Imperial College London

ProfessorMatthewJackson

Faculty of EngineeringDepartment of Earth Science & Engineering

Chair in Geological Fluid Dynamics
 
 
 
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Contact

 

+44 (0)20 7594 6538m.d.jackson

 
 
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Location

 

1.34Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

147 results found

Rowan TSL, Karantoni VA, Butler AP, Jackson MDet al., 2023, 3D-printed Ag–AgCl electrodes for laboratory measurements of self-potential, Geoscientific Instrumentation, Methods and Data Systems, Vol: 12, Pages: 259-270, ISSN: 2193-0856

This paper details the design, development, and evaluation of a 3D-printed rechargeable Ag–AgCl electrode to measure self-potential (SP) in laboratory experiments. The challenge was to make a small, cheap, robust, and stable electrode that could be used in a wide range of applications. The new electrodes are shown to offer comparable performance to custom-machined laboratory standards, and the inclusion of 3D printing (fused filament fabrication or FFF and stereolithography or SLA) makes them more versatile and significantly less expensive – of the order of × 40 to ×75 cost reduction – to construct than laboratory standards. The devices are demonstrated in both low-pressure experiments using bead packs and high-pressure experiments using natural rock samples. Designs are included for both male and female connections to laboratory equipment. We report design drawings, practical advice for electrode printing and assembly, and printable 3D design files to facilitate wide uptake.

Journal article

Collini H, Jackson MD, 2023, Zeta potential of crude oil in aqueous solution, ADVANCES IN COLLOID AND INTERFACE SCIENCE, Vol: 320, ISSN: 0001-8686

Journal article

Alshakri J, Hampson GJ, Jacquemyn C, Jackson MD, Petrovskyy D, Geiger S, Silva JDM, Judice S, Rahman F, Costa Sousa Met al., 2023, A screening assessment of the impact of sedimentological heterogeneity on CO2 migration and stratigraphic-baffling potential: Sherwood and Bunter Sandstones, UK, Enabling Secure Subsurface Storage in Future Energy Systems, Publisher: Geological Society of London, Pages: 245-266

We use a combination of experimental design, sketch-based reservoir modelling, and flow diagnostics to rapidly screen the impact of sedimentological heterogeneities that constitute baffles and barriers on CO2 migration in depleted hydrocarbon reservoirs and saline aquifers of the Sherwood Sandstone Group and Bunter Sandstone Formation, UK. These storage units consist of fluvial sandstones with subordinate aeolian sandstones, floodplain and sabkha heteroliths, and lacustrine mudstones. The predominant control on effective horizontal permeability is the lateral continuity of aeolian-sandstone intervals. Effective vertical permeability is controlled by the lateral extent, thickness and abundance of lacustrine-mudstone layers and aeolian-sandstone layers, and the mean lateral extent and mean vertical spacing of carbonate-cemented basal channel lags in fluvial facies-association layers. The baffling effect on CO2 migration and retention is approximated by the pore volume injected at breakthrough time, which is controlled largely by three heterogeneities, in order of decreasing impact: (1) the lateral continuity of aeolian-sandstone intervals; (2) the lateral extent of lacustrine-mudstone layers, and (3) the thickness and abundance of fluvial-sandstone, aeolian-sandstone, floodplain-and-sabkha-heterolith and lacustrine-mudstone layers. Future effort should be focussed on characterising these three heterogeneities as a precursor for later capillary, dissolution and mineral trapping.

Book chapter

Regnier G, Salinas P, Jackson MD, 2023, Predicting the risk of saltwater contamination of freshwater aquifers during aquifer thermal energy storage, HYDROGEOLOGY JOURNAL, Vol: 31, Pages: 1067-1082, ISSN: 1431-2174

Journal article

Petrovskyy D, Jacquemyn C, Geiger S, Jackson M, Hampson G, Machado Silva J, Judice S, Rahman F, Costa Sousa Met al., 2023, Rapid flow diagnostics for prototyping of reservoir concepts and models for subsurface CO2 storage, International Journal of Greenhouse Gas Control, Vol: 124, Pages: 1-16, ISSN: 1750-5836

