A three-dimensional microseismic downhole noise suppression based on polarization filtering method in Shearlet transform

Abstract

Microseismic noise suppression is widely used in the exploration of unconventional oil and gas resources. The effective microseismic downhole signals have extremely weak energy and are contaminated by strong interference, making data processing and interpretation difficult. The need for high-frequency effective signal reservation presents a basic problem in the design of noise suppression methods. The effective signals represent as the continuous reflection event and have more concentrated features in the transform domain, which can be used to tell the signal from the irregular microseismic noise. However, the high-frequency signal and extremely complex noise bring difficulty in accurately separating them by a single threshold. In this study, we propose a novel denoising method called Shearlet-polarization filtering to effectively suppress the microseismic noise. In general, Shearlet-polarization filtering is the combination of polarization filtering and conventional Shearlet transform. Specifically, the Shearlet transform can decompose the microseismic data into multi-directional and multi-scale information, providing a solid foundation for the separation of effective signals and background noise. From this basis, polarization filtering achieves signal reservation and noise attenuation by making full use of the three-dimensional information. To evaluate the performance, we also compare the proposed method with conventional Shearlet threshold filtering and polarization filtering. Experimental results both in synthetic and field data processing indicate that the Shearlet-polarization filtering is superior to the competing methods because it can significantly improve the continuity and smoothness of the microseismic events, even in low SNR conditions.