Publications
153 results found
Jacquemyn C, Jackson MD, Hampson GJ, et al., 2024, Sketch-based geological modelling with flow diagnostics: the digital back-of-the-envelope for 3D geology and subsurface flow
<jats:p>Sketch-based geological modelling with flow diagnostics provides an interactive and intuitive prototyping approach to quickly build geomodels and generate quantitative results to evaluate volumetrics and flow behaviour. This approach allows users to rapidly test the sensitivity of model outputs to different geological concepts and uncertain parameters, and informs selection of geological concepts, scales and resolutions to be investigated in more detailed models. Here we apply the sketching and prototyping approach to different aspects of geo-energy modelling and use in geoscience and engineering training.Rapid Reservoir Modelling (RRM) is a free open-source sketch-based geological modelling tool with an intuitive interface that allows users to rapidly sketch geological models in 3D (bitbucket.org/rapidreservoirmodelling/rrm). Geological models that capture the essence of heterogeneity of interest and related uncertainty can be created within minutes. Geological operators ensure correct truncation relationships between these 3D surfaces by the modelling engine. Flow diagnostics then computes key indicators of predicted flow and storage behaviour within seconds. Example use cases and how models can be shared, will be discussed, including:(1) Scenario screening to identify heterogeneities with the most impact on CO2 storage. Capturing uncertainty in geological concepts cannot be achieved by changing a numerical variable but can be varied easily by sketching the different concepts, such as lateral connectivity, continuity and geometry of geological heterogeneities that act as flow barriers and pathways. Capturing multiple different concepts in conventional modelling approaches is time-consuming and in practice not often carried out.(2) Use of mini-models and hierarchical models to derive effective properties. Models with varying complexity of heterogeneity are sketched at smallest relevant scale, and effective properties are calculated. Calculated effecti
Stemmle R, Hanna R, Menberg K, et al., 2024, Policies for Aquifer Thermal Energy Storage (ATES)
<jats:p>Aquifer thermal energy storage (ATES) is a promising technology for sustainable and climate-friendly space heating and cooling. Compared to conventional heating and cooling techniques, ATES-based systems offer several benefits such as lower greenhouse gas emissions and reduced primary energy consumption. Despite these benefits and the availability of suitable aquifers in many places around the world, ATES has yet to see a widespread global utilization. Currently the vast majority of installed systems is located in the Netherlands, Belgium, Sweden and Denmark. Besides technical and hydrogeological feasibility, appropriate national policies driving ATES deployment are therefore of high importance. Hence, this study provides an international comparison of ATES policies, highlighting best practice examples and revealing where appropriate policy measures are missing. To this end, multi-disciplinary views from experts in geothermal energy and ATES from academia, companies, government authorities, national geological surveys and industrial associations in 30 countries were obtained through an online survey. Subsequent semi-structured interviews with a smaller selection of experts revealed further insights. The online survey results show significant differences regarding the existence and the strength of supporting policy elements between countries of different ATES market maturity. Going beyond these descriptive findings, the interviews provided more country-specific details on how favorable conditions came into effect and what obstacles have still to be overcome for an increased ATES deployment. Based on the lessons learned from the online survey and the expert interviews, recommendations for sophisticated ATES policies are derived which address the following areas: legislative and regulatory issues, raising awareness and expertise, the role of ATES in local energy transitions, and social engagement. This work aims at steering energy policy towards a wider i
Jacquemyn C, Jackson MD, 2024, Impact of aquifer properties, well spacing and vertical offsetting of warm and cool plumes on ATES systems.
<jats:p>Aquifer Thermal Energy Storage (ATES) can store and supply a high capacity of seasonal heating and cooling. Well-balanced and well-designed ATES systems provide a very efficient energy storage, up to around 70-90% and thereby play an important role in providing a sustainable, and low-carbon solution for heating and cooling. Factors affecting the efficiency and capacity of ATES deployments are mainly subsurface properties and related design decisions. We set up a framework to test the impact of a wide range subsurface and design parameters to deduce their impact on ATES system performance. Aquifer thickness, lateral permeability and permeability anisotropy are considered as main aquifer properties, and cool-warm well lateral spacing and vertical offsetting of cool and warm plumes as main design decisions. The thickness of the injection and production interval can be dictated by aquifer permeability variations and/or be chosen by varying screen length. &#160;The parameters listed above are combined into dimensionless numbers, such as effective aspect ratio of the system and effective lateral spacing of wells to summarize and group different aquifers and possible ATES deployment designs. For a wide range of effective aspect ratios and effective well spacing ATES system behaviour is predicted by flow simulation and key performance indicators computed, including thermal efficiency, CO2 savings, cool/warm plume sizes and stored energy density. The first two indicate the potential expected capacity of ATES systems. The latter provide recommendations for best use of land area, especially if multiple ATES systems are planned in areas with high concentration of cooling and heating demand. Given heating and cooling demand, specific aquifer conditions and land area available for use, the predicted behaviour metrics will help design optimal ATES deployments and show the potential for energy savings across multiple different settings.Results indicate that AT
Firth H, Jacquemyn C, Hampson G, et al., 2024, Impact of Aquifer Heterogeneity on LT-ATES Performance: A Case Study from the Chalk Aquifer, London, UK
