Analytic formulation for subsurface volumetric estimation

Abstract

We have developed an analytic formulation for quick and more accurate volumetric estimations of subsurface resource potential. Our formulation is conceptually based on a structurally conformable model built deterministically using known and interpreted reservoir properties from wells, such as net-to-gross, porosity, and hydrocarbon saturation, along with oil-water contact or lowest known oil depth and interpreted seismic top-of-pay depth horizon. We have evaluated an important function, the hydrocarbon pore capacity (HPC), which is a product of net-to-gross, porosity, and hydrocarbon saturation. HPC reflects the heterogeneity of key reservoir rock and fluid properties, particularly in the vertical direction. We calculated the total hydrocarbon pore volume directly from HPC and the top-of-pay horizon, without the explicit need for building a geologic model first. Our efficient solution form can preserve the vertical resolution of wireline logging with transparent parameterization and the least amount of averaging and upscaling. We also provided additional formulation for incorporating different HPC regimes for cases of multiple existing wells in the reservoir. We demonstrate the practical application of the formulation with a data example from a Cretaceous carbonate reservoir in the southern Gulf of Mexico offshore and with comparisons to other common approaches. In the application example, we determine that the most common approach of using single-average-values can underestimate the reserve upside by as much as 30%, whereas the stochastic modeling approach provided improved estimates when simulating porosity with a lognormal distribution and preserving the net-to-gross log in its original vertical resolution.