Imperial College London

DrCarlJacquemyn

Faculty of EngineeringDepartment of Earth Science & Engineering

Research Fellow
 
 
 
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Contact

 

+44 (0)20 7594 7384c.jacquemyn Website CV

 
 
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Location

 

440/34Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

49 results found

Salinas P, Regnier G, Jacquemyn C, Pain CC, Jackson MDet al., 2021, Dynamic mesh optimisation for geothermal reservoir modelling, Geothermics, Vol: 94, 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

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, Pages: 1-1, 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

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

Jackson CA-L, Magee C, Jacquemyn C, 2020, Rift-related magmatism influences petroleum system development in the NE Irish Rockall Basin, offshore Ireland, PETROLEUM GEOSCIENCE, Vol: 26, Pages: 511-524, ISSN: 1354-0793

Journal article

Osman H, Graham GH, Moncorge A, Jacquemyn C, Jackson MDet 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.

Journal article

Zhang Z, Geiger S, Rood M, Jacquemyn C, Jackson M, Hampson G, De Carvalho FM, Silva CCMM, Silva JDM, Sousa MCet al., 2020, Fast flow computation methods on unstructured tetrahedral meshes for rapid reservoir modelling, Computational Geosciences, Vol: 24, Pages: 641-661, ISSN: 1420-0597

Subsurface reservoir models have a high degree of uncertainty regarding reservoir geometry and structure. A range of conceptual models should therefore be generated to explore how fluids-in-place, reservoir dynamics, and development decisions are affected by such uncertainty. The rapid reservoir modelling (RRM) workflow has been developed to prototype reservoir models across scales and test their dynamic behaviour. RRM complements existing workflows in that conceptual models can be prototyped, explored, compared, and ranked rapidly prior to detailed reservoir modelling. Reservoir geology is sketched in 2D with geological operators and translated in real-time into geologically correct 3D models. Flow diagnostics provide quantitative information for these reservoir model prototypes about their static and dynamic behaviours. A tracing algorithm is reviewed and implemented to compute time-of-flight and tracer concentrations efficiently on unstructured grids. Numerical well testing (NWT) is adopted in RRM to further interrogate the reservoir model. A new edge-based fast marching method is developed and implemented to solve the diffusive time-of-flight for approximating pressure transients efficiently on unstructured tetrahedral meshes. We demonstrate that an implementation of the workflow consisting of integrated sketch-based interface modelling, unstructured mesh generation, flow diagnostics, and numerical well testing is possible.

Journal article

Zhang Z, Geiger S, Rood M, Jacquemyn C, Jackson M, Hampson G, De Carvalho FM, Silva CCMM, Silva JDM, Sousa MCet al., 2020, Fast flow computation methods on unstructured tetrahedral meshes for rapid reservoir modelling, 16th European Conference on the Mathematics of Oil Recovery (ECMOR), Publisher: SPRINGER, Pages: 641-661, ISSN: 1420-0597

Conference paper

Salinas P, Pain C, Osman H, Jacquemyn C, Xie Z, Jackson Met al., 2020, Vanishing artifficial diffusion as a mechanism to accelerate convergence for multiphase porous media flow, Computer Methods in Applied Mechanics and Engineering, Vol: 359, Pages: 1-15, ISSN: 0045-7825

Numerical solution of the equations governing multiphase porous media flow is challenging. A common approach to improve the performance of iterative non-linear solvers for these problems is to introduce artificial diffusion. Here, we present a mass conservative artificial diffusion that accelerates the non-linear solver but vanishes when the solution is converged. The vanishing artificial diffusion term is saturation dependent and is larger in regions of the solution domain where there are steep saturation gradients. The non-linear solver converges more slowly in these regions because of the highly non-linear nature of the solution. The new method provides accurate results while significantly reducing the number of iterations required by the non-linear solver. It is particularly valuable in reducing the computational cost of highly challenging numerical simulations, such as those where physical capillary pressure effects are dominant. Moreover, the method allows converged solutions to be obtained for Courant numbers that are at least two orders of magnitude larger than would otherwise be possible.

