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Rigid transformations for stabilized lower dimensional space to support subsurface uncertainty quantification and interpretation Comput. Geosci. (IF 2.5) Pub Date : 2024-03-08 Ademide O. Mabadeje, Michael J. Pyrcz
Subsurface datasets commonly are big data, i.e., they meet big data criteria, such as large data volume, significant feature variety, high sampling velocity, and limited data veracity. Large data volume is enhanced by the large number of necessary features derived from the imposition of various features derived from physical, engineering, and geological inputs, constraints that may invoke the curse
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Improved spatial understanding of induced seismicity hazard from the discretization of a curved fault surface Comput. Geosci. (IF 2.5) Pub Date : 2024-02-22 Kevin L. McCormack, Philip J. Smith
In some geomechanical treatments of induced seismicity, the fault surface is idealized to be a plane. We depart from this assumption by comparing a discretization model and a kriging model, both of which allow the incorporation of rugosity, roughness, and curvature into the fault surface and subsequent geomechanical models of hazard. We test the Hogback Flexural Faults of the San Juan Basin, which
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Derivative-free search approaches for optimization of well inflow control valves and controls Comput. Geosci. (IF 2.5) Pub Date : 2024-02-13 Mathias C. Bellout, Thiago L. Silva, Jan Øystein Haavig Bakke, Carl Fredrik Berg
Decisions regarding problem conceptualization, search approach, and how best to parametrize optimization methods for practical application are key to successful implementation of optimization approaches within georesources field development projects. This work provides decision support regarding the application of derivative-free search approaches for concurrent optimization of inflow control valves
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A mortar method for the coupled Stokes-Darcy problem using the MAC scheme for Stokes and mixed finite elements for Darcy Comput. Geosci. (IF 2.5) Pub Date : 2024-02-08 Wietse M. Boon, Dennis Gläser, Rainer Helmig, Kilian Weishaupt, Ivan Yotov
A discretization method with non-matching grids is proposed for the coupled Stokes-Darcy problem that uses a mortar variable at the interface to couple the marker and cell (MAC) method in the Stokes domain with the Raviart-Thomas mixed finite element pair in the Darcy domain. Due to this choice, the method conserves linear momentum and mass locally in the Stokes domain and exhibits local mass conservation
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A benchmark study on reactive two-phase flow in porous media: Part II - results and discussion Comput. Geosci. (IF 2.5) Pub Date : 2024-02-03 Etienne Ahusborde, Brahim Amaziane, Stephan de Hoop, Mustapha El Ossmani, Eric Flauraud, François P. Hamon, Michel Kern, Adrien Socié, Danyang Su, K. Ulrich Mayer, Michal Tóth, Denis Voskov
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Modeling low saline carbonated water flooding including surface complexes Comput. Geosci. (IF 2.5) Pub Date : 2024-02-01
Abstract Carbonated water flooding (CWI) increases oil production due to favorable dissolution effects and viscosity reduction. Accurate modeling of CWI performance requires a simulator with the ability to capture the true physics of such process. In this study, compositional modeling coupled with surface complexation modeling (SCM) are done, allowing a unified study of the influence in oil recovery
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A generalized time-domain velocity-stress seismic wave equation for composite viscoelastic media with a topographic relief and an irregular seabed Comput. Geosci. (IF 2.5) Pub Date : 2024-02-01 Chao Jin, Bing Zhou, Mohamed Kamel Riahi, Mohamed Jamal Zemerly
Accurate seismic wave modeling of viscoelastic anisotropic medium is a fundamental tool for seismic data processing, interpretation and full waveform inversion. Also, free water surface, topographic relief and irregular seabed are often encountered in practical seismic surveys. Thus, basing on the General Maxwell Body, we proposed a generalized matrix form of the velocity-stress seismic wave equation
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A benchmark study on reactive two-phase flow in porous media: Part I - model description Comput. Geosci. (IF 2.5) Pub Date : 2024-01-29
