Hydrocarbon saturation in upper Wolfcamp shale formation

Abstract

Water saturation (Sw) and hydrocarbon saturation (Shc=1-Sw) estimates in hydrocarbon-bearing formations are generally derived from Dean-Stark core measurements, NMR log, and electromagnetic (EM) logs, such as induction log, galvanic resistivity (laterolog), or dielectric dispersion logs. In-situ estimation of hydrocarbon saturation in conventional reservoirs primarily rely on the deep-sensing or high-resolution EM logs. However, in the hydrocarbon-bearing shale formations, hydrocarbon saturation estimates obtained from EM logs tend to be unreliable. Conventional EM-log-interpretation models tend to break down for shale formations because they neglect the interfacial polarization effects and the dispersive behavior of EM properties of such geomaterials. This can be addressed by jointly processing the subsurface galvanic resistivity, induction, propagation and dielectric dispersion logs using an integrated model that accounts for the interfacial polarization mechanisms.One galvanic resistivity (laterolog) and dielectric dispersion logs, comprising 4 conductivity and 4 dielectric permittivity logs measured at four distinct frequencies, were acquired in a 520-feet depth interval of a well drilled in the upper Wolfcamp shale formation. We implement a novel log interpretation technique for the improved estimation of water saturation (Sw), brine conductivity (Cw), textural index/cementation exponent (m), and saturation exponent (n) in the upper Wolfcamp shale. Log processing was performed with an integrated mechanistic model, which combines Complex Refractive Index (CRI) model to analyze the conductivity and permittivity logs acquired at 1 GHz, Stroud-Milton-De (SMD) model to analyze the 3 conductivity dispersion and 3 permittivity dispersion logs in the frequency range of 10 MHz to 0.3 GHz, and Waxman-Smits (WS) model to analyze the deep galvanic resistivity log (RLA5) measured by the EM laterolog tool at 1 kHz.In the upper Wolfcamp shale, estimates derived from the joint inversion were robust in the presence of pyrite, low water saturation, and low porosity as compared to estimates from the inversion of only four-frequency dielectric dispersion logs. Formation brine conductivity and saturation-exponent estimates are more reliable compared to water saturation and cementation exponent estimates. Water saturation estimates obtained using the proposed methodology are compared against those obtained using multi-mineral inversion and those derived using CRIM model. Average relative errors in fitting the 1 laterolog resistivity and 8 dielectric dispersion logs using the estimates obtained from the proposed method are 10% and 20%, respectively, and their extreme values are 55% and 60%, respectively, in the 520-ft depth interval of the upper Wolfcamp shale formation.