A New Efficient Averaging Technique for Scaleup of Multimillion-Cell Geologic Models

Li, D.; Beckner, B.L.; Kumar, Arvind

doi:10.2118/56554-ms

Cited by 21 publications

(7 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Often averaging, or a combination of averages (arithmetic-harmonic, or harmonic-arithmetic) is used for speed in more complex models (e.g. Li et al, 2001). When the permeability variation is small (permeability contrast 5:1 or less), the errors will not be severe (Pickup and Hern, 2002).…”

Section: Permeability Structure and Contrastmentioning

confidence: 99%

Multi-Stage Upscaling: Selection of Suitable Methods

Pickup

Stephen

et al. 2005

Transp Porous Med

View full text Add to dashboard Cite

Reservoirs are often composed of an assortment of rock types giving rise to permeability heterogeneities at a variety of length-scales. To predict fluid flow at the fullfield scale, it is necessary to be aware of these different types of heterogeneity, to recognise which are likely to have important effects on fluid flow, and to capture them by upscaling. In fact, we may require a series of stages of upscaling to go from small-scales (mm or cm) to a full-field model. When there are two (or more) phases present, we also need to know how these heterogeneities interact with fluid forces (capillary, viscous and gravity). We discuss how these effects may be taken into account by upscaling. This study focusses on the effects of steady-state upscaling for viscous-dominated floods and tests carried out on a range of 2D models are described. Upscaling errors are shown to be reduced slightly by the increase in numerical dispersion at the coarse scale. We select a combination of three different upscaling methods, and apply this approach to a model of a North Sea oil reservoir in a deep marine environment. Six different genetic units (rock types) were identified, including channel sandstone and inter-bedded sandstone and mudstone. These units were modelled using different approaches, depending on the nature of the heterogeneities. Our results show that the importance of small-scale heterogeneity depends on the large-scale distribution of the rock types. Upscaling may not be worthwhile in sparsely distributed genetic units. However, it is important in the dominant rock type, especially if there is good connectivity through the unit between the injector wells (or aquifer) and the producer wells.

show abstract

Section: Permeability Structure and Contrastmentioning

confidence: 99%

Multi-Stage Upscaling: Selection of Suitable Methods

Pickup

Stephen

et al. 2005

Transp Porous Med

View full text Add to dashboard Cite

show abstract

“…The interested reader can refer to [20] and [22] for detailed formulations in the case of Cartesian grids. Let us consider CPG grids and denote v i;j;k the volume of a fine cell.…”

Section: The Cardwell and Parsons Boundsmentioning

confidence: 99%

About the Use of Quality Indicators to Reduce Information Loss When Performing Upscaling

Preux

2014

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

View full text Add to dashboard Cite

-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...

show abstract

“…For scalar variables, such as porosity or mineral volume fractions, the method of volume averaging is required to conserve mass and volume within the domains of interest. For tensor variables, such as permeability and relative permeability, fast approximate methods include weighted combinations of arithmetic and harmonic means (Fleckenstein and Fogg 2008, Li et al 2001, Malik and Lake 1997, renormalization methods (Hinrichsen et al 1993, King 1989, and continuoustime random walk particle tracking (McCarthy 1995).…”

Section: A7 Upscalingmentioning

confidence: 99%

Data Assimilation Tools for CO2 Reservoir Model Development ? A Review of Key Data Types, Analyses, and Selected Software

Rockhold¹,

Sullivan²,

Murray³

et al. 2009

View full text Add to dashboard Cite

Printed in the United States of America AbstractPacific Northwest National Laboratory (PNNL) has embarked on an initiative to develop world-class capabilities for performing experimental and computational analyses associated with geologic sequestration of carbon dioxide. The ultimate goal of this initiative is to provide science-based solutions for helping to mitigate the adverse effects of greenhouse gas emissions. This Laboratory-Directed Research and Development (LDRD) initiative currently has two primary focus areas-advanced experimental methods and computational analysis. The experimental methods focus area involves the development of new experimental capabilities, supported in part by the U.S. Department of Energy's (DOE) Environmental Molecular Science Laboratory (EMSL) housed at PNNL, for quantifying mineral reaction kinetics with CO 2 under high temperature and pressure (supercritical) conditions. The computational analysis focus area involves numerical simulation of coupled, multi-scale processes associated with CO 2 sequestration in geologic media, and the development of software to facilitate building and parameterizing conceptual and numerical models of subsurface reservoirs that represent geologic repositories for injected CO 2 . This report describes work in support of the computational analysis focus area.The computational analysis focus area currently consists of several collaborative research projects. These are all focused on the development and application of conceptual and numerical models for geologic sequestration of CO 2 . The software being developed for this focus area is referred to as the Geologic Sequestration Software Suite or GS 3 . A wiki-based software framework is being developed to support GS 3 . This report summarizes work performed in FY09 on one of the LDRD projects in the computational analysis focus area. The title of this project is Data Assimilation Tools for CO 2 Reservoir Model Development. Some key objectives of this project in FY09 were to assess the current state-of-theart in reservoir model development, the data types and analyses that need to be performed in order to develop and parameterize credible and robust reservoir simulation models, and to review existing software that is applicable to these analyses. This report describes this effort and highlights areas in which additional software development, wiki application extensions, or related GS 3 infrastructure development may be warranted. v vii Acknowledgments

show abstract

A New Efficient Averaging Technique for Scaleup of Multimillion-Cell Geologic Models

Cited by 21 publications

References 22 publications

Multi-Stage Upscaling: Selection of Suitable Methods

Multi-Stage Upscaling: Selection of Suitable Methods

About the Use of Quality Indicators to Reduce Information Loss When Performing Upscaling

Data Assimilation Tools for CO2 Reservoir Model Development ? A Review of Key Data Types, Analyses, and Selected Software

Contact Info

Product

Resources

About