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Seismic Characterization of Montney Shale Using Passey's Approach

Abstract

Seismic characterization of shale reservoir formations or source rocks is an important goal, considering the high level of activity in oil companies that are engaged in shale-resource exploitation across North America. Well logging carried out in these formations yields some of the measured parameters helping us understand their properties. Resistivity and velocity are two such parameters that are of interest, as they can indicate the presence of organic material or kerogen in these rocks. Higher values of resistivity and lower values of velocity seen on the well-log curves are indicative of the sweet spots in these formations. Passey et al. (1990) demonstrated that at any well location, DeltalogR is a useful measurement, in that when the resistivity and sonic transit-time curves are scaled and overlaid, they follow each other almost everywhere, except in the kerogen-rich zones where they crossover. However, our goal is to characterize the shale formations not vertically but laterally, so that sweet spots over different pockets could be detected and targeted for drilling. For doing this we turn our attention to seismic data. Any set of seismic attributes that incorporate both resistivity and velocity could be useful for the delineation of sweet spots. In this study, we introduce a methodology for computing DeltalogR from seismic data. Considering the importance of resistivity, porosity, gamma ray and brittleness information for characterizing shale reservoir rocks, different techniques namely, extended elastic impedance, simultaneous inversion, and the proposed DeltalogR approach were followed to derive these properties for the Montney shale formation, one of the most active natural gas plays in Canada. At the well location, the Passey et al's (1990) method indicates that Upper Montney shows the characteristics of the reservoir rock as DeltalogR showed high values. Subsequently, using crossplotting between different attributes and DeltalogR, it was found that the λρ attribute showed the highest correlation (94%). The linear relationship between these two attributes was used to transform the λρ volume into a DeltalogR volume. Finally, sweet spots were identified adopting the criteria of low Poisson's ratio, high DeltalogR, high porosity, and high Young's modulus. The developed methodology has been followed through with applications to shale plays other than the Montney application cited here, and shows promise.