Geologically-Realistic Facies Distribution in Static Reservoir Models for CO2 Sequestration: From Core to Wireline Logs to Grid Cells

Abstract

The Precipice Sandstone and Evergreen Formation are an important target for potential carbon sequestration in the Surat Basin, Australia. However, the geological data necessary to characterize flow units and build reliable static reservoir models is mostly absent from the basin centre where prospective storage is the highest. To deal with this limitation, detailed facies analysis was undertaken on the relatively limited core dataset, comprising 8 wells and over 2000 m of cumulative section. From this, neural networks were trained to recognize facies using wireline logs as a means to predict the distribution of geological units across the basin. Facies from 186 wells were used to produce basin wide gross depositional environment maps and the maps allowed type locations to be identified to showcase the range of possible scenarios at the basin centre where injection potential is the highest. Facies predictions were upscaled to grid cells and these then helped guide object modelling of geobodies. The result was geologically-realistic facies distributions that controlled parameterization of three alternative static models. This work is an important contribution to the world of reservoir modelling, as it shows an important method that can be used to predict a range of possible geobody distributions and corresponding flow units in areas where data is limited.