Abstract
Summary The Lower Silurian shale-gas formation in the Sichuan Basin shows a property of transverse isotropy with vertical axis of symmetry (VTI). We present a case study of seismic inversion and quantitative interpretation of the target shale-gas reservoir formation. An AVO inversion method for VTI media is applied to estimate three elastic parameters (the acoustic impedance - A, the shear modulus weighted by an anelliptical anisotropy parameter - B, and the approximated horizontal P-wave velocity - C). Statistical rock-physics and machine learning are applied to the inverted parameters for the characterization of the reservoir formation. Brittleness-related shales can be successfully discriminated from surrounding formations using the attribute pair A-C, and the organic-rich gas-bearing shale can be successfully identified using the attribute pair A-B. Estimated TOC results using statistical rock-physics and support vector regression (SVR) method show highly consistent with the each other. Comparison between the prediction results and well logs demonstrates the feasibility of the inversion and quantitative interpretation approaches.
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