Génération de grilles de type volumes finis : adaptation à un modèle structural, pétrophysique et dynamique

Voronoi grids are generated under constraints to reduce the errors due to cells geometry during flow simulation in reservoirs. The Voronoi points are optimized by minimizing objective functions relevant to various geometrical constraints. An original feature of this approach is to combine simultaneously the constraints: - Cell quality, by placing the Voronoi points at the cell barycenters. - Local refinement according to a density field rho, relevant to permeability, velocity or vorticity. - Cell anisotropy according to a matrix field M built with the three principal vectors of the anisotropy, which one is defined by the velocity vector or by the stratigraphic gradient. - Faces orientation according to a matrix field M built with the three vectors orthogonal to the faces, which one is defined by the velocity vector. - Conformity to structural features, faults and horizons. - Voronoï points alignment along well path. The quality of the generated grids is assessed from geometrical criteria and from comparisons of flow simulation results with reference fine grids. Results show geometrical improvements, that are not necessarily followed by flow simulation results improvementsCet ouvrage aborde la génération de grilles de Voronoï sous contrainte pour réduire les erreurs liées à la géométrie des cellules lors de la simulation réservoir. Les points de Voronoï sont optimisés en minimisant des fonctions objectif correspondant à différentes contraintes géométriques. L'originalité de cette approche est de pouvoir combiner les contraintes simultanément : - la qualité des cellules, en plaçant les points de Voronoï aux barycentres des cellules ; - le raffinement local, en fonction d'un champ de densité [rho], correspondant à la perméabilité, la vitesse ou la vorticité ; - l'anisotropie des cellules, en fonction d'un champ de matrice M contenant les trois vecteurs principaux de l'anisotropie, dont l'un est défini par le vecteur vitesse ou par le gradient stratigraphique ; - l'orientation des faces des cellules, en fonction d'un champ de matrice M contenant les trois vecteurs orthogonaux aux faces, dont l'un est défini par le vecteur vitesse ; - la conformité aux surfaces du modèle structural, failles et horizons ; - l'alignement des points de Voronoï le long des puits. La qualité des grilles générées est appréciée à partir de critères géométriques et de résultats de simulation comparés à des grilles fines de référence. Les résultats indiquent une amélioration de la géométrie, qui n'est pas systématiquement suivie d'une amélioration des résultats de simulatio

Generation of finite volume grids : Adaptation to a structural, petrophysical and dynamical model

Cet ouvrage aborde la génération de grilles de Voronoï sous contrainte pour réduire les erreurs liées à la géométrie des cellules lors de la simulation réservoir. Les points de Voronoï sont optimisés en minimisant des fonctions objectif correspondant à différentes contraintes géométriques. L'originalité de cette approche est de pouvoir combiner les contraintes simultanément : - la qualité des cellules, en plaçant les points de Voronoï aux barycentres des cellules ; - le raffinement local, en fonction d'un champ de densité [rho], correspondant à la perméabilité, la vitesse ou la vorticité ; - l'anisotropie des cellules, en fonction d'un champ de matrice M contenant les trois vecteurs principaux de l'anisotropie, dont l'un est défini par le vecteur vitesse ou par le gradient stratigraphique ; - l'orientation des faces des cellules, en fonction d'un champ de matrice M contenant les trois vecteurs orthogonaux aux faces, dont l'un est défini par le vecteur vitesse ; - la conformité aux surfaces du modèle structural, failles et horizons ; - l'alignement des points de Voronoï le long des puits. La qualité des grilles générées est appréciée à partir de critères géométriques et de résultats de simulation comparés à des grilles fines de référence. Les résultats indiquent une amélioration de la géométrie, qui n'est pas systématiquement suivie d'une amélioration des résultats de simulationVoronoi grids are generated under constraints to reduce the errors due to cells geometry during flow simulation in reservoirs. The Voronoi points are optimized by minimizing objective functions relevant to various geometrical constraints. An original feature of this approach is to combine simultaneously the constraints: - Cell quality, by placing the Voronoi points at the cell barycenters. - Local refinement according to a density field rho, relevant to permeability, velocity or vorticity. - Cell anisotropy according to a matrix field M built with the three principal vectors of the anisotropy, which one is defined by the velocity vector or by the stratigraphic gradient. - Faces orientation according to a matrix field M built with the three vectors orthogonal to the faces, which one is defined by the velocity vector. - Conformity to structural features, faults and horizons. - Voronoï points alignment along well path. The quality of the generated grids is assessed from geometrical criteria and from comparisons of flow simulation results with reference fine grids. Results show geometrical improvements, that are not necessarily followed by flow simulation results improvement

Building PEBI Grids Conforming To 3D Geological Features Using Centroidal Voronoi Tessellations

