Multiple-point Geostatistics: A Quantitative Vehicle for Integrating Geologic Analogs into Multiple Reservoir Models
Jef Caers, Tuanfeng Zhang, 2004. "Multiple-point Geostatistics: A Quantitative Vehicle for Integrating Geologic Analogs into Multiple Reservoir Models", Integration of Outcrop and Modern Analogs in Reservoir Modeling, G. Michael Grammer, Paul M. “Mitch” Harris, Gregor P. Eberli
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Whereas outcrop models can provide important information on reservoir architecture and heterogeneity, it is not entirely clear how such information can be used exhaustively in geostatistical reservoir modeling. Traditional, variogram-based geostatistics is inadequate in that regard because the variogram is too limiting in capturing geologic heterogeneity from outcrops. A new field, termed multiple-point geostatistics, does not rely on variogram models. Instead, it allows capturing structure from so-called “training images.” Multiple-point geostatistics borrows multiple-point patterns from the training image, then anchors them to subsurface well-log, seismic, and production data. However, multiple-point geostatistics does not escape from the same principles as traditional variogram-based geostatistics: it is still a stochastic method and, hence, relies on the commonly forgotten principles of stationarity and ergodicity. These principles dictate that the training image used in multiple-point geostatistics cannot be chosen arbitrarily and that not all outcrops might be suitable training image models. In this paper, we outline the guiding principles of using analog models in multiple-point geostatistics and show that simple, so-called modular training images can be used to build complex reservoir models using geostatistics algorithms.
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Building robust 3-D reservoir models is a major challenge that requires incorporation of geologically defined input parameters. This publication provides an overview of current approaches used in the development of geologically constrained and integrated reservoir models. Each of the 18 papers addresses various stages in the process of creating a reservoir model through the development and incorporation of an analog, extracting the quantitative input parameters on lateral and vertical variability, and the development and modification of a 3-D reservoir model based upon geologically constrained data. This applied volume is divided into two sections. The first is a set of papers illustrating the value and methodology of acquiring geometrical data on the lateral and vertical distribution of reservoir facies, within a sequence stratigraphic framework, using both outcrop analogs and detailed study of modern depositional systems. The second section includes both case studies where outcrop and modern analog data have been incorporated into subsurface reservoir models, as well as papers that illustrate recent advances in simulation and geostatistical methodologies. Together, the two sections provide a comprehensive look at integrated reservoir modeling.