Seismic petrophysics workflow applied to Delaware Basin

Abstract

Petrophysical analysis of unconventional plays that are comprised of organic mudrock needs detailed data QC and preparation to optimize the results of quantitative interpretation. This includes accurate computation of mineral volumes, total organic carbon (TOC), porosity, and saturations. We used TOC estimation to aid the process of determining the best pay zones for development of such reservoirs. TOC was calculated as a weighted average of Passey’s (empirical) and the bulk density-based (theoretical) methods. In organic mudrock reservoirs, the computed TOC log was used as an input to compute porosity and calibrate rock-physics models (RPMs), which are needed for understanding the potential of source rocks or finding sweet spots and their contribution to the amplitude variation with offset (AVO) changes in the seismic data. Using calibrated RPM templates, we found that TOC is driving the elastic property variations in the Avalon Formation. We determined the layering and rock fabric anisotropy using empirical relationships or modeled in the rock property characterization process because reflectivity effects are often seen in the observed seismic used for well tie and wavelet estimation. A Class IV AVO response was seen at the top of the Avalon Formation, which is typical of an unconventional reservoir. We then performed solid organic matter (TOC) substitution to account for variability of elastic properties and their contrasts as expressed in seismic amplitudes. To complete the characterization of the intervals of interest, we used conventional seismic petrophysical methods in the workflow and found that the main driver modifying the elastic properties for the Avalon shales was TOC; this conclusion serves as a foundation in integrated seismic inversion that may target lithofacies, TOC, and geomechanical properties. Seismic reservoir characterization results are critical in constraining landing zones and trajectories of the horizontal wells. The final interpretation may be used to rank targets, optimize drilling campaigns, and ultimately improve production.