Acid etching, as the consequence of heterogeneous distribution of petrophysical and compositional properties, results in the conductivity of acid fractures in carbonate reservoirs. Reliable characterization of small-scale formation spatial heterogeneity by use of geostatistical analysis (i.e., variogram analysis) can improve prediction of acid-fracture conductivity significantly. Previous publications suggest that permeability correlation length can be used to assimilate spatial heterogeneity in prediction of acid-fracture conductivity. Well logs are good candidates to provide information about petrophysical and compositional properties of the formation with the required resolution for prediction of acid-fracture conductivity. However, the assessment of permeability and mineralogy from conventional well logs is challenging because of high spatial heterogeneity and complex pore structure. Rock typing has been suggested in the literature to improve permeability assessment in carbonates. Most of the previously introduced rock-typing methods are dependent on core measurements. However, core data are generally sparse and not available with the sampling rate required for prediction of acid-fracture conductivity.
The main objective of this paper is to quantify formation spatial heterogeneity with variogram analysis of well logs and well-log-based estimates of petrophysical and compositional properties in carbonate reservoirs. We introduce an iterative permeability-assessment technique that is based on well logs, which takes into account characteristics of different rock classes in the reservoir. Furthermore, we propose three rock-classification techniques that are based on conventional well logs and that take into account static and dynamic petrophysical properties of the formation as well as mineral composition.
We applied the proposed techniques successfully in two carbonate formationsHappy Spraberry oil field and Hugoton gas field. The petrophysical rock classification is in good agreement with identified core-derived rock classes. The results show approximately 54% improvement in permeability assessment compared with conventional permeability-assessment techniques, which can improve prediction of acid-stimulation jobs significantly. Finally, we investigated the direct application of well logs and well-log-based estimates of petrophysical and compositional properties for variogram analysis required to characterize formation spatial heterogeneity. We conducted variogram analysis in both field examples. The results show that the direct application of well logs and well-log-based estimates of petrophysical/compositional properties is reliable to characterize formation spatial heterogeneity. We also showed that application of well logs can enhance assessment of spatial heterogeneity compared with core measurements.