arXiv subjects

David Landa-Marbán

Publications and source records attributed to David Landa-Marbán.

18 recordsLinked to original sources

arXiv2026

pycopm: An open-source tool to tailor OPM Flow geological models

Reservoir simulations help the energy industry make better decisions by predicting how fluids like oil, gas, water, hydrogen, and carbon dioxide will flow underground. To keep these predictions accurate, engineers often need to update geological models quickly as new information becomes available. pycopm is a tool designed to make this process faster and easier. It allows users to adjust geological models in several ways, such as simplifying complex grids, focusing on specific parts of a reservoir, or changing the shape and position of the model. These capabilities help engineers test different scenarios efficiently. Although pycopm was first used on two well-known public datasets, it has since become useful in many other situations because of its easy-to-use features and recent extensions. Today, it supports studies involving model refinement, comparing coarse and detailed models, analyzing interactions between nearby sites, and speeding up troubleshooting in large simulations.

physics.geo-ph↗

arXiv2026

A Machine-Learned Near-Well Model in OPM Flow

Recent advances in reservoir simulation increasingly utilize hybrid approaches that couple physics-based simulators with machine-learning (ML) components. ML components offer high fidelity to training data and fast inference, enabling efficient and accurate modeling of complex multi-scale or multi-physics phenomena. Modern reservoir simulators rely on automatic differentiation (AD) to support efficient and flexible strategies for nonlinear solvers, inverse problems, and optimization problems. Efficient hybrid modeling therefore requires tight integration of the ML components with the simulator's AD framework. We present the first integration of neural networks into the high-performance reservoir simulator OPM Flow. Networks are trained in TensorFlow and imported into OPM, where they are accessed as native AD functions. This presents an efficient framework for hybrid modeling and enables seamless integration in existing simulator workflows. As an application, we introduce a novel, data-driven near-well model. Near-well models are essential in reservoir simulation for accurately representing singular pressure gradients around wells. Commonly used are the Peaceman near-well model and its extensions, or local grid refinement around the wells. Peaceman-type models are limited to simplified flow regimes, whereas local grid refinement is computationally expensive. We address these limitations by training a neural network to infer a Peaceman-like well index from fine-scale ensemble simulations of the near-well region. It is then integrated into OPM Flow with the new framework. Tested on relevant examples for CO$_2$ storage, the method offers high fidelity to fine-scale results at low computational cost, demonstrating the potential of the OPM Flow-Neural Network framework for hybrid modeling.

math.NA↗

arXiv2025

Performance of an open-source image-based history matching framework for CO$_2$ storage

We present a history matching (HM) workflow applied to the International FluidFlower benchmark study dataset, which features high-resolution images of CO$_2$ storage in a meter-scale, geologically complex reservoir. The dataset provides dense spatial and temporal observations of fluid displacement, offering a rare opportunity to validate and enhance HM techniques for geological carbon storage (GCS). The combination of detailed experimental data and direct visual observation of flow behavior at this scale is novel and valuable. This study explores the potential and limitations of using experimental data to calibrate standard models for GCS simulation. By leveraging high-resolution images and resulting interpretations of fluid phase distributions, we adjust uncertain parameters and reduce the mismatch between simulation results and observed data. Simulations are performed using the open-source OPM Flow simulator, while the open-source Everest decision-making tool is employed to conduct the HM. After the HM process, the final simulation results show good agreement with the experimental CO$_2$ storage data. This suggests that the system can be effectively described using standard flow equations, conventional saturation functions, and typical PVT properties for CO$_2$-brine mixtures. Our results demonstrate that the Wasserstein distance is a particularly effective metric for matching multi-phase, multi-component flow data. The entire workflow is implemented in a Python package named pofff (Python OPM Flow FluidFlower), which organizes all functionality through a single input file. This design ensures reproducibility and facilitates future extensions of the study.