International audienceFor numerical reservoir flow simulation, grids that are conformal to the geological features are needed in order to reduce the homogenization error (in particular between horizons) and to re- trieve the major flow features (such as faults).In this paper, Voronoi Tessellations are obtained by an optimization method where the minimized function is modified from the classical Cen- troidal Voronoi function. The geological features are considered as inner surfaces, dividing the reservoir into closed subdomains.These methodologies are applied successfully to 3D synthetic reservoirs with internal features such as horizons, faults, partly cutting faults and pinch-outs

Génération de grilles de type volumes finis (adaptation à un modèle structural, pétrophysique et dynamique)

Cet ouvrage aborde la génération de grilles de Voronoï sous contrainte pour réduire les erreurs liées à la géométrie des cellules lors de la simulation réservoir. Les points de Voronoï sont optimisés en minimisant des fonctions objectif correspondant à différentes contraintes géométriques. L'originalité de cette approche est de pouvoir combiner les contraintes simultanément : - la qualité des cellules, en plaçant les points de Voronoï aux barycentres des cellules ; - le raffinement local, en fonction d'un champ de densité [rho], correspondant à la perméabilité, la vitesse ou la vorticité ; - l'anisotropie des cellules, en fonction d'un champ de matrice M contenant les trois vecteurs principaux de l'anisotropie, dont l'un est défini par le vecteur vitesse ou par le gradient stratigraphique ; - l'orientation des faces des cellules, en fonction d'un champ de matrice M contenant les trois vecteurs orthogonaux aux faces, dont l'un est défini par le vecteur vitesse ; - la conformité aux surfaces du modèle structural, failles et horizons ; - l'alignement des points de Voronoï le long des puits. La qualité des grilles générées est appréciée à partir de critères géométriques et de résultats de simulation comparés à des grilles fines de référence. Les résultats indiquent une amélioration de la géométrie, qui n'est pas systématiquement suivie d'une amélioration des résultats de simulationVoronoi grids are generated under constraints to reduce the errors due to cells geometry during flow simulation in reservoirs. The Voronoi points are optimized by minimizing objective functions relevant to various geometrical constraints. An original feature of this approach is to combine simultaneously the constraints: - Cell quality, by placing the Voronoi points at the cell barycenters. - Local refinement according to a density field rho, relevant to permeability, velocity or vorticity. - Cell anisotropy according to a matrix field M built with the three principal vectors of the anisotropy, which one is defined by the velocity vector or by the stratigraphic gradient. - Faces orientation according to a matrix field M built with the three vectors orthogonal to the faces, which one is defined by the velocity vector. - Conformity to structural features, faults and horizons. - Voronoï points alignment along well path. The quality of the generated grids is assessed from geometrical criteria and from comparisons of flow simulation results with reference fine grids. Results show geometrical improvements, that are not necessarily followed by flow simulation results improvementsMETZ-SCD (574632105) / SudocNANCY1-Bib. numérique (543959902) / SudocNANCY2-Bibliotheque electronique (543959901) / SudocNANCY-INPL-Bib. électronique (545479901) / SudocSudocFranceF

Building Centroidal Voronoi Tesselations for Flow Simulation in Reservoirs Using Flow Information

National audienceThe generation of reservoir grids has to take into account numerous flow parameters, static and dynamic, from the fine-scale geological models to minimize discretization errors. These parameters are generally encoded separately as constraints on cell size, orientation and aspect ratio. In this paper, we propose to encode them all at a time in a Riemannian metric tensor field and to apply a global optimization method. This method is based on Centroidal Voronoi Tesselation algorithms under Lp norm and generates unstructured hex-dominant reservoir grids, optimum in terms of sampling. We appy these principles to generate flow-based reservoir grids. We use a fine-scale velocity field to compute the norm and the directions of the metric tensor: the generated grids are refined in regions of high flow, and the cell facets are oriented along the streamline directions. The grids are therefore suitable to a discretization with two-point flux approximation. The simulation results obtainedd with these grids are then compared with those computed on a standard Cartesian grid of the same size. These first results are encouraging and need further investigation. The method is general, and can account for other dynamic parameters, such as vorticity, that can be weighted and introduced in the metric tensor. Furthermore, CVT algorithms can be adapted to take into account fine-scale static features in the grid generation process. Because the gridding is fully automatic, a possible extension of this work is to update the grid between simulation time steps to reflect changes in boundary conditions