Abstract This paper proposes a benchmark study for reactive multiphase multicomponent flow in porous media. Modeling such problem leads to a highly nonlinear coupled system of partial differential equations, ordinary differential equations and algebraic constraints, which requires special numerical treatment. The benchmark consists of five test problems in total (both in 1D and in 2D), with varying
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Extraction of weak geochemical anomalies based on multiple-point statistics and local singularity analysis Comput. Geosci. (IF 2.5) Pub Date : 2024-01-27 Wenyao Fan, Gang Liu, Qiyu Chen, Laijun Lu, Zhesi Cui, Boxin Zuo, Xuechao Wu
Traditional interpolations might cause smoothing effect on geochemical anomaly detection due to the moving weighted average properties. Since Multiple-Point Statistics (MPS) is a kind of stochastic simulation based on regional variables statistical patterns in a certain space, it can reduce the smoothing effect and quantify the element distribution uncertainties effectively. However, due to the insufficient
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Ensemble-based history matching of the Edvard Grieg field using 4D seismic data Comput. Geosci. (IF 2.5) Pub Date : 2024-01-27 Rolf J. Lorentzen, Tuhin Bhakta, Kristian Fossum, Jon André Haugen, Espen Oen Lie, Abel Onana Ndingwan, Knut Richard Straith
The Edvard Grieg field is a highly complex and heterogeneous reservoir with an extensive fault structure and a mixture of sandstone, conglomerate, and shale. In this paper, we present a complete workflow for history matching the Edvard Grieg field using an ensemble smoother for Bayesian inference. An important aspect of the workflow is a methodology to check that the prior assumptions are suitable
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Numerical simulation on staggered grids of three-dimensional brinkman-forchheimer flow and heat transfer in porous media Comput. Geosci. (IF 2.5) Pub Date : 2024-01-05 Wei Liu, Yingxue Song, Yanping Chen, Gexian Fan, Pengshan Wang, Kai Li
In this paper, three-dimensional numerical algorithm is constructed to simulate the behavior of the Brinkman-Forchheimer flow and thermal fields. Numerical results of velocity, pressure and temperature are obtained by applying the efficient modified two-grid marker and cell (MAC) algorithm on staggered grids with the second-order backward difference formula (BDF2) time approximation. The modified-upwind
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Power law slip boundary condition for Navier-Stokes equations: Discontinuous Galerkin schemes Comput. Geosci. (IF 2.5) Pub Date : 2023-12-29 J. K. Djoko, V. S. Konlack, T. Sayah
This study deals with the numerical analysis of several discontinuous Galerkin (DG) methods for the resolution of the Navier-Stokes equations with power law slip boundary condition. The physical context corresponding to this problem is the description of a flow when a position and the direction slip boundary condition is taken into consideration. The main goal in this work is to examine the solvability
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On spatially correlated observations in importance sampling methods for subsidence estimation Comput. Geosci. (IF 2.5) Pub Date : 2023-12-06 Samantha S. R. Kim, Femke C. Vossepoel
The particle filter is a data assimilation method based on importance sampling for state and parameter estimation. We apply a particle filter in two different quasi-static experiments with models of subsidence caused by a compacting reservoir. The first model considers uncorrelated model state variables and observations, with observed subsidence resulting from a single source of strain. In the second
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Parameterizing the fluid forces on limpet shells in unidirectional flow Comput. Geosci. (IF 2.5) Pub Date : 2023-11-25 Carley Walker, Julian Simeonov, Ian Adams
Current parameterizations of the hydrodynamic forces on irregular particles consider some shape dependencies, but lack an explicit dependence on the orientation with respect to the flow. In this paper, we propose a new parameterization of the drag and lift forces acting on whole Limpet shells at arbitrary orientations with respect to the direction of flow through the linear regression of fluid forces
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Comparative calibration of 1D+2D and 3D hydrogeological watershed models Comput. Geosci. (IF 2.5) Pub Date : 2023-11-23 Gillien Latour, Pierre Horgue, François Renard, Romain Guibert, Gérald Debenest
