ABSORPTION COMPENSATION BASED ON CURVELET TRANSFORM

摘要

Wang, D., Sun, J., Meng, D., Feng, F. and Zhu, H., 2013. Absorption compensation based on curvelet transform. Journal of Seismic Exploration, 22: 19-32. Stratal absorption of seismic waves caused time-varying of source wavelet and lowered the resolution of data, especially for deep signals. After the stratal absorption attenuation of the longer propagation path, high-frequency signals are absorbed so strong that it cannot reflect the real situation of the strata, which make the processing and interpretation encounter many problems. We assume that there is no strata absorption, the energy distribution relations of the time between seismic records of the different frequency bands have similarity. The energy of all frequency bands of deep reflection should be the same as that of shallow reflection of the same frequency band energy ratio, but the absolute energy of the different bands have different sizes. Because of the low-frequency energy loss less, when the high-frequency record is multiplied by time-varying factor, the energy ratio of deep layer would be the same to that of low frequency, playing the role of the compensation. In this paper we use the curvelet transform to divide the frequency of seismic data, then use the directional characteristics of curvelet transform to select the signal of each frequency band selected angle, extract the weighting factor of each time location and reciprocal weighting to make sure that the ratio of deep and shallow energy of relative angle signal for each frequency band was the same, and then reconstruct the weighted data. In practice ,we can see with this method the strata absorption is well compensated by the strata absorption. Using curvelet transform can directly compensate for the seismic data and basically does not enhance the noise, and effectively improve the signal to noise ratio of seismic data. Here we provide a new method for high precision seismic data processing. The method does not need to know the Q value in advance and can adapt to the constant Q and variable Q.