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The AAPG/Datapages Combined Publications Database

CSPG Bulletin

Abstract


Bulletin of Canadian Petroleum Geology
Vol. 63 (2015), No. 4. (December), Pages 374-392

Stochastic Regridding of Geological Models for Flow Simulation

Saina Lajevardi, Clayton V. Deutsch

Abstract

Regridding geological models to a higher Previous HitresolutionNext Hit for flow simulation is an important problem in geostatistical modeling. For practical reasons, over a large area, models can only be built at a relatively coarse Previous HitresolutionNext Hit. Subsequently, the Previous HitresolutionNext Hit of specified regions of interest must be increased before upscaling for flow modeling. The construction of a high-Previous HitresolutionNext Hit model of the entire reservoir at the beginning of the evaluation may be impractical because of computational and time constraints. It is standard practice to implement nearest neighbor interpolation to increase the Previous HitresolutionNext Hit of models. Although it is a simple practical solution, nearest neighbor interpolation introduces spatial continuity artifacts that are often unrealistic. This paper proposes an automatic stochastic regridding approach based on simulation. The simulation is conditioned to the initial coarse Previous HitresolutionNext Hit model/realization. The process includes the extraction of specified regions of interest, definition of corresponding local variography, and implementation of Sequential Gaussian Simulation (SGS) and/or Sequential Indicator Simulation (SIS) to characterize continuous and categorical variables, respectively. In each specified region, the local variography can be defined by either implementing automatic fitting algorithms or assigning the global variography initially used to build the coarse Previous HitresolutionNext Hit model. The regridding process is automated. The advantage of this approach over the conventional nearest neighbor interpolation is in the improvement in the realistic spatial variability features of small scale geologic heterogeneity. The benefits of obtaining a proper regridded model are discussed in a case study of a fluvial reservoir in the McMurray formation. One of the main reasons for generating high Previous HitresolutionNext Hit models is in the appropriate characterization of small scale impermeable geobodies such as remnant shales. The coarse Previous HitresolutionNext Hit models are not able to properly characterize the small scale geologic features of the shales; more amount of information is required to characterize smaller scale features. The metric of performance considered is the effective vertical permeability. The automated stochastic regridding workflow described in this paper is available on a Fortran platform with additional scripting which will be distributed upon request. Note that the terms “regridding” and “stochastic regridding” are used interchangeably and both refer to the proposed workflow of modeling at higher Previous HitresolutionTop.


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