Sketch-based interface and modelling is an approach to reservoir modelling that allows rapid and intuitive creation of 3D reservoir models to test and evaluate geological concepts and hypotheses and thus explore the impact of geological uncertainty on reservoir behaviour. A key advantage of such modelling is the quick creation and quantitative evaluation of reservoir model prototypes. Flow diagnostics capture key aspects of reservoir flow behaviour under simplified physical conditions that enable the rapid solution of the governing equations, and are essential for such quantitative evaluation. In this paper, we demonstrate a novel and highly efficient implementation of a flow diagnostics framework, illustrated with applications to geological storage of CO2. Our implementation permits ‘on-the-fly’ estimation of the key reservoir properties that control CO2 migration and storage during the active injection period when viscous forces dominate. The results substantially improve the efficiency of traditional reservoir modelling and simulation workflows by highlighting key reservoir uncertainties that need to be evaluated in subsequent full-physics reservoir simulations that account for the complex interplay of viscous, gravity, and capillary forces.The methods are implemented in the open-source Rapid Reservoir Modelling software, which includes a simple to use graphical user interface with no steep learning curve. We present proof-of-concept studies of the new flow diagnostics implementation to investigate the CO2 storage potential of sketched 3D models of shallow marine sandstone tongues and deep water slope channels.

Journal article

Al Kubaisy J, Salinas P, Jackson MD, 2023, A hybrid pressure approximation in the control volume finite element method for multiphase flow and transport in heterogeneous porous media, JOURNAL OF COMPUTATIONAL PHYSICS, Vol: 475, ISSN: 0021-9991

Journal article

Hu H, Jackson MD, Blundy J, 2022, Melting, Compaction and Reactive Flow: Controls on Melt Fraction and Composition Change in Crustal Mush Reservoirs, JOURNAL OF PETROLOGY, Vol: 63, ISSN: 0022-3530

Journal article

Jackson WA, Hampson GJ, Jacquemyn C, Jackson MD, Petrovskyy D, Geiger S, Machado Silva JD, Judice S, Rahman F, Costa Sousa Met al., 2022, A screening assessment of the impact of sedimentological heterogeneity on CO2 migration and stratigraphic-baffling potential: Johansen and Cook formations, Northern Lights project, offshore Norway, International Journal of Greenhouse Gas Control, Vol: 120, Pages: 1-23, ISSN: 1750-5836

We use a method combining experimental design, sketch-based reservoir modelling, and single-phase flow diagnostics to rapidly screen the impact of sedimentological heterogeneities that constitute baffles and barriers to CO2 migration in the Johansen and Cook formations at the Northern Lights CO2 storage site. The types and spatial organisation of sedimentological heterogeneities in the wave-dominated deltaic sandstones of the Johansen-Cook storage unit are constrained using core data from the 31/5-7 (Eos) well, previous interpretations of seismic data and regional well-log correlations, and outcrop and subsurface analogues. Delta planform geometry, clinoform dip, and facies-association interfingering extent along clinoforms control: (1) the distribution and connectivity of high-permeability medial and proximal delta-front sandstones, (2) effective horizontal and vertical permeability characteristics of the storage unit, and (3) pore volumes injected at breakthrough time (which approximates the efficiency of stratigraphic baffling). In addition, the lateral continuity of carbonate-cemented concretionary layers along transgressive surfaces impacts effective vertical permeability, and bioturbation intensity impacts effective horizontal and vertical permeability. The combined effects of these and other heterogeneities are also influential. Our results suggest that the baffling effect on CO2 migration and retention of sedimentological heterogeneity is an important precursor for later capillary, dissolution and mineral trapping.

Journal article

Alarouj M, Jackson MD, 2022, Experimental measurement of the exclusion-diffusion potential in sandstone and shaly sand samples at full and partial water saturation, GEOPHYSICS, Vol: 87, Pages: M235-M246, ISSN: 0016-8033

Journal article

Bahlali ML, Salinas P, Jackson MD, 2022, Efficient Numerical Simulation of Density-Driven Flows: Application to the 2-and 3-D Elder Problem, WATER RESOURCES RESEARCH, Vol: 58, ISSN: 0043-1397

Journal article

Regnier G, Salinas P, Jacquemyn C, Jackson MDet al., 2022, Numerical simulation of aquifer thermal energy storage using surface-based geologic modelling and dynamic mesh optimisation, HYDROGEOLOGY JOURNAL, Vol: 30, Pages: 1179-1198, ISSN: 1431-2174