Journal article

Titus Z, Pain C, Jacquemyn C, Salinas P, Heaney C, Jackson Met al., 2020, Conditioning surface-based geological models to well data using neural networks

Generating representative reservoir models that accurately describe the spatial distribution of geological heterogeneities is crucial for reliable predictions of historic and future reservoir performance. Surface-based geological models (SBGMs) have been shown to better capture complex reservoir architecture than grid-based methods; however, conditioning such models to well data can be challenging because it is an ill-posed inverse problem with spatially distributed parameters. Here, we propose the use of deep Convolutional Neural Networks (CNNs) to generate geologically plausible SBGMs that honour well data. Deep CNNs have previously demonstrated capability in learning representative features of spatially correlated data for large scale and highly non-linear geophysical systems similar to those encountered in subsurface reservoirs. In the work reported here, a CNN is trained to learn the relationship between parameterised inputs to SBGM, the resulting geometry and heterogeneity distribution, and the mis-match between model surfaces and well data. We show that the trained CNN can generate a range of geologically plausible models that honour well data. The method is demonstrated for a 2D example model, representing a shallow marine reservoir and a 3D extension of the model that captures typical heterogeneities encountered in the subsurface such as parasequences, clinoforms and facies boundaries. These test cases highlight the improvement in reservoir characterisation for realistic geological cases. We present here a method of generating geologically consistent reservoir models that match well data. The developed method will allow the generation of new high-fidelity realizations of subsurface geology conditioned to information at wells, which is the most direct observational data that can be acquired. Technical Contributions - The use of surface-based modelling to describe even complex geological features compared to grid-based modelling significantly decreases the co

Conference paper

Salinas P, Jacquemyn C, Heaney C, Pain C, Jackson Met al., 2020, Well location optimisation by using surface-based modelling and dynamic mesh optimisation

Predictions of production obtained by numerical simulation often depend on grid resolution as fine resolution is required to resolve key aspects of flow. Moreover, the controls on flow can depend on well location in a model. In some cases, it may be key to capture coning or cusping; in others, it might be the location of specific high permeability thief zones or low permeability flow barriers. Thus, models with a suitable grid resolution for one particular set of well locations may fail to properly capture key aspects of flow if the wells are moved. During well optimisation, it is impossible to predict a-priori which well locations will be tested in a given model. Thus, it is unlikely to know a-priori if the grid resolution is suitable for all possible locations tested during a well optimisation procedure on a single model, and the problem is even more profound if well optimisation is tested over a range of different models. Here, we report an optimisation methodology based on Dynamic Mesh Optimisation (DMO). DMO will produce optimised meshes for a given model, set of well locations, pressure (and other key fields) distribution and timelevel. Grid-free Surface-Based Modelling (SBM) models are automatically generated in which well trajectories are introduced (also not constrained by a mesh), respected by DMO. For the optimization of the well location a Genetic Algorithm (GA) approach is used, more specifically the open-source software package DEAP. DMO ensures that all the models automatically generated and simulated in the optimisation process are modelled with an equivalent mesh resolution without user interaction, in this way, the local pressure drawdown and associated physical effects (such as coning or cusping) can be properly captured if they appear in any of the many scenarios that are studied . We demonstrate that the method has wide application in reservoir-scale models of oil and gas fields, and regional models of groundwater resources.

Conference paper

Jacquemyn C, Jackson MD, Hampson GJ, 2019, Surface-based reservoir modelling: Automatic assembly for multiple stochastic realizations

© 81st EAGE Conference and Exhibition 2019. All rights reserved. Surface-based reservoir modelling for hydrocarbon or geothermal reservoirs is a modelling approach that represents subsurface heterogeneity by surfaces. All heterogeneity of interest is modelled only by its bounding surfaces, free from a predefined grid. This overcomes grid-related limitations of conventional modelling approaches such as stair-stepping, loss of connectivity or continuity and resolution limitations to capture small features that are essential to flow. Creating surface-based models relies on generating 100's of surfaces of different geometries, scales and relationships, all representing a boundary between volumes with different properties. We show how adding metadata to every surface enables automatic assembly of all these individual surfaces into a surface-based reservoir model. Metadata signifies why a surface exists and includes what properties are on either side of a surface, which volume it intersects and the level of detail it represents. Multiple model realisations can now be built automatically from stochastically generated bounding surfaces.

