Application and limitation of improved statistical filtering method in seismic data processing

Noise suppression technology of seismic data is in great demand for applications. In an abstract sense, seismic data can be considered as the composition of the seismic events determined by a certain time-distance relationship and the random noise determined by a certain statistical rule. The traditional statistical filtering based on weighted superposition often affects the event information in seismic data, which leads to unsatisfactory filtering effects. Therefore, the statistical filter should be improved according to the characteristics of seismic data. Filtering should be considered from a statistical perspective, and statistical filtering needs to track the seismic reflection events to adaptively design a flat window function that matches the geological characteristics of different regions. Therefore, we propose an anisotropic filter along the events to adaptively filters along the events in different regions, which conforms to the laws of seismic data. Then, synthetic data and real data verify the effectiveness of the proposed method in improving the signal-to-noise ratio (SNR) and retaining events. Finally, the quantitative and qualitative results of SNR, residual, and error curves are analyzed to state the application limitations of the statistical filter. © 2022, Editorial Department OIL GEOPHYSICAL PROSPECTING. All right reserved.