Journal article

Hamzehloo A, Bahlali ML, Salinas P, Jacquemyn C, Pain CC, Butler AP, Jackson MDet al., 2022, Modelling saline intrusion using dynamic mesh optimization with parallel processing, ADVANCES IN WATER RESOURCES, Vol: 164, ISSN: 0309-1708

Journal article

Alarouj M, Jackson MD, 2022, Numerical modeling of self-potential in heterogeneous reservoirs, GEOPHYSICS, Vol: 87, Pages: E103-E120, ISSN: 0016-8033

Journal article

Collini H, Jackson MD, 2022, Relationship between zeta potential and wettability in porous media: insights from a simple bundle of capillary tubes model, Journal of Colloid and Interface Science, Vol: 608, Pages: 605-621, ISSN: 0021-9797

Hypothesis & MotivationExperimental data suggest a relationship between the macroscopic zeta potential measured on intact rock samples and the sample wettability. However, there is no pore-scale model to quantify this relationship.MethodsWe consider the simplest representation of a rock pore space: a bundle of capillary tubes of varying size. Equations describing mass and charge transfer through a single capillary are derived and the macroscopic zeta potential and wettability determined by integrating over capillaries. Model predictions are tested against measured data yielding a good match.FindingsMixed- and oil-wet models return a macro-scale zeta potential that is a combination of the micro-scale zeta potential of mineral-brine and oil-brine interfaces and the relationship between macro-scale zeta potential and water saturation exhibits hysteresis. The model predicts a similar relationship between zeta potential and wettability to that observed in experimental data but does not provide a perfect match. Fitting the model to experimental data allows the oil-brine zeta potential to be estimated at conditions where it cannot be measured directly. Results suggest that positive values of the oil-brine zeta potential may be more common than previously thought with implications for surface complexation models and the design of controlled salinity waterflooding of oil reservoirs.

Journal article

Silva V, Regnier G, Salinas P, Heaney C, Jackson M, Pain Cet al., 2022, Rapid modelling of reactive transport in porous media using machine learning

Reactive transport in porous media can play an important role in a variety of processes in subsurface reservoirs, such as groundwater flow, geothermal heat production, oil recovery and CO2 storage. However, numerical solution of fluid flow in porous media coupled with chemical reaction is very computationally demanding. Simultaneously, the success of machine learning in different fields has opened up new possibilities in reactive transport simulations. In this project, we focus on using machine learning techniques to replace the geochemical kinetic calculations generated by PHREEQC. PHREEQC is an open-source aqueous geochemical code that can be used in stand-alone mode or as a reaction module coupled with a flow and transport simulator. Here, we apply machine learning approaches to produce a fast proxy model of PHREEQC. This enables us to have a coupling between transport and reaction while minimizing the added computational cost. We focus initially on calcite dissolution during CO2 sequestration. Different machine learning techniques are investigated and compared to see which is more appropriate for the calcite dissolution problem. The proposed machine learning approach is designed to deal with different time-step sizes and unstructured elements. It accelerates the numerical simulation and proves to be practical to replace the reaction model presented in PHREEQC. This considerably reduces the computational cost of reactive transport while ensuring excellent simulation accuracy. The rapid modelling of reactive transport in porous media has a broad potential to replace many other phase equilibrium models across a wide range of reactive transport problems.

Conference paper

Al Kubaisy J, Salinas P, Jackson MD, 2022, Hybrid finite element pressure approximation for multiphase flow and transport in highly heterogeneous porous media

Control volume finite element (CVFE) methods are commonly used for modeling flow and transport in geometrically complex porous media domains with unstructured meshes. The CVFE approach is based on the finite element method to approximate the pressure and velocity fields, and uses the finite volume method to model saturation ensuring mass conservation. Control volumes are constructed by spanning element boundaries, leading to an artificial smearing of the numerical solution in the presence of sharp material interfaces. Recently, a CVFE method based on discontinuous pressure was introduced that enabled the construction of discontinuous control volumes, thus preventing control volumes from spanning element boundaries. This modification of the method provides accurate solutions but is computationally very expensive due to the discontinuous approximation which incorporates additional degrees of freedom per element. In this work, we propose using hybrid finite element pressure approximations to capture flow and transport in highly heterogeneous porous media. The CVFE element pair $P_{0,DG}-P_{1,H}$ denotes a constant, element-wise, discontinuous Galerkin velocity vector approximation and a hybrid (continuous/discontinuous) Galerkin first-order pressure scalar approximation of the flow model. The method exploits the efficient continuous CVFE method in most of the model domain while the discontinuous CVFE approach is applied exclusively along material discontinuities. We demonstrate that this hybrid scheme outperforms the classical CVFE continuous approach as well as the discontinuous Galerkin modification by incorporating the best of both approaches. The presented hybrid approach computational requirements are comparable to the continuous approach while the accuracy of the transport solution corresponds to that of the discontinuous pressure method. We validate the presented hybrid approach and discuss the convergence of the method. The effectiveness of the new scheme is de

