【摘要】：智能井通過安裝井下設(shè)備,實施遠程監(jiān)控油井參數(shù)和油藏動態(tài),在增加產(chǎn)量和提高油氣采收率方面表現(xiàn)出巨大的潛力,因而得到迅速發(fā)展和應(yīng)用。國內(nèi)外在智能井系統(tǒng)硬件方面的研究已經(jīng)取得很大進展,但是包括實時數(shù)據(jù)處理與解釋在內(nèi)的軟件系統(tǒng)的研究仍然比較滯后,如何快速有效地進行實時監(jiān)測數(shù)據(jù)的處理與解釋乃是智能井實現(xiàn)全面智能化亟待解決的問題之一。論文在充分調(diào)研國內(nèi)外研究成果的基礎(chǔ)上,深入剖析了智能井的系統(tǒng)組成及關(guān)鍵技術(shù),完成智能井光纖監(jiān)測傳輸系統(tǒng)的設(shè)計,實現(xiàn)對井下壓力數(shù)據(jù)的實時采集;運用小波分析理論,通過MATLAB軟件對智能井光纖監(jiān)測傳輸系統(tǒng)采集到的井下壓力數(shù)據(jù)進行降噪、精簡等處理,為后續(xù)的井下壓力數(shù)據(jù)解釋提供更加明確、可靠的信息;結(jié)合油氣層滲流理論,采用數(shù)據(jù)曲線擬合的方法研究了井下壓力數(shù)據(jù)解釋模型,并將其運用到實際生產(chǎn)數(shù)據(jù)中進行計算、分析,識別地層滲流類型,解釋地層參數(shù)的變化規(guī)律。本文引入MATLAB—小波分析和MATLAB—數(shù)據(jù)曲線擬合方法,初步實現(xiàn)了井下壓力監(jiān)測數(shù)據(jù)的處理與解釋,并結(jié)合智能實驗井的實際生產(chǎn)數(shù)據(jù)進行了實例分析和驗證。充實了智能井實時監(jiān)測數(shù)據(jù)處理與解釋方面的研究工作,對智能井技術(shù)基礎(chǔ)研究的進一步發(fā)展具有重要意義。
[Abstract]:Through installation of downhole equipment and remote monitoring of oil well parameters and reservoir performance, intelligent wells have shown great potential in increasing production and increasing oil and gas recovery, so they have been rapidly developed and applied. Great progress has been made in the research of intelligent well system hardware at home and abroad, but the research of software system, including real-time data processing and interpretation, is still lagging behind. How to process and interpret real-time monitoring data quickly and effectively is one of the urgent problems to be solved to realize the full intelligence of intelligent wells. Based on the research results at home and abroad, the paper deeply analyzes the system composition and key technology of intelligent well, completes the design of optical fiber monitoring and transmission system of intelligent well, and realizes the real-time acquisition of downhole pressure data. By using wavelet analysis theory and MATLAB software, the downhole pressure data collected by the optical fiber monitoring and transmission system of intelligent wells are processed by noise reduction and simplification, which provides more clear and reliable information for the subsequent interpretation of downhole pressure data. Combined with the theory of oil and gas reservoir percolation, the interpretation model of underground pressure data is studied by the method of data curve fitting, and it is applied to actual production data to calculate, analyze, identify the type of percolation and explain the variation rule of formation parameters. In this paper, MATLAB- wavelet analysis and MATLAB- data curve fitting method are introduced to realize the processing and interpretation of downhole pressure monitoring data, and the actual production data of intelligent experimental well are analyzed and verified. It enriches the research work of real-time monitoring data processing and interpretation of intelligent wells and is of great significance to the further development of the basic research of intelligent wells technology.
【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】：TE928

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本文編號：2226201