Hydrocarbon and Lithology Indicators by Coordinate Rotations in the AI-Vp/Vs Domain

Abstract

Summary Elastic inversion of pre-stack seismic yields two reliable elastic properties: Acoustic Impedance (AI) and Shear Impedance (SI) or, equivalently, AI and Vp/Vs. Combining these two, several attributes discriminating fluids and lithologies have been proposed. An alternative approach, known as Extended Elastic Impedance (EEI), combines AI and Gradient Impedance (GI), the AVO gradient “equivalent” impedance, through a log-log coordinate rotation. The rotation angle is optimized for fluid or lithology discrimination. This method requires the estimation of reliable AVO attributes which, particularly the gradient, are affected by several data pitfalls such as, among others, unbalanced amplitude spectra through offset. Heavy seismic pre-conditioning is necessary to overcome these issues which, in turn, are managed more efficiently in available elastic inversion algorithms by the use, for instance, of multiple offset-varying wavelets. However, inversion platforms are parameterized to output reliable AI and Vp/Vs but not GI. In order to integrate the benefits of elastic inversion and EEI, we propose to combine, post-inversion, AI and Vp/Vs through a coordinate rotation analogous to that described for EEI in order to derive hydrocarbon and lithology indicators. Real examples from the Mamba supergiant gas discovery in deep-water Mozambique illustrate the potentialities of these tailored inversion attributes.