Voronoi grids conforming to 3D structural features

International audienceFlow simulation in a reservoir can be highly impacted by upscaling errors. These errors can be reduced by using simulation grids with cells as homogeneous as possible, hence conformable to horizons and faults. In this paper, the coordinates of 3D Voronoi seeds are optimized so that Voronoi cell facets honor the structural features. These features are modeled by piecewise linear complex (PLC). The optimization minimizes a function made of two parts: (1) a barycentric function, which ensures that the cells will be of good quality by maximizing their compactness; and (2) a conformity function, which allows to minimize the volume of cells that is isolated from the Voronoi seed w.r.t., a structural feature. To determine the isolated volume, a local approximation of the structural feature inside the Voronoi cells is used to cut the cells. It improves the algorithm efficiency and robustness compared to an exact cutting procedure. This method, used jointly with an adaptive gradient solver to minimize the function, allows dealing with complex 3D geological cases. It always produces a Voronoi simulation grid with the desired number of cells

Structural Framework and Reservoir Gridding: Current Bottlenecks and Way Forward

International audienceAfter some 20 years of progress, reservoir modeling still raises practical and theoretical challenges. Standard workflows are primarily built in a linear fashion (fault framework modeling, stratigraphic modeling, gridding, petrophysical modeling, upscaling, flow simulation and history matching). Modifying decisions in an early step in this workflow requires performing again all the dependent steps and the associated quality controls. Whereas robustness has significantly improved and makes it now possible to improve automation and running of multiple scenarios, we identify four main limitations in the current workflows and corresponding research axes: 1- Well correlations are most often deterministic in reservoir models, whereas they are affected by significant uncertainty. We need new ways to effectively sample this uncertainty by using sedimentological concepts and propagate it in existing time-to-depth conversion and gridding workflows. 2- Determination of the fault connectivity is often suboptimal: connectivity is decided from seismic fault sticks before stratigraphic modeling, whereas fault displacement is, with well test data, one of the most important arguments to decide about fault connectivity. We argue that evaluating fault displacement earlier in structural modeling workflows would most probably help choosing more realistic fault connectivity patterns right from the beginning, or stochastically sampling possible fault networks. 3- Gridding is a complex task and should ideally account for geological structures, facies and permeability fields and well geometry. The discretization of flow equations imposes additional gridding constraints to guarantee the performance and accuracy of flow simulation. Stair-step grids are a significant improvement to better handle some of these constraints, but locally flexible unstructured grids are the only way forward to appropriately integrate all available information while honoring discretization constraints. 4- Scale management has been a buzzword in reservoir modeling for years, but the current practice is still to take into account at best for two scales, and this after the reservoir gridding stage. We think that multiple scales should be used earlier on, and that connectivity and topological considerations should be used to ensure consistency between scales and between models and first-order dynamic information

Current bottlenecks in geomodeling workflows and ways forward

International audienceAfter more than 20 years of progress, reservoir modeling still raises practical and theoretical challenges. Standard workflows are primarily built in a linear fashion (fault framework modeling, stratigraphic modeling, gridding, petrophysical modeling, upscaling, flow simulation and history matching). Modifying decisions taken at an early step of this workflow requires going through all the dependent steps and the associated quality controls once more. Whereas robustness has significantly improved and now makes it possible to improve automation and running of multiple scenarios, we identify four main limitations in the current workflows and propose possible strategies to address these limitations.First, we suggest ways to effectively sample uncertainty about well correlations by using sedimentological concepts and propagate it in existing time-to-depth conversion and gridding workflows. Then, we propose to analyze fault displacement when deciding about fault connectivity rather than discovering fault displacement in the last stage of structural framework building. Gridding should then ideally account for static data (geological structures, facies and associated permeability fields) and dynamic data (boundary conditions) while honouring discretization constraints. Although stair-step grids are a significant improvement to better handle some of these constraints, recent developments in unstructured gridding open new perspectives to address gridding challenges with more flexibility. Last, we advocate that multiple scales should be considered before the reservoir grid is created, and that connectivity and topological considerations should be used to ensure internal consistency between scales, once models have been constrained by first-order dynamic information.Après plus de 20 années de développement, la modélisation de réservoirs soulève encore des défis théoriques et pratiques. Comme les processus de géomodélisation sont organisés de manière séquentielle (modélisation du réseau de failles, de la stratigraphie, maillage, remplissage pétrophysique, mise à l’échelle, simulation d’écoulement et calage historique), toute modification à une étape donnée nécessite des mises à jour souvent fastidieuses des étapes ultérieures. De récentes améliorations de robustesse rendent possible une meilleure automatisation des tâches de géomodélisation, et permettent d’étudier plusieurs scénarios. Toutefois, nous identifions quatre pistes d’amélioration des processus de géomodélisation, et proposons des stratégies pour y remédier.Premièrement, nous suggérons d’échantillonner l’incertitude relative aux corrélations de puits à l’aide de concepts sédimentologiques, et de propager ces incertitudes aux étapes ultérieures de modélisation de réservoir. Puis, nous proposons d’analyser le champ de déplacement des failles au moment où se décide la connectivité du réseau plutôt que de considérer cette étape comme un contrôle qualité seulement à la fin de la modélisation structurale. Le maillage de réservoir doit ensuite s’accommoder de données statiques (structures, faciès et champ de perméabilité associé) et dynamiques (conditions aux limites) tout en honorant des contraintes de discrétisation. Si de récents progrès dans la création de grilles hexaédriques vont dans la bonne direction pour intégrer certaines de ces contraintes, des développements récents en génération de grilles non structurées semblent aujourd’hui prometteurs pour plus de flexibilité et d’intégration. Enfin, la problématique de l’échelle devrait trouver sa place en géomodélisation avant le maillage du réservoir. Un point fondamental est d’utiliser des critères de topologie et de connectivité pour assurer la cohérence des échelles entre elles, après avoir contraint les modèles au premier ordre avec les données dynamiques

