January Monthly Luncheon

A primary task of the petroleum geologist is to integrate and evaluate all available core, mudlog, DST, and log data associated with a well to identify zones of interest likely to produce commercial hydrocarbons (“pay zones”). In the Permian Basin, the availability of core, mudlogs, and/or DSTs is a rare treasure, resulting in the reliance upon open hole well log data of various vintages as the primary tool for determining the presence of moveable hydrocarbons. Often this log analysis takes the form of calculating water saturation (Sw) from the Archie equation using standard parameters (a=1, m=2, n=2) and applying minimum porosity and maximum Sw cutoffs to flag potential pay zones.

However, log analysis in carbonate reservoirs can present unique challenges. When a carbonate reservoir has textures and pore types similar to the sandstones used to develop Archie’s equation (i.e., interparticle pores), the calculation of Sw from well logs is relatively straightforward. Yet carbonates are extremely susceptible to cementation and dissolution and often contain non-Archie pore types (e.g., intraparticle, vuggy, moldic, etc.), which may grossly violate the assumption of m=2 (if m>2, calculated Sw is lower than actual) and inherently possess a higher relative permeability to water. Without alternative methods to confirm the standard Archie Sw assumptions, porosity and Sw cutoffs alone are inadequate for differentiating between a profitable target and an uneconomic teaser.

To address these challenges, over the decades several authors have established empirical relationships and interpretation techniques that provide insight into the pore types present, predict the fluid produced, and better estimate Sw using common open hole log suites. The Carbonate Well Log and Core Analysis spreadsheet tool brings together many of these underutilized log analysis techniques advocated by Dr. George Asquith and others to rapidly screen and de-risk potential pay zones in carbonate reservoirs. When routine core data and/or capillary pressure data is also available, additional productivity insights can be gained by comparing log analysis results with core-derived s