發(fā)布時間：2018-05-31 22:24

  本文選題：S變換 + 主動源�。� 參考：《中國地震局地球物理研究所》2015年碩士論文

【摘要】：無論是天然地震學(xué)還是勘探地震學(xué),要實現(xiàn)對地下介質(zhì)變化與地下構(gòu)造的精確刻畫,我們都面臨著提高地震資料信噪比的難題。人們通常根據(jù)信號與噪聲在時間或者空間方面的差異來確定選取合適的濾波方法,以提高地震資料的信噪比。但是各種濾波方法都有其使用條件,通常只有滿足某種濾波條件的地震資料,才能取得良好的去噪效果。近年來,利用各種震源研究地下介質(zhì)變化成為地震學(xué)發(fā)展的一個熱點問題。本文中,我們針對主動源數(shù)據(jù)的特點,發(fā)展了相關(guān)的濾波方法。本文詳細(xì)介紹了S變換的基本理論,并對其公式推導(dǎo)及特性做了詳細(xì)闡述。S變換是短時傅里葉變換和連續(xù)小波變換的結(jié)合,它的基本小波不必滿足容許性條件,時頻分辨率與頻率有關(guān),并且反變換與傅里葉變換有直接的聯(lián)系。在實際應(yīng)用中我們可以把信號從時間域轉(zhuǎn)化到時頻域,再變換到頻率域,最后轉(zhuǎn)化到時間域,其變換快速且無損可逆,沒有信息的丟失。S變換克服了短時傅里葉變換固定分辨率的缺陷,具有多種分辨率。它相當(dāng)于對小波變換的進(jìn)行了相位校正,具有小波變換沒有的相位因子,保留了每個頻率所對應(yīng)的相位信息。S變換又是線性變換,和Wigner-Ville分布和Cohen類等雙線性變換比較,不會存在交叉項的干擾,具有較高的時頻分辨率。但是S變換的基本小波固定,因此許多學(xué)者對S變換進(jìn)行了改進(jìn),得到了各種形式的廣義S變換。為了提高地震資料的信噪比,我們基于S變換的獨特優(yōu)勢,將其應(yīng)用于時頻域的濾波去噪。通過把信號從時間域變換到時頻域,在時頻域分析信號和噪聲隨時間的分布情況,設(shè)計合適的濾波器保留有效信號濾除噪聲和干擾,再反變換到時間域從而達(dá)到信噪分離,提高地震資料的信噪比。主動源探測技術(shù)是一種很有發(fā)展前景的地球深部構(gòu)造探測技術(shù),從勘探地震學(xué)發(fā)展出來的氣槍震源,為人們突破天然地震的一些限制,實現(xiàn)對地下結(jié)構(gòu)進(jìn)行主動探測提供了很好的技術(shù)平臺。相較于一些傳統(tǒng)的人工震源,氣槍震源具有高信噪比、精確定位、震源特性可測量和低成本等優(yōu)勢。氣槍震源的低頻成分豐富,適合探測地球深部地殼；并且它由GPS授時,激發(fā)時間精確；氣槍信號傳播距離遠(yuǎn),最遠(yuǎn)在離氣槍源百公里內(nèi)可以發(fā)現(xiàn)很強(qiáng)的氣槍信號；而氣槍源的高度可重復(fù)性可以讓我們通過源的疊加來提高信噪比。雖然地震資料的多次疊加可以提高地震信號的信噪比,但是我們希望結(jié)合S變換時頻濾波設(shè)計一種專門處理主動源氣槍信號的濾波方法,用來提高單次激發(fā)氣槍信號的信噪比。在本文中我們提出了一種S變換模板濾波去噪新方法,通過對同一臺站接收到的氣槍信號進(jìn)行多次疊加從而得到高信噪比的信號,然后用疊加的高信噪比信號作為模板,在時頻域根據(jù)模板設(shè)置濾波器并對每一次激發(fā)產(chǎn)生的氣槍信號進(jìn)行濾波去噪。通過應(yīng)用S變換模板濾波技術(shù)對模擬數(shù)據(jù)的處理,驗證了我們方法的可行性和實用性。然后又對距離氣槍源112km的臺站接收到的實際氣槍數(shù)據(jù)進(jìn)行了處理,得到了高信噪比的單次激發(fā)氣槍信號,并且與帶通濾波和小波變換濾波結(jié)果做了簡單比較,說明了S變換模板濾波不僅能有效壓制噪聲并且不會削弱有效信號,而且經(jīng)過濾波的單次激發(fā)氣槍信號和疊加信號的波形相似性也很高,證明了我們方法的有效性。
[Abstract]:Whether it is natural seismology or exploration seismology, in order to realize the accurate characterization of underground medium change and underground structure, we all face the problem of improving the signal to noise ratio of seismic data. People usually determine the suitable filtering method according to the difference of time or space between signal and noise, in order to improve the signal to noise of seismic data. However, all kinds of filtering methods have their use conditions, usually only the seismic data that satisfy some filter conditions can obtain good denoising effect. In recent years, using various sources to study the change of underground media has become a hot issue in the development of seismology. In this paper, we have developed the related filter for the characteristics of the active source data. In this paper, the basic theory of S transformation is introduced in detail, and the derivation and characteristics of the formula are described in detail. The combination of.S transformation is the combination of short time Fu Liye transform and continuous wavelet transform. The basic wavelet does not have to satisfy admissibility, the time frequency resolution is related to the frequency, and the inverse transform is directly related to the Fu Liye transform. In practical applications, we can transform the signal from time domain to time domain, then transform it to frequency domain, and then transform it into time domain. Its transformation is fast and lossless. The loss of.S transform without information can overcome the defect of fixed resolution of short time Fourier transform. It has a variety of discrimination rate. It is equivalent to the phase correction of wavelet transform. It has the phase factor that the wavelet transform does not have, preserving the phase information.S transformation