Automatic lithofacies segmentation using the Wavelet Transform Modulus Maxima lines(WTMM) combined with the Detrended Fluctuation Analysis(DFA)

In this paper, we design and develop a new software tool that helps automatic lithofacies segmentation from geological data. Lithofacies is a crucial problem in reservoir characterization, and our study intends to prove that soft computing techniques like Wavelet transform modulus maxima lines (WTMM) and Detrended fluctuation analysis (DFA) approaches allow a geological lithology segmentation from differed well logging. On one hand, WTMM prove to be useful for delimitation of each layer. We based on his sensitivity on the presence of more then one layer, On the other hand, DFA is used to enhance the estimation if the roughness coefficient of each lithology. We use them jointly to segment the lithofacies of wells located in the Algerian Sahara. Obtained results are encouraging to publish this method, because the principal benefit is economic