Effects of Sedimentologic and Stratigraphic Heterogeneity on Production in Carbonate Reservoirs: An Integrated Outcrop, Synthetic Geologic Modeling, and Flow Simulation Study

Abstract

Most geoscientists recognize, characterize, and understand the many scales and types of heterogeneity in carbonate reservoirs; however, systematic quantitative assessment of the impact of this range of geological variations on production from carbonate reservoirs is rare. To explore and quantify the impact of geologic heterogeneity of hydrocarbon production from carbonate shoreface reservoirs, this study couples an outcrop-derived conceptual model and petrophysical data from reservoir analogs to generate a spectrum of simple geologic models of carbonate shoreface reservoir systems. The 25 geologic models, designed to isolate and evaluate the influence of geologic variables, capture a range of heterogeneity related to depositional geometry, facies stacking patterns, diagenetic surfaces and bodies, porosity distribution, and permeability distribution. A total of 750 flow simulations of these geologic models provide a means to quantify the impact, relative importance, and risk associated with each geologic factor on original oil in place (OOIP), production rate, and cumulative production. Results reveal how geological parameters influence OOIP and dynamic production measures. For example, in the absence of flow baffles (subaerial exposure surfaces or flooding units), the presence of clinoformal geometries does not markedly influence static or dynamic production metrics. In contrast, the presence of flow barriers along clinoform surfaces can result in marked (in excess of 30%) changes in production, accompanied by minimal change in OOIP. Changing either facies proportions (e.g. foreshore:upper shoreface:lower shoreface) or porosity (mean porosity) impacts both static and dynamic reservoir attributes, in many cases by more than 10% from the base model. Collectively, these results, derived from systematic analysis of a suite of simple (but fully constrained) models, quantify the impacts and risks associated with a range of geological parameters. These insights can be used to characterize, understand, and predict the important roles and risks of geological variability on production of comparable subsurface reservoirs.