基于互相关的自适应TFPF算法在地震勘探技术中的应用

发布时间：2018-03-26 22:38

本文选题：地震信号处理　切入点：多道互相关　出处：《吉林大学》2015年硕士论文

【摘要】：地震勘探技术是现代探测油田、天然气等矿藏资源开发的主要手段。它主要是利用人工技术来爆破产生地震波，根据不同的地震波传播规律即可判断出是否含有矿藏资源。在地震勘探过程中，实际地震波的采集过程中不可避免的会混入人文噪声、风成环境噪声以及仪器设备噪声等。这些噪声直接影响着对地震勘探结果的判断。为了提高地震勘探准确性，消减地震记录中噪声就显得极为重要。时频峰值滤波(Time-frequency peak filtering，TFPF)是压制地震勘探随机噪声的一种非常行之有效的方法。时频峰值滤波方法一种无偏估计的算法，在时频域压制随机噪声的方法中，尤为突出。而实际地震勘探信号处理中，由于随机噪声的不确定性和地震信号的非线性影响，时频峰值滤波算法对有效信号的估计有误差，信号幅值衰减严重，有时甚至引起信号波形畸变，这导致了时频峰值滤波的差剖面中存在有效信号的残留。为了提高时频峰值滤波算法对信号估计的准确性，本文基于地震勘探记录多道信号互相关特性，提出了一种基于互相关的自适应TFPF的方法。该方法在多道互相关最大的约束下对TFPF的差剖面中的有效信号自适应的提取，增加了包含差剖面滤波算子和权重系数的保真项，使用保真项达到提高TFPF算法保真度的目的。基于地震勘探同相轴相干特性，通过地震勘探相邻多道互相关函数最大自适应调整保真项的权重系数。基于互相关的自适应TFPF算法对有效信号部分获得较大权重系数，更好的保持有效信号不失真；而在随机噪声部分权重系数被进一步降低，从而增强TFPF压制噪声能力。将本方法分别应用人工合成模拟地震记录和实际共炮点记录，地震数据处理结果表明，，基于互相关的自适应TFPF方法与传统TFPF方法相比，滤波后有效信号的幅值更接近真实值，更好的改善了地震记录的信噪比。
[Abstract]:Seismic exploration technology is the main means of exploiting mineral resources such as oil fields and natural gas in modern times. It mainly uses artificial technology to produce seismic waves by blasting. According to different laws of seismic wave propagation, we can determine whether there are mineral resources or not. In the process of seismic exploration, human noise will inevitably be mixed in the process of actual seismic wave acquisition. In order to improve the accuracy of seismic exploration, it is very important to reduce the noise in seismic records. Time-frequency peak filtering is a very effective method for suppressing random noise in seismic exploration. But in the actual seismic exploration signal processing, due to the uncertainty of random noise and the nonlinear effect of seismic signal, the estimation error of time-frequency peak filter algorithm to the effective signal and the attenuation of signal amplitude are serious. Sometimes it even leads to the distortion of signal waveform, which leads to the residual of effective signal in the difference profile of time-frequency peak filter. In order to improve the accuracy of time-frequency peak filtering algorithm for signal estimation, this paper based on the cross-correlation characteristics of multi-channel signals recorded in seismic exploration. In this paper, an adaptive TFPF method based on cross-correlation is proposed. The method adaptively extracts the effective signal from the differential profile of TFPF under the maximum constraints of multi-channel cross-correlation, and increases the fidelity items including the differential profile filter operator and the weight coefficient. The fidelity term is used to improve the fidelity of TFPF algorithm. Through the maximum adaptive adjustment of the weight coefficients of the fidelity terms by the maximum cross-correlation function of adjacent channels in seismic exploration, the adaptive TFPF algorithm based on cross-correlation obtains a large weight coefficient for the effective signal, so that the effective signal is better kept without distortion. However, the partial weight coefficient of random noise is further reduced to enhance the ability of TFPF to suppress noise. The artificial synthetic seismic record and the actual common shot record are used in this method, and the results of seismic data processing show that, Compared with the traditional TFPF method, the amplitude of the filtered effective signal is closer to the real value, and the signal-to-noise ratio of seismic records is improved better.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：P631.4

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