Automatic Source Localization and Attenuation of Seismic Interference Noise Using Density-Based Clustering Method

Abstract

Marine seismic data may be contaminated by external source interference noise (ESIN) in some cases. These ESINs can be suppressed automatically, provided we can localize these external sources correctly. In this paper, we propose an automatic method to localize the external sources using a density-based clustering method and then suppress the ESINs according to the sources. In a shot gather, the time delays between three randomly selected seismic traces are used to calculate the location of one potential external source directly. Since there are many seismic traces in one shot gather, we can get a lot of estimates of the external source locations. In general, some of these locations are falsely detected sources. Assuming that the location of the external source is fixed or slowly changes during one seismic shot acquisition, multiple true estimates of an external source location, which are obtained from different trace groups, should focus together. In contrast, the false locations are arbitrarily distributed. Therefore, a density-based clustering method is applied to obtain the final source location estimate. Since each potential source corresponds to one cluster, we find out the strongest ESIN corresponding to the cluster with maximum sample number to ensure the accuracy. After that, the detected ESIN is flattened and then extracted by singular value decomposition. This method is an iterative method, and in each iteration, one ESIN is suppressed. And the high-pass filter is optional to detect the weak ESINs and protect the valid signals. The synthetic data example and real field marine data example prove that the proposed method can localize the external sources accurately and suppress multiple ESINs effectively.