本文關(guān)鍵詞：遼河油區(qū)鉆具失效分析與檢測研究　出處：《東北石油大學》2017年碩士論文　論文類型：學位論文

  更多相關(guān)文章： 遼河油區(qū) 鉆具失效 失效分析 檢測 圖像檢測

【摘要】：鉆具在井下的受力十分復(fù)雜,服役條件苛刻,鉆柱要承受應(yīng)力交變載荷、溫度、環(huán)境介質(zhì)、鉆柱與井壁的摩擦、高頻撞擊、腐蝕和氫脆影響等,容易發(fā)生多種多樣的鉆具失效事故。一旦發(fā)生失效事故,造成的損失相當嚴重。通過采取有效措施對于防止鉆具失效意義重大。研究分析鉆具的失效故障,弄清楚鉆具失效的主要原因和機理,并通過相應(yīng)的檢測技術(shù)手段提前判斷出鉆具失效的部位,確定鉆具的使用狀態(tài),可以便于我們使用和維護好鉆具,從而能夠為預(yù)防井下鉆具失效,降低事故損失,增強鉆井競爭力提供有力的保障。本文首先對遼河油區(qū)鉆具失效情況進行了統(tǒng)計和研究,研究表明疲勞是影響鉆具失效的主要原因,鉆具表面應(yīng)力集中部位都易發(fā)生疲勞失效狀況。數(shù)據(jù)顯示,鉆桿和鉆鋌失效事故占所有總數(shù)的84.7%,其中螺紋部位是重點發(fā)生事故點,且這些失效事故中的大部分都是與疲勞相關(guān)。然后針對當前5種檢測手段在遼河油區(qū)鉆具失效檢測的效果和適應(yīng)性進行了研究。通過對現(xiàn)場的應(yīng)用情況研究發(fā)現(xiàn),螺紋檢測主要采用超聲波檢測方法,管體的檢測主要采用整體漏磁檢測設(shè)備進行檢測,但這些方法也有依賴于檢測人員具有一定的經(jīng)驗,而且超聲波對螺紋的形貌無法進行自動檢測。基于此種情況,文中提出了設(shè)計一套鉆桿自動檢測系統(tǒng)。該檢測系統(tǒng)包括6大部分:第一部分是鉆具回收臺,可以將不同尺寸類型的鉆桿分別存放,便于后面的檢測;第二部分是自動校直鉆桿,實現(xiàn)鉆桿的直線度檢測和自動校直;第三部分是管體漏磁檢測,與當前采用的檢測系統(tǒng)相同;第四部分是自動清洗螺紋,設(shè)計了一個螺紋清洗裝置,可進行鉆具螺紋的清潔處理,去除螺紋表面的污泥及其它污垢,使螺紋牙表面光潔;第五部分是螺紋檢測,提出了基于數(shù)字處理的圖像檢測系統(tǒng),可以快速精確的判定螺紋情況,完成形貌方面的檢測;最后是鉆桿分級分類,通過PLC控制,綜合