本文選題：煤層氣　切入點(diǎn)：高分辨率　出處：《中國石油大學(xué)(華東)》2015年碩士論文

【摘要】：煤層氣是一種清潔能源,煤層氣的勘探開發(fā)在世界范圍內(nèi)日益受到重視。煤層氣的研究已經(jīng)成為地震學(xué)中的前沿課題之一,開展對煤層氣的研究對于深入了解地球介質(zhì)結(jié)構(gòu),勘探開發(fā)復(fù)雜油氣藏和地質(zhì)災(zāi)害的預(yù)報等具有重要理論意義和現(xiàn)實(shí)意義。地震資料分辨率是進(jìn)一步提高地震反演、地震屬性分析、煤儲層含氣性預(yù)測精度的重要研究內(nèi)容。實(shí)際上由于地層的吸收以及采集、接收等各方面因素的影響,使常規(guī)地震勘探得到的地震記錄頻帶較窄,分辨率較低。對地震數(shù)據(jù)同時進(jìn)行振幅和相位的補(bǔ)償,提高地震資料的有效帶寬,使地震資料在保持信噪比前提下提高分辨率。本文討論了通過反Q濾波的方法提高地震資料的分辨率。地震道時頻分解方法可以將地震道分解為各種各樣不同的子波,這些子波具有不同主頻、不同子波寬度、以及不同時間位置。時頻分析作為分析時變非平穩(wěn)信號的有力工具,成為現(xiàn)代信號處理研究的一個熱點(diǎn)。地震信號屬于一種非平穩(wěn)信號,這種分析方法提供了時間域與頻率域的聯(lián)合分布信息,清楚地為我們描述了地震信號頻率隨時間變化的關(guān)系,本文主要通過匹配追蹤以及視頻譜分解的方法對地震數(shù)據(jù)進(jìn)行時頻分析。某地區(qū)煤層氣產(chǎn)層單煤層薄,煤層氣含量橫向變化大,通過對高分辨率處理的應(yīng)用研究,對地震數(shù)據(jù)同時進(jìn)行振幅和相位的補(bǔ)償,提高地震資料的有效帶寬,使地震資料在保持信噪比前提下提高分辨率;利用追蹤匹配算法的時頻分解方法進(jìn)行薄層分析和煤層氣富集區(qū)預(yù)測研究,根據(jù)地震數(shù)據(jù)的頻率域變化特征,運(yùn)用神經(jīng)網(wǎng)絡(luò)綜合聚類方法對煤系地層的空間分布及含氣性進(jìn)行描述。
[Abstract]:Coalbed methane (CBM) is a kind of clean energy, and the exploration and development of CBM have been paid more and more attention in the world. The study of CBM has become one of the frontier topics in seismology. Exploration and development of complex reservoirs and geological hazard prediction have important theoretical and practical significance. The resolution of seismic data is to further improve seismic inversion, seismic attribute analysis, In fact, due to the influence of stratigraphic absorption, acquisition, reception and other factors, the frequency band of seismic records obtained from conventional seismic exploration is relatively narrow. Low resolution. The amplitude and phase of the seismic data are compensated at the same time to increase the effective bandwidth of the seismic data. In this paper, we discuss how to improve the resolution of seismic data by inverse Q filter. The seismic trace can be decomposed into a variety of wavelet by time-frequency decomposition method. These wavelets have different main frequencies, different wavelet widths, and different time positions. Time-frequency analysis is a powerful tool for analyzing time-varying non-stationary signals. Seismic signal is a kind of non-stationary signal, which provides the joint distribution information between time domain and frequency domain. The relationship between the frequency of seismic signal and time is clearly described for us. In this paper, the time-frequency analysis of seismic data is carried out by means of matching tracing and video spectrum decomposition. The transverse variation of CBM content is large. By studying the application of high-resolution processing, the amplitude and phase of seismic data are compensated at the same time, the effective bandwidth of seismic data is increased, and the resolution of seismic data is improved under the premise of keeping signal-to-noise ratio. Thin-layer analysis and prediction of coalbed methane rich area are studied by time-frequency decomposition method of tracing matching algorithm. According to the variation characteristics of seismic data in frequency domain, The spatial distribution and gas-bearing property of coal measure strata are described by neural network comprehensive clustering method.
【學(xué)位授予單位】：中國石油大學(xué)(華東)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：P631.44;P618.13

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本文編號：1699339