Approaches to predicting reservoir quality in sandstones

Journal Article · Sun Jan 01 04:00:00 EST 1995 · AAPG Bulletin

OSTI ID:54893

Bloch, S ^[1]; Helmold, K P ^[2]

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1. ARCO Exploration and Production Technology, Plano, TX (United States)
2. ARCO Alaska, Inc., Anchorage, AK (United States)

Despite limited understanding of the details of many diagenetic processes, empirical techniques can be used effectively to predict reservoir quality prior to drilling. In frontier basins, mean or maximum porosity of a potential sandstone reservoir can be estimated for a given composition and level of thermal exposure (or burial depth). 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, and are 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 porosity are detrital composition, sorting, and burial history. Permeability can be predicted independently of porosity using the same variables plus grain size. These variables can be evaluated from seismic data and facies models. This approach is best suited either for sandstones in which compaction is the main porosity-reducing process or for quartz-rich sandstones. An adequate predictive model for sandstone 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. Porosity and permeability in the first subset are then expressed by linear regression, whereas controls on reservoir quality in the more heavily cemented sandstones are determined independently based on understanding of cement distribution patterns.

• OSTI ID: 54893
• Journal Information: AAPG Bulletin, Journal Name: AAPG Bulletin Journal Issue: 1 Vol. 79; ISSN 0149-1423; ISSN AABUD2
• Country of Publication: United States
• Language: English

Related Subjects

02 PETROLEUM
DIAGENESIS
EXPLORATION
PETROLEUM DEPOSITS
POROSITY
REGRESSION ANALYSIS
RESERVOIR ROCK
RESOURCE POTENTIAL
SEDIMENTARY BASINS