Using sparse-constrained nonstationary polynomial regression to remove seismic noises and picking up first arrival
LIU Guochang1, CAI Jiaming2, YAN Haiyang3, LI Jieli1, CHEN Xiaohong1
1. College of Geophysics, China University of Petroleum(Beijing), Beijing 102249, China; 2. Geophysical Research Institute, BGP, CNPC, Zhuozhou, Hebei 072751, China; 3. Division of Marine Geophysical Exploration, BGP, CNPC, Tianjin 300450, China
Abstract:Nonstationary polynomial fitting relates to optimization with L2 norm.Although the time-dependent characteristics of signals are considered,the residual is still assumed to be randomly distributed.In the case that there are strong non-random noises in seismic data,conventional nonstationary polynomial fitting based on L2 norm is no longer applicable.This study investigated the theory and method of sparse-constrained nonstationary polynomial regression.First,we reviewed the basic principle of non-stationary polynomial regression.Second,to solve the problem related to the complex sparse residual,under the framework of inverse problem regularization theory,we combined non-stationary polynomial regression with L1 norm constraint,followed the combined constraint strategy of shaping regularization with L1 norm,and solved the multi-constraint inverse problem with conjugate gradient and projection algorithm.In addition,we estimated the coefficient of polynomial regression with time-varying smoothing characteristics and the residual sparsely distributed,which can reduce the influence of sparse strong noises on inversion.Finally,we proposed the basic process and parameter analysis of the algorithm.Synthetic and field data have proved that sparse constrained non-stationary polynomial regression is effective for noise suppression and pick up first arrival.
刘国昌, 蔡加铭, 闫海洋, 李洁丽, 陈小宏. 利用稀疏约束非平稳多项式回归去除地震噪声及拾取初至[J]. 石油地球物理勘探, 2020, 55(3): 548-556.
LIU Guochang, CAI Jiaming, YAN Haiyang, LI Jieli, CHEN Xiaohong. Using sparse-constrained nonstationary polynomial regression to remove seismic noises and picking up first arrival. Oil Geophysical Prospecting, 2020, 55(3): 548-556.
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