An amplitude suppression method based on the decibel criterion  

基于数据驱动的小波域分贝准则强能量振幅压制方法（英文）

作　　者：孔选林[1,2] 陈辉[1,3] 王金龙 胡治权[2] 徐丹 李录明[1] 

机构地区：[1]成都理工大学,成都610059 [2]中石化西南油气分公司勘探开发研究院,成都610041 [3]数学地质四川省重点实验室(成都理工大学),成都610059

出　　处：《Applied Geophysics》2017年第3期387-398,460,461,共14页应用地球物理（英文版）

基　　金：supported by the National Science and Technology Major Project(No.2011ZX05002-004-002);the National Natural Science Foundation of China(No.41304111);Key Project of Science and Technology Department of Sichuan Province(No.2016JY0200);Natural Science project of Education Department of Sichuan Province(Nos.16ZB0101 and 14ZA0061);the Sichuan Provincial Youth Science&Technology Innovative Research Group Fund(No.2016TD0023);the Cultivating Program of Excellent Innovation Team of Chengdu University of Technology(No.KYTD201410)

摘　　要：To suppress the strong noise in seismic data with wide range of amplitudes, commonly used methods often yield unsatisfactory denoising results owing to inappropriate thresholds and require parametric testing as well as iterations to achieve the anticipated results. To overcome these problems, a data-driven strong amplitude suppression method based on the decibel criterion in the wavelet domain （ISANA） is proposed. The method determines the denoising threshold based on the decibel criterion and statistically analyzes the amplitude index rather than the abnormally high amplitudes. The method distinguishes the frequency band distributions of the valid signals in the time-frequency domain based on the wavelet transformation and then calculates thresholds in selected time windows, eventually achieving frequency-divided noise attenuation for better denoising. Simulations based on theoretical and real-world data verify the adaptability and low dependence of the method on the size of the time window. The method suppresses noise without energy loss in the signals.在对振幅值动态范围分布较大的地震数据进行强能量去噪处理时,针对常规方法通常会面临的阈值求取不准导致效果不理想、需要反复测试模块参数以及需要多轮迭代联合去噪才能达到预期效果等问题,本文提出了基于数据驱动的分贝准则小波域强能量振幅压制方法。与常规方法相比,该方法不直接对异常强振幅能量值进行统计分析,而是对振幅的能量级指数进行统计分析来确定去噪阈值,即分贝判定准则。本文采用小波变换在时频域选取最佳有效信号分布时窗进行阈值统计,然后分频压制,以进一步提升去噪效果。理论和实际数据测试表明,该方法能有效压制地震数据中的强能量振幅,对强能量振幅分布动态范围适应广、时窗依赖程度低、保幅性好,具有良好的应用前景。

关 键 词：wavelet transformation AMPLITUDE decibel criterion DENOISING 

分 类 号：P631.44[天文地球—地质矿产勘探]