Abstract

The gamma ray log has over the years provided the conventional means for shale volume (Vsh) estimation. Knowledge of Vsh is used in the prediction of petrophysical parameters like effective porosity and water saturation, which are the input parameters for the calculation of oil in place. Currently, many studies have been conducted on the Bornu Basin of Nigeria, to access its hydrocarbon potential. Unfortunately, the practice of using best gamma ray log value for the computation of gamma ray index, IGR, and subsequently Vsh estimation incorporates huge uncertainty in the estimated volumes. Uncertainty is best captured when estimates are represented in a possible range rather than single value measurements. To the best of our knowledge, this is the first time shale volume has been estimated from the gamma ray log using sampling techniques. The gamma ray log data of the two upper shaly intervals of the NGAMMAEAST_1 well, which penetrates the Gombe formation of the basin, were utilized for this study. The gamma ray log response of the zone of interest is the uncertain parameter in Vsh estimation. A histogram plot of the uncertain log data was used to assume the probability distribution of the data. In the MATLAB platform, Standard Monte Carlo (MC) and Latin Hypercube sampling techniques were used to model the uncertain log response using random numbers. Possible input log data generated from the distribution of the uncertain log data were used in the linear and non-linear models for shale volume estimation to run a series of simulations to determine the possible range of estimates with their probabilities. The Latin hypercube method has shown to be a quick and accurate alternative method to the standard MC method. The approach presented here sets a guideline for the implementation of a probabilistic approach for the volume of shale estimation.

Key words: Shale volume, Monte Carlo, Latin hypercube, sampling techniques, gamma ray log.