Simulation of Geochemical Log Using CACS Algorithm Based on Clustering Analysis

One of the important geochemical parameters used to evaluate the hydrocarbon potential of source rock is total organic carbon (TOC). TOC measurement is time-consuming and rather expensive and considerable number of drill hole samples including core or cuttings have to be analyzed. In this study, TOC values were estimated initially using petrophysical logs generally available from drilled wells. For this purpose, an ant colony system was used based on hierarchical clustering analysis. The first stage was comprised of hierarchical clustering and the second stage included ant colony system, which was designed continuously with a normal probability distribution function. Continuous ant colony system (CACS) calculated weight coefficients of nonlinear proposed function for the petrophysical data of each cluster. The results show that this algorithm has a successful performance in combination with clustering for the estimation of TOC log. Using these coefficients and petrophysical data, TOC log can be generated for other wells in this field. This study is based on the data collected from three wells of the Ahwaz oilfields and can be generalized to other developmental wells.