Geostatistical integration of core and well log data for high-resolution reservoir modeling

Analyzing data derived from well logging and core plugs to understand the heterogeneity of porosity in geologic formations is paramount in petrological studies. The well-log data and core-plug data are integrated in order to generate an accurate model describing the porosity distribution; however these data exist at different scales and resolution. This difference necessitates scaling of one or both sets of the data to aid in integration.;The present study established a geostatistical scaling (GS) model combining mean, variance, skewness, kurtosis and standard deviation with a misfit algorithm and sequential Gaussian simulation to integrate porosity data in conjunction with correlating the depth of core-plug data within the well-log data through a scaling process. The GS model examined well-log porosity data from a Permian-age formation in the Hugoton Embayment in Kansas and well log data from a Cretaceous-age formation in the GyeongSang Basin in The Republic of Korea. Synthetic core-plug porosity data was generated from well-log data with random number generation.;The GS model requires basic histograms and variogram models for scaling the computerized tomography (CT) plug data to well log scale as well as integrating the data in a sequential Gaussian simulation. Variance-based statistics were calculated within specific intervals, based on the CT plug size, then a best fit for depth correlation determined. A new correlation algorithm, named the multiplicative inverse misfit correlation method (MIMC), was formulated for accurate depth correlation. This associated depth then constrained the well log porosity data at reservoir- or field-scale to interpolate higher-resolution porosity distributions.;Results for all the wells showed the MIMC method accurately identified the depth from which the CT plug data originated. The porosity from the CT plug data was applied in a sequential Gaussian co-simulation, after kriging the well log data. This culminated in a greater refinement in determining the higher porosities distributions than the interpolation of solely the well log data. These results validate the proposed high-resolution model for integrating data and correlating depths in reservoir characterization.