Grain Size Geostatistics Enhance Reservoir Characterisation
Robert Duller1, Ricki Walker2, and Barrie Wells2
Are we making valid assumptions when relying on correlations to underpin the construction of stochastic reservoir models in Petrel™? (www.slb.com) Many times during the course of constructing a geostatistical reservoir model we rely on significant correlations to allow a densely sampled secondary variable (typically derived from a seismic data set) to augment a primary variable such as porosity or permeability. This may or may not be justified but straightforward petrographic analysis performed in PETROG™ (www.petrog.com) can readily confirm or otherwise the assumption. Further, the same analysis, without further effort, can validate the principle assumptions of first and second order stationarity required for our data to give us unbiased models. That this is not routine is a symptom of a decline in ground-truthing which not only dismays old-school geologists, brought up on the principle that the rock itself is central to the story of the reservoir, but also confounds geostatistician, seeing their subject built on unreliable foundations.
AAPG Search and Discovery Article #90188 ©GEO-2014, 11th Middle East Geosciences Conference and Exhibition, 10-12 March 2014, Manama, Bahrain