BLOCH, S., ARCO Exploration and Production Technology, Plano, Texas

ABSTRACT: Predrill Reservoir Quality Prediction in Sandstones

Mean porosity and permeability of many sandstone intervals can be predicted accurately prior to drilling. The predictive technique involves use of multivariate regression equations derived from appropriate calibration data sets. The effectiveness of this approach has been proven by numerous case studies, including successful predrill porosity and permeability predictions in a number of sedimentary basins.

The critical independent variables controlling porosity are detrital composition, sorting, temperature history, and/or pressure history. Permeability can be predicted independently of porosity using similar independent variables. Importantly, the independent variables, that correlate with porosity and permeability, often can be estimated prior to drilling from facies models and seismic data.

Accurate empirical predictions of total porosity can be made for sandstones containing secondary porosity, particularly where secondary porosity is formed predominantly by dissolution of framework grains. This is possible because the presence of secondary porosity is implicitly accounted for by the calibration data set that provides the basis for empirical predictions.

The predictive applicability of the empirical approach is constrained by the limits imposed by the calibration data set. Furthermore, this approach generally is limited to samples containing less than 10% cement. However, a satisfactory predictive model for samples with a wide range in cement content can be obtained by dividing the calibration data set into two or more subsets and developing a predictive model for each of the subsets. For example, porosity and permeability in the first subset can be expressed by multivariate regression equations, whereas reservoir quality in the more heavily cemented samples can be estimated prior to drilling if the geologic factors controlling the spatial distribution of the cement or cements are predictable.

AAPG Search and Discovery Article #90990©1993 AAPG International Conference and Exhibition, The Hague, Netherlands, October 17-20, 1993.