本文選題：海底混輸管道 + 多相流　； 參考：《西南石油大學》2015年碩士論文

【摘要】：國內早期鋪設的海底管道中有相當數(shù)量的管道從未實施過內檢測,由于管道內部情況復雜,亦難以實施內檢測。隨著服役年限的增長,由于投建初期管道在建設、施工等方面的諸多不足以及隨后運行管理過程中維護措施的欠缺,導致此類管道存在著不同程度的安全隱患,同時伴隨著輸送效率的低下等問題。海底多相流管道其腐蝕影響因素很多,各因素之間又相互作用,當下還沒有一種通用的腐蝕速率預測模型。針對這一現(xiàn)狀,文中以非線性的人工神經網(wǎng)絡算法為基礎,通過建立海底管道多相流內腐蝕速率預測模型,自主編制了“多相流海底管道內腐蝕速率預測”程序,主要研究內容如下：(1)海底多相流管道基礎參數(shù)收集與分析及目標管道的選定針對海底混輸管道的輸送介質、輸送壓力、含水量等進行現(xiàn)場資料調研與收集,包括但不限于管道設計、建造、生產、運行與維護資料�；谀壳耙延械墓艿纼葯z測情況、清管情況、運行工況等,選定SP76-EP76管道為研究對象,對目標管道進行參數(shù)資料整理和分析。(2)內腐蝕直接評估軟件OLGA的管道內部工況分析基于海底混輸管道(SP76-EP76管段)的路由圖,結合海底管道走向高程變化,將目標管道劃分為9段,共計60小段。通過對管道內部工況的模擬計算,確定管道內與腐蝕相關參數(shù)的分布情況,為自主編制的“多相流海底管道內腐蝕速率預測”程序提供有效的基礎參數(shù)支撐。(3)基于神經網(wǎng)絡算法的“多相流海底管道內腐蝕速率預測”程序編制以OLGA計算得到的與腐蝕速率相關的參數(shù)(如溫度、壓力、持液率、酸性組分含量等)在管道內部的分布情況為基礎,建立人工神經網(wǎng)絡腐蝕速率預測模型,通過C語言對“多相流海底管道內腐蝕速率預測”程序進行編制。(4)“多相流海底管道內腐蝕速率預測”程序誤差分析對自主編制程序“多相流海底管道內腐蝕速率預測”的計算結果、主流“內腐蝕直接評估軟件OLGA"的計算結果、現(xiàn)場實際內檢測結果進行比較分析,驗證“多相流海底管道內腐蝕速率預測”程序的準確性。結果顯示：“多相流海底管道內腐蝕速率預測”程序計算結果更符合實際情況。
[Abstract]:A considerable number of pipelines laid in China have never carried out internal inspection, and it is difficult to carry out internal inspection because of the complex internal conditions. With the increase of service life, due to many deficiencies in the construction and construction of pipelines in the initial stage of construction, and the lack of maintenance measures in the subsequent operation and management process, there are some hidden dangers to the safety of such pipelines to varying degrees. At the same time accompanied by the low transport efficiency and other problems. There are many factors affecting corrosion of submarine multiphase flow pipeline, and the factors interact with each other. There is no universal corrosion rate prediction model. In view of this situation, based on the nonlinear artificial neural network algorithm and by establishing the prediction model of internal corrosion rate of multiphase flow in submarine pipeline, the program of "prediction of internal corrosion rate of multi-phase flow submarine pipeline" has been programmed independently. The main research contents are as follows: (1) the collection and analysis of the foundation parameters of the multiphase flow pipeline and the selection of the target pipeline are carried out on the spot investigation and collection for the transport medium, transport pressure and water content of the submarine mixed pipeline. Includes, but is not limited to, piping design, construction, production, operation and maintenance data. Based on the existing pipeline detection situation, pipe-clearing situation, operating conditions and so on, the SP76-EP76 pipeline is selected as the research object. The pipeline internal working condition analysis of OLGA software is based on the route diagram of SP76-EP76 pipeline), and the target pipeline is divided into 9 sections according to the elevation change of submarine pipeline. A total of 60 segments. The distribution of the corrosion related parameters in the pipeline is determined by the simulation calculation of the internal working conditions of the pipeline. It provides effective basic parameter support for the self-compiled program of "Prediction of Internal corrosion rate of Multiphase flow Submarine Pipeline". Based on neural network algorithm, the program of "Prediction of Internal corrosion rate of Multiphase flow Submarine Pipeline" is calculated by OLGA. To parameters related to the corrosion rate (such as temperature, Based on the distribution of pressure, liquid holdup, acid component content and so on, an artificial neural network (Ann) corrosion rate prediction model is established. Programming of "Prediction of Internal corrosion rate of Multiphase flow Submarine Pipeline" by C language.) "Prediction of Internal corrosion rate of Multiphase flow Submarine Pipeline" Program error Analysis of Independent programming Program "Internal corrosion rate of Multiphase flow Submarine Pipeline" The results of the calculation of the rate prediction, The calculation results of the mainstream "direct evaluation software OLGA" are compared and analyzed in the field to verify the accuracy of the program "Prediction of corrosion rate in multiphase flow submarine pipeline". The results show that the calculation results of "prediction of internal corrosion rate of multiphase flow submarine pipeline" are more in line with the actual situation.
【學位授予單位】：西南石油大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TE988.2

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本文編號：1911565