智能井壓力數(shù)據(jù)分析方法研究
[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(jí)別】:碩士
【學(xué)位授予年份】:2015
【分類(lèi)號(hào)】:TE928
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