Publications
96 results found
Titus Z, Pain C, Jacquemyn C, et 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
Osman H, Salinas P, Pain C, et al., 2019, An enriched control volume finite element method for multi-phase flow in porous media on challenging meshes
We introduce a new, efficient control volume finite element method that improves the modelling of multi-phase flow in heterogeneous porous media. The method uses discontinuous piecewise linear functions enriched with bubble functions for velocity and discontinuous piecewise linear functions for pressure evaluated on control volumes (CVs). LBB stability is maintained with a very efficient velocity:pressure degrees of freedom ratio of 1.25 on tetrahedral meshes. Classical CVFE methods on the other hand may reach a ratio of 5. The method does not require CVs to span element boundaries and as a result is able to accurately preserve saturation discontinuities across material boundaries. Finally, the use of control volume representation for pressure yields significant improvements in stability of the method on challenging meshes.
Osman H, Salinas P, Pain C, et al., 2019, An Enriched Control Volume Finite Element Method for Multi-Phase Flow in Porous Media on Challenging Meshes, EAGE annual
Osman H, Salinas P, Pain C, et al., 2019, An enriched control volume finite element method for multi-phase flow in porous media on challenging meshes
© 81st EAGE Conference and Exhibition 2019. All rights reserved. We introduce a new, efficient control volume finite element method that improves the modelling of multi-phase flow in heterogeneous porous media. The method uses discontinuous piecewise linear functions enriched with bubble functions for velocity and discontinuous piecewise linear functions for pressure evaluated on control volumes (CVs). LBB stability is maintained with a very efficient velocity:pressure degrees of freedom ratio of 1.25 on tetrahedral meshes. Classical CVFE methods on the other hand may reach a ratio of 5. The method does not require CVs to span element boundaries and as a result is able to accurately preserve saturation discontinuities across material boundaries. Finally, the use of control volume representation for pressure yields significant improvements in stability of the method on challenging meshes.
Osman H, Salinas P, Pain C, et al., 2019, An efficient control volume finite element method for multi-phase flow in fractured porous media, Interpore 2019
Obeysekara A, Salinas P, Xiang J, et al., 2019, Numerical Modelling of Coupled Flow and Fluid-Driven Fracturing in Fractured Porous Media using the Immersed Body Method, Interpore 2019
Salinas P, Jacquemyn C, Kampitsis A, et 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.
Kampitsis A, Salinas P, Pain C, et al., 2019, Mesh adaptivity and parallel computing for 3D simulation of immiscible viscous fingering
© 2019 European Association of Geoscientists and Engineers, EAGE. All Rights Reserved. We present the recently developed Double Control Volume Finite Element Method (DCVFEM) in combination with dynamic mesh adaptivity in parallel computing to simulate immiscible viscous fingering in two- and three-dimensions. Immiscible viscous fingering may occur during the waterflooding of oil reservoirs, resulting in early breakthrough and poor areal sweep. Similarly to miscible fingering it is triggered by small-scale permeability heterogeneity while it is controlled by the mobility ratio of the fluid and the level of transverse dispersion / capillary pressure. Up to this day, most viscous fingering studies have focussed on the miscible problem since immiscible fingering is significantly more challenging. It requires numerical simulations capable to capture the interaction of the shock front with the capillary pressure, which is a saturation dependent dispersion term. That leads to models with very fine mesh in order to minimise numerical diffusion, resulting in computationally intensive simulations. In this study, we apply the dynamic mesh adaptive DCVFEM in parallel computing to simulate immiscible viscous fingering with capillary pressure. Parallelisation is achieved by using the MPI libraries. Dynamic mesh adaptivity is achieved by mapping of data between meshes. The governing multiphase flow equations are discretised using double control volumes on tetrahedral finite elements. The discontinuous representation for pressure and velocity allows the use of small control volumes, yielding higher resolution of the saturation field. We demonstrate convergence of fingers using our parallel numerical method in 2d and 3d, on fixed and adaptive meshes, quantifying the speed-up due to parallelisation and mesh adaptivity and the achieved accuracy. Dynamic mesh adaptivity allows resolution to be automatically employed where it is required to resolve the fingers with lower resolution
