Abstract

Abstract Seismic anisotropy is sensitive to intensity and orientation of fractures aligned by tectonic or local stress field. Azimuthal anisotropy of amplitude versus offset (AzAVO) is one common measure of seismic anisotropy for fracture detection. For this study, we calculated P-wave AzAVO attributes for a lower Cretaceous limestone reservoir in east Texas. Our study tests AzAVO inversion for the relatively low-fold, fair data quality typical of some land surveys. We developed a workflow to integrate the AzAVO inversion with rock physics, forward seismic modeling, seismic-scale fault interpretation, image logs, and core. Our AzAVO inversion method was based on Rüger's equation, which describes the observed reflectivity (R) as a function of normal incidence amplitude (A0), AVO slope (B0), anisotropy magnitude (B1), anisotropy orientation (ϕ0), and noise (ni): R ( θ i , ϕ i ) ∼ A 0 + [ B 0 + B 1 cos 2 ( ϕ i − ϕ 0 ) ] sin 2 θ i + n i Inversion of Rüger's equation yielded four attribute volumes (corresponding to A0, B0, B1, and ϕ0). Additionally, we proposed a additional data quality parameter which describes the relative amount of the total reflection energy predicted by the model. Pre-inversion processing carefully preserved signal via random noise attenuation, super-binning, bandwidth balancing, and phase alignment. In general, AzAVO inversion displayed geologically interpretable, high anisotropy anomalies. Noise, however, limited our confidence for quantitative fracture prediction. On the flanks of the anticline, data quality was high (greater than 50% fit). Here the magnitude of the anisotropy (B1) volume showed strong lineations parallel to NE-SW trending faults. Over the crest of the anticline, the inversion quality was degraded by an overburden effect, coincident with poor data quality fit (less than 50%). AzAVO orientation maps were noisy and in some places obscured by an acquisition footprint. Locally, however, AzAVO orientations were parallel to ENE fracture orientations from core, maximum horizontal stress from image logs, and fast-velocity direction from a dipole sonic log.

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