Conference paper

Jacquemyn C, Jackson MD, Hampson GJ, 2019, Surface-based reservoir modelling: Automatic assembly for multiple stochastic realizations

Surface-based reservoir modelling for hydrocarbon or geothermal reservoirs is a modelling approach that represents subsurface heterogeneity by surfaces. All heterogeneity of interest is modelled only by its bounding surfaces, free from a predefined grid. This overcomes grid-related limitations of conventional modelling approaches such as stair-stepping, loss of connectivity or continuity and resolution limitations to capture small features that are essential to flow. Creating surface-based models relies on generating 100's of surfaces of different geometries, scales and relationships, all representing a boundary between volumes with different properties. We show how adding metadata to every surface enables automatic assembly of all these individual surfaces into a surface-based reservoir model. Metadata signifies why a surface exists and includes what properties are on either side of a surface, which volume it intersects and the level of detail it represents. Multiple model realisations can now be built automatically from stochastically generated bounding surfaces.

Conference paper

Jacquemyn C, Jackson MD, Hampson GJ, 2019, Surface-based reservoir modelling: Automatic assembly for multiple stochastic realizations

© 81st EAGE Conference and Exhibition 2019. All rights reserved. Surface-based reservoir modelling for hydrocarbon or geothermal reservoirs is a modelling approach that represents subsurface heterogeneity by surfaces. All heterogeneity of interest is modelled only by its bounding surfaces, free from a predefined grid. This overcomes grid-related limitations of conventional modelling approaches such as stair-stepping, loss of connectivity or continuity and resolution limitations to capture small features that are essential to flow. Creating surface-based models relies on generating 100's of surfaces of different geometries, scales and relationships, all representing a boundary between volumes with different properties. We show how adding metadata to every surface enables automatic assembly of all these individual surfaces into a surface-based reservoir model. Metadata signifies why a surface exists and includes what properties are on either side of a surface, which volume it intersects and the level of detail it represents. Multiple model realisations can now be built automatically from stochastically generated bounding surfaces.

Conference paper

Jacquemyn C, Jackson MD, Hampson GJ, 2019, Surface-based geological reservoir modelling using grid-free NURBS curves and surfaces, Mathematical Geosciences, Vol: 51, Pages: 1-28, ISSN: 1874-8953

Building geometrically realistic representations of geological heterogeneity in reservoir models is a challenging task that is limited by the inflexibility of pre-defined pillar or cornerpoint grids. Surface-based modelling workflow uses grid-free surfaces that allows efficient creation of geological models without the limitations of pre-defined grids. Surface-based reservoir modelling uses a boundary representation approach in which all heterogeneity of interest (structural, stratigraphic, sedimentological, diagenetic) is modelled by its bounding surfaces, independent of any grid. Volumes bounded by these surfaces are internally homogeneous and thus no additional facies or petrophysical modelling is performed within these geological domains and no grid or mesh discretization is needed during modelling. Any heterogeneity to be modelled within such volumes is incorporated by adding surfaces. Surfaces and curves are modelled using a parametric NURBS (non-uniform rational B-splines) description. These surfaces are efficient to generate and manipulate, and allow fast creation of multiple realizations of geometrically realistic reservoir models. Multiple levels of surface hierarchy are introduced to allow modelling of all features of interest at the required level of detail; surfaces at one hierarchical level are constructed so as to truncate or conform to surfaces of a higher hierarchical level. This procedure requires joining, terminating and stacking of surfaces to ensure that models contain “watertight” surface-bounded volumes. NURBS curves are used to represent well trajectories accurately, including multi-laterals or side-tracks. Once all surfaces and wells have been generated, they are combined into a reservoir model that takes into account geological relationships between surfaces and preserves realistic geometries.

Journal article

Salinas P, Jacquemyn C, Kampitsis A, Via-Estrem L, Heaney C, Pain C, Jackson Met al., 2019, A parallel load-balancing reservoir simulator with dynamic mesh optimisation

The use of dynamic mesh optimization (DMO) for multiphase flow in porous have been proposed recently showing a very good potential to reduce the computational cost by placing the resolution where and when necessary. Nonetheless, further work needs to be done to prove its usability in very large domains where parallel computing with distributed memory, i.e. using MPI libraries, may be necessary. Here, we describe the methodology used to parallelize a multiphase porous media flow simulator in combination with DMO as well as study of its performance. Due to the peculiarities and complexities of the typical porous media simulations due to its high aspect ratios, we have included a fail-safe for parallel simulations with DMO that enhance the robustness and stability of the methods used to parallelize DMO in other fields (Navier-Stokes flows). The results show that DMO for parallel computing in multiphase porous media flows can perform very well, showing good scaling behaviour.