Conference paper

Sparks RSJ, Blundy JD, Cashman K, Jackson M, Rust A, Wilson CJNet al., 2022, Large silicic magma bodies and very large magnitude explosive eruptions, BULLETIN OF VOLCANOLOGY, Vol: 84, ISSN: 0258-8900

Journal article

Alarouj M, Collini H, Jackson MD, 2021, Positive Zeta Potential in Sandstones Saturated With Natural Saline Brine, GEOPHYSICAL RESEARCH LETTERS, Vol: 48, ISSN: 0094-8276

Journal article

Silva VLS, Salinas P, Jackson MD, Pain CCet al., 2021, Machine learning acceleration for nonlinear solvers applied to multiphase porous media flow, Computer Methods in Applied Mechanics and Engineering, Vol: 384, Pages: 1-17, ISSN: 0045-7825

A machine learning approach to accelerate convergence of the nonlinear solver in multiphase flow problems is presented here. The approach dynamically controls an acceleration method based on numerical relaxation. It is demonstrated in a Picard iterative solver but is applicable to other types of nonlinear solvers. The aim of the machine learning acceleration is to reduce the computational cost of the nonlinear solver by adjusting to the complexity/physics of the system. Using dimensionless parameters to train and control the machine learning enables the use of a simple two-dimensional layered reservoir for training, while also exploring a wide range of the parameter space. Hence, the training process is simplified and it does not need to be rerun when the machine learning acceleration is applied to other reservoir models. We show that the method can significantly reduce the number of nonlinear iterations without compromising the simulation results, including models that are considerably more complex than the training case.

Journal article

Kampitsis AE, Kostorz WJ, Muggeridge AH, Jackson MDet al., 2021, The life span and dynamics of immiscible viscous fingering in rectilinear displacements (vol 33, 096608, 2021), PHYSICS OF FLUIDS, Vol: 33, ISSN: 1070-6631

Journal article

Titus Z, Heaney C, Jacquemyn C, Salinas P, Jackson MD, Pain Cet al., 2021, Conditioning surface-based geological models to well data using artificial neural networks, Computational Geosciences: modeling, simulation and data analysis, Vol: 26, Pages: 779-802, ISSN: 1420-0597

Surface-based modelling provides a computationally efficient approach for generating geometrically realistic representations of heterogeneity in reservoir models. However, conditioning Surface-Based Geological Models (SBGMs) to well data can be challenging because it is an ill-posed inverse problem with spatially distributed parameters. To aid fast and efficient conditioning, we use here SBGMs that model geometries using parametric, grid-free surfaces that require few parameters to represent even realistic geological architectures. A neural network is trained to learn the underlying process of generating SBGMs by learning the relationship between the parametrized SBGM inputs and the resulting facies identified at well locations. To condition the SBGM to these observed data, inverse modelling of the SBGM inputs is achieved by replacing the forward model with the pre-trained neural network and optimizing the network inputs using the back-propagation technique applied in training the neural network. An analysis of the uncertainties associated with the conditioned realisations demonstrates the applicability of the approach for evaluating spatial variations in geological heterogeneity away from control data in reservoir modelling. This approach for generating geologically plausible models that are calibrated with observed well data could also be extended to other geological modelling techniques such as object- and process-based modelling.