physics.flu-dyn↗

arXiv2025

A Coarsening Approach to the Troll Aquifer Model

Effective management of pressure communication and interference between concurrent CO$_2$ storage operations is essential for the development of gigaton-scale storage hubs. Coarse models in reservoir simulation offer a simplified representation of the subsurface to efficiently predict pressure distribution. By averaging properties over larger grid blocks, coarsened models significantly reduce computational demands, enabling faster and more manageable simulations. The approach focuses on preserving key physical properties, namely cell connectivity (transmissibilities) and storage capacity (pore volumes). The effectiveness of the coarsened model is demonstrated by applying the improved well location derived from the coarsened model to the full-resolution Troll aquifer model, resulting in improved pressure distribution. The coarsened model enabled the execution of approximately 100,000 simulations over five days using a local server with 144 CPUs, an effort that would have required around seven months using the original model. The coarsening methodology is implemented using pycopm, an open-source tool design to tailor geological models based on industry-standard grid formats, facilitating its application to other models and applications in reservoir engineering.

physics.geo-ph↗

arXiv2025

Benchmarking CO$_2$ Storage Simulations: Results from the 11th Society of Petroleum Engineers Comparative Solution Project

The 11th Society of Petroleum Engineers Comparative Solution Project (shortened SPE11 herein) benchmarked simulation tools for geological carbon dioxide (CO$_2$) storage. A total of 45 groups from leading research institutions and industry across the globe signed up to participate, with 18 ultimately contributing valid results that were included in the comparative study reported here. This paper summarizes the SPE11. A comprehensive introduction and qualitative discussion of the submitted data are provided, together with an overview of online resources for accessing the full depth of data. A global metric for analyzing the relative distance between submissions is proposed and used to conduct a quantitative analysis of the submissions. This analysis attempts to statistically resolve the key aspects influencing the variability between submissions. The study shows that the major qualitative variation between the submitted results is related to thermal effects, dissolution-driven convective mixing, and resolution of facies discontinuities. Moreover, a strong dependence on grid resolution is observed across all three versions of the SPE11. However, our quantitative analysis suggests that the observed variations are predominantly influenced by factors not documented in the technical responses provided by the participants. We therefore identify that unreported variations due to human choices within the process of setting up, conducting, and reporting on the simulations underlying each SPE11 submission are at least as impactful as the computational choices reported.

physics.geo-ph↗

arXiv2022

Field-scale optimization of injection strategies for leakage mitigation using microbially induced calcite precipitation

An optimization procedure for sealing leakage paths in field-scale application of microbially induced calcite precipitation (MICP) is develop and applied to CO$_2$ storage. The procedure utilizes a recently developed field-scale MICP mathematical model implemented in the industry-standard simulator Open Porous Media (OPM) Flow. The optimization problem is solved using the ensemble-based optimization (EnOpt) algorithm where the objective function is defined such that maximizing calcite precipitation is done in the shortest possible MICP operational time. An injection strategy is developed to efficiently produce calcite in and around the leakage paths, and to avoid clogging unwanted areas of the reservoir, e.g., the near-well area. The injection strategy consists of combined injection of growth and cementation solutions in separate well segments to initiate the MICP process after establishing a biofilm in the leakage paths with an initial injection phase. The optimization procedure is applied to three synthetic CO$_2$ leakage scenarios. The numerical results show that the leakage paths in all scenarios are effectively sealed while keeping the total MICP operational time low.

physics.geo-ph↗

arXiv2022

Field-scale impacts of long-term wettability alteration in geological CO$_2$ storage