<jats:p>The Chalk comprises a highly heterogeneous dual porosity aquifer, characterized by intervals of high permeability formed by fracturing and/or karstification of a low-permeability matrix. Many boreholes in London show evidence of a high-permeability flow zone at the top of the Chalk. Despite this, models used to predict ATES system operation in the Chalk aquifer in London have typically assumed a homogeneous aquifer, so that simulated warm and cold plumes have a simple cylindrical geometry around the wells. In this study, we investigate the impact of aquifer heterogeneity on system operation.We examine an operating LT-ATES installation. The system employs 4 cold wells and 4 warm wells and is sized to deliver peak heating of 1.8 MW and peak cooling of 2.75 MW. Analysis of flowrate and temperature data shows that the system has a well-balanced energy ratio of 0.09 and exhibits a low but increasing thermal recovery which is currently ca. 40% for warm storage and 25% for cold storage.We use a Surface-Based Modelling (SBM) approach to represent geological heterogeneity, which allows us to accurately and realistically capture geometrically complex subsurface features. We develop a range of parametrised 3D models of different geological scenarios, to capture uncertainty in geological heterogeneity between the wells. Flow and heat transport during ATES operation are simulated using the Imperial College Finite Element Reservoir Simulator (IC-FERST). The models are calibrated using Nelder-Mead methods to match pressure transient data and well inflow logs obtained from the boreholes prior to commissioning. Temperature and flowrate data collected during operation are subsequently employed in thermal simulations using the calibrated models.Our findings suggest that aquifer heterogeneity has a significant impact on the formation of the warm and cold plumes. Heterogeneity has resulted in a thermal recovery bias toward warm water, despite ambient aquifer temperature be
Bahlali M, Woitischek J, Jacquemyn C, et al., 2024, Integrated Modeling of Cu-Rich Fluid Migration and Mineralization in the Katangan Basin, Central African Copperbelt: Insights from Numerical Experiments
<jats:p>Sediment-hosted Cu deposits are a significant global source of copper. This study employs a mineral system approach, focusing on basin-scale groundwater flow as a key mechanism for Cu transport from source to trap. Numerical experiments using the open-source IC-FERST code investigate the controls on Cu transport in the Katangan Basin, Central African Copperbelt. The models developed for early and late stages of basin evolution incorporate fluid flow, heat and solute transport, and dynamic mesh optimization to enhance computational efficiency.The early-stage model, corresponding to the salt deposition period, attributes the formation of saline brine to a dense residual phase resulting from evaporite formation. In the late-stage model, corresponding to Cu mobilization and mineralization, Cu dissolution and mineralization are simulated using a partition coefficient informed by experimental data.Results reveal that density gradients induced by salinity and temperature variations play a crucial role in initiating convective groundwater flow. Highly saline, dense brines generated during salt deposition or dissolution form complex, downward-propagating plumes influenced by flow instabilities and geologic heterogeneity. Permeable faults and fractures in basement rocks enable groundwater to percolate, potentially mobilizing Cu from intra- or extra-basinal source rocks. Salinity and temperature gradients drive upwelling plumes, transporting Cu from deeper source rocks to shallower, organic-rich sedimentary rocks where mineralization occurs.</jats:p>
Jackson M, Regnier G, Staffell I, 2024, Prospects for Aquifer Thermal Energy Storage in the UK
<jats:p>Aquifer Thermal Energy Storage (ATES) is an underground thermal energy storage technology that provides large capacity (of order MWth to 10s MWth), low carbon heating and cooling to large buildings or complexes of buildings, or district heating/cooling networks.&#160; The technology operates through seasonal capture, storage and re-use of thermal energy in shallow aquifers, reducing carbon emissions and electricity demand for heating and cooling compared to direct ground- or air-sourced heat pump systems.We demonstrate that ATES could make a significant contribution to decarbonising UK heating and cooling, but uptake is currently very low.&#160; We identify eleven low temperature (LT-ATES) systems operating in the UK, with the first having been installed in 2006. These systems currently meet <0.01% of the UK&#8217;s heating and <0.5% of cooling demand.&#160; Despite the current low uptake, the UK has large potential for widespread deployment of LT-ATES, due to its seasonal climate and the wide availability of suitable aquifers which are co-located with urban centres of high heating and cooling demand.&#160; We use a probabilistic approach to estimate that ATES could supply approximately 64.5 % of current UK heating demand, and 80 % of cooling demand. &#160;A key barrier to increasing UK uptake is lack of awareness of the technology. &#160;We analyse the performance of a successful UK installation, and also report installations in which problems with design and operation have caused sub-optimal performance. &#160;The UK can benefit from experience of both successful and unsuccessful deployments but these need to be more widely reported.</jats:p>
Rowan TSL, Karantoni VA, Butler AP, et 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.
Collini H, Jackson MD, 2023, Zeta potential of crude oil in aqueous solution, ADVANCES IN COLLOID AND INTERFACE SCIENCE, Vol: 320, ISSN: 0001-8686
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.
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
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, 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
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- Citations: 1
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
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- Citations: 2
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
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
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- Citations: 3
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
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- Citations: 2
Alarouj M, Jackson MD, 2022, Numerical modeling of self-potential in heterogeneous reservoirs, GEOPHYSICS, Vol: 87, Pages: E103-E120, ISSN: 0016-8033
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- 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.
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
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
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- Citations: 4
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
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- Citations: 7
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.
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
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- Citations: 1
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
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- Citations: 2
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.
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
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- Citations: 2
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