In this work, we study the calibration of the parameters of a hydrogeological watershed model by comparing a 1D+2D approach that combines unsaturated 1D columns and a saturated 2D model, with a full 3D approach. In a first step, a heterogeneous permeability field is estimated by an inversion procedure for each model (2D saturated and 3D unsaturated). The fields obtained are similar but the calculation
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The effects of dispersion and non-linearity on the simulation of landslide-generated waves using the reduced two-layer non-hydrostatic model Comput. Geosci. (IF 2.5) Pub Date : 2023-11-17 Dede Tarwidi, Sri Redjeki Pudjaprasetya, Didit Adytia
This paper revisits the previously developed NH-2LR (reduced two-layer non-hydrostatic) model. The governing equations and numerical schemes are written in terms of normalized variables, with two dimensionless parameters representing dispersion and non-linearity. By utilizing analytical solutions and laboratory experiments, this study aims to validate the numerical NH-2LR model and investigate the
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Multi-asset closed-loop reservoir management using deep reinforcement learning Comput. Geosci. (IF 2.5) Pub Date : 2023-11-03 Yusuf Nasir, Louis J. Durlofsky
Closed-loop reservoir management (CLRM), in which history matching and production optimization are performed multiple times over the life of an asset, can provide significant improvement in the specified objective. These procedures are computationally expensive due to the large number of flow simulations required for history matching and optimization. Existing CLRM procedures are applied asset by asset
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Numerical simulation of multiscale fault systems with rate- and state-dependent friction Comput. Geosci. (IF 2.5) Pub Date : 2023-10-31 Carsten Gräser, Ralf Kornhuber, Joscha Podlesny
We consider the deformation of a geological structure with non-intersecting faults that can be represented by a layered system of viscoelastic bodies satisfying rate- and state-depending friction conditions along the common interfaces. We derive a mathematical model that contains classical Dieterich- and Ruina-type friction as special cases and accounts for possibly large tangential displacements.
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A 3D organized point cloud clustering algorithm for seismic fault data based on region growth Comput. Geosci. (IF 2.5) Pub Date : 2023-10-26 Lihong Zhao, Minghao Cai, Renwei Ding, Yujie Zhang, Shuo Zhao, Jinwei Zhang, Jing Yang
Traditional classification methods for seismic fault 3D point cloud data rely on fault annotation data. Fault annotation data is usually stored in the data structure of a 3D array, and represented by organized point cloud data. The artificial fault annotation method analyses point data in each 2D slice respectively, without considering the 3D spatial distribution of all points, produces results without
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Implementation of Soreide and Whitson EoS in a GPU-based reservoir simulator Comput. Geosci. (IF 2.5) Pub Date : 2023-10-21 P. Panfili, L. Patacchini, A. Ferrari, T. Garipov, K. Esler, A. Cominelli
Reservoir simulation is traditionally based on the assumption that water is an inert phase, while hydrocarbon components split into oil and gas phases. This approach is usually reasonable when modeling conventional hydrocarbon recovery, but specific applications may require accounting for mass exchange between the water and hydrocarbon phases. We here present the extension of our Graphics Processing
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Numerical modeling on high-temperature and high-pressure gas condensate recovery considering the viscosity variation and dynamic relative permeability Comput. Geosci. (IF 2.5) Pub Date : 2023-10-16 Lihua Shao, Yichen Wei, Yuhe Wang
The production evaluation of high-temperature and high-pressure gas condensate remains unsatisfactory in terms of precision due to the inadequate knowledge of viscosity variation and dynamic relative permeability. Here, we first conduct phase behavior experiments to clarify the mechanisms of viscosity variation followed by core flooding experiments to reveal the dynamic relative permeability. The viscosity
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Impact of artificial topological changes on flow and transport through fractured media due to mesh resolution Comput. Geosci. (IF 2.5) Pub Date : 2023-10-13 Aleksandra A. Pachalieva, Matthew R. Sweeney, Hari Viswanathan, Emily Stein, Rosie Leone, Jeffrey D. Hyman
