Absorption analysis promoting multiattribute inversion and application for fluid recognition

Summary A new wavelet energy absorption (WEA) method named GST_WEA and a consequent multi-attribute inversion technique are proposed in this paper. The GST_WEA method, which is based on the generalized S-transform (GST), integrates the high time-frequency resolution of GST and the advantage of WEA algorithm. From the GST_WEA, a high/low frequency absorption factor is calculated, and then the absorption factor combined with the other hydrocarbon related seismic attributes are used for the resistivity logs inversion via the Neural Network algorithm, which is referred as absorption analysis promoting multi-attribute inversion technique. The real data examples demonstrate the effectiveness of the two proposed methods for the hydrocarbon detection in the exploration stage, and the fluid recognition within sand body in the development stage, respectively.