Time-Lapse Variations of Multi-Component Electrical Resistivity Measurements Acquired In High-Angle Wells

Abstract

Measurements of electrical conductivity anisotropy are becoming increasingly common in LWD and open-hole environments. At the same time, field experience indicates that invasion and time of logging can have a significant effect on multi-component induction measurements acquired in high-angle wells, specifically in the presence of highly permeable formations and large fluid density and viscosity contrasts. Some efforts have been made to study these effects, but the actual spatial distribution of fluid saturation due to invasion has not been considered previously. We use a commercial multiphase fluid-flow simulator to reproduce invasion behavior in high-angle wells. Simulations provide an effective and reliable environment to study time-lapse effects of different geometrical and petrophysical parameters on the ensuing spatial distribution of fluid saturation. The study considers the effects of both water- and oil-base muds invading hydrocarbon-bearing formations in interbedded sand-shale sequences. Simulations show that gravity segregation causes off-centered and asymmetric spatial distributions of electrical resistivity in high-angle wells. Further, no-flow boundary conditions at impermeable shale boundaries cause high local concentrations of mud-filtrate. These effects can vary significantly with time. Depending on the time of measurement acquisition, three-dimensional (3D) effects due to invasion can distort multi-component apparent resistivity estimates. Consequently, inversion techniques should not be blindly used to synthesize all the measurements into estimates of conductivity anisotropy. It is necessary that 3D effects, including those due to invasion, be diagnosed in the analysis prior to estimating anisotropic conductivity parallel and perpendicular to bedding plane. Our work suggests that cross-coupled components of opposite sign and non-monotonic time variations in the coplanar components could diagnose time dependent invasion effects on multi-component induction measurements.