As the land internal multiples could not been obviously attenuated, the authors develop the dimensionality reduced virtual event method to suppress the internal multiples in pre-stack land seismic data. Compared with the traditional virtual event method, the authors apply the virtual event method trace by trace on the pre-stack gathers after accurate dynamic correction to predict internal multiples. It achieves dimensionality reduction, greatly reduces the amount of calculation, and no longer requires a regular and dense enough distribution. Meanwhile, this method introduces a weighted reference trace with high signal-to-noise ratio to participate in the cross-correlation and convolution operations of the pre-stack gathers, which improves the prediction accuracy of the virtual event method. This method is applied to actual land seismic data in western China and achieved obvious effect when suppressing internal multiples.

In order to apply the fault enhancement method to improve the accuracy of fault identification, a three-dimensional fault enhancement method based on multi-directional recognition is developed. This method applies directional filtering to enhance the continuity of the seismic events and suppress the background noise, and applies edge-preserving filtering to preserve the fault information in seismic profiles. This method is further improved in two aspects. 1) Multi-directional fault recognition is designed to adapt to the presence of inclined formations. 2) The two-dimensional fault enhancement method is extended to the three-dimensional one which achieves the effect of three-dimensional fault enhancement with a lower amount of calculation. The applications on synthetic data and the three-dimensional post-stacked actual data show that the proposed method can effectively suppress the background noise, enhance the continuity of the seismic events, and improve the resolution of the fault image, which is conducive to the subsequent structural interpretation.