Probabilistic neural method combined with radial-bias functions applied to reservoir characterization in the Algerian Triassic province

Abstract

In this paper, we combine a probabilistic neural method with radial-bias functions in order to construct the lithofacies of the wells DF01, DF02 and DF03 situated in the Triassic province of Algeria (Sahara). The determination of lithofacies is a crucial problem in reservoir characterization. Our objective is to facilitate the experts' work in the geological domain and allow them to obtain quickly the structure and nature of the land around the drilling. This study intends to design a tool that helps automatic deduction from numerical data. We use a probabilistic formalism to enhance the classification process initiated by a self-organized map procedure. Our system gives the lithofacies, from well-log data, of the reservoir wells concerned in a way that is easy to read by a geology expert who identifies the potential for oil production at a given source and so forms the basis for estimating the financial returns and economic benefits. © 2004 Nanjing Institute of Geophysical Prospecting.