Structural Framework and Reservoir Gridding: Current Bottlenecks and Way Forward

International audienceAfter some 20 years of progress, reservoir modeling still raises practical and theoretical challenges. Standard workflows are primarily built in a linear fashion (fault framework modeling, stratigraphic modeling, gridding, petrophysical modeling, upscaling, flow simulation and history matching). Modifying decisions in an early step in this workflow requires performing again all the dependent steps and the associated quality controls. Whereas robustness has significantly improved and makes it now possible to improve automation and running of multiple scenarios, we identify four main limitations in the current workflows and corresponding research axes: 1- Well correlations are most often deterministic in reservoir models, whereas they are affected by significant uncertainty. We need new ways to effectively sample this uncertainty by using sedimentological concepts and propagate it in existing time-to-depth conversion and gridding workflows. 2- Determination of the fault connectivity is often suboptimal: connectivity is decided from seismic fault sticks before stratigraphic modeling, whereas fault displacement is, with well test data, one of the most important arguments to decide about fault connectivity. We argue that evaluating fault displacement earlier in structural modeling workflows would most probably help choosing more realistic fault connectivity patterns right from the beginning, or stochastically sampling possible fault networks. 3- Gridding is a complex task and should ideally account for geological structures, facies and permeability fields and well geometry. The discretization of flow equations imposes additional gridding constraints to guarantee the performance and accuracy of flow simulation. Stair-step grids are a significant improvement to better handle some of these constraints, but locally flexible unstructured grids are the only way forward to appropriately integrate all available information while honoring discretization constraints. 4- Scale management has been a buzzword in reservoir modeling for years, but the current practice is still to take into account at best for two scales, and this after the reservoir gridding stage. We think that multiple scales should be used earlier on, and that connectivity and topological considerations should be used to ensure consistency between scales and between models and first-order dynamic information

Structural Framework and Reservoir Gridding: Current Bottlenecks and Way Forward

International audienceAfter some 20 years of progress, reservoir modeling still raises practical and theoretical challenges. Standard workflows are primarily built in a linear fashion (fault framework modeling, stratigraphic modeling, gridding, petrophysical modeling, upscaling, flow simulation and history matching). Modifying decisions in an early step in this workflow requires performing again all the dependent steps and the associated quality controls. Whereas robustness has significantly improved and makes it now possible to improve automation and running of multiple scenarios, we identify four main limitations in the current workflows and corresponding research axes: 1- Well correlations are most often deterministic in reservoir models, whereas they are affected by significant uncertainty. We need new ways to effectively sample this uncertainty by using sedimentological concepts and propagate it in existing time-to-depth conversion and gridding workflows. 2- Determination of the fault connectivity is often suboptimal: connectivity is decided from seismic fault sticks before stratigraphic modeling, whereas fault displacement is, with well test data, one of the most important arguments to decide about fault connectivity. We argue that evaluating fault displacement earlier in structural modeling workflows would most probably help choosing more realistic fault connectivity patterns right from the beginning, or stochastically sampling possible fault networks. 3- Gridding is a complex task and should ideally account for geological structures, facies and permeability fields and well geometry. The discretization of flow equations imposes additional gridding constraints to guarantee the performance and accuracy of flow simulation. Stair-step grids are a significant improvement to better handle some of these constraints, but locally flexible unstructured grids are the only way forward to appropriately integrate all available information while honoring discretization constraints. 4- Scale management has been a buzzword in reservoir modeling for years, but the current practice is still to take into account at best for two scales, and this after the reservoir gridding stage. We think that multiple scales should be used earlier on, and that connectivity and topological considerations should be used to ensure consistency between scales and between models and first-order dynamic information