瞬变电磁数据交叉型组合域去噪技术研究与应用

Research and application of cross combined domain denoising technology for transient electromagnetic data

高效的瞬变电磁数据处理对后续的精确地质解译具有决定性的作用,而数据信号的去噪是数据处理环节的重中之重.时频分析方法是当前广泛应用于瞬变电磁数据处理去噪领域的主要方法技术,但其基本是单域方法的应用探索,各自单域方法实际应用效果不尽人意.本文基于曲波变换、小波变换及高阶相关统计技术,进行了交叉型组合域瞬变电磁数据去噪技术的研究与探索.通过引入高阶相关统计理论提供自适应的阈值函数、采用小波变换进行残留噪声成分小波系数分解,结合曲波变换正反过程实现交叉型组合域去噪技术.设计了包含随机噪声、相关噪声的数值模拟合成数据去噪算例验证了本文方法的可行性.将本文方法应用于两个实测数据去噪分析,表明本文方法可有效解决不同复杂程度的含噪声瞬变电磁数据去噪领域.研究成果为瞬变电磁高精度数据处理提供了新的技术手段.

Efficient transient electromagnetic data processing plays a decisive role in the following accurate geological interpretation, and data signal denoising is the most important part of data processing. Time frequency analysis method is widely used in the field of transient electromagnetic data processing denoising, but it is basically the application of single domain method exploration, the actual application effect of each single domain method is not satisfactory. In this paper, based on curvelet transform, wavelet transform and high-order correlation statistical technology, the cross combined domain transient electromagnetic data denoising technology is studied and explored. The adaptive threshold function is provided by introducing the high-order correlation statistical theory. The wavelet transform is used to decompose the residual noise component wavelet coefficients. The cross combined domain denoising technology is realized by combining the positive and negative process of curvelet transform. A numerical simulation example of synthetic data denoising including random noise and correlated noise is designed to verify the feasibility of the proposed method. The proposed method is applied to the denoising analysis of two measured data, which shows that this method can effectively solve the denoising field of Transient Electromagnetic Data(TEM data)with different complexity. The research results provide a new technical means for high-precision transient electromagnetic data processing.