Hu R, Fang F, Salinas P, et al., 2019, Numerical simulation of floods from multiple sources using an adaptive anisotropic unstructured mesh method, Advances in Water Resources, Vol: 123, Pages: 173-188, ISSN: 0309-1708
The coincidence of two or more extreme events (precipitation and storm surge, for example) may lead to severe floods in coastal cities. It is important to develop powerful numerical tools for improved flooding predictions (especially over a wide range of spatial scales - metres to many kilometres) and assessment of joint influence of extreme events. Various numerical models have been developed to perform high-resolution flood simulations in urban areas. However, the use of high-resolution meshes across the whole computational domain may lead to a high computational burden. More recently, an adaptive isotropic unstructured mesh technique has been first introduced to urban flooding simulations and applied to a simple flooding event observed as a result of flow exceeding the capacity of the culvert during the period of prolonged or heavy rainfall. Over existing adaptive mesh refinement methods (AMR, locally nested static mesh methods), this adaptive unstructured mesh technique can dynamically modify (both, coarsening and refining the mesh) and adapt the mesh to achieve a desired precision, thus better capturing transient and complex flow dynamics as the flow evolves.In this work, the above adaptive mesh flooding model based on 2D shallow water equations (named as Floodity) has been further developed by introducing (1) an anisotropic dynamic mesh optimization technique (anisotropic-DMO); (2) multiple flooding sources (extreme rainfall and sea-level events); and (3) a unique combination of anisotropic-DMO and high-resolution Digital Terrain Model (DTM) data. It has been applied to a densely urbanized area within Greve, Denmark. Results from MIKE 21 FM are utilized to validate our model. To assess uncertainties in model predictions, sensitivity of flooding results to extreme sea levels, rainfall and mesh resolution has been undertaken. The use of anisotropic-DMO enables us to capture high resolution topographic features (buildings, rivers and streets) only where and when
Kampitsis A, Salinas P, Pain C, et al., 2019, Mesh adaptivity and parallel computing for 3D simulation of immiscible viscous fingering
We present the recently developed Double Control Volume Finite Element Method (DCVFEM) in combination with dynamic mesh adaptivity in parallel computing to simulate immiscible viscous fingering in two- and three-dimensions. Immiscible viscous fingering may occur during the waterflooding of oil reservoirs, resulting in early breakthrough and poor areal sweep. Similarly to miscible fingering it is triggered by small-scale permeability heterogeneity while it is controlled by the mobility ratio of the fluid and the level of transverse dispersion / capillary pressure. Up to this day, most viscous fingering studies have focussed on the miscible problem since immiscible fingering is significantly more challenging. It requires numerical simulations capable to capture the interaction of the shock front with the capillary pressure, which is a saturation dependent dispersion term. That leads to models with very fine mesh in order to minimise numerical diffusion, resulting in computationally intensive simulations. In this study, we apply the dynamic mesh adaptive DCVFEM in parallel computing to simulate immiscible viscous fingering with capillary pressure. Parallelisation is achieved by using the MPI libraries. Dynamic mesh adaptivity is achieved by mapping of data between meshes. The governing multiphase flow equations are discretised using double control volumes on tetrahedral finite elements. The discontinuous representation for pressure and velocity allows the use of small control volumes, yielding higher resolution of the saturation field. We demonstrate convergence of fingers using our parallel numerical method in 2d and 3d, on fixed and adaptive meshes, quantifying the speed-up due to parallelisation and mesh adaptivity and the achieved accuracy. Dynamic mesh adaptivity allows resolution to be automatically employed where it is required to resolve the fingers with lower resolution elsewhere, enabling capture of complex non-linearity such as tip-splitting. We achieve conv
Salinas P, Jacquemyn C, Kampitsis A, et 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.
Salinas P, Jacquemyn C, Kampitsis A, et 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.
Salinas P, Jacquemyn C, Kampitsis A, et 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.