Conference paper

Salinas P, Jacquemyn C, Kampitsis A, Via-Estrem L, Heaney C, Pain C, Jackson Met al., 2019, A parallel load-balancing reservoir simulator with dynamic mesh optimisation

Copyright 2019, Society of Petroleum Engineers. The use of dynamic mesh optimization (DMO) for multiphase flow in porous have been proposed recently showing a very good potential to reduce the computational cost by placing the resolution where and when necessary. Nonetheless, further work needs to be done to prove its usability in very large domains where parallel computing with distributed memory, i.e. using MPI libraries, may be necessary. Here, we describe the methodology used to parallelize a multiphase porous media flow simulator in combination with DMO as well as study of its performance. Due to the peculiarities and complexities of the typical porous media simulations due to its high aspect ratios, we have included a fail-safe for parallel simulations with DMO that enhance the robustness and stability of the methods used to parallelize DMO in other fields (Navier-Stokes flows). The results show that DMO for parallel computing in multiphase porous media flows can perform very well, showing good scaling behaviour.

Conference paper

Salinas P, Jacquemyn C, Kampitsis A, Via-Estrem L, Heaney C, Pain C, Jackson Met al., 2019, A parallel load-balancing reservoir simulator with dynamic mesh optimisation

Copyright 2019, Society of Petroleum Engineers. The use of dynamic mesh optimization (DMO) for multiphase flow in porous have been proposed recently showing a very good potential to reduce the computational cost by placing the resolution where and when necessary. Nonetheless, further work needs to be done to prove its usability in very large domains where parallel computing with distributed memory, i.e. using MPI libraries, may be necessary. Here, we describe the methodology used to parallelize a multiphase porous media flow simulator in combination with DMO as well as study of its performance. Due to the peculiarities and complexities of the typical porous media simulations due to its high aspect ratios, we have included a fail-safe for parallel simulations with DMO that enhance the robustness and stability of the methods used to parallelize DMO in other fields (Navier-Stokes flows). The results show that DMO for parallel computing in multiphase porous media flows can perform very well, showing good scaling behaviour.

Conference paper

Salinas P, Jacquemyn C, Kampitsis A, Via-Estrem L, Heaney C, Pain C, Jackson Met al., 2019, A parallel load-balancing reservoir simulator with dynamic mesh optimisation

Copyright 2019, Society of Petroleum Engineers. The use of dynamic mesh optimization (DMO) for multiphase flow in porous have been proposed recently showing a very good potential to reduce the computational cost by placing the resolution where and when necessary. Nonetheless, further work needs to be done to prove its usability in very large domains where parallel computing with distributed memory, i.e. using MPI libraries, may be necessary. Here, we describe the methodology used to parallelize a multiphase porous media flow simulator in combination with DMO as well as study of its performance. Due to the peculiarities and complexities of the typical porous media simulations due to its high aspect ratios, we have included a fail-safe for parallel simulations with DMO that enhance the robustness and stability of the methods used to parallelize DMO in other fields (Navier-Stokes flows). The results show that DMO for parallel computing in multiphase porous media flows can perform very well, showing good scaling behaviour.

Conference paper

Onyenanu GI, Jacquemyn CEMM, Graham GH, Hampson GJ, Fitch PJR, Jackson MDet al., 2018, Geometry, distribution and fill of erosional scours in a heterolithic, distal lower shoreface sandstone reservoir analogue: Grassy Member, Blackhawk Formation, Book Cliffs, Utah, USA, Sedimentology, Vol: 65, Pages: 1731-1760, ISSN: 0037-0746