We performed a set of numerical simulations to characterize the interplay of fracture network topology, upscaling, and mesh refinement on flow and transport properties in fractured porous media. We generated a set of generic three-dimensional discrete fracture networks at various densities, where the radii of the fractures were sampled from a truncated power-law distribution, and whose parameters were
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A preliminary model for optimal control of moisture content in unsaturated soils Comput. Geosci. (IF 2.5) Pub Date : 2023-10-09 Marco Berardi, Fabio V. Difonzo, Roberto Guglielmi
In this paper we introduce an optimal control approach to Richards’ equation in an irrigation framework, aimed at minimizing water consumption while maximizing root water uptake. We first describe the physics of the nonlinear model under consideration, and then develop the first-order necessary optimality conditions of the associated boundary control problem. We show that our model provides a promising
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Fracture network flow prediction with uncertainty using physics-informed graph features Comput. Geosci. (IF 2.5) Pub Date : 2023-10-03 Justin D. Strait, Kelly R. Moran, Jeffrey D. Hyman, Hari S. Viswanathan, Matthew R. Sweeney, Philip H. Stauffer
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Competitive algorithm to balance and predict blasting outcomes using measured field data sets Comput. Geosci. (IF 2.5) Pub Date : 2023-09-19 N. Sri Chandrahas, B. S. Choudhary, M. S. Venkataramayya
In this investigation, a new technique termed Firefly-XGBoost was developed to forecast and reconcile blasting results like mean fragmentation size (MFS) and peak particle velocity (PPV). As a result, the particle swarm optimization (PSO) algorithm and firefly algorithm were used to enhance the effectiveness of the XG Boost conventional model. A total of 152 blast experiments were performed at three
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Stacked ensemble model for reservoir characterisation to predict log properties from seismic signals Comput. Geosci. (IF 2.5) Pub Date : 2023-09-14 Pallabi Saikia, Rashmi Dutta Baruah
Sparse and limited well data in oil fields pose challenges in accurately estimating petrophysical properties for reservoir characterization. Conventional Machine Learning (ML) models often struggle to provide accurate estimations in such scenarios. This paper presents an ensemble modeling solution, named ”SEMoRC”, which effectively predicts various log (petrophysical) properties using seismic data
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Traveling wave solutions describing the foam flow in porous media for low surfactant concentration Comput. Geosci. (IF 2.5) Pub Date : 2023-09-11 Rosmery Q. Zavala, Luis F. Lozano, Grigori Chapiro
We present a foam displacement model with a separate balance equation for the surfactant concentration in the aqueous phase. We consider the gas mobility that depends on the surfactant concentration and the dynamic behavior of foam as Newtonian. We study traveling wave solutions for the proposed model considering a high initial water saturation (drainage scenario) and varying the injected water saturation
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Stochastic reconstruction of shale combining multi-scale generators and discriminators with attention mechanisms Comput. Geosci. (IF 2.5) Pub Date : 2023-09-11 Ting Zhang, Yue Dong, Hualin Bai, Yuan Peng
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Local and global timeseries proxies using functional principal component analysis: application to history-matching and uncertainty quantification Comput. Geosci. (IF 2.5) Pub Date : 2023-09-09 Hamidreza Hamdi, Christopher R. Clarkson, Mario Costa Sousa
Accurate surrogate models are essential for the application of computational methods such as Markov chain Monte Carlo (McMC) using numerical reservoir simulation. Previous studies have often focused on building surrogates to represent the misfit (or likelihood) function. However, building an accurate constrained surrogate for the likelihood/misfit is difficult for higher dimensions unless an overly
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Meshing strategies for 3d geo-electromagnetic modeling in the presence of metallic infrastructure Comput. Geosci. (IF 2.5) Pub Date : 2023-09-08 Octavio Castillo-Reyes, Paula Rulff, Evan Schankee Um, Adrian Amor-Martin
