-Hydrocarbon reservoirs are characterized by the spatial distributions of petrophysical properties. These spatial characteristics are usually derived from well data and seismic information. To study a reservoir, the engineers build a fine geological model, also called a geostatistical model, to represent the field. The purpose is to capture as well as possible the peculiarities and heterogeneity of the true reservoir. At this stage, performing a flow simulation with such detailed geological models is just too time-demanding. Therefore, a possibility consists of upscaling the geological model to an upscaled mesh, thus resulting in a coarse reservoir model for which fluid flow can be numerically simulated in a reasonable amount of time. The coarse grid blocks of this reservoir model are attributed equivalent petrophysical properties related to the properties populating the fine grid blocks. These properties are upscaled, and so they do not capture all of the details of the fine model. In this paper, we investigate the potential of various numerical and easy to compute criteria, which help evaluate the information loss due to the upscaling process. Our final purpose is to provide and access the reliability of quality indicators, which make it possible to evaluate the quality of the upscaled reservoir model. The potential of this systematic and integrated study is illustrated with two types of numerical experiments based upon the SPE10 case. First, we apply different upscaling methods to determine coarse reservoir models. Quality indicators are computed for each of them so that we identify the most suitable upscaling methods. Then, the upscaled models are input to flow simulators to check the accuracy of our quality estimations. Second, we also investigate the influence of coarsening and try to determine from the computed quality indicators the coarse cell size above which too much information is lost.Re´sume´-À propos de l'utilisation d'indicateurs de qualite´afin de re´duire la perte d'information lors d'un upscaling -Les re´servoirs pe´troliers sont caracte´rise´s par une distribution spatiale de proprie´te´s pe´trophysiques. Ces caracte´ristiques spatiales sont ge´ne´ralement de´rive´es de donne´es de puits et sismiques. Les inge´nieurs construisent alors un mode`le ge´ologique fin, aussi appeleḿ ode`le ge´ostatistique, pour repre´senter le champ. Le but est de capturer aussi bien que possible les particularite´s et l'he´te´roge´ne´ite´du re´servoir. À ce stade, re´aliser une simulation d'e´coulement avec ces mode`les ge´ologiques aussi de´taille´s est trop couˆteux en temps de calcul. Par conse´quent, une possibilite´consiste a`« upscaler » le mode`le ge´ologique sur une grille grossie`re, afin d'obtenir un mode`le de re´servoir grossier pour lequel l'e´coulement peut eˆtre simule´nume´riquement dans un laps de temps raisonnable. On attribue alors des proprie´te´s pe´trophysiques e´quivalentes aux cellules de la grille grossie`re. Meˆme si ces donne´es e´quivalentes sont obtenues a`partir des proprie´t...
and available online here Cet article fait partie du dossier thématique ci-dessous publié dans la revue OGST, Vol. 67, n°6, pp. 883-1039 et téléchargeable ici
Abstract. Viscous flow, effusion, and thermal transpiration are the main gas transport modalities for a rarefied gas in a macro-porous medium. They have been well quantified only in the case of simple geometries. This paper develops a model based on the homogenization of kinetic equations producing effective transport properties (permeability, Knudsen diffusivity, thermal transpiration ratio) in any porous medium sample, as described e. g. by a digitized 3D image. The homogenization procedureneglecting the effect of gas density gradients on heat transfer through the solid -leads to macroscopic transfer relations, and to closure problems in R 6 for the obtention of effective properties. Coherence of the approach with previous literature on the subject is discussed. The asymptotic limits of the model (rarefied and continuum regimes) are also studied. One of the main results is that the effect of the geometry on thermal transpiration has to be described by a tensor which is distinct from the permeability and Knudsen diffusion tensors.
-Reservoir engineers aim to build reservoir models to investigate fluid flows within hydrocarbon reservoirs. These models consist of three-dimensional grids populated by petrophysical properties. In this paper, we focus on permeability that is known to significantly influence fluid flow. Reservoir models usually encompass a very large number of fine grid blocks to better represent heterogeneities. However, performing fluid flow simulations for such fine models is extensively CPU-time consuming. A common practice consists in converting the fine models into coarse models with less grid blocks: this is the upscaling process. Many upscaling methods have been proposed in the literature that all lead to distinct coarse models. The problem is how to choose the appropriate upscaling method. Various criteria have been established to evaluate the information loss due to upscaling, but none of them investigate connectivity. In this paper, we propose to first perform a connectivity analysis for the fine and candidate coarse models. This makes it possible to identify shortest paths connecting wells. Then, we introduce two indicators to quantify the length and trajectory mismatch between the paths for the fine and the coarse models. The upscaling technique to be recommended is the one that provides the coarse model for which the shortest paths are the closest to the shortest paths determined for the fine model, both in terms of length and trajectory. Last, the potential of this methodology is investigated from two test cases. We show that the two indicators help select suitable upscaling techniques as long as gravity is not a prominent factor that drives fluid flows.Résumé -Sélection de méthodes d'upscaling par analyse de connectivité -Les ingénieurs de réservoir construisent des modèles de réservoir pour comprendre les écoulements de fluides dans les réservoirs d'hydrocarbures. Ces modèles se composent de grilles en trois dimensions peuplées par des propriétés pétrophysiques. Dans cet article, nous nous concentrons sur la perméabilité qui est connue pour influencer de manière significative l'écoulement du fluide. Les modèles de réservoir ont généralement un très grand nombre de mailles fines afin de mieux représenter les hétérogénéités. Cependant, les simulations d'écoulement sur ces modèles fins sont très coûteuses en temps CPU. Une pratique courante consiste à convertir les modèles fins en modèles grossiers avec moins de mailles : c'est le processus de mise à l'échelle. De nombreuses méthodes de changement d'échelle ont été proposées dans la littérature qui mènent à des modèles grossiers différents. Le problème est de savoir comment choisir la méthode de mise à l'échelle appropriée. Différents critères ont été établis pour évaluer la perte d'information due à l'upscaling, mais aucun d'entre eux ne s'intéresse à la connectivité. Dans cet article, nous nous proposons d'abord d'effectuer une analyse de connectivité pour les modèles fins et grossiers. Cela nous permet d'identifier les chemins les plus courts reliant l...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.