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The AAPG/Datapages Combined Publications Database

AAPG Bulletin


Volume: 79 (1995)

Issue: 1. (January)

First Page: 97

Last Page: 114

Title: Approaches to Previous HitPredictingNext Hit Previous HitReservoirNext Hit Quality in Sandstones

Author(s): S. Bloch (2), K. P. Helmold (3)


Despite limited understanding of the details of many diagenetic processes, empirical techniques can be used effectively to predict Previous HitreservoirNext Hit quality prior to drilling. The predictive approach depends mainly on the availability of empirical data in the area of interest. In frontier basins, mean or maximum Previous HitporosityNext Hit of a potential Previous HitsandstoneNext Hit Previous HitreservoirNext Hit can be estimated for a given composition and level of thermal exposure (or burial depth). The reliability of the estimates is constrained by input data. Approximate values of input parameters can be obtained from seismic data in combination with geological analysis of the area.

In basins with sufficient information to generate calibration data sets, the predictive technique uses regression analysis. The applicability of this approach is constrained by the limits imposed by the calibration data set and is generally limited to samples containing less than 10% pore-filling cement. Quartz-rich sandstones (>85% framework quartz), cemented with quartz, are an exception to the 10% limit because quartz cementation commonly is related to burial history and rock texture. In weakly cemented sandstones, the critical variables controlling Previous HitporosityNext Hit are detrital composition, sorting, and burial history. Permeability can be predicted independently of Previous HitporosityNext Hit using the same variables plus grain size. These variables can be evaluated from seismic data and facies models. T is approach is best suited either for sandstones in which compaction is the main Previous HitporosityNext Hit-reducing process or for quartz-rich sandstones.

An adequate predictive model for Previous HitsandstoneNext Hit suites with a wide range of cement content can be obtained by dividing the calibration data set into two or more subsets and developing a predictive model for each. For example, one subset can be limited to samples with less than 10% cement, whereas the second subset will consist of samples with more than 10% nonquartz cement. Previous HitPorosityNext Hit and permeability in the first subset are then expressed by linear regression, whereas controls on Previous HitreservoirTop quality in the more heavily cemented sandstones are determined independently based on understanding of cement distribution patterns.

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