In 3D geo-electromagnetic modeling, an adequate discretisation of the modeling domain is crucial to obtain accurate forward responses and reliable inversion results while reducing the computational cost. This paper investigates the mesh design for subsurface models, including steel-cased wells, which is relevant for many exploration settings but still remains a numerically challenging task. Applying
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Lattice Boltzmann study of the double-diffusive convection in porous media with Soret and Dufour effects Comput. Geosci. (IF 2.5) Pub Date : 2023-09-07 Xuguang Yang, Yuze Zhang
In this work, a coupled representative elementary volume scale lattice Boltzmann method (LBM) is developed to investigate double-diffusive convection in a porous cavity, taking into account Dufour and Soret effects. The governing equations comprise the incompressible Navier-Stokes equations and the coupled convection diffusion equations with cross diffusion terms, which pose challenges to the numerical
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Bayesian model evaluation for multiple scenarios Comput. Geosci. (IF 2.5) Pub Date : 2023-08-29 Sigurd Ivar Aanonsen, Kristian Fossum, Trond Mannseth
Traditional uncertainty analysis for subsurface models is typically based on a single dynamic model with a number of uncertain parameters. Improved and more robust forecasting can be obtained by combining several models in a Bayesian setting using model averaging. The traditional Bayesian Model Averaging (BMA), however, suffers from several drawbacks, such as too large sensitivity to prior model assumptions
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A new formulation of the surface charge/surface potential relationship in electrolytes with valence less than three Comput. Geosci. (IF 2.5) Pub Date : 2023-08-29 Oddbjørn Nødland, Aksel Hiorth
Surface complexation models (SCMs) based on Gouy-Chapman theory are often used to describe adsorption of ions onto mineral surfaces. To compensate for the buildup of charge at a solid surface, the composition of the electric diffuse layer next to the surface must balance the surface charge. To calculate the diffuse layer composition, several nonlinear equations and integrals must be solved, usually
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Deep learning discovery of macroscopic governing equations for viscous gravity currents from microscopic simulation data Comput. Geosci. (IF 2.5) Pub Date : 2023-08-28 Junsheng Zeng, Hao Xu, Yuntian Chen, Dongxiao Zhang
Although deep learning has been successfully applied in a variety of science and engineering problems owing to its strong high-dimensional nonlinear mapping capability, it is of limited use in scientific knowledge discovery. In this work, we propose a deep learning based framework to discover the macroscopic governing equation of an important geophysical process, i.e., viscous gravity current, based
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Marginalized iterative ensemble smoothers for data assimilation Comput. Geosci. (IF 2.5) Pub Date : 2023-08-26 Andreas S. Stordal, Rolf J. Lorentzen, Kristian Fossum
Data assimilation is an important tool in many geophysical applications. One of many key elements of data assimilation algorithms is the measurement error that determines the weighting of the data in the cost function to be minimized. Although the algorithms used for data assimilation treat the measurement uncertainty as known, it is in many cases estimated or set based on some expert opinion. Here
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A reduced-order model based on C-R mixed finite element and POD technique for coupled Stokes-Darcy system with solute transport Comput. Geosci. (IF 2.5) Pub Date : 2023-08-22 Junpeng Song, Hongxing Rui, Zhijiang Kang
As we all know, numerically solving nonlinear coupling systems usually requires expensive computational costs. In this paper, we present a novel approach to address the coupled Stokes-Darcy system with solute transport, utilizing a reduced-order model that integrates the Crouzeix-Raviart mixed finite element method (CRMFE) and the proper orthogonal decomposition (POD) technique. The established reduced-order
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Generating subsurface earth models using discrete representation learning and deep autoregressive network Comput. Geosci. (IF 2.5) Pub Date : 2023-08-15 Jungang Chen, Chung-Kan Huang, Jose F. Delgado, Siddharth Misra
