發(fā)布時(shí)間：2018-08-24 17:11

【摘要】：地震勘探作為地球物理勘探中的一種主要的勘探方法,在資源勘探,地質(zhì)結(jié)構(gòu)研究中發(fā)揮著重要的作用。野外采集的地震資料中往往含有大量的噪聲,嚴(yán)重影響了后續(xù)的反演和解釋工作。因此,對(duì)地震資料中的噪聲進(jìn)行消減,提高地震資料的信噪比和分辨率對(duì)地質(zhì)構(gòu)造的研究以及尋找油氣等礦藏資源具有重要意義。國(guó)內(nèi)外現(xiàn)有的消噪方法大多受到某種假設(shè)或條件限制,在某些特定條件下,如低信噪比、復(fù)雜隨機(jī)噪聲等,無(wú)法獲得理想的消噪效果。與其他方法相比,近幾年發(fā)展起來(lái)的時(shí)頻峰值濾波(TFPF:Time Frequency Peak Filtering)算法具有低信噪比、于非平穩(wěn)信號(hào)等處理能力,但是傳統(tǒng)TFPF算法仍存在固定窗長(zhǎng)、忽略相鄰道間相關(guān)性等不足。為此,本文以消減強(qiáng)噪聲環(huán)境下地震記錄中的隨機(jī)噪聲為目的,針對(duì)傳統(tǒng)TFPF在地震勘探數(shù)據(jù)處理中的不足,結(jié)合徑向道變換理論,分別提出了基于平行徑向軌線和非線性雙曲軌線的時(shí)空二維方向軌線TFPF算法,并通過(guò)人工合成地震記錄以及野外實(shí)際地震資料的處理驗(yàn)證了新算法的濾波性能及實(shí)用性。本研究基于徑向道變換思想,突破傳統(tǒng)TFPF處理非線性信號(hào)的局限,首次構(gòu)建平行徑向軌線TFPF消噪模型,實(shí)現(xiàn)中高頻信號(hào)的高保真恢復(fù)。平行徑向軌線TFPF利用地震記錄中相鄰地震道間反射波的相關(guān)性,打破了傳統(tǒng)TFPF算法僅沿時(shí)間方向?yàn)V波的局限性,從根本上減小了由TFPF產(chǎn)生的誤差,克服了傳統(tǒng)TFPF中采用固定濾波窗長(zhǎng)造成不同頻率成分反射波的幅值衰減,甚至畸變等缺點(diǎn),有效實(shí)現(xiàn)了中高頻反射波的高保真恢復(fù)。文中深入探討了徑向軌線方程建立、最優(yōu)濾波軌線選取、重采樣點(diǎn)坐標(biāo)近似以及樣本點(diǎn)插值等關(guān)鍵環(huán)節(jié),結(jié)合模擬地震記錄討論了不同斜率的徑向軌線對(duì)消噪結(jié)果的影響以及濾波窗長(zhǎng)的選取。在平行徑向軌線TFPF算法中,沿軌線重采樣后隨機(jī)噪聲無(wú)明顯變化,而有效地震波線性度顯著提高,主頻明顯降低,進(jìn)而有效降低TFPF估計(jì)偏差,使恢復(fù)出的地震波幅值與能量得到很好的保持。不同背景噪聲下合成地震記錄的仿真實(shí)驗(yàn)及其與傳統(tǒng)TFPF的對(duì)比結(jié)果表明,在相同窗長(zhǎng)條件下,平行徑向軌線TFPF方法有效消減隨機(jī)噪聲的同時(shí),恢復(fù)出的反射波幅值和能量更接近理想值,有效頻率成分(尤其是高頻反射同相軸)保持得更完整。同時(shí),該算法對(duì)記錄中的低頻噪聲也有較好的消減能力。實(shí)際共炮點(diǎn)地震資料的濾波結(jié)果表明,平行徑向軌線TFPF處理后反射同相軸更清晰,更連續(xù);原本淹沒(méi)于強(qiáng)隨機(jī)噪聲中的弱反射同相軸的能量及連續(xù)性均得到增強(qiáng)而清晰顯現(xiàn)。為獲得高品質(zhì)的地震資料及進(jìn)一步提高信噪比,針對(duì)徑向軌線與反射同相軸不能完全匹配的局限性,本文充分利用了地震子波的時(shí)空相關(guān)性并結(jié)合反射同相軸在地震記錄中的分布形態(tài),從反射波時(shí)距關(guān)系曲線出發(fā),建立了非線性雙曲軌線TFPF去噪模型,有效避免了軌線與同相軸不匹配造成部分能量的衰減,完善了平行徑向軌線TFPF消噪模型。本文對(duì)模型中的雙曲軌線方程建立、最優(yōu)濾波軌線選取及數(shù)據(jù)樣本點(diǎn)采樣等進(jìn)行了研究。雙曲軌線與同相軸的高匹配度最大限度地提高了采樣后有效波的線性度,其頻率顯著降低,濾波窗長(zhǎng)更長(zhǎng),消減噪聲的能力更強(qiáng),濾波效果不再受到濾波窗長(zhǎng)的嚴(yán)格限制,窗長(zhǎng)的選擇范圍更大。雙曲軌線TFPF較徑向軌線TFPF的窗長(zhǎng)選取更靈活。合成地震記錄的消噪結(jié)果表明,雙曲軌線TFPF算法在低信噪比環(huán)境中具有良好的濾波性能。與平行徑向軌線TFPF相比,在相同窗長(zhǎng)條件下具有更好的噪聲消減效果,其恢復(fù)的反射波幅值和頻帶與理想值最為接近,子波能量得到更好的保持,濾波后記錄的信噪比大幅提高。對(duì)實(shí)際共炮點(diǎn)地震資料的處理結(jié)果表明,雙曲軌線TFPF算法在地震勘探隨機(jī)噪聲壓制中更具優(yōu)越性,恢復(fù)出的反射同相軸也更清晰、連貫,其輪廓更平滑,濾波后地震記錄的信噪比和分辨率明顯提高。兩種時(shí)空軌線TFPF模型均充分利用了地震波時(shí)空相關(guān)性,將濾波方向拓展為與反射同相軸形態(tài)接近的最優(yōu)濾波軌線方向,實(shí)現(xiàn)有效反射波線性度的優(yōu)化。濾波軌線的形態(tài)與樣式直接影響重采樣后信號(hào)的線性度及主頻變化,進(jìn)而影響TFPF估計(jì)偏差與去噪效果,因此最優(yōu)濾波軌線選取是整個(gè)時(shí)空軌線TFPF消噪模型中的關(guān)鍵環(huán)節(jié)。本文針對(duì)不同軌線樣式分別提出了兩種最優(yōu)濾波軌線選取方法。在平行徑向軌線模型中,首次提出通過(guò)尋找同相軸上距軸兩端點(diǎn)連線最遠(yuǎn)點(diǎn)來(lái)確定最佳濾波軌線。根據(jù)幾何中點(diǎn)到直線的距離公式分別計(jì)算出同相軸上不同點(diǎn)到兩端點(diǎn)連線的距離值,連接最大距離點(diǎn)與某一軸端點(diǎn)來(lái)獲得最優(yōu)濾波軌線。在雙曲軌線模型中,將地震記錄中同相軸看成圖像邊緣,并基于Canny算子邊緣檢測(cè)法實(shí)現(xiàn)同相軸位置及走勢(shì)檢測(cè),根據(jù)反射波與噪聲沿同相軸方向的相關(guān)性差異,采用加權(quán)均值方法確定軌線曲率變化范圍,選取該范圍內(nèi)沿軌線疊加能量最大值所對(duì)應(yīng)的軌線作為最優(yōu)濾波軌線。