Lei Q, Xie Z, Pavlidis D, et al., 2018, The shape and motion of gas bubbles in a liquid flowing through a thin annulus, Journal of Fluid Mechanics, Vol: 285, Pages: 1017-1039, ISSN: 0022-1120
We study the shape and motion of gas bubbles in a liquid flowing through a horizontal or slightly inclined thin annulus. Experimental data show that in the horizontal annulus, bubbles develop a unique ‘tadpole-like’ shape with a semi-circular cap and a highly stretched tail. As the annulus is inclined, the bubble tail tends to vanish, resulting in a significant decrease of bubble length. To model the bubble evolution, the thin annulus is conceptualised as a ‘Hele-Shaw’ cell in a curvilinear space. The three-dimensional flow within the cell is represented by a gap-averaged, two-dimensional model, which achieved a close match to the experimental data. The numerical model is further used to investigate the effects of gap thickness and pipe diameter on the bubble behaviour. The mechanism for the semi-circular cap formation is interpreted based on an analogous irrotational flow field around a circular cylinder, based on which a theoretical solution to the bubble velocity is derived. The bubble motion and cap geometry is mainly controlled by the gravitational component perpendicular to the flow direction. The bubble elongation in the horizontal annulus is caused by the buoyancy that moves the bubble to the top of the annulus. However, as the annulus is inclined, the gravitational component parallel to the flow direction becomes important, causing bubble separation at the tail and reduction in bubble length.
Obeysekara A, Xiang J, Latham JP, et al., 2018, Modelling stress-dependent single and multi-phase flows in fractured porous media based on an immersed-body method with mesh adaptivity, Computers and Geotechnics, Vol: 103, Pages: 229-241, ISSN: 0266-352X
This paper presents a novel approach for hydromechanical modelling of fractured rocks by linking a finite-discrete element solid model with a control volume-finite element fluid model based on an immersed-body approach. The adaptive meshing capability permits flow within/near fractures to be accurately captured by locally-refined mesh. The model is validated against analytical solutions for single-phase flow through a smooth/rough fracture and reported numerical solutions for multi-phase flow through intersecting fractures. Examples of modelling single- and multi-phase flows through fracture networks under in situ stresses are further presented, illustrating the important geomechanical effects on the hydrological behaviour of fractured porous media.
Salinas P, Pavlidis D, Xie Z, et al., 2018, A robust mesh optimisation method for multiphase porous media flows, Computational Geosciences, Vol: 22, Pages: 1389-1401, ISSN: 1420-0597
Flows of multiple fluid phases are common in many subsurface reservoirs. Numerical simulation of these flows can bechallenging and computationally expensive. Dynamic adaptive mesh optimisation and related approaches, such as adaptivegrid refinement can increase solution accuracy at reduced computational cost. However, in models or parts of the modeldomain, where the local Courant number is large, the solution may propagate beyond the region in which the mesh isrefined, resulting in reduced solution accuracy, which can never be recovered. A methodology is presented here to modifythe mesh within the non-linear solver. The method allows efficient application of dynamic mesh adaptivity techniques evenwith high Courant numbers. These high Courant numbers may not be desired but a consequence of the heterogeneity of thedomain. Therefore, the method presented can be considered as a more robust and accurate version of the standard dynamicmesh adaptivity techniques.
Xiao D, Fang F, Pain C, et al., 2018, Non-intrusive model reduction for a 3D unstructured mesh control volume finite element reservoir model and its application to fluvial channels, International Journal of Oil, Gas and Coal Technology, Vol: 19, Pages: 316-339, ISSN: 1753-3309
non-intrusive model reduction computational method using hypersurfaces representation has been developed for reservoir simulation and further applied to 3D fluvial channel problems in this work. This is achieved by a combination of a radial basis function (RBF) interpolation and proper orthogonal decomposition (POD) method. The advantage of the method is that it is generic and non-intrusive, that is, it does not require modifications to the original complex source code, for example, a 3D unstructured mesh control volume finite element (CVFEM) reservoir model used here. The capability of this non-intrusive reduced order model (NIROM) based on hypersurfaces representation has been numerically illustrated in a horizontally layered porous media case, and then further applied to a 3D complex fluvial channel case. By comparing the results of the NIROM against the solutions obtained from the high fidelity full model, it is shown that this NIROM results in a large reduction in the CPU computation cost while much of the details are captured.