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Surrogate-assisted distributed swarm optimisation for computationally expensive geoscientific models Comput. Geosci. (IF 2.5) Pub Date : 2023-08-05 Rohitash Chandra, Yash Vardhan Sharma
Evolutionary algorithms provide gradient-free optimisation which is beneficial for models that have difficulty in obtaining gradients; for instance, geoscientific landscape evolution models. However, such models are at times computationally expensive and even distributed swarm-based optimisation with parallel computing struggle. We can incorporate efficient strategies such as surrogate-assisted optimisation
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Data-driven modelling with coarse-grid network models Comput. Geosci. (IF 2.5) Pub Date : 2023-08-04 Knut-Andreas Lie, Stein Krogstad
We propose to use a conventional simulator, formulated on the topology of a coarse volumetric 3D grid, as a data-driven network model that seeks to reproduce observed and predict future well responses. The conceptual difference from standard history matching is that the tunable network parameters are calibrated freely without regard to the physical interpretation of their calibrated values. The simplest
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Deep-learning-based upscaling method for geologic models via theory-guided convolutional neural network Comput. Geosci. (IF 2.5) Pub Date : 2023-08-02 Nanzhe Wang, Qinzhuo Liao, Haibin Chang, Dongxiao Zhang
Large-scale or high-resolution geologic models usually comprise a huge number of grid blocks, which can be computationally demanding and time-consuming to solve with numerical simulators. Therefore, it is advantageous to upscale geologic models (e.g., hydraulic conductivity) from fine-scale (high-resolution grids) to coarse-scale systems. Numerical upscaling methods have been proven to be effective
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A new computational model for karst conduit flow in carbonate reservoirs including dissolution-collapse breccias Comput. Geosci. (IF 2.5) Pub Date : 2023-07-31 Isamara Landim, Marcio A. Murad, Patricia Pereira, Eduardo Abreu
We construct a new computational model to describe coupled 3D/1D flow in carbonate rocks intertwined by a network of karst cave conduits. The proposed approach shows ability to incorporate pointwise velocity-dependent jumps in the pressure field arising from localized partial obstructions due to the presence of collapse-breccia within the discrete conduit network. At the microscale, we postulate single
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Hybrid Neural Network - Variational Data Assimilation algorithm to infer river discharges from SWOT-like data Comput. Geosci. (IF 2.5) Pub Date : 2023-07-27 Kevin LARNIER, Jérôme MONNIER
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Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements Comput. Geosci. (IF 2.5) Pub Date : 2023-07-28 Stefano Nardean, Massimiliano Ferronato, Ahmad Abushaikha
This work proposes an original preconditioner that couples the Constrained Pressure Residual (CPR) method with block preconditioning for the efficient solution of the linearized systems of equations arising from fully implicit multiphase flow models. This preconditioner, denoted as Block CPR (BCPR), is specifically designed for Lagrange multipliers-based flow models, such as those generated by Mixed
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Nonlinear domain-decomposition preconditioning for robust and efficient field-scale simulation of subsurface flow Comput. Geosci. (IF 2.5) Pub Date : 2023-07-27 Olav Møyner, Atgeirr F. Rasmussen, Øystein Klemetsdal, Halvor M. Nilsen, Arthur Moncorgé, Knut-Andreas Lie
We discuss a nonlinear domain-decomposition preconditioning method for fully implicit simulations of multicomponent porous media flow based on the additive Schwarz preconditioned exact Newton method (ASPEN). The method efficiently accelerates nonlinear convergence by resolving unbalanced nonlinearities in a local stage and long-range interactions in a global stage. ASPEN can improve robustness and
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XFVM modelling of fracture aperture induced by shear and tensile opening Comput. Geosci. (IF 2.5) Pub Date : 2023-07-25 Giulia Conti, Stephan Matthäi, Patrick Jenny
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Modeling 3-D anisotropic elastodynamics using mimetic finite differences and fully staggered grids Comput. Geosci. (IF 2.5) Pub Date : 2023-07-26 Harpreet Sethi, Fatmir Hoxha, Jeffrey Shragge, Ilya Tsvankin
