發(fā)布時間：2018-10-16 10:30

【摘要】：隨著地震勘探逐步走入復雜地形勘探的環(huán)境,因而所獲得的地震信號的信噪比較低。同時這些復雜地形中的地震信號,往往存在著較為嚴重的信號缺失和廢道,廢炮,這為地震信號的處理提出了新的要求和挑戰(zhàn)。而由于地震信號在頻域的稀疏性,其可以使用較少量的系數(shù)來表征整個地震信號,同時,各種使得地震信號質量下降的污染都可以被視為對這種稀疏性的破壞。因而該性質可以被有效地應用其來對地震信號進行更加精確的處理,從而提高地震剖面的質量。本文圍繞地震信號的去噪,地震信號的缺失道重建以及超分辨率重建這三個主要問題,從深入學習稀疏表示和壓縮感知的理論框架出發(fā),重點研究了稀疏表示和壓縮感知理論在地震信號處理流程中得典型應用。主要研究內容如下:對于地震去噪問題,本文在研究了Shearlet變換的理論與實現(xiàn)和閾值去噪的基礎上,提出了運用各向異性擴散濾波器對子帶進行處理的去噪方法,達到了同時在Shearlet域上進行了信號增強和噪聲抑制的目的。同時,本文對其進行了數(shù)值仿真與分析另外,本文針對地震數(shù)據(jù)的缺失道重構問題,在對地震缺失道的模型進行了分析的基礎上,針對多種促稀疏重構方法進行的研究,應用與詳細的結果分析。并針對這些方法在地震數(shù)據(jù)重構領域中的應用范圍進行了對比和分析。繼而本文設計了一種兩步法進行地震數(shù)據(jù)的超分辨率重建的策略,依據(jù)不同的數(shù)據(jù)規(guī)模,選擇不同的方法和稀疏表示來分別對時間分辨率和空間分辨率進行處理。并對理論地震數(shù)據(jù)以及實際地震數(shù)據(jù)進行了算法的仿真與測試,取得了較好的效果。
[Abstract]:The signal-to-noise ratio (SNR) of the obtained seismic signal is low with the seismic exploration gradually moving into the environment of complex terrain exploration. At the same time, the seismic signals in these complex terrain often have more serious signal missing, abandoned road, abandoned gun, which put forward new requirements and challenges for seismic signal processing. Due to the sparsity of seismic signal in frequency domain, a small number of coefficients can be used to characterize the whole seismic signal. At the same time, all kinds of pollution that make the quality of seismic signal decline can be regarded as damage to the sparsity. Therefore, this property can be effectively used to process seismic signals more accurately, thus improving the quality of seismic profiles. This paper focuses on the three main problems of seismic signal denoising, seismic signal missing channel reconstruction and super-resolution reconstruction, starting from the theoretical framework of sparse representation and compression perception. The typical application of sparse representation and compression sensing theory in seismic signal processing is studied. The main research contents are as follows: for the problem of seismic denoising, based on the study of the theory and implementation of Shearlet transform and threshold denoising, an anisotropic diffusion filter is proposed to deal with subband denoising. The aim of both signal enhancement and noise suppression in Shearlet domain is achieved. At the same time, numerical simulation and analysis are carried out. In addition, aiming at the problem of reconstruction of missing traces in seismic data, based on the analysis of the model of seismic missing traces, this paper studies several methods to promote sparse reconstruction. Application and detailed result analysis. The application scope of these methods in seismic data reconstruction is compared and analyzed. Then this paper designs a two-step method for super-resolution reconstruction of seismic data. According to different data scale, different methods and sparse representation are selected to process temporal resolution and spatial resolution respectively. The theoretical seismic data and the actual seismic data are simulated and tested, and good results are obtained.
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：P631.4;TN911.7

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相關碩士學位論文 前1條

1 魏芳;基于多尺度幾何分析的紅外弱小目標檢測方法研究[D];電子科技大學;2012年

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本文編號：2274076