【摘要】：隨著油氣田開發(fā)難度的不斷增加,油井管套損也愈加嚴(yán)重,對套損的檢測和預(yù)防日益成為油氣田研究領(lǐng)域的熱點之一。井下電視系統(tǒng)是進行井下工況監(jiān)測及套損預(yù)防的重要手段之一,通過井下攝像機直接對套管內(nèi)壁進行攝像,對實時截取到的套損圖像進行邊緣檢測及相應(yīng)的定量分析可以便捷的判斷出套損程度�；疑P(guān)聯(lián)分析作為灰色理論重要的組成部分,已廣泛應(yīng)用于圖像工程中。本文嘗試將灰色關(guān)聯(lián)分析亞像素檢測理論首次引入到套損檢測分析中,實現(xiàn)了對套管損壞程度的定量解釋。論文研究了灰色關(guān)聯(lián)分析理論,主要介紹了灰色關(guān)聯(lián)分析的定義、數(shù)據(jù)序列預(yù)處理和灰色關(guān)聯(lián)度的計算。針對從井下電視系統(tǒng)截取到的含噪聲的套損圖像,引入灰色B型關(guān)聯(lián)度算法對油井管套損圖像進行去噪聲處理。對除噪后的套損圖像,首先,提出了采用灰色關(guān)聯(lián)分析算法對油井管套損圖像進行邊緣檢測,實現(xiàn)了圖像邊緣的像素級定位,解決了傳統(tǒng)邊緣檢測算子對不同特性邊緣所表現(xiàn)出來的差異性問題。其次,利用基于Zernike矩的亞像素檢測理論對像素級邊緣點進一步精確定位,實現(xiàn)了對這些有效邊緣點的亞像素級邊緣提取,提高了后續(xù)套損分析中定量解釋的精確度。本文將灰色關(guān)聯(lián)分析和亞像素檢測理論相結(jié)合,將其應(yīng)用于油井管套損檢測,仿真實驗表明該方法具有較好的檢測效果,在提高檢測精度的同時也減少了運算時間。最后,采用面向?qū)ο笳Z言開發(fā)了油井管套損檢測系統(tǒng),實現(xiàn)了油井管套損程度的定量解釋和相關(guān)套損數(shù)據(jù)的實時顯示,為套損檢測和預(yù)防提供了一定指導(dǎo)作用。
[Abstract]:With the increasing difficulty of oil and gas field development, casing damage of oil well pipe is becoming more and more serious, and the detection and prevention of casing damage has become one of the hotspots in the field of oil and gas field research. Downhole television system is one of the important means to monitor downhole working conditions and prevent casing damage. The edge detection and quantitative analysis of the real time captured casing damage image can easily judge the casing damage degree. As an important part of grey theory, grey correlation analysis has been widely used in image engineering. This paper attempts to introduce the theory of sub-pixel detection of grey correlation analysis into casing damage detection for the first time, and realize the quantitative interpretation of casing damage degree. This paper studies the theory of grey correlation analysis, mainly introduces the definition of grey correlation analysis, the preprocessing of data sequence and the calculation of grey correlation degree. Aiming at the noise-contained casing damage image intercepted from downhole television system, grey B-type correlation algorithm is introduced to remove noise from casing damage image of oil well pipe. First of all, the gray correlation analysis algorithm is used to detect the edge of casing damage image of oil well pipe, and the pixel level location of image edge is realized. It solves the problem of the difference of the traditional edge detection operator to different characteristic edges. Secondly, the sub-pixel detection theory based on Zernike moment is used to locate the edge points of pixel level, and the sub-pixel edge detection of these effective edge points is realized, which improves the accuracy of quantitative interpretation in the subsequent casing damage analysis. In this paper, grey correlation analysis is combined with sub-pixel detection theory, which is applied to oil well casing damage detection. The simulation results show that the method has better detection effect, and improves the detection accuracy and reduces the calculation time. Finally, an oil well casing damage detection system is developed by using object-oriented language. The quantitative interpretation of casing damage degree and the real-time display of relevant casing damage data are realized, which provides some guidance for casing damage detection and prevention.
【學(xué)位授予單位】：西安石油大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TE931.2;TP391.41

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