Multivariate statistical analysis for monitoring the hydrocarbon potentiality of the source rocks in the North Western Desert,Egypt

The authors aimed to examine a multivariate statistical analysis approach for monitoring the hydrocarbon potentiality of source rocks in the North Western Desert to recognize the potentiality of source rocks and subsequently investigate the maturation level of the proven potential source formations for oil preservation. To achieve this aim, they applied multivariate statistics analysis (principle component analysis PCA], cluster analysis, and correlation coefficient) and Rock-Eval pyrolysis analyses. The results showed that both PCA and cluster analyses have showed two types of source rocks. The first is classified as poor to fair source rock and immature to marginally mature source rock, the second is considered as fair to good source rock and mature to post mature source rock. PCA extracted two independent factors, which explained 81.87% of the total variance. The first type of source rock was responsible for 50% of the total variance and was best represented by variables TOC, S2, OI, and R_o, and the second one was responsible for 31.65% of the total variance and was represented by the HI variable. Pearson correlation coefficient showed a significant positive correlation between TOC and S2 or R_o. A positive correlation between S2 and HI or OI and also between OI and R_o was observed, while no significant correlation was noticed between HI and R_o.