Elastic–electrical seismic inversion for deep low-resistivity pay characterization

Abstract Deep low-resistivity pay (LRP) reservoirs contain significant hydrocarbon volumes that frequently evade detection because high clay content and complex pore geometries reduce electrical resistivity contrasts against surrounding conductive shales. The same factors also weaken the elastic contrast on which acoustic-impedance (AI) inversion relies. To address this challenge, this study tests an empirical seismic inversion workflow in which a power-exponential Poro-Resistivity (PR) attribute, calculated from porosity and resistivity logs, is used as a proxy for AI in synthetic seismic modeling and colored inversion. PR is not an elastic property. Its use is justified here by its strong correlation with AI and by an Extended Elastic Impedance (EEI) analysis, which shows that the PR log correlates strongly with EEI (R > 0.9) over a wide range of pseudo-angles that includes 0°, the angle at which EEI equals AI and which is represented by post-stack data. The workflow was applied to three deepwater Gulf of Mexico wells and to SEAM seismic data. At well No. 1, PR correlates with AI at R = 0.95, compared with R = 0.53 for raw resistivity, and R exceeds 0.94 in wells No. 1 and 3. Along two seismic lines through well No. 1, the PR volume shows a more continuous and more sharply bounded sand body than the AI volume. This comparison is qualitative, rests on one tied well and on thick sands (25–40 m), and has not been tested on laminated sand–shale sequences. PR is therefore proposed as a complementary attribute for sand–shale discrimination, not as a replacement for AI inversion or for EEI inversion of pre-stack data, which remains the physically preferable approach when angle stacks are available.