[Abstract]:Seismic exploration, as one of the main exploration methods in geophysical exploration, plays an important role in resource exploration and geological structure research. The seismic data collected in the field often contain a lot of noise, which seriously affects the follow-up inversion and interpretation work. The signal-to-noise ratio (SNR) and the resolution of the data are of great significance to the study of geological structure and the exploration of oil and gas resources.Most of the existing denoising methods at home and abroad are limited by certain assumptions or conditions.Under certain conditions, such as low SNR, complex random noise, etc., ideal denoising effect can not be obtained. TFPF (Time Frequency Peak Filtering) algorithm developed in 1998 has low signal-to-noise ratio (SNR) and non-stationary signal processing ability, but the traditional TFPF algorithm still has some shortcomings, such as fixed window length, ignoring the correlation between adjacent channels and so on. The shortcomings of traditional TFPF in seismic exploration data processing are discussed. Combining with the theory of radial trace transform, the TFPF algorithm of space-time two-dimensional directional trajectory based on parallel radial trajectory and nonlinear hyperbolic trajectory is proposed respectively. The filtering performance and practicability of the new algorithm are verified by processing synthetic seismograms and field seismic data. Based on the idea of radial track transform, this paper breaks through the limitation of traditional TFPF in processing nonlinear signals, and constructs a parallel radial track TFPF denoising model for the first time to realize high fidelity recovery of medium and high frequency signals. The limitation of filtering can reduce the error caused by TFPF fundamentally, overcome the disadvantage of amplitude attenuation or even distortion of reflected waves with different frequency components caused by fixed filtering window length in traditional TFPF, and effectively realize high fidelity recovery of medium and high frequency reflections. Taking, resampling point coordinate approximation and sample point interpolation as key links, the influence of radial trajectories with different slopes on noise reduction and the selection of filtering window length are discussed in combination with simulated seismic records. The simulation results of synthetic seismograms under different background noises and their comparison with traditional TFPF show that the parallel radial trajectory TFPF method can effectively reduce the random noise under the same window length. The amplitude and energy of the reflected wave recovered are closer to the ideal value, and the effective frequency components (especially the high frequency reflection in-phase axis) are more complete. In order to obtain high-quality seismic data and further improve the signal-to-noise ratio, in view of the limitation of the incomplete matching between the radial trajectory and the reflection coaxial, this paper makes full use of the spatial-temporal correlation of seismic wavelet. The TFPF denoising model of nonlinear hyperbolic trajectory is established based on the