Heterogeneity in the Petrophysical Properties of Carbonate Reservoirs

In comparison to sandstone reservoirs, carbonate exploration is commonly more challenging because of intrinsic heterogeneities, occurring at all scales of observation and measurement. Heterogeneity in carbonates can be attributed to variable lithology, chemistry/mineralogy, pore types, pore connectivity, and sedimentary facies. These intrinsic complexities can be related to geological processes controlling carbonate production and deposition, and to changes during their subsequent diagenesis. The term 'heterogeneity' is rarely defined and almost never numerically quantified in petrophysical analysis although it is widely stated that carbonate heterogeneities are poorly understood. This work has investigated how heterogeneity can be defined and how we can quantify this term by describing a range of statistical heterogeneity measures (e.g. Lorenz and Dykstra-Parsons coefficients). These measures can be used to interpret variation in wireline log data, allowing for comparison of their heterogeneities within individual and multiple reservoir units. Through this investigation, the Heterogeneity Log has been developed by applying these techniques to wireline log data, over set intervals of 10, 5, 2 and 1m, through a carbonate reservoir. Application to petrophysical rock characterisation shows a strong relationship to underlying geological heterogeneities in carbonate facies, mud content and porosity. Zones of heterogeneity identified through the successions show strong correlation to fluid flow zones. By applying the same statistical measures of heterogeneity to established flow zones it is possible to rank these units in terms of their internal heterogeneity. Both increased and decreased heterogeneity is documented with high reservoir quality in different wireline measurements, this can be related to underlying geological heterogeneities. Heterogeneity Logs can be used as a visual indicator of where to focus sampling strategies to ensure intrinsic variabilities are captured.