Multi-Scale Interpretation of Electrical Resistivity Measurements in the Presence of Complex Pore Structure and Anisotropy

Abstract

Integrating the petrophysical properties obtained from fine scale (e.g., core scale and pore-scale) and coarse scale (e.g., well-log scale and reservoir scale) has always been a challenge. Core data and well-log interpretation results are well comparable in isotropic conventional reservoirs. However, in anisotropic and heterogeneous formations such as carbonates, core-log integration is challenging and the fluid saturations estimated from well logs are often not comparable to core measurements. Previous publications confirmed that the correlations between formation factor versus porosity can persist over a wide scale range in isotropic and homogeneous rock types. However, these correlations do not persist in rocks with complex pore structure. In this paper, we introduce a directional connectivity tensor to quantify directional connectivity of rock components (e.g., water and pyrite), quantify rock fabric using the introduced directional connectivity tensor, and investigate the persistence of correlations between electrical resistivity and the directional connectivity parameter at different scales in anisotropic rocks. We first process and digitize the three-dimensional (3D) pore-scale rock images and divide each pore-scale volume into smaller subsamples. Afterwards, we estimate the tortuosity of rock components in each subsample using a random walk algorithm. The directional connectivity tensor is calculated based on the estimated tortuosity, volumetric concentration, and shape of each conducting component in the subsamples. We numerically solve the Laplace's equation to estimate electric field distribution and effective conductivity of samples. The results from five carbonate rock types showed that a persistent correlation exists between multi-scale resistivity measurements, if the rock fabric and directional connectivity of the pore structure are taken into account. Taking into account rock fabric and directional connectivity of conductive rock components in multi-scale formation evaluation is essential for (a) improved assessment of fluid saturations using integrated interpretation of multi-scale measurements, (b) core-log integration for reliable formation evaluation, and (c) completion decisions for selecting the zones with the highest pore-network connectivity. The outcomes of this work is also promising for pore network connectivity assessment using multi-scale formation data (e.g., electrical resistivity), which has not been pursued previously.

AAPG Datapages/Search and Discovery Article #90259 ©2016 AAPG Annual Convention and Exhibition, Calgary, Alberta, Canada, June 19-22, 2016