LAUSR

Identification with accuracy of prospective and dry zone from well log data is of prime importance in reservoir or hydrocarbon studies. This issue has greater stake, where in return many conventional methods have been established. The purpose of this study is to recognize the hydrocarbon and non-hydrocarbon bearing portion within a reservoir by using a non-conventional technique. Application of rescaled range (R/S) analysis and wavelet-based fractal analysis (WBFA) on the wire-line log data to obtain the pre-defined hydrocarbon (HC) and non-hydrocarbon (NHC) zones by their fractal nature is demonstrated in this paper. Among these two techniques, the WBFA tool has provided more prolific results. Applicability of the proposed approach is tested with the help of the most commonly used well log data like self-potential, gamma ray, and porosity log responses. These are used in the industry to distinguish several HC and NHC zones of all wells in the study region belonging to the Upper Assam Basin, India. The results are found to be of lower fractal dimension in this study for a particular log response having HC-bearing zones, which are mainly situated in a variety of sandstone lithology. On the other hand, NHC-bearing zones correspond to lithology with higher shale content categorized with higher fractal dimension. Hence, the WBFA technique can overcome the chance of misinterpretation, which is quite possible in the case of conventional reservoir characterization.