Abstract: A Case Study on Using Geostatistical Data Integration for Porosity Prediction in a Complex Carbonate Reservoir in West Texas

Joseph G. Gallagher Jr., Gary M. Hoover

Geostatistical methods have been used to integrate dense, 3-D seismic amplitude information with sparse, well log porosity data to predict porosity variations on the scale of the CDP spacing in seismic data in a complex carbonate reservoir of the Permian basin, West Texas. The porosity variations in these shelf carbonate environments are highly variable in an areal sense and do not conform to a predictable stratigraphic framework. This setting makes geostatistical data integration methods, which use data with different scales of spatial density, a useful took for obtaining improved maps of porosity and its uncertainty. In this case study, comparisons were made in the porosity predictions from ordinary kriging and stochastic geostatistical methods using well log porosity d ta alone and integrating well log porosity with 3-D seismic amplitude data. The porosity predications and their uncertainty were then checked by comparing the geostatistical-predicted average porosities with the well log porosities from 25 new infill wells, drilled for a waterflood project. Comparisons showed that a stochastic geostatistical data integration of well log porosities and 3-D seismic amplitudes provided a superior porosity prediction over using just well log porosities. Using one standard deviation in the average porosity as the prediction criterion, 72 percent of wells were predicted by the data-integrated porosity estimates while only 44 percent were predicted using well log porosities alone.

AAPG Search and Discovery Article #90960©1995 AAPG Southwest Section Meeting, Dallas, Texas