Heaney C, Salinas P, Pain C, et al., 2018, Well Optimisation With Goal-Based Sensitivity Maps Using Time Windows And Ensemble Perturbations, European conference on mathematics of oil recovery
Salinas P, Jacquemyn C, Heaney C, et al., 2018, Simulation of enhanced geothermal systems using dynamic unstructured mesh optimisation, EAGE annual conference and exhibition
Jacquemyn C, Rood M, Melnikova Y, et al., 2018, My Geology Is Too Complex for My Grid: Grid-Free Surface-Based Geological Modelling, EAGE annual conference and exhibition
Salinas P, Pain C, Osman H, et al., 2018, Vanishing artificial capillary pressure as a mechanism to accelerate convergence, Interpore
Debbabi Y, Jackson M, Hampson G, et al., 2018, Impact of the buoyancy–viscous force balance on two-phase flow in layered porous media., Transport in Porous Media, Vol: 2018, ISSN: 0169-3913
Motivated by geological carbon storage and hydrocarbon recovery, the effect of buoyancy and viscous forces on the displacement of one fluid by a second immiscible fluid, along parallel and dipping layers of contrasting permeability, is characterized using five independent dimensionless numbers and a dimensionless storage or recovery efficiency. Application of simple dimensionless models shows that increased longitudinal buoyancy effects increase storage efficiency by reducing the distance between the leading edges of the injected phase in each layer and decreasing the residual displaced phase saturation behind the leading edge of the displacing phase. Increased transverse buoyancy crossflow increases storage efficiency if it competes with permeability layering effects, but reduces storage efficiency otherwise. When both longitudinal and transverse buoyancy effects are varied simultaneously, a purely geometrical dip angle group defines whether changes in storage efficiency are dominated by changes in the longitudinal or transverse buoyancy effects. In the limit of buoyancy-segregated flow, we report an equivalent, unidimensional flow model which allows rapid prediction of storage efficiency. The model presented accounts for both dip and layering, thereby generalizing earlier work which accounted for each of these but not both together. We suggest that the predicted storage efficiency can be used to compare and rank geostatistical realizations, and complements earlier heterogeneity measures which are applicable in the viscous limit.
Hu R, Fang F, Salinas P, et al., 2018, Unstructured mesh adaptivity for urban flooding modelling, Journal of Hydrology
Salinas P, Lei Q, Jacquemyn C, et al., 2018, DYNAMIC UNSTRUCTURED MESH ADAPTIVITY FOR IMPROVEDSIMULATION OF GEOTHERMAL WATER EXTRACTION INRESERVOIR-SCALE MODELS, 3rd Thermal and Fluids Engineering Conference
Salinas P, Jacquemyn C, Heaney C, et 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.
Salinas P, Jacquemyn C, Heaney C, et 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.
Jacquemyn C, Rood MP, Melnikova Y, et 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).
Heaney CE, Salinas P, Pain CC, et al., 2018, Well optimisation with goal-based sensitivity maps using time windows and ensemble perturbations
Knowledge of the sensitivity of a solution to small changes in the model parameters is exploited in many areas in computational physics and used to perform mesh adaptivity, or to correct errors based on discretisation and sub-grid-scale modelling errors, to perform the assimilation of data based on adjusting the most sensitive parameters to the model-observation misfit, and similarly to form optimised sub-grid-scale models. We present a goal-based approach for forming sensitivity (or importance) maps using ensembles. These maps are defined as regions in space and time of high relevance for a given goal, for example, the solution at an observation point within the domain. The presented approach relies solely on ensembles obtained from the forward model and thus can be used with complex models for which calculating an adjoint is not a practical option. This provides a simple approach for optimisation of sensor placement, goal based mesh adaptivity, assessment of goals and data assimilation. We investigate methods which reduce the number of ensembles used to construct the maps yet which retain reasonable fidelity of the maps. The fidelity comes from an integrated method including a goal-based approach, in which the most up-to-date importance maps are fed back into the perturbations to focus the algorithm on the key variables and domain areas. Also within the method smoothing is applied to the perturbations to obtain a multi-scale, global picture of the sensitivities; the perturbations are orthogonalised in order to generate a well-posed system which can be inverted; and time windows are applied (for time dependent problems) where we work backwards in time to obtain greater accuracy of the sensitivity maps. The approach is demonstrated on a multi-phase flow problem.
Salinas P, Lei Q, Jacquemyn C, et 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.
Jacquemyn C, Rood MP, Melnikova Y, et 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).
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