corresponding to each frequency and the linear transformation. Compared with the bilinear transformation of the Wigner-Ville and Cohen classes, there is no interference in the cross term and has a higher time-frequency resolution. But the basic wavelet transform of the S transformation is fixed, so many scholars have the S transformation In order to improve the signal-to-noise ratio of seismic data, based on the unique advantage of S transform, we apply it to the filtering de-noising of time and frequency domain in order to improve the signal-to-noise ratio of seismic data. By changing the signal from time domain to time domain, we design a suitable filter guarantee in time and frequency domain to analyze the distribution of signal and noise with time. The active signal can be filtered to filter noise and interference and then reverse to the time domain to achieve the signal to noise separation and improve the signal to noise ratio of seismic data. Active source detection technology is a very promising technology for deep tectonic detection of the earth. The gas gun source developed from the exploration seismology has achieved some restrictions for people to break through natural earthquakes. The underground structure provides a good technical platform for active detection. Compared with some traditional artificial sources, the gas gun source has the advantages of high signal to noise ratio, accurate location, measurable source characteristics and low cost. The low frequency components of the gas gun source are rich in the exploration of the earth's deep crust, and it is given time by GPS and the time of excitation is accurate; The distance of the gun signal is far away, and the strong air gun signal can be found in a hundred kilometers away from the source of the air gun. The repeatability of the air gun source can improve the signal to noise ratio by the superposition of the source. Although the multiple superposition of the seismic data can improve the signal to noise ratio of the seismic signal, we hope to combine the S transform time frequency filter design. A filtering method specially dealing with the active source gas gun signal is used to improve the signal to noise ratio of the single excitation air gun signal. In this paper, a new method of S transform template filtering de-noising is proposed. By superimposing the air gun signals received at the same station many times, the signal of high signal to noise ratio is obtained, and then the superimposed high signal to noise ratio is used. As a template, the filter is set according to the template in the time and frequency domain and the air gun signal produced by each excitation is filtered and de-noised. The feasibility and practicability of our method are verified by using the S transform template filtering technique to simulate the simulated data. Then the actual air gun data received from the station of the distance air gun source 112km is also obtained. The single shot gas gun signal with high signal to noise ratio is obtained, and it is compared with the band pass filter and the wavelet transform filtering results. It shows that the S transform template filter not only effectively suppress the noise and will not weaken the effective signal, but also the waveform similarity of the filtered single shot air gun signal and the superimposed signal is also similar. It is very high, which proves the effectiveness of our method.
【學(xué)位授予單位】：中國地震局地球物理研究所
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：P631.44

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