Constitutive functions that govern macroscale capillary pressure and relative permeability are central in constraining both storage efficiency and sealing properties of CO$_2$ storage systems. Constitutive functions for porous systems are in part determined by wettability, which is a pore-scale phenomenon that influences macroscale displacement. While wettability of saline aquifers and caprocks are assumed to remain water-wet when CO$_2$ is injected, there is recent evidence of contact angle change due to long-term CO$_2$ exposure. Weakening of capillary forces alters the saturation functions dynamically over time. Recently, new dynamic models were developed for saturation functions that capture the impact of wettability alteration (WA) due to long-term CO$_2$ exposure. In this paper, these functions are implemented into a two-phase two-component simulator to study long-term WA dynamics for field-scale CO$_2$ storage. We simulate WA effects on horizontal migration patterns under injection and buoyancy-driven migration in the caprock. We characterize the behavior of each scenario for different flow regimes. Our results show the impact on storage efficiency can be described by the capillary number, while vertical leakage can be scaled by caprock sealing parameters. Scaling models for CO$_2$ migration into the caprock show that long-term WA poses little risk to CO$_2$ containment over relevant timescales.

physics.geo-ph↗

arXiv2021

Numerical studies of long-term wettability alteration effects in CO$_2$ storage applications

The wettability of the rock surface in porous media has an effect on the constitutive saturation functions that govern capillary pressure and relative permeability. The term wettability alteration refers to the change of this property over time by processes such as CO$_2$ interactions with the rock. In this work, we perform numerical simulations considering a two-phase two-component flow model including time-dependent wettability alteration in a two-dimensional aquifer-caprock system using the open porous media framework. Particularly, we study the spatial distribution over time of injected CO$_2$ into the aquifer neglecting and including wettability alteration effects. The numerical simulations show that wettability alteration on the caprock results in a loss of containment; however, the CO$_2$ front into the caprock advances very slow since the unexposed caprock along the vertical migration path also needs to be changed by the slow wettability alteration process. The simulations also show that wettability alteration on the aquifer results in an enhancement of storage efficiency; this since the CO$_2$ front migrates more slowly and the capillary entry pressure decreases after wettability alteration.

physics.geo-ph↗

arXiv2021

Numerical studies of CO$_2$ leakage remediation by micp-based plugging technology

Microbially induced calcite precipitation (MICP) is a technology for sealing leakage paths to ensure the safe storage of CO$_2$ in geological formations. In this work we introduce a numerical simulator of MICP for field-scale studies. This simulator is implemented in the open porous media (OPM) framework. We compare the numerical results to simulations using an upgraded implementation of the mathematical model in the MATLAB reservoir simulation toolbox (MRST). Finally, we consider a 3D system consisting of two aquifers separated by caprock with a leakage path across the width of the reservoir. We study a strategy where microbial solution is injected only at the beginning of the treatment and subsequently either growth solution or cementation solution is injected for biofilm development or calcite precipitation. By applying this strategy, the numerical results show that the MICP technology could be used to seal these leakage paths.

cs.CE↗

arXiv2021

Practical approaches to study microbially induced calcite precipitation at the field scale

Microbially induced calcite precipitation (MICP) is a new and sustainable technology which utilizes biochemical processes to create barriers by calcium carbonate cementation; therefore, this technology has a potential to be used for sealing leakage zones in geological formations. The complexity of current MICP models and present computer power limit the size of numerical simulations. We describe a mathematical model for MICP suitable for field-scale studies. The main mechanisms in the conceptual model are as follow: suspended microbes attach themselves to the pore walls to form biofilm, growth solution is added to stimulate the biofilm development, the biofilm uses cementation solution for production of calcite, and the calcite reduces the pore space which in turn decreases the rock permeability. We apply the model to study the MICP technology in two sets of reservoir properties including a well-established field-scale benchmark system for CO$_2$ leakage. A two-phase flow model for CO$_2$ and water is used to assess the leakage prior to and with MICP treatment. Based on the numerical results, this study confirms the potential for this technology to seal leakage paths in reservoir-caprock systems.

physics.geo-ph↗

arXiv2019

Mathematical Modeling, Laboratory Experiments, and Sensitivity Analysis of Bioplug Technology at Darcy Scale

