论文部分内容阅读
海洋可控源电磁 (MCSEM) 信号极易受到多种噪声的干扰, 从而影响后期数据的反演解释精度.基于小波技术的降噪理论和方法已被广泛应用于MCSEM信号的消噪领域, 但小波基均为通用小波基, 消噪效果有待提升, 提出了构造专用于MCSEM信号的新型小波基.首先, 通过粒子群优化算法 (PSO), 以新型小波函数与MCSEM信号的平均相似度作为约束条件, 迭代求解滤波器组的最优系数;然后利用得到的系数构造新型小波基.其次, 针对深海勘探中的海水扰动噪声, 设计了基于新型小波基消噪方法, 并利用仿真的含噪数据与传统小波基消噪方法进行了对比实验;通过信噪比 (SNR) 及均方误差 (MSE) 进行消噪效果评价, 表明新型小波基消噪方法优于传统小波基消噪方法.最后, 将新型小波基消噪方法应用到了实测MCSEM数据中;通过消噪前后的时域信号及振幅随偏移距变化 (MVO) 曲线对比分析, 结果表明, 该方法不仅可以去除海水扰动类噪声, 还可以扩大MVO曲线偏移距的解释范围, 证明了基于新型小波基消噪方法的有效性和实用性.“,”The marine controlled source electromagnetic (MCSEM) signals are susceptible to various kinds of noises, which affects the accuracy of the inversion interpretation of subsequent data. Wavelet-based denoising theory and methods have been widely used in the field of MCSEM signal denoising. However, the applied wavelet bases are general-purpose ones, and the denoising effect needs to be improved. This study proposes to construct a new wavelet base specially used for MCSEM signals. Firstly, through the particle swarm optimization (PSO) algorithm, the optimal coefficients of the filter banks were iteratively calculated taking the average similarity of the new wavelet function and the MCSEM signal as the constraints, and then the new wavelet base was constructed using the obtained coefficients. Secondly, aiming at the seawater turbulence noise in deep sea exploration, a denoising method based on the new wavelet-base was designed. An experiment was conducted to compare the new wavelet-based denoising method and the traditional wavelet-based denoising method using the simulated noisy data. The signal to noise ratio (SNR) and mean square error (RSE) were used to evaluate the denoising effects, and the results demonstrate that the new wavelet-based denoising method is superior to the traditional wavelet-based denoising method. Finally, the new wavelet-based denoising method was applied to the actually measured MCSEM data. The time domain signals and magnitude versus offset (MVO) curves before and after denoising were compared and analyzed, the results show that the proposed method can not only remove the noise of sea water turbulence, but also extend the interpretation range of the MVO curves, which proves the effectiveness and practicability of the new wavelet-based denoising method.