remains a challenge for two main reasons. First, the workflow typically used to construct and run the simulation problems has been developed for structured grids and needs to be adapted to the unstructured case. Second, the use of unstructured grids that do not satisfy the K-orthogonality property may require advanced numerical schemes that preserve the accuracy of the results and reduce potential grid orientation effects. These two challenges are at the center of the present paper. We describe in detail the steps of our workflow to prepare and run a large-scale unstructured simulation of a real field case with faults. We perform the simulation using four different discretization schemes, including the cell-centered Two-Point and Multi-Point Flux Approximation (respectively, TPFA and MPFA) schemes, the cell- and vertex-centered Vertex Approximate Gradient (VAG) scheme, and the cell- and face-centered hybrid Mimetic Finite Difference (MFD) scheme. We compare the results in terms of accuracy, robustness, and computational cost to determine which scheme offers the best compromise for the test case considered here.
Higher Resolution Hybrid-Upwind Spectral Finite-Volume Methods, for Flow in Porous and Fractured Media on Unstructured Grids
Authors: Xie Yawei , Edwards Michael G. 
Published: October 2021

Abstract
A novel higher resolution spectral volume method coupled with a control-volume distributed multi-Point flux approximation (CVD-MPFA) is presented on unstructured triangular grids for subsurface reservoir simulation. The flow equations involve an essentially hyperbolic convection equation coupled with an elliptic pressure equation resulting from Darcy’s law together with mass conservation. The spectral volume (SV) method is a locally conservative, efficient high-order finite volume method for convective flow. In 2D geometry, the triangular cell is subdivided into sub-cells, and the average state variables in the sub-cells are used to reconstruct a high-order polynomial in the triangular cell. The focus here is on an efficient strategy for reconstruction of both a higher resolution approximation of the convective transport flux and Darcy-flux approximation on sub-cell interfaces, which is also coupled with a discrete fracture model. The strategy involves coupling of the SV method and reconstructed CVD-MPFA fluxes at the faces of the spectral volume, to obtain an efficient finer scale higher resolution finite-volume method which solves for both the saturation and pressure. A limiting procedure based on a Barth-Jespersen type limiter is used to prevent non-physical oscillations on unstructured grids. The fine scale saturation/concentration field is then updated via the reconstructed finite volume approximation over the sub-cell control-volumes. Performance comparisons are presented for two phase flow problems on 2D unstructured meshes including fractures. The results demonstrate that the spectral-volume method achieves further enhanced resolution of flow and fronts in addition to that of achieved by the standard higher resolution method over first order upwind, while improving upon efficiency.
Coupled Simulation of Flow and Geomechanics in Fractured Reservoirs Using an Integrally Embedded Discrete Fracture Model
Authors: Wu Dawei , Di Yuan , Wu Yu-Shu 
Published: October 2021

Abstract
Fluid flow in fractured reservoirs is significantly affected by the effect of geomechanics since fractures can be more stress-sensitive than rock matrix. In this work, we present a flow and geomechanics coupled model for the simulation of fractured reservoirs. The flow model uses the integrally embedded discrete fracture model (IEDFM). This model considers a more improved pressure distribution assumption in the vicinity of fractures compared to traditional EDFM and calculates the matrix-fracture transmissibility semi-analytically. Another advantage of the IEDFM is the capability of modeling flow between matrix and fractures in anisotropic reservoirs. The geomechanical model uses the equivalent continuum approach, which introduces an equivalent material to capture the deformation of both rock matrix and fractures. Constitutive models are established for both natural fractures and hydraulic fractures to capture the stress-dependent fracture stiffness. The force balance equation is discretized by the finite element method (FEM) and coupled with IEDFM to form an iterative coupling simulation approach. A water flooding example in a naturally fractured reservoir and a depletion example from a horizontal well with hydraulic fractures in a tight oil reservoir are investigated to demonstrate the feasibility of the proposed model in coupled flow and geomechanics simulation of fractured reservoirs.
Comparative Immunomodulatory Efficacy of Rosemary and Fenugreek against Escherichia Coli-Infection via Suppression of Inflammation and Oxidative Stress in Broilers
Authors: Farouk Sameh Mohamed , Abd-El-Rahman Haidy G. , Abdallah Osama A. , ElBehidy Nashwa G. 
Published: October 2021

Abstract
Broiler chickens are frequently infected with Escherichia coli (E.Coli) bacteria, which often leads to the emergence of many diseases and huge economic losses. Hence, the current study was conducted to evaluate the relative efficacy of dietary rosemary and fenugreek, under E.Coli-infection in broilers, via evaluation of growth performance, biochemical indices, immune response and histo-morphological changes. Eighty Cobb broilers were allotted to four equal groups (n = 20 chicks/group); control non-infected (CN), control infected (CI), rosemary infected (RI) and fenugreek infected (FI) groups. The RI and FI groups revealed a significant elevation in their body weight and body weight gain compared with the CI group. However, both groups showed a significant decline in serum aspartate and alanine aminotransferase activities, as well as uric acid and creatinine levels. A significant decrease in total antioxidant capacity, catalase and superoxide dismutase activities were noted among CI chicks. Moreover, distinctly higher activities were evident in both RI and FI groups. Assessment of immunomodulatory markers showed a significant increase in immunoglobulin G along with a significant decline in interleukin-6 level in both RI and FI groups, with the lowest IL-6 value within FI group. Histopathological evaluations focused on the deleterious effect associated with E-Coli infection of broilers’ liver, kidney, intestine, spleen, bursa of fabricius, and thymus. Partial histological improvement was noticed among RI group, and nearly normal tissues were recorded in FI group. Overall, our findings suggest the ability of fenugreek to mitigate the adverse effects of E.Coli-infection on broiler performance and tissue profiles, by improving the general health status of the broiler chickens.