Abstract：Deep-water turbidite sandstone reservoirs in the Niger Delta Basin have a great potential of oil and gas exploration. Drilling data from this area indicate that both oil and water layers with high porosity show "bright spots" and classes Ⅱ-Ⅲ AVO anomaly. However, it is difficult to distinguish oil from water using conventional amplitude and AVO attribute. In this study, we firstly investigated amplitude responses and their controlling factors, and found that high porosity is the key factor controlling the multiple solutions of amplitude and AVO response; then we performed a series of AVO modeling with different porosity and fluid substitution, and output the intercept-gradient crossplot whose variation with the porosity is different from that with the fluid saturation, and based on this conclusion, we introduced an exten-ded AVO attribute by rotating the axis, which can improve the precision of hydrocarbon detection; finally, after applying pre-stack inversion to further enhance the realiability of hydrocarbon detection, a new fluid factor quantitative evaluation method was proposed for selecting the best sensitive fluid factor while suppressing the effect of porosity. According to our nalysis, λ/μ is the most applicable parameter for detecting hydrocarbon in this area. And application to real data has proved that both the extended AVO attribute and λ/μ could effectively distinguish water layers from oil layers with "bright spots". The predicted results are well consistent with the drilling data, indicating the feasibility of the method.
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