本文選題：地震信號處理　切入點：多道互相關　出處：《吉林大學》2015年碩士論文

【摘要】：地震勘探技術是現(xiàn)代探測油田、天然氣等礦藏資源開發(fā)的主要手段。它主要是利用人工技術來爆破產生地震波，根據(jù)不同的地震波傳播規(guī)律即可判斷出是否含有礦藏資源。在地震勘探過程中，實際地震波的采集過程中不可避免的會混入人文噪聲、風成環(huán)境噪聲以及儀器設備噪聲等。這些噪聲直接影響著對地震勘探結果的判斷。為了提高地震勘探準確性，消減地震記錄中噪聲就顯得極為重要。 時頻峰值濾波(Time-frequency peak filtering，TFPF)是壓制地震勘探隨機噪聲的一種非常行之有效的方法。時頻峰值濾波方法一種無偏估計的算法，在時頻域壓制隨機噪聲的方法中，尤為突出。而實際地震勘探信號處理中，由于隨機噪聲的不確定性和地震信號的非線性影響，時頻峰值濾波算法對有效信號的估計有誤差，信號幅值衰減嚴重，有時甚至引起信號波形畸變，這導致了時頻峰值濾波的差剖面中存在有效信號的殘留。 為了提高時頻峰值濾波算法對信號估計的準確性，本文基于地震勘探記錄多道信號互相關特性，提出了一種基于互相關的自適應TFPF的方法。該方法在多道互相關最大的約束下對TFPF的差剖面中的有效信號自適應的提取，增加了包含差剖面濾波算子和權重系數(shù)的保真項，使用保真項達到提高TFPF算法保真度的目的�；诘卣鹂碧酵噍S相干特性，通過地震勘探相鄰多道互相關函數(shù)最大自適應調整保真項的權重系數(shù)�；诨ハ嚓P的自適應TFPF算法對有效信號部分獲得較大權重系數(shù)，更好的保持有效信號不失真；而在隨機噪聲部分權重系數(shù)被進一步降低，從而增強TFPF壓制噪聲能力。將本方法分別應用人工合成模擬地震記錄和實際共炮點記錄，地震數(shù)據(jù)處理結果表明，，基于互相關的自適應TFPF方法與傳統(tǒng)TFPF方法相比，濾波后有效信號的幅值更接近真實值，更好的改善了地震記錄的信噪比。
[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.
【學位授予單位】：吉林大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：P631.4

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