关键词: 横波预测, 最小二乘, 叠前反演, 经验公式法

Abstract:

Because of the P-wave impedance parameters obtained from post stack inversion, the reservoir and non-reservoir characteristics cannot be distinguished well and compared with poststack inversion, prestack inversion can obtain more elastic parameters to predict favorable reservoir spatial distribution characteristics, but shear wave data is the key factor of prestack inversion. Generally speaking, the shear wave data in the actual study area are very few, even missing. Under these circumstances, it is more important to predict shear wave data fromp-wave data or other logging data. And reconstructing shear wave information from conventional logging data is a widely used shear wave prediction technology. In this paper, the S-wave velocity prediction of all wells in S area of the Daqing oil field is completed based on the least square fitting polynomial method on the basis of comprehensive research and analysis. The comparison and analysis of six S-wave logging curves in the study area show that the average coincidence rate between the predicted S-wave and the measured S-wave is above 96%. The prediction accuracy of S-wave data can be effectively used for prestack inversion calculation of seismic data. Based on the predicted S-wave velocity, a low-frequency model is established, and the pre-stack simultaneous inversion calculation in S area is completed. The elastic parameter data obtained from inversion and logging data are compared and analyzed. The results show that the predicted elastic parameters obtained from inversion are in good agreement with the well data. The practice of seismic interpretation, reservoir prediction and development in S area of Daqing oilfield shows that prestack AVO/AVA inversion can improve the accuracy of reservoir prediction and reservoir identification, and then improve the accuracy of remaining oil prediction, and determine the key areas for tapping potential of remaining oil. The least square fitting method is used to complete the S-wave prediction, and the S-wave prediction formula suitable for the study area is given. The calculation shows that the method can be widely used in the study area of similar reservoirs.

Key words: S-wave prediction, Least square algorithm, Least square algorithm, Empirical formula method