Identificação de fácies em perfis de poço com algoritmo inteligente

Abstract

Facies identification in an uncored borehole is a classic problem in formation evaluation. In this study, this problem is treated as the extraction of geological information or facies descriptions from a cored borehole in terms of their physical properties registered in well logs and perform their encoding through the parameters L and K calculated from porosity logs, and shaliness calculated using the natural gamma ray log to construct the Vsh-L-K plot. For interpretation is presented an intelligent algorithm based on the competitive generalized angular neural network, built for angular pattern classification or data clustering in ndimensional space that have an approximately ellipsoidal envelope, which are the characteristics of clusters in the Vsh-L-K plot and make your visual interpretation extremely complex. The application of intelligent algorithm is able to identify and classify the layers present in uncored boreholes, in terms of the facies identified in the cored borehole or in terms of its main mineral, when it is absent in the cored borehole. This methodology is presented with synthetic data and well logs from cored boreholes in Namorado oil field, in the Campos Basin, located on the continental shelf of Rio de Janeiro, Brazil.