In this paper we study a Darcy-scale mathematical model for biofilm formation in porous media. The pores in the core are divided into three phases: water, oil, and biofilm. The water and oil flow are modeled by an extended version of Darcy's law and the substrate is transported by diffusion and convection in the water phase. Initially there is biofilm on the pore walls. The biofilm consumes substrate for production of biomass and modifies the pore space which changes the rock permeability. The model includes detachment of biomass due to water flux and death of bacteria, and is implemented in MRST. We discuss the capability of the numerical simulator to capture results from laboratory experiments. We perform a novel sensitivity analysis based on sparse-grid interpolation and multi-wavelet expansion to identify the critical model parameters. Numerical experiments using diverse injection strategies are performed to study the impact of different porosity-permeability relations in a core saturated with water and oil.

physics.app-ph↗

arXiv2019

An upscaled model for permeable biofilm in a thin channel and tube

In this paper, we derive upscaled equations for modelling biofilm growth in porous media. The resulting macro-scale mathematical models consider permeable multi-species biofilm including water flow, transport, detachment and reactions. The biofilm is composed of extracellular polymeric substances (EPS), water, active bacteria and dead bacteria. The free flow is described by the Stokes and continuity equations and the water flux inside the biofilm by the Brinkman and continuity equations. The nutrients are transported in the water phase by convection and diffusion. This pore-scale model includes variations of the biofilm composition and size due to reproduction of bacteria, production of EPS, death of bacteria and shear forces. The model includes a water-biofilm interface between the free flow and the biofilm. Homogenization techniques are applied to obtain upscaled models in a thin channel and a tube, by investigating the limit as the ratio of the aperture to the length $\varepsilon$ of both geometries approaches to zero. As $\varepsilon$ gets smaller, we obtain that the percentage of biofilm coverage area over time predicted by the pore-scale model approaches the one obtained using the effective equations, which shows a correspondence between both models. The two derived porosity-permeability relations are compared to two empirical relations from the literature. The resulting numerical computations are presented to compare the outcome of the effective (upscaled) models for the two mentioned geometries.

physics.flu-dyn↗

arXiv2018

Numerical simulation of biofilm formation in a microchannel

The focus of this paper is the numerical solution of a pore-scale model for the growth of a permeable biofilm. The model includes water flux inside the biofilm, different biofilm components, and shear stress on the biofilm-water interface. To solve the resulting highly coupled system of model equations, we propose a splitting algorithm. The Arbitrary Lagrangian Eulerian (ALE) method is used to track the biofilm-water interface. Numerical simulations are performed using physical parameters from the existing literature. Our computations show the effect of biofilm permeability on the nutrient transport and on its growth.

physics.flu-dyn↗

arXiv2018

A pore-scale model for permeable biofilm: numerical simulations and laboratory experiments

In this paper we derive a pore-scale model for permeable biofilm formation in a two-dimensional pore. The pore is divided in two phases: water and biofilm. The biofilm is assumed to consist of four components: water, extracellular polymeric substances (EPS), active bacteria, and dead bacteria. The flow of water is modeled by the Stokes equation whereas a diffusion-convection equation is involved for the transport of nutrients. At the water/biofilm interface, nutrient transport and shear forces due to the water flux are considered. In the biofilm, the Brinkman equation for the water flow, transport of nutrients due to diffusion and convection, displacement of the biofilm components due to reproduction/dead of bacteria, and production of EPS are considered. A segregated finite element algorithm is used to solve the mathematical equations. Numerical simulations are performed based on experimentally determined parameters. The stress coefficient is fitted to the experimental data. To identify the critical model parameters, a sensitivity analysis is performed. The Sobol sensitivity indices of the input parameters are computed based on uniform perturbation by $\pm 10 \%$ of the nominal parameter values. The sensitivity analysis confirms that the variability or uncertainty in none of the parameters should be neglected.