Journal article

Kampitsis AE, Kostorz WJ, Muggeridge AH, Jackson MDet al., 2021, The life span and dynamics of immiscible viscous fingering in rectilinear displacements, PHYSICS OF FLUIDS, Vol: 33, ISSN: 1070-6631

Journal article

Salinas P, Regnier G, Jacquemyn C, Pain CC, Jackson MDet al., 2021, Dynamic mesh optimisation for geothermal reservoir modelling, Geothermics, Vol: 94, Pages: 1-13, ISSN: 0375-6505

Modelling geothermal reservoirs is challenging due to the large domain and wide range of length- and time-scales of interest. Attempting to represent all scales using a fixed computational mesh can be very computationally expensive. Application of dynamic mesh optimisation in other fields of computational fluid dynamics has revolutionised the accuracy and cost of numerical simulations. Here we present a new approach for modelling geothermal reservoirs based on unstructured meshes with dynamic mesh optimisation. The resolution of the mesh varies during a simulation, to minimize an error metric for solution fields of interest such as temperature and pressure. Efficient application of dynamic mesh optimisation in complex subsurface reservoirs requires a new approach to represent geologic heterogeneity and we use parametric spline surfaces to represent key geological features such as faults and lithology boundaries. The resulting 3D surface-based models are mesh free; a mesh is created only when required for numerical computations. Dynamic mesh optimisation preserves the surfaces and hence geologic heterogeneity. The governing equations are discretised using a double control volume finite element method that ensures heat and mass are conserved and provides robust solutions on distorted meshes. We apply the new method to a series of test cases that model sedimentary geothermal reservoirs. We demonstrate that dynamic mesh optimisation yields significant performance gains, reducing run times by up to 8 times whilst capturing flow and heat transport with the same accuracy as fixed meshes.

Journal article

Kostorz WJ, Muggeridge AH, Jackson MD, 2021, Non-intrusive reduced order modeling: Geometrical framework, high-order models, and a priori analysis of applicability, INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Vol: 122, Pages: 2545-2565, ISSN: 0029-5981

Journal article

Lyu Z, Lei Q, Yang L, Heaney C, Song X, Salinas P, Jackson M, Li G, Pain Cet al., 2021, A novel approach to optimising well trajectory in heterogeneous reservoirs based on the fast-marching method, Journal of Natural Gas Science and Engineering, Vol: 88, Pages: 1-12, ISSN: 1875-5100

To achieve efficient recovery of subsurface energy resources, a suitable trajectory needs to be identified for the production well. In this study, a new approach is presented for automated identification of optimum well trajectories in heterogeneous oil/gas reservoirs. The optimisation procedures are as follows. First, a productivity potential map is generated based on the site characterisation data of a reservoir (when available). Second, based on the fast-marching method, well paths are generated from a number of entrance positions to a number of exit points at opposite sides of the reservoir. The well trajectory is also locally constrained by a prescribed maximum curvature to ensure that the well trajectory is drillable. Finally, the optimum well trajectory is selected from all the candidate paths based on the calculation of a benefit-to-cost ratio. If required, a straight directional well path, may also be derived through a linear approximation to the optimised non-linear trajectory by least squares analysis. Model performance has been demonstrated in both 2D and 3D. In the 2D example, the benefit-to-cost ratio of the optimised well is much higher than that of a straight well; in the 3D example, laterals of various curvatures are generated. The applicability of the method is tested by exploring different reservoir heterogeneities and curvature constraints. This approach can be applied to determine the entrance/exit positions and the well path for subsurface energy system development, which is useful for field applications.

Journal article

Jacquemyn C, Pataki MEH, Hampson GJ, Jackson MD, Petrovskyy D, Geiger S, Marques CC, Machado Silva JD, Judice S, Rahman F, Costa Sousa Met al., 2021, Sketch-based interface and modelling of stratigraphy and structure in three dimensions, Journal of the Geological Society, Vol: 178, Pages: 1-17, ISSN: 0016-7649

Geological modelling is widely used to predict resource potential in subsurface reservoirs. However, modelling is often slow, requires use of mathematical methods that are unfamiliar to many geoscientists, and is implemented in expert software. We demonstrate here an alternative approach using sketch-based interface and modelling, which allows rapid creation of complex three-dimensional (3D) models from 2D sketches. Sketches, either on vertical cross-sections or in map-view, are converted to 3D surfaces that outline geological interpretations. We propose a suite of geological operators that handle interactions between the surfaces to form a geologically realistic 3D model. These operators deliver the flexibility to sketch a geological model in any order and provide an intuitive framework for geoscientists to rapidly create 3D models. Two case studies are presented, demonstrating scenarios in which different approaches to model sketching are used depending on the geological setting and available data. These case studies show the strengths of sketching with geological operators. Sketched 3D models can be queried visually or quantitatively to provide insights into heterogeneity distribution, facies connectivity or dynamic model behaviour; this information cannot be obtained by sketching in 2D or on paper.

