Publications
146 results found
Alshakri J, Hampson GJ, Jacquemyn C, et 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.
Collini H, Jackson MD, 2023, Zeta potential of crude oil in aqueous solution., Adv Colloid Interface Sci, Vol: 320
Despite the broad range of interest and applications, controls on the surface charge of crude oil in aqueous solution remain poorly understood. The primary data source to understand the surface charge on crude oil comprises measurements of zeta potential on individual drops or emulsions obtained using the electrophoretic method (EPM). Here we (i) collate and review previous measurements of zeta potential on crude oil, (ii) compare and contrast the results, and (iii) report new measurements of zeta potential on crude oil wetting films and layers relevant to oil-saturated porous media, obtained using the streaming potential method (SPM). Results show that the zeta potential depends on electrolyte pH and the concentration of divalent ions Ca2+ and Mg2+. Lower pH and higher concentration of these divalent ions yields more positive zeta potential. The isoelectric point (IEP) in simple NaCl electrolytes lies in the pH range 3-5. The IEP in simple CaCl2 and MgCl2 electrolytes can be expressed as pCa or pMg, respectively, and lies in the range 0-1. Close to the IEP, the zeta potential varies linearly with pH, pCa or pMg, suggesting simple Nernstian behaviour of the crude oil surface. The sensitivity of the zeta potential to pH, pCa and pMg decreases with increasing total ionic strength. The impact of pH, pCa and pMg on zeta potential varies significantly across different crude oils and differs from non-polar hydrocarbons. The potential for other multivalent ions to modify crude oil zeta potential has not been tested. Data for crude oil wetting films and layers, obtained using the SPM and strongly oil-wet porous substrates in which the solid surfaces are coated with the crude oil of interest, are comparable to those obtained using emulsions and the EPM, suggesting that the controls on zeta potential on crude oil are the same irrespective of whether the oil forms droplets or wetting layers. The literature data reviewed here, along with new measured data, provide important ins
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
Aquifer thermal energy storage (ATES) is an underground thermal energy storage technology with a large potential to decarbonise the heating and cooling of buildings. ATES installations typically store thermal energy in aquifers that are also exploited for potable water, so a major consideration during development is ensuring that system operation will not lead to groundwater pollution. In this study, the risk of contamination due to upconing of a shallow freshwater/saltwater interface during ATES operation is investigated. Fluid flow, and heat and salt (chloride ion) transport are simulated in a homogeneous aquifer during ATES operation via a well doublet. The impact of geological, hydrological and operational parameters is investigated in a sensitivity analysis. Two new dimensionless numbers are proposed to characterise salt upconing and redistribution during ATES operation and provide a close match to simulated concentrations: CR,w characterises the contamination risk at the ATES installation, and CR,d characterises the risk at locations downstream of the ATES installation with respect to background groundwater flow. ATES systems with CR,w and CR,d < 10 introduce low risk of contamination in a homogenous aquifer, with chloride concentration at, and downstream of, the ATES system, remaining below the World Health Organisation’s advised limit. ATES installations with CR,w and CR,d > 10 cause a rapid increase in aquifer chloride concentration. The results are used to estimate an exclusion distance beyond which ATES system operation will not cause contamination in a homogenous aquifer. The dimensionless parameters proposed allow rapid assessment of the potential for saltwater contamination during ATES operation.
Petrovskyy D, Jacquemyn C, Geiger S, et 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.
Al Kubaisy J, Salinas P, Jackson MD, 2022, 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
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
Jackson WA, Hampson GJ, Jacquemyn C, et 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.
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
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
Hamzehloo A, Bahlali ML, Salinas P, et al., 2022, Modelling saline intrusion using dynamic mesh optimization with parallel processing, ADVANCES IN WATER RESOURCES, Vol: 164, ISSN: 0309-1708
Regnier G, Salinas P, Jacquemyn C, et 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
Alarouj M, Jackson MD, 2022, Numerical modeling of self-potential in heterogeneous reservoirs, GEOPHYSICS, Vol: 87, Pages: E103-E120, ISSN: 0016-8033
- Author Web Link
- Cite
- Citations: 1
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.
Sparks RSJ, Blundy JD, Cashman K, et al., 2022, Large silicic magma bodies and very large magnitude explosive eruptions, BULLETIN OF VOLCANOLOGY, Vol: 84, ISSN: 0258-8900
- Author Web Link
- Cite
- Citations: 1
Silva V, Regnier G, Salinas P, et 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.
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
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
- Author Web Link
- Cite
- Citations: 4
Kampitsis AE, Kostorz WJ, Muggeridge AH, et 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
- Author Web Link
- Cite
- Citations: 1
Silva VLS, Salinas P, Jackson MD, et 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.
Titus Z, Heaney C, Jacquemyn C, et 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.
Kampitsis AE, Kostorz WJ, Muggeridge AH, et al., 2021, The life span and dynamics of immiscible viscous fingering in rectilinear displacements, PHYSICS OF FLUIDS, Vol: 33, ISSN: 1070-6631
- Author Web Link
- Cite
- Citations: 1
Salinas P, Regnier G, Jacquemyn C, et 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.
Lyu Z, Lei Q, Yang L, et 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.
Jacquemyn C, Pataki MEH, Hampson GJ, et 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.
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
- Author Web Link
- Cite
- Citations: 2
Alarouj M, Ijioma A, Graham MT, et 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.
Costa Sousa M, Silva J, Silva C, et 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.
Yekta A, Salinas P, Hajirezaie S, et 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.
Li S, Jackson MD, Agenet N, 2020, Role of the calcite-water interface in wettability alteration during low salinity waterflooding, FUEL, Vol: 276, ISSN: 0016-2361
- Author Web Link
- Cite
- Citations: 12
Osman H, Graham GH, Moncorge A, et al., 2020, Is cell-to-cell scale variability necessary in reservoir models?, Mathematical Geosciences, Vol: 53, Pages: 271-296, ISSN: 1573-8868
Reservoir models typically contain hundreds-of-thousands to millions of grid cells in which petrophysical properties such as porosity and permeability vary on a cell-to-cell basis. However, although the petrophysical properties of rocks do vary on a point-to-point basis, this variability is not equivalent to the cell-to-cell variations in models. We investigate the impact of removing cell-to-cell variability on predictions of fluid flow in reservoir models. We remove cell-to-cell variability from models containing hundreds of thousands of unique porosity and permeability values to yield models containing just a few tens of unique porosity and permeability values grouped into a few internally homogeneous domains. The flow behavior of the original model is used as a reference. We find that the impact of cell-to-cell variability on predicted flow is small. Cell-to-cell variability is not necessary to capture flow in reservoir models; rather, it is the spatially correlated variability in petrophysical properties that is important. Reservoir modelling effort should focus on capturing correlated geologic domains in the most realistic and computationally efficient manner.
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.