PERMEABILITY AND POROSITY DISTRIBUTION PATTERNS IN A SHOREFACE RESERVOIR: LOWER CRETACEOUS FLACOURT FORMATION, BARROW SUB-BASIN, NORTH WEST SHELF, WESTERN AUSTRALIA

Abstract

Porosity and permeability measurements on 926 core plugs were taken from 18 exploration, wildcat and producing wells from the Lower Cretaceous Flacourt Formation, Barrow Sub-basin and analysed for their spatial and temporal variability using both sedimentological and geostatistical methods.

The porosity and permeability distribution shows a strong relationship to depositional facies and diagenetic modification. The samples are variably cemented with porosity ranging from 1.3 to 39.4 per cent and permeability from less than 0.01 to 24,400 md. Both porosity and permeability exhibit strong heterogeneity as a result of change of the depositional facies within the same well and the amount of detrital matrix within each facies.

The degree of spatial and temporal variability observed in both porosity and permeability data is well reflected by the Levy-stable statistical analysis and variogram modelling. The heterogeneity is shown to be strongly controlled by texture, composition and sedimentary structures of the specific sedimentary facies. The heterogeneity of both permeability and porosity for each individual facies was characterised by the correlation length in the vertical direction from both the variogram and Levy C-gram analyses, and Levy index parameter.

The sands of the Flacourt Formation, which form the principal reservoirs in the Barrow Sub-basin, were deposited in a paralic environment. Five major facies were recognised including a tidal channel, an upper shoreface, a middle shoreface, a lower shoreface and a background facies.

Sedimentological and statistical analysis of the porosity and permeability of the Flacourt Formation shoreface sandstones enabled us to better understand the heterogenity of the petrophysical properties. The finding can be used to understand similar heterogeneous reservoirs elsewhere, and will provide a basis for reservoir simulations. We have shown that the approach of using genetically related sedimentary facies, can significantly improve the predicability of the porosity and permeability distribution.