Accurate modeling of elastic wavefields in 3-D anisotropic media is important for many seismic processing and inversion applications. However, efficient wavefield simulation for tilted transversely isotropic (TTI) media and, especially, for orthorhombic and lower symmetries remains challenging. Finite-difference (FD) implementations using centered Taylor-series coefficients on singly staggered grids
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An extended peridynamic bond-based constitutive model for simulation of crack propagation in rock-like materials Comput. Geosci. (IF 2.5) Pub Date : 2023-07-26 Gang Sun, Junxiang Wang, Haiyue Yu, Lianjun Guo
The stress of rock-like materials first increases and then decreases with an increase in the strain, and finally become damaged under tensile or compressive loads. It is not suitable to use the traditional bond-based peridynamics model to simulate the crack propagation of rock-like materials. Based on the bond-based peridynamics theory, a constitutive model has here been proposed that can reflect the
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Global sensitivity analysis using multi-resolution polynomial chaos expansion for coupled Stokes–Darcy flow problems Comput. Geosci. (IF 2.5) Pub Date : 2023-07-26 Ilja Kröker, Sergey Oladyshkin, Iryna Rybak
Determination of relevant model parameters is crucial for accurate mathematical modelling and efficient numerical simulation of a wide spectrum of applications in geosciences. The conventional method of choice is the global sensitivity analysis (GSA). Unfortunately, at least the classical Monte-Carlo based GSA requires a high number of model runs. Response surfaces based techniques, e.g. arbitrary
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The non-monotonicity of growth rate of viscous fingers in heterogeneous porous media Comput. Geosci. (IF 2.5) Pub Date : 2023-07-26 I. A. Starkov, D. A. Pavlov, S. B. Tikhomirov, F. L. Bakharev
The paper presents a stochastic analysis of the growth rate of viscous fingers in miscible displacement in a heterogeneous porous medium. The statistical parameters characterizing the permeability distribution of a reservoir vary over a wide range. The formation of fingers is provided by the mixing of different-viscosity fluids — water and polymer solution. The distribution functions of the growth
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Binary well placement optimization using a decomposition-based multi-objective evolutionary algorithm with diversity preservation Comput. Geosci. (IF 2.5) Pub Date : 2023-07-25 Matheus Bernardelli de Moraes, Guilherme Palermo Coelho, Antonio Alberto S. Santos, Denis José Schiozer
In binary multi-objective well placement optimization, multiple conflicting objective functions must be optimized simultaneously in reservoir simulation models containing discrete decision variables. Although multi-objective algorithms have been developed or adapted to tackle this scenario, such as the derivative-free evolutionary algorithms, these methods are known to generate a high number of duplicated
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An integrated framework for optimal monitoring and history matching in CO $$_{2}$$ storage projects Comput. Geosci. (IF 2.5) Pub Date : 2023-07-23 Dylan M. Crain, Sally M. Benson, Sarah D. Saltzer, Louis J. Durlofsky
Monitoring is an important component of geological carbon storage operations because it provides data that can be used to estimate key quantities such as CO\(_{2}\) plume location. The design of the monitoring strategy is complicated, however, because the monitoring plan must be established prior to the availability of extensive flow data. In this work, we present and apply a framework that integrates
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Hard enforcement of physics-informed neural network solutions of acoustic wave propagation Comput. Geosci. (IF 2.5) Pub Date : 2023-07-23 Harpreet Sethi, Doris Pan, Pavel Dimitrov, Jeffrey Shragge, Gunter Roth, Ken Hester
Simulating the temporal evolution of wavefield solutions through models with heterogeneous material properties is of practical interest for many scientific applications. The acoustic wave equation (AWE) is often used for studying wave propagation in both fluids and solids and is crucial for many applications including seismic imaging and inversion and non-destructive testing. Because analytical AWE
