Heterogeneity study of the Little Creek field from petrophysical data

Reservoir characterization determines the quality and characteristics of a subsurface body to accumulate and produce oil. This characterization involves the study of reservoir heterogeneity, which has the objective to estimate the variability of geological properties directly related to flow and, consequently, they have a great impact in the overall production of the field. Although a thorough analysis of heterogeneity is performed, it is common to estimate the reservoir heterogeneity with screening tools that offer a brief assessment of the variability in the field. Nevertheless, there is a tendency of the screening methods to either i) consider the petrophysical data as an indivisible set, or ii) to not relate flow performance with heterogeneity. Otherwise, the decisions executed based on an inaccurate model would be wrong. Thus, this thesis focuses to overcome the previous drawbacks studying the interstitial velocity of the Little Creek field with two methods. First, statistical partitioning attempts to associate the producing sandstones of the field in terms of the assumed constituent parents. Second, the Koval theory is used to better estimate the heterogeneity as a function of the recovery process to be undertaken and to forecast the flow performance of an immiscible process as a function of the more representative heterogeneity appraisal. Even though the statistical partitioning did not correlate lognormal distributed parents with the producing facies, insightful results were obtained from this work. First, the overall interstitial velocity of the field, and from most of the wells studied, do not follow any of the probability distributions studied in this thesis. Second, roughly 73% of the wells studied are statistically different in their interstitial velocity means, standard deviations, or both. Third, the region within flow and storage capacities less than 90% are more meaningful for a practical recovery process. Finally, the Koval theory estimates the heterogeneity at the intra-well scale and predicts better production performance for low heterogeneous reservoirs, agreeing with field results. Hence, the Koval theory could be categorized as a reliable screening tool to estimate heterogeneity and accurately forecast the performance of recovery processes that are immiscible, like waterfloods. In other words, it is a helpful method to complement a successful reservoir characterizationPetroleum and Geosystems Engineerin