time-distance relation curve of reflection wave. The TFPF denoising model of parallel radial trajectory is improved by avoiding the partial energy attenuation caused by the mismatch between the trajectory and the phase axis. Establishment, selection of optimal filtering trajectory and sampling of data sample points are studied. The high matching degree between hyperbolic trajectory and phase axis maximizes the linearity of the effective wave after sampling. Its frequency is significantly reduced, the filtering window is longer, the ability of noise reduction is stronger, the filtering effect is no longer strictly limited by the filtering window length and the window length. The results of synthetic seismic data denoising show that the hyperbolic track TFPF algorithm has good filtering performance in low signal-to-noise ratio environment. Compared with the parallel radial track TFPF, the hyperbolic track TFPF has better noise reduction effect under the same window length, and its recovery is opposite. The amplitude and frequency band are the closest to the ideal value, the wavelet energy is better maintained, and the signal-to-noise ratio is greatly improved after filtering. The processing results of real common shot seismic data show that the hyperbolic trajectory TFPF algorithm has more advantages in suppressing random noise in seismic exploration, and the reconstructed reflection coaxiality is clearer and more coherent. Both TFPF models make full use of the spatial-temporal correlation of seismic waves and extend the filtering direction to the optimal filtering trajectory direction close to the reflection in-phase shape, so as to optimize the linearity of the effective reflection wave. In this paper, two optimal filtering trajectory selection methods are proposed for different trajectory patterns. In the parallel radial trajectory model, the optimal filtering trajectory selection is the key link of the whole time-space trajectory TFPF denoising model. For the first time, the optimal filtering trajectory is determined by finding the farthest point of the line connecting the two ends of the coaxial axis. According to the distance formula from the geometric midpoint to the straight line, the distances from different points on the coaxial axis to the two ends of the line are calculated respectively, and the maximum distances are connected with the end points of a certain axis to obtain the optimal filtering trajectory. In seismic records, the in-phase axis is regarded as the edge of the image, and the position and trend of the in-phase axis are detected based on the Canny operator edge detection method. According to the correlation difference between the reflected wave and noise along the in-phase axis, the curvature range of the track is determined by the weighted mean method, and the track corresponding to the maximum superimposed energy along the track is selected. As the optimal filtering trajectory.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：P631.4

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