In the Hongze Area, the reservoirs vary rapidly laterally and are controlled by many factors, such as structure, lithology, oil source, and so on. S-wave well log curves are calculated from an equation derived from mu...In the Hongze Area, the reservoirs vary rapidly laterally and are controlled by many factors, such as structure, lithology, oil source, and so on. S-wave well log curves are calculated from an equation derived from multiple-attribute regression analysis of RT, DT, GR, and DEN logs. Representative P-and S-wave velocities and Poisson＇s ratio are statistically computed for oil and water bearing reservoir rock, shale, and calcareous shale in each well. The averaged values are used for AVO forward modeling. Comparing the modeling results with actual seismic data limit the possible AVO interpretations. Well and seismic data are used to calibrate inverted P-wave, S-wave, Poisson＇s ratio, and AVO gradient attribute data sets. AVO gradient data is used for lithofacies interpretation, P-wave data is used for acoustic impedance inversion, S-wave data is used for elastic impedance, and Poisson＇s ratio data is used for detecting oil and gas. The reservoir and hydrocarbon detections are carried out sequentially. We demonstrate that the AVO attributes method can efficiently predict reservoir and hydrocarbon potential.展开更多
文摘In the Hongze Area, the reservoirs vary rapidly laterally and are controlled by many factors, such as structure, lithology, oil source, and so on. S-wave well log curves are calculated from an equation derived from multiple-attribute regression analysis of RT, DT, GR, and DEN logs. Representative P-and S-wave velocities and Poisson＇s ratio are statistically computed for oil and water bearing reservoir rock, shale, and calcareous shale in each well. The averaged values are used for AVO forward modeling. Comparing the modeling results with actual seismic data limit the possible AVO interpretations. Well and seismic data are used to calibrate inverted P-wave, S-wave, Poisson＇s ratio, and AVO gradient attribute data sets. AVO gradient data is used for lithofacies interpretation, P-wave data is used for acoustic impedance inversion, S-wave data is used for elastic impedance, and Poisson＇s ratio data is used for detecting oil and gas. The reservoir and hydrocarbon detections are carried out sequentially. We demonstrate that the AVO attributes method can efficiently predict reservoir and hydrocarbon potential.
