Abstract

A pilot study of 13 wells in the Means oil field of the Permian basin, West Texas, established the porosity and permeability relationships in the Permian Queen, Grayburg, and San Andres formations. An optimized workflow that used borehole image and conventional log processing with calibration to core data, quantified porosity and permeability heterogeneity in vuggy carbonate facies in the field. In different vuggy zones of the San Andres formation, with similar total porosity values of approximately 8%, permeability varied by 2 to 3 orders of magnitude. This variation was modeled by an exponential relationship between permeability and the vuggy porosity partitioned from borehole image processing. A methodology using a modified sonic porosity analysis estimates the vuggy porosity index. Permeability estimation, using both the vuggy porosity partitioned from borehole image logs and the vuggy porosity index from conventional logs, provides thief-zone identification for optimized well completion. In the San Andres formation, vugs developed in thin zones and resulted in layer-cake structures of thin, superpermeable zones sandwiched between thicker, nonvuggy zones with bypassed oil. The averaged conventional-log porosity in the thin zones, which were below log resolution, resulted in an erroneous permeability profile because of the exponential relationship between vuggy porosity and permeability. Similarly, the thin-bedded Grayburg silieiclastic and dolomite facies roeks, which were generally thought to be poor reservoirs in this field, exhibit significant vertical variation in porosity and permeability. Petrophysical rock types were differentiated using image and conventional log data and neural network processing. The integration of log-derived permeability and rock type with production data provided the basis for interwell heterogeneity prediction and fieldwide completion strategies.