Enhanced Assessment of Water Saturation in Organic-Rich Mudrocks Incorporating the Vertical Heterogeneity Through Resistivity Image Logs

Abstract

Reliable assessment of hydrocarbon saturation is essential for reserves evaluation, which can be straightforward using resistivity well logs in formations with well-connected pore structures where water can be considered as the only conductive component. It is, however, challenging in the case of organic-rich mudrocks, where calibration efforts become extensive. Conventional resistivity-based models do not consider all the conductive rock components that contribute to the conductivity of the rock. Application of resistivity models in organic-rich mudrocks is challenging due to high vertical heterogeneity and significant shoulder-bed effects. In this paper, we introduce a new workflow for the assessment of water/hydrocarbon saturation in organic-rich mudrocks, which enables direct incorporation of borehole image logs for honoring rock fabric (i.e., the spatial distribution of rock components). First, we estimate the layer boundaries from resistivity image logs. Then, we perform rock classification of the identified layers. The volumetric concentration of various minerals for each rock class is populated from zones of the same rock classes where their thickness is beyond a threshold value. This reduces the shoulder-bed effects in the evaluation of well logs in thin laminations. We then estimate the geometric model parameters, which are shape-related factors, for each rock class and, subsequently, the depth-by-depth water saturation. Additional inputs to the workflow include the volumetric concentration and electrical conductivity of minerals and porosity estimates from preliminary formation evaluation. We successfully applied the introduced methods to multiple wells in the Wolfcamp formation. We estimated water saturation using the introduced workflow. The estimates of water saturation from the new method improved by 40.8% and 48.4%, relatively, compared to those obtained from Archie’s and Waxman-Smits models, respectively. The results showed an improvement of 22.2%, relatively, when water saturation was estimated by incorporating the resistivity image logs compared to the case where resistivity image logs were not used for the assessment of hydrocarbon saturation. A comparison of the results showed significant improvement in water/hydrocarbon saturation assessment in the Middle Wolfcamp formation, where the heterogeneity detected from the resistivity image logs was higher than that of the other zones. The novelties of this workflow include (a) improving the evaluation of hydrocarbon reserves in highly heterogeneous rocks such as organic-rich mudrocks, (b) incorporating the rock fabric information with the help of high-resolution borehole resistivity image logs into the workflow for assessment of water saturation, and (c) providing improved reserves estimates without the need for core-based calibration for water saturation.