Improved Total Organic Carbon (TOC) Prediction for Vaca Muerta Shale

Abstract

TOC evaluation in Vaca Muerta is challenging due to its complex mineralogy and depositional settings. Laboratory measurements can be affected by sample preparation, especially for wells drilled with oil-based mud. Empirical methods like Passey ∆log R relies on resistivity as one of the inputs, which can be affected by clay and mineralogy in shale. In this study, an improved TOC prediction using a multiple regression equation is proposed. The findings reflect the vertical variability of TOC. The method developed in this study first evaluates the TOC correlation with available electrical logs from a vertical well that includes spectral gamma ray, neutron porosity, density and resistivity. It also assesses the correlation with clay and inorganic mineralogy available from X-ray diffraction. This study also incorporates for the first time, thin bed heterogeneity that comprises calcite beef, ash beds and nodules. They make up a considerable portion of the facies, especially in the organic-rich unit of Lower Vaca Muerta (LVM). Despite the complexity, the modelled TOC calibrate well with the laboratory-measured TOC. The TOC regression equation is developed based on two key findings. First, the TOC is positively correlated with uranium and resistivity; and negatively correlated with dolomite and calcite. High TOC is observed in low Ca (calcite, dolomite and ankerite) and high QFP (quartz, k-feldspar and plagioclase) intervals, and vice versa. This negative correlation is unique to Vaca Muerta, which is attributed to the mixed carbonate-siliciclastic depositional system (Kietzmann et al., 2014). Second, the TOC is also strongly affected by thin bed heterogeneity that is identified through micro-resistivity image log and high-resolution logs. Their effect is more pronounced on resistivity log; therefore, an adjustment factor is applied to the regression to account for their presences. Results show that the modelled TOC match well the core TOC as compared to Passey ∆log R method. An important observation is that the Passey ∆log R technique would overestimate the TOC at the top of Upper Vaca Muerta due to high and resistive Ca content; and underestimate it in LVM due to conductive clay in the argillaceous ash beds. Consequently, it would mislead the estimation of reservoir thickness, identification of sweet spot for landing zones, as well as resource estimation in Vaca Muerta shale. This paper develops an original regression equation that models TOC in the presence of thin bed heterogeneity in Vaca Muerta. The results compare well with the laboratory-measured TOC. The study reveals the vertical variability of TOC across the five stratigraphic units in a vertical well. More importantly, it highlights potential TOC discrepancy by Passey ∆log R technique that could mislead reservoir thickness estimation due to the effects of mineralogy and thin bed heterogeneity on resistivity.