Many shoreface sandstone reservoirs host significant hydrocarbon volumes within distal intervals of interbedded sandstones and mudstones. Hydrocarbon production from these reservoir intervals depends on the abundance and proportion of sandstone beds that are connected by erosional scours, and on the lateral extent and continuity of interbedded mudstones. Cliff‐face exposures of the Campanian ‘G2’ parasequence, Grassy Member, Blackhawk Formation in the Book Cliffs of east‐central Utah, USA, allow detailed characterization of 128 erosional scours within such interbedded sandstones and mudstones in a volume of 148 m length, 94 m width and 15 m height. The erosional scours have depths of up to 1·1 m, apparent widths of up to 15·1 m and steep sides (up to 35°) that strike approximately perpendicular (N099 ± 36°) to the local north–south palaeoshoreline trend. The scours have limited lateral continuity along strike and down dip, and a relatively narrow range of apparent aspect ratio (apparent width/depth), implying that their three‐dimensional geometry is similar to non‐channelized pot casts. There is no systematic variation in scour dimensions, but ‘scour density’ is greater in amalgamated (conjoined) sandstone beds over 0·5 m thick, and increases upward within vertical successions of upward‐thickening conjoined sandstone beds. There is no apparent organization of the overall lateral distribution of scours, although localized clustering implies that some scours were re‐occupied during multiple erosional events. Scour occurrence is also associated with locally increased amplitude and laminaset thickness of hummocky cross‐stratification in sandstone beds. The geometry, distribution and infill character of the scours imply that they were formed by storm‐generated currents coincident with riverine sediment influx (‘storm floods’). The erosional scours increase the vertical and lateral connectivity

Journal article

Salinas P, Jacquemyn C, Heaney C, Pavlidis D, Pain C, Jackson Met al., 2018, Simulation of enhanced geothermal systems using dynamic unstructured mesh optimisation, EAGE annual conference and exhibition

Conference paper

Jacquemyn C, Rood M, Melnikova Y, Salinas P, Jackson M, Hampson Get al., 2018, My Geology Is Too Complex for My Grid: Grid-Free Surface-Based Geological Modelling, EAGE annual conference and exhibition

Conference paper

Jacquemyn C, Jackson MD, Hampson GJ, John CM, Cantrell DL, Zűhlke R, AbuBshait A, Lindsay RF, Monsen Ret al., 2018, Geometry, spatial arrangement and origin of carbonate grain-dominated, scour-fill and event-bed deposits: Late Jurassic Jubaila Formation and Arab-D Member, Saudi Arabia, Sedimentology, Vol: 65, Pages: 1043-1066, ISSN: 0037-0746

Journal article

Salinas P, Lei Q, Jacquemyn C, Pavlidis D, Xie Z, Pain C, Jackson Met al., 2018, DYNAMIC UNSTRUCTURED MESH ADAPTIVITY FOR IMPROVEDSIMULATION OF GEOTHERMAL WATER EXTRACTION INRESERVOIR-SCALE MODELS, 3rd Thermal and Fluids Engineering Conference

Conference paper

Jacquemyn C, Rood MP, Melnikova Y, Salinas P, Jackson MD, Hampson GJet al., 2018, My geology is too complex for my grid: Grid-free surface-based geological modelling

Building spatially realistic representations of heterogeneity in reservoir models is a challenging task that is limited by predefined pillar or cornerpoint grids. Diverse rock types are ‘averaged’ within grid cells of arbitrary size and shape; continuity of baffles, barriers or high-permeability streaks is often lost; large features are over-resolved and small features are under-resolved or omitted. We present a surface-based modelling workflow using grid-free surfaces that allows creation of geological models without the limitations of predefined grids. Surface-based modelling uses a boundary-representation approach, modelling all heterogeneity of interest by its bounding surfaces, independent of any grid. Surfaces are modelled using a NURBS description. These surfaces are efficient, and allow fast creation of multiple realizations of geometrically realistic reservoir models. Surfaces are constructed by (1) extruding a cross section along a plan-view trajectory, or (2) using geostatistical models. Surface metadata is created to allow automatic assembly of these individual surfaces into full reservoir models. We demonstrate this surface-based approach using common elements such as facies belts, clinoforms, channels and concretions, which are combined into reservoir models that preserve realistic geometries. This is applied to a coastal-plain and overlying shoreface succession, analogous to an upper Brent Group reservoir, North Sea (e.g. SPE10-model).

