本文選題：高分辨率Radon變換 + 時頻峰值濾波(TFPF)�。� 參考：《吉林大學(xué)》2015年碩士論文

【摘要】：地震勘探是探索地震結(jié)構(gòu)，判斷油層儲氣有無及位置的重要方法。這種方法主要通過高能沖擊作為大地的輸入，通過檢波器收集響應(yīng)信號，從而判斷地質(zhì)界面的屬性及地質(zhì)結(jié)構(gòu)。但是由于油氣資源的過度利用，使得勘探者很難在淺表位置找到油氣資源，地震勘探技術(shù)就要向更深的地域發(fā)展。由于信號傳播距離遠(yuǎn)，信號的幅值衰減嚴(yán)重，并會被隨機噪聲淹沒，這將導(dǎo)致無法識別信號。因而地震去噪就尤為重要了。 時頻峰值濾波作為新興的去噪方法在地震噪聲去除上獲得很好的效果，近些年來引起了地球物理屆的關(guān)注。但傳統(tǒng)時頻峰值濾波僅沿時間方向進行濾波，沒有利用信號的時空域相關(guān)性恢復(fù)信號，這將影響信號的保留。其次傳統(tǒng)算法對地震記錄采用固定的窗長濾波，大窗長可以很好的壓制噪聲，但信號保幅不理想；小窗長信號保幅理想，但噪聲仍然大量遺留。為達到時頻峰值濾波保幅性能和壓噪性能兼顧的目標(biāo)，本論文提出了新的二維時空域濾波方法，即高分辨率雙曲Radon域變窗長時頻峰值濾波，這種算法首先利用高分辨率Radon變換將雙曲同相軸集中于Radon域下的幾個高能量位置。由于有效信號的疊加，在Radon域信號部分更容易識別，這為后續(xù)的濾波提供了有利條件。之后在Radon域通過設(shè)定合理的閾值，識別出信號和噪聲，并對信號采用小窗長濾波，，對噪聲采用大窗長濾波，這樣可以做到保幅的同時，去掉更多的隨機噪聲。 同時，為減弱時頻峰值濾波對高頻信號的衰減，本文提出了一種新的算法，即變曲率雙曲軌線時頻峰值濾波。該算法首先利用Radon變換把地震記錄不同彎曲程度的同相軸分離不同的子記錄，之后對每一個子記錄選擇合適的采樣軌線，使得采樣后的頻率降低，這樣經(jīng)過TFPF后信號幅度衰減將減小此方法可以減少TFPF對有效信號帶來的誤差，從而提高濾波結(jié)果的信噪比。我們將此算法應(yīng)用到了模擬以及實際地震記錄中，都達到了很好的保幅和去噪的結(jié)果。
[Abstract]:Seismic exploration is an important method to explore seismic structure and determine the location of reservoir gas. This method mainly uses high-energy shock as the input of the earth and collects the response signal by geophone to judge the properties and geological structure of the geological interface. However, due to the overuse of oil and gas resources, it is difficult for prospectors to find oil and gas resources in shallow positions, and seismic exploration technology will develop to deeper areas. Because the signal propagates far away, the amplitude of the signal attenuates seriously, and will be submerged by random noise, which will lead to the failure to recognize the signal. So seismic denoising is particularly important. As a new denoising method, time-frequency peak filtering has achieved good results in seismic noise removal, which has attracted the attention of geophysics in recent years. However, the traditional time-frequency peak filter only filters along the time direction and does not recover the signal by using the temporal and spatial correlation of the signal, which will affect the retention of the signal. Secondly, the traditional algorithm uses the fixed window length filter to the seismic records, the large window length can suppress the noise very well, but the signal amplitude preservation is not ideal; the small window length signal keeps the amplitude ideal, but the noise is still largely left behind. In order to achieve both amplitude preserving performance and denoising performance of time-frequency peak filtering, a new two-dimensional spatio-temporal filtering method is proposed in this paper, that is, high-resolution hyperbolic Radon domain variable window time-frequency peak filtering. In this algorithm, the hyperbolic cophase axis is firstly concentrated in several high energy positions in Radon domain using high-resolution Radon transform. Because of the superposition of the effective signal, it is easier to identify the signal in the Radon domain, which provides favorable conditions for the subsequent filtering. After that, the signal and noise are identified in Radon domain by setting a reasonable threshold, and the signal is filtered with small window length, and the noise is filtered with large window length, which can preserve the amplitude and remove more random noise at the same time. At the same time, in order to reduce the attenuation of high frequency signals by time-frequency peak filtering, a new algorithm, time-frequency peak filtering for hyperbolic track with variable curvature, is proposed in this paper. The algorithm firstly uses Radon transform to separate different sub-records from the same phase axis of seismic records with different bending degrees, and then selects appropriate sampling tracks for each sub-record, so that the frequency after sampling is reduced. In this way, the signal amplitude attenuation after TFPF can reduce the error caused by TFPF to the effective signal, thus improving the signal-to-noise ratio of the filtering results. The algorithm is applied to the simulation and the actual seismic records, and the results of amplitude preserving and denoising are very good.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：P631.4;TN911.7

【參考文獻】

相關(guān)期刊論文 前3條

1 李亞峻;李月;楊寶俊;高穎;;SVD與小波變換相結(jié)合抑制面波與隨機噪聲[J];計算機工程與應(yīng)用;2007年31期

2 劉保童;朱光明;;去假頻高分辨率τ-p變換法波場分離[J];煤田地質(zhì)與勘探;2006年02期

3 曾有良;樂友喜;單啟銅;孫銀行;;基于高分辨率Radon變換的VSP波場分離方法[J];石油物探;2007年02期

相關(guān)博士學(xué)位論文 前1條

1 鞏向博;金屬礦地震高精度成像與數(shù)據(jù)處理方法研究[D];吉林大學(xué);2011年

本文編號：1850901