The Borehole Properties Analysist Using Advanced Algorithms and Automatic Inversion

Abstract

The study is based on multi well analysist drilled side by side in carbonate reservoir using high-resolution resistivity image. The objective is to define reservoir characterization, facies architecture, heterogeneity, and connectivity between two wells that is ready for reservoir modeling. The methods presented in this paper are using an automatic inversion and advanced algorithm to generate matrix conductivity images and curves, histogram, analyses rock texture heterogeneities, quantify fluid filled vugs density from high resolution borehole images, fast extraction of dips (beds, fractures), delineate planar features crossing deviated borehole over long distances, extract fracture traces and statistics. More than 3,000 picks of boundaries and fractures were found in a 3,300 ft horizontal length. Those divided into 6 different categories (Bed Boundary, Conductive Fracture, Discontinuous Conductive Fracture, Resistive Fracture, Litho-Bound Fracture, and Vugular fracture). Using high-definition imaging-while-drilling service provides supreme logging-while-drilling (LWD) imaging for reservoir description, from structural modeling, sedimentology analysis, image-based porosity determination and thin-bed analysis. The presence of heterogeneity in carbonates poses a challenge for the characterization of such rocks. The identification of textural variations advanced techniques in borehole image analysis have been applied and presented good results that determine secondary porosity and litho-facies, and, moreover, delivered new insight into previously established interpretations of the reservoir. The data comparison and validation to other measurement show a significant relationship to bring the value even beyond. By using an automatic inversion, the geological interpretation can be constantly delivered around the clock with higher consistency with the number of feature variation. It has been demonstrated that with the advanced analysis, microelectrical borehole images can provide quantitative measures of important reservoir parameters. Accuracy and consistency have been greatly improved since the introduction of microelectrical borehole image logging and subsequent automatic interpretation workflows.