Journal article

Alarouj M, Ijioma A, Graham MT, MacAllister DJ, Jackson MDet al., 2021, Numerical modelling of self-potential in subsurface reservoirs, Computers & Geosciences, Vol: 146, Pages: 1-19, ISSN: 0098-3004

We report a new, open-source, MATLAB-based 3D code for numerically simulating the self-potential (SP) in subsurface reservoirs. The code works as a post-processor, using outputs from existing reservoir flow and transport simulators at a selected timestep to calculate the SP throughout the reservoir model. The material properties required to calculate the SP are user defined and may be constant or vary in each cell. The code solves the equations governing flow and transport of electrical charge and global charge conservation using a control-volume-finite-difference scheme. Electrical currents associated with the SP may spread beyond the reservoir model domain, and the code allows for the domain to be extended vertically and laterally to account for this. Here, we present the governing equations and the numerical method used and demonstrate application of the code using an example in which we predict the SP signals associated with oil production from a subsurface reservoir supported by water injection.

Journal article

Costa Sousa M, Silva J, Silva C, De Carvalho F, Judice S, Rahman F, Jacquemyn C, Pataki M, Hampson G, Jackson M, Petrovskyy D, Geiger Set al., 2020, Smart modelling of geologic stratigraphy concepts using sketches, Smart Tools and Applications in computer Graphics (STAG) 2020, Publisher: The Eurographics Association, Pages: 89-100

Several applications of Earth Science require geologically valid interpretation and visualization of complex physical structures in data-poor subsurface environments. Hand-drawn sketches and illustrations are standard practices used by domain experts for conceptualizing their observations and interpretations. These conceptual geo-sketches provide rich visual references for exploring uncertainties and helping users formulate ideas, suggest possible solutions, and make critical decisions affecting the various stages in geoscience studies and modelling workflows. In this paper, we present a sketch-based interfaces and modelling (SBIM) approach for the rapid conceptual construction of stratigraphic surfaces, which are common to most geologic modelling scales, studies, and workflows. Our SBIM approach mirrors the way domain users produce geo-sketches and uses them to construct 3D geologic models, enforcing algorithmic rules to ensure geologically-sound stratigraphic relationships are generated, and supporting different scales of geology being observed and interpreted. Results are presented for two case studies demonstrating the flexibility and broad applicability of our rule-based SBIM approach for conceptual stratigraphy.

Conference paper

Yekta A, Salinas P, Hajirezaie S, Amooie MA, Pain CC, Jackson MD, Jacquemyn C, Soltanian MRet al., 2020, Reactive transport modeling in heterogeneous porous media with dynamic mesh optimization, Computational Geosciences: modeling, simulation and data analysis, Vol: 25, Pages: 357-372, ISSN: 1420-0597

This paper presents a numerical simulator for solving compositional multiphase flow and reactive transport. The simulator was developed by effectively linking IC-FERST (Imperial College Finite Element Reservoir SimulaTor) with PHREEQCRM. IC-FERST is a next-generation three-dimensional reservoir simulator based on the double control volume finite element method and dynamic unstructured mesh optimization and is developed by the Imperial College London. PHREEQCRM is a state-of-the-art geochemical reaction package and is developed by the United States Geological Survey. We present a step-by-step framework on how the coupling is performed. The coupled code is called IC-FERST-REACT and is capable of simulating complex hydrogeological, biological, chemical, and mechanical processes occurring including processes occur during CO2 geological sequestration, CO2 enhanced oil recovery, and geothermal systems among others. In this paper, we present our preliminary work as well as examples related to CO2 geological sequestration. We performed the model coupling through developing an efficient application programming interface (API). IC-FERST-REACT inherits high-order methods and unstructured meshes with dynamic mesh optimization from IC-FERST. This reduces the computational cost by placing the mesh resolution where and when necessary and it can better capture flow instabilities if they occur. This can have a strong impact on reactive transport simulations which usually suffer from computational cost. From PHREEQCRM the code inherits the ability to efficiently model geochemical reactions. Benchmark examples are used to show the capability of IC-FERST-REACT in solving multiphase flow and reactive transport.

Journal article

Kostorz WJ, Muggeridge AH, Jackson MD, 2020, An efficient and robust method for parameterized nonintrusive reduced-order modeling, INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Vol: 121, Pages: 4674-4688, ISSN: 0029-5981

Journal article

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