physics.flu-dyn↗

arXiv2018

A Non-standard Model for Microbial Enhanced Oil Recovery Including the Oil-water Interfacial Area

In this work we present a non-standard model for microbial enhanced oil recovery including the oil-water interfacial area. Including the interfacial area in the model, we eliminate the hysteresis in the capillary pressure relationship. One of the characteristics that a surfactant should have, it is biological production at the oil-water interface. Therefore, we consider the production rate of surfactants not only as a function of the nutrient concentration, but also the interfacial area. To solve the model equations, we use an efficient and robust linearization scheme that considers a linear approximation of the capillary pressure gradient. A comprehensive, 1D implementation based on two-point flux approximation of the model is achieved. We consider different parameterizations for the interfacial tension and residual oil saturation reduction. Illustrative numerical simulations are presented, where we study the spatial distribution and evolution in time of the average pressure, water saturation, interfacial area, capillary pressure, residual oil saturation and bacterial, nutrient and surfactant concentrations. Inclusion of the interfacial area in the model leads to different predictions of oil recovery. The model can also be used to design new experiments contributing to a better understanding and optimization of MEOR.

physics.flu-dyn↗

arXiv2016

Modeling and simulation of microbial enhanced oil recovery including interfacial area

The focus of this paper is the derivation of a non-standard model for microbial enhanced oil recovery (MEOR) that includes the interfacial area (IFA) between the oil and water. We consider the continuity equations for water and oil, a balance equation for the oil-water interface and advective-dispersive transport equations for bacteria, nutrients and surfactants. Surfactants lower the interfacial tension (IFT), which improves the oil recovery. Therefore, we include in the model parameterizations of the IFT reduction and residual oil saturation as a function of the surfactant concentration. We consider for the first time in context of MEOR, the role of IFA in enhanced oil recovery (EOR). The motivation to include the IFA in the model is to reduce the hysteresis in the capillary pressure relationship, include the effects of observed bacteria migration towards the oil-water interface and biological production of surfactants at the oil-water interface. An efficient and robust linearization scheme was implemented, in which we use an implicit scheme that considers a linear approximation of the capillary pressure gradient, resulting in an efficient and stable scheme. A comprehensive, 2D implementation based on two-point flux approximation (TPFA) has been achieved. Illustrative numerical simulations are presented. We give an explanation of the differences in the oil recovery profiles obtained when we consider the IFA and MEOR effects. The model can also be used to design new experiments in order to gain a better understanding and optimization of MEOR.

physics.flu-dyn↗

arXiv2014

Features of a 2d Gauge Theory with Vanishing Chiral Condensate

The Schwinger model with $N_f \geq 2$ flavors is a simple example for a fermionic model with zero chiral condensate Sigma (in the chiral limit). We consider numerical data for two light flavors, based on simulations with dynamical chiral lattice fermions. We test properties and predictions that were put forward in the recent literature for models with Sigma = 0, which include IR conformal theories. In particular we probe the decorrelation of low lying Dirac eigenvalues, and we discuss the mass anomalous dimension and its IR extrapolation. Here we encounter subtleties, which may urge caution with analogous efforts in other models, such as multi-flavor QCD.

hep-lat↗

arXiv2013

Microscopic Dirac Spectrum in a 2d Gauge Theory with Zero Chiral Condensate

Fermionic theories with a vanishing chiral condensate (in the chiral limit) have recently attracted considerable interest; in particular variants of multi-flavour QCD are candidates for this behaviour. Here we consider the 2-flavour Schwinger model as a simple theory with this property. Based on simulations with light dynamical overlap fermions, we test the hypothesis that in such models the low lying Dirac eigenvalues could be decorrelated. That has been observed in 4d Yang-Mills theories at high temperature, but it cannot be confirmed for the 2-flavour Schwinger model. We also discuss subtleties in the evaluation of the mass anomalous dimension and its IR extrapolation.

hep-lat↗