Implementation of Partial CRS-Stack method in order to obtain sophisticated supergathers for gas reservoir characterization

Abstract

Seismic gathers produced from a conventional seismic data processing method has been normally used for gas reservoir characterization for many years. The conventional method has many difficulties in imaging reflectors which have curvature, especially in a complex geological structure with small number of traces in a gather. Considering the difficulties in conducting AVO (Amplitude Versus Offset) analysis under such conditions, more sophisticated methods should be applied to overcome the above limitations. This paper discusses how supergathers obtained from Partial CRS (Common Reflection Surface) stack method improve signal to noise ratio, which leads to better reservoir characterization. Because CRS supergathers consist of preserved amplitude traces (Baykulov, 2009), cross-plot and cross-product analyzes in the gas reservoir characterization can be performed. Cross product analysis is a convolution operation between intercept and gradient of AVO curves, which gives positive values for a gas reservoir. To proof this hypothesis, a complex geological model was constructed to generate a synthetic seismic dataset, by using an elastic waveform modeling software. Using the model of a half-graben structure with gas trap, the gas reservoir was identified as class-3 in the AVO classification, which was more obvious in the CRS supergathers. As the quality of the supergathers is high, the quality of the cross-product analysis is also higher than the conventional CMP (Common Mid Point). The AVO anomaly can be seen clearly and strongly, so that the boundary of gas reservoir can be seen clearly. Hence, the interpretation of unclear events that have been seen in the conventional stack section can be improved and thus this approach can enhance the quality of gas reservoir characterization.