本文選題：表面多次波　切入點(diǎn)：3D　出處：《東北石油大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：多次反射波廣泛存在于地震數(shù)據(jù)中,海洋資料尤為嚴(yán)重。目前,絕大多數(shù)的處理方法僅利用一次反射波進(jìn)行成像,多次反射波的存在會(huì)嚴(yán)重掩蓋一次反射波信息,多次波處理不當(dāng)將直接影響后續(xù)的地震成像和解釋,因此,地震資料多次波壓制方法研究意義甚大�；诓▌�(dòng)方程的表面多次波壓制方法,又稱SRME(Surface-Related Multiple Elimination),是一種數(shù)據(jù)驅(qū)動(dòng)的方法,無需其他先驗(yàn)信息,運(yùn)用了反饋迭代的思想,可有效壓制復(fù)雜介質(zhì)表面多次波。該方法由多次波預(yù)測(cè)和自適應(yīng)相減兩個(gè)關(guān)鍵步驟組成。目前,受計(jì)算和數(shù)據(jù)存儲(chǔ)等因素影響,多次波預(yù)測(cè)大多局限于二維,或者通過諸多的假設(shè)、振幅匹配等將三維地震數(shù)據(jù)利用二維算法近似計(jì)算,其有悖于地下介質(zhì)的真實(shí)情況,往往難以獲取理想效果。常規(guī)基于L2范數(shù)匹配濾波方法盡管計(jì)算速度快,求解穩(wěn)定,但是需要滿足兩個(gè)假設(shè)條件:一是壓制多次波后記錄能量最小;二是一次波與多次波具有正交性。本文在完成常規(guī)二維SRME預(yù)測(cè)方法和L2范數(shù)匹配濾波方法的基礎(chǔ)上,創(chuàng)新性的完成了五方面內(nèi)容:一是三維SRME方法預(yù)測(cè)多次波,該方法突破了二維算法的局限,充分考慮到地震波在地下介質(zhì)中的空間傳播效應(yīng),使得預(yù)測(cè)出的多次波更加精確;二是無需插值計(jì)算的基于拋物稀疏反演的三維多次波預(yù)測(cè)方法,該方法利用拋物Radon變換代替crossline方向多次波貢獻(xiàn)道集的求和,避免了地震數(shù)據(jù)在crosline方向的內(nèi)插和外推,同時(shí)減少空間假頻的引入;三是基于L1范數(shù)匹配濾波方法,該方法能夠避免基于L2范數(shù)濾波方法的兩個(gè)假設(shè)條件,利用L1范數(shù)的魯棒性對(duì)大值的異常保持穩(wěn)健;四是基于L1/L2范數(shù)結(jié)合匹配濾波方法,考慮到L1范數(shù)和L2范數(shù)匹配濾波方法的各自特性,在較短的時(shí)間內(nèi)得到收斂的維納濾波器,使預(yù)測(cè)的多次波模型和原始記錄中的多次波能夠更好的擬合;五是將GPU(Graphics Processing Unit)和CPU(Central Processing Unit)協(xié)同并行加速技術(shù)成功應(yīng)用于上述算法,極大地提高了多次波預(yù)測(cè)和自適應(yīng)相減的計(jì)算效率。
[Abstract]:Multiple reflection waves are widely used in seismic data, especially in marine data. At present, most of the processing methods use only one reflection wave to image, and the existence of multiple reflection waves will cover up the information of one reflection wave seriously. The improper processing of multiple waves will directly affect the subsequent seismic imaging and interpretation. Therefore, the study of seismic data multiple suppression method is of great significance. The surface multiple suppression method based on wave equation, also known as SRME(Surface-Related Multiple delay, is a data-driven method. Without other prior information, the feedback iteration method is used to suppress the complex media surface multiple effectively. The method consists of two key steps: multiple prediction and adaptive subtraction. At present, it is affected by the factors such as computation and data storage, etc. The prediction of multiple waves is mostly confined to two dimensions, or through many assumptions and amplitude matching, 3D seismic data are approximately calculated by two-dimensional algorithm, which is contrary to the real situation of underground media. It is difficult to obtain ideal results. Although the conventional L2-norm matched filtering method is fast and stable, it needs to satisfy two hypotheses: first, the minimum recording energy is obtained after suppression of multiple waves; The second is the orthogonality between primary wave and multiple wave. On the basis of the conventional 2-D SRME prediction method and L2-norm matched filtering method, five aspects have been innovatively completed in this paper: first, the 3D SRME method is used to predict multiple waves. This method breaks through the limitation of two-dimensional algorithm and fully takes into account the spatial propagation effect of seismic waves in underground media, which makes the prediction of multiple waves more accurate. The second is the 3D multiples prediction method based on parabolic sparse inversion, which uses parabolic Radon transform instead of the sum of crossline direction multiple contribution traces, thus avoiding the interpolation and extrapolation of seismic data in the crosline direction. The third is based on L1 norm matched filtering method, which can avoid the two hypotheses based on L2 norm filtering method, and keep robust to the anomaly of large value by using the robustness of L1 norm. Fourth, based on L _ 1 / L _ 2 norm combined with matched filtering method, considering the characteristics of L1 norm and L _ 2 norm matching filtering method, we obtain convergent Wiener filter in a relatively short time. The predicted multiples model and the original records can be fitted better. Fifth, the GPU(Graphics Processing Unit and CPU(Central Processing Unit are successfully applied to the above algorithms. The computational efficiency of multiple prediction and adaptive subtraction is greatly improved.
【學(xué)位授予單位】：東北石油大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：P631.4

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