A fully integrated petrophysical characterization is necessary to accurately identify the mineralogy and fluid types contained in source rock reservoirs. This characterization is the foundation for sweet spot mapping and landing zone optimization. The complex mineralogy associated with source rocks requires modeling to take into account the effects of total organic carbon (TOC), clay volume and heavy minerals in order to properly determine the various matrix and fluid types. Petrophysical interpretation utilizing log, core, and geomechanics data is needed to predict zones of producible hydrocarbons. In this study, we incorporated nuclear magnetic resonance (NMR) (Mirth et al., 1999), dielectric dispersion (Hizem et al., 2008), capture spectroscopy logs (Radtke et al., 2012), x-ray diffraction analysis (XRD), scanning electron microscope images (SEM), crushed rock porosity and permeability, vitrinite reflectance analysis (VR), dipole sonic logs and geochemical /geomechanical core analysis to determine the quantity and quality of the resource.
This study describes the techniques for building a calibrated multi-mineral petrophysical model based on advanced datasets. The advanced dataset model was then used to develop a workflow for wells that only had triple-combo data. We discuss the methodology and pitfalls of our unconventional petrophysical workflow and guidelines for applying this technique in a larger regional context.
The Permian Basin is located in the western portion of Texas and southeast New Mexico and encompasses approximately 86,000 sq. mi. (222,739 sq. km.) It has produced over 29 billion barrels of oil and 75 trillion cubic feet of gas since the first discovery well in 1923 (Ball, 1995). It is typically divided as seen here between the Delaware Basin, Central Basin Platform, and Midland Basin (Figure 1.).