Conference paper

Salinas P, Jacquemyn C, Heaney C, Pavlidis D, Pain C, Jackson Met al., 2018, Simulation of enhanced geothermal systems using dynamic unstructured mesh optimisation

Recently, a novel method for heat extraction from geothermal reservoirs has been proposed, it is named radiator enhance geothermal system (RAD-EGS). In this method, the heat is extracted by placing two horizontal wells separated vertically, and injecting the cold water in the deepest one. Modelling a geothermal reservoir with wells can be very challenging as the scales to be considered can span several orders of magnitude. Around the wells (metres scale) it is well known that there is a high-pressure drawdown, while the dimensions of the reservoir are typically of many kilometres. Modelling across these scales using a fixed mesh can be computationally very expensive. Here, an unstructured dynamic mesh optimisation method is used to dynamically optimise the mesh to the fields of interest such as temperature and/or pressure to ensure that a certain precision across the domain is obtained. This methodology places the resolution where and when necessary, reducing the number of elements to ensure a certain accuracy when compared to an equivalent fixed mesh. Wells are represented using a 1D line which is represented by a line vector, whose position is not modified when adapting the mesh.

Conference paper

Jacquemyn C, Rood MP, Melnikova Y, Salinas P, Jackson MD, Hampson GJet al., 2018, My geology is too complex for my grid: Grid-free surface-based geological modelling

© 2018 Society of Petroleum Engineers. All rights reserved. Building spatially realistic representations of heterogeneity in reservoir models is a challenging task that is limited by predefined pillar or cornerpoint grids. Diverse rock types are ‘averaged’ within grid cells of arbitrary size and shape; continuity of baffles, barriers or high-permeability streaks is often lost; large features are over-resolved and small features are under-resolved or omitted. We present a surface-based modelling workflow using grid-free surfaces that allows creation of geological models without the limitations of predefined grids. Surface-based modelling uses a boundary-representation approach, modelling all heterogeneity of interest by its bounding surfaces, independent of any grid. Surfaces are modelled using a NURBS description. These surfaces are efficient, and allow fast creation of multiple realizations of geometrically realistic reservoir models. Surfaces are constructed by (1) extruding a cross section along a plan-view trajectory, or (2) using geostatistical models. Surface metadata is created to allow automatic assembly of these individual surfaces into full reservoir models. We demonstrate this surface-based approach using common elements such as facies belts, clinoforms, channels and concretions, which are combined into reservoir models that preserve realistic geometries. This is applied to a coastal-plain and overlying shoreface succession, analogous to an upper Brent Group reservoir, North Sea (e.g. SPE10-model).

Conference paper

Salinas P, Lei Q, Jacquemyn C, Pavlidis D, Xie Z, Pain CC, Jackson MDet al., 2018, Dynamic unstructured mesh adaptivity for improved simulation of geothermal water extraction in reservoir-scale models, Pages: 1245-1248

A novel method to simulate near-wellbore flow in geothermal reservoirs by using dynamic unstructured mesh optimisation and the Double Control Volume Finite Element method (DCVFEM) is presented. The mesh resolution is dynamically adapted to a field of interest, allowing to focus the mesh resolution only when and where it is required. Geology is represented by bounded surfaces whose petrophysical properties are constant within each of this surfaces. We demonstrate that the method has wide application in reservoir-scale models of geothermal fields, and regional models of groundwater resources.

Conference paper

Salinas P, Jacquemyn C, Heaney C, Pavlidis D, Pain C, Jackson Met al., 2018, Simulation of enhanced geothermal systems using dynamic unstructured mesh optimisation

© 2018 Society of Petroleum Engineers. All rights reserved. Recently, a novel method for heat extraction from geothermal reservoirs has been proposed, it is named radiator enhance geothermal system (RAD-EGS). In this method, the heat is extracted by placing two horizontal wells separated vertically, and injecting the cold water in the deepest one. Modelling a geothermal reservoir with wells can be very challenging as the scales to be considered can span several orders of magnitude. Around the wells (metres scale) it is well known that there is a high-pressure drawdown, while the dimensions of the reservoir are typically of many kilometres. Modelling across these scales using a fixed mesh can be computationally very expensive. Here, an unstructured dynamic mesh optimisation method is used to dynamically optimise the mesh to the fields of interest such as temperature and/or pressure to ensure that a certain precision across the domain is obtained. This methodology places the resolution where and when necessary, reducing the number of elements to ensure a certain accuracy when compared to an equivalent fixed mesh. Wells are represented using a 1D line which is represented by a line vector, whose position is not modified when adapting the mesh.

Conference paper

Salinas P, Pavlidis D, Jacquemyn C, Lei Q, Xie Z, Pain C, Jackson Met al., 2017, Simulation of geothermal water extraction in heterogeneous reservoirs using dynamic unstructured mesh optimisation, AGU FALL

Conference paper

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