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Robustness and efficiency of iteration schemes for variably saturated flow across the range of soils, initial and boundary conditions found in practice Comput. Geosci. (IF 2.5) Pub Date : 2023-07-23 Denis Maier, Héctor Montenegro, Bernhard Odenwald
Water flow in partially saturated porous media is of importance in many disciplines such as hydrology, agriculture, environmental management or geotechnical engineering. A robust and accurate solution methodology applicable across the range of soils, initial and boundary conditions found in practice is difficult to identify. Three mass conservative iteration schemes for the approximation of the flow
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A surrogate-assisted uncertainty-aware Bayesian validation framework and its application to coupling free flow and porous-medium flow Comput. Geosci. (IF 2.5) Pub Date : 2023-07-13 Farid Mohammadi, Elissa Eggenweiler, Bernd Flemisch, Sergey Oladyshkin, Iryna Rybak, Martin Schneider, Kilian Weishaupt
Existing model validation studies in geoscience often disregard or partly account for uncertainties in observations, model choices, and input parameters. In this work, we develop a statistical framework that incorporates a probabilistic modeling technique using a fully Bayesian approach to perform a quantitative uncertainty-aware validation. A Bayesian perspective on a validation task yields an optimal
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High-order compact difference schemes based on the local one-dimensional method for high-dimensional nonlinear wave equations Comput. Geosci. (IF 2.5) Pub Date : 2023-07-14 Mengling Wu, Zhi Wang, Yongbin Ge
In this paper, two compact difference schemes are established for solving two-dimensional (2D) and three-dimensional (3D) nonlinear wave equations with variable coefficients, respectively, by using the local one-dimensional (LOD) method and the fourth-order compact difference approximation formulas of the second-order derivatives. Firstly, a four-step fourth-order compact scheme is derived to solve
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Adaptive mesh refinement in locally conservative level set methods for multiphase fluid displacements in porous media Comput. Geosci. (IF 2.5) Pub Date : 2023-07-13 Deepak Singh, Helmer André Friis, Espen Jettestuen, Johan Olav Helland
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Solving the fixed gravimetric boundary value problem by the finite element method using mapped infinite elements. Comput. Geosci. (IF 2.5) Pub Date : 2023-07-05 Marek Macák, Zuzana Minarechová, Lukáš Tomek, Róbert Čunderlík, Karol Mikula
The numerical approach for solving the fixed gravimetric boundary value problem (FGBVP) based on the finite element method (FEM) with mapped infinite elements is developed and implemented. In this approach, the 3D semi-infinite domain outside the Earth is bounded by the triangular discretization of the whole Earth’s surface and extends to infinity. Then the FGBVP consists of the Laplace equation for
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An enhanced V-cycle MgNet model for operator learning in numerical partial differential equations Comput. Geosci. (IF 2.5) Pub Date : 2023-07-01 Jianqing Zhu, Juncai He, Qiumei Huang
This study used a multigrid-based convolutional neural network architecture known as MgNet in operator learning to solve numerical partial differential equations (PDEs). Given the property of smoothing iterations in multigrid methods where low-frequency errors decay slowly, we introduced a low-frequency correction structure for residuals to enhance the standard V-cycle MgNet. The enhanced MgNet model
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A quasi-Newton trust-region method for optimization under uncertainty using stochastic simplex approximate gradients Comput. Geosci. (IF 2.5) Pub Date : 2023-06-24 Esmail Eltahan, Faruk Omer Alpak, Kamy Sepehrnoori
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Lattice Boltzmann method with diffusive scaling for thermal flows in porous media Comput. Geosci. (IF 2.5) Pub Date : 2023-06-16 Xinyue Liu, Lei Wang, Jiangxu Huang, Xuguang Yang
In this work, we propose a lattice Boltzmann method for thermal flows in porous media, and show that the governing equations for thermal flows in porous media can be recovered correctly through the Maxwell iteration. Unlike previous works, the current model is constructed under diffusive scaling such that the volume-average velocity and temperature computations are just related to the density/temperature