Three seismic attributes commonly used to predict pore fluid and lithology are the fluid factor (ΔF), Poisson impedance (PI), and lambda-rho (λρ). We evaluated the pore-fluid sensitivity of these attributes with both well-log and seismic data in Tertiary unconsolidated sediments from the Gulf of Mexico where sand and shale are the only expected lithologies. While the sensitivity of one attribute versus another to discriminate pore fluid is often debated in the literature, the sensitivities of the three attributes are not independent but can be traced back to the fluid factor, which is a function of the P- and S-wave normal-incident reflection coefficients. Interestingly, the fluid factor, which is a reflectivity attribute, at the top of a hydrocarbon-saturated reservoir, is basically independent of the shale properties above the reservoir. It is a function of the brine and hydrocarbon impedances of the reservoir. The next attribute, Poisson impedance, is thenequal to the fluid factor times the sum of the brine and hydrocarbon impedances. Finally, the lambda-rho attribute is equal to the Poisson impedance multiplied by the same impedance sum. Essentially, the same scale factor differentiates these attributes, which does not significantly affect the sensitivity of the attributes. PI is the basis of the sensitivity for these attributes. As a means of testing their sensitivity for predicting pore fluid, we generated the three attributes along with their statistical distributions for different pore fluids for 183 reservoirs. The well-log statistical descriptions were then used to calibrate the seismic amplitude in a 3D survey to reflectivity values, thus allowing pore-fluid classification schemes based on Bayes’ decision rules. In essence, seismic-amplitude quantification was based on regional statistics rather than individual wells within the 3D seismic survey to delineate the portions of the reservoir that were saturated with oil, gas, or brine.

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