论文详情
陆上地震勘探可控震源采集的单炮道集中,“黑三角”噪声在三维情形下分布于以炮点位置为顶点的锥形体内,其特征复杂且多变,因而严重降低了地震数据的信噪比和成像结果的质量。为此,首先分析了以瑞雷型面波及其强散射波为主的“黑三角”噪声特征,提出了“黑三角”噪声压制方案,发展出了数据自适应压制方法。关键步骤包括:显式或隐式地划分出“黑三角”噪声区域,基于划分区域的最大视速度对数据进行线性动校正(LMO),对数据局部取窗(时间空间窗),分频进行稳健主成分分析(robust principal component analysis,RPCA)以提取线性信号,利用统计滤波器消除异常幅值噪声。实际数据的处理结果表明,该技术方案可以较好地压制面波,保留有效信号。
In the single shot gather of vibroseis seismic data for 3D land seismic exploration,“black triangle” noise is distributed in a cone,with the shot point as the apex.Owing to its complex and variable characteristics,black triangle noise seriously reduces the signal-to-noise ratio of data gathered and the quality of imaging results.In this study,black triangle noise characteristics was analyzed and found to be mainly composed of Rayleigh-type surface waves and strong,scattered waves.A noise suppression scheme was then proposed and an adaptive data suppression method was developed.The key steps were as follows:first,the black triangle noise area was explicitly or implicitly separated.Second,linear move-out correction was performed on the data based on the maximum apparent velocity of the separated area.Third,a local window of the data (a time-space window) was defined and frequency-division robust Principal component analysis was performed to extract the linear signal.Finally,statistical filters were utilized to eliminate anomalous amplitude noise.Tests on field data showed that this method can suppress surface waves while preserving effective signals.
基金项目：南方海洋科学与工程广东省实验室(湛江)资助项目(ZJW-2019-04)、国家重点研发计划深海关键技术与装备重点专项(2019YFC0312004)、国家重点研发计划变革性技术关键科学问题重点专项(2018YFA0702503)、国家自然科学基金(41774126)和国家科技重大专项(2016ZX05024-001,2016ZX05006-002,2017ZX05005-004)联合资助。