An Innovative Methodology for Permeability Estimation in a Carbonate Sequence

Abstract

This paper discusses an innovative interpretation technique based on the integration of different logging-while-drilling tools to determine the secondary porosity and permeability indicator in horizontal wells drilled in a carbonate sequence. The study was initiated because for many carbonates, traditional density-neutron porosity, even after calibration to the cores, is only marginally useful for predicting production performance. Consequently, new methods are required for better permeability predictions in such cases. One such method is introduced based on the analysis of vugs. To determine these vugs, a methodology was introduced that grouped, analyzed, and interpreted available data in a new way. Secondary porosity was estimated and then integrated with average resistivity and conventional density-neutron porosity measurements, which enabled permeability estimates by calibrating them to any other source of permeability indicators; in this case, formation tester mobility measurements were used. Based on this analysis, the horizontal section was partitioned into several permeability zones according to their petrophysical properties. As a result, several independent measurements were observed to correlate satisfactorily in this environment, which facilitated qualitative permeability predictions and the potential detection of the best production zones. The method was then applied on several additional wells to confirm the relationships and reduce uncertainty within the reservoir sector where data is available. This paper is based on a previously published work using logging-while-drilling measurements recorded in heterogeneous carbonate reservoirs for predicting permeability estimates. It incorporates multiple well analyses using the same technique, as well as a discussion on the viability, integrity, and reliability of logged data and interpreted results. Additional investigation is desirable to better understand the applicability of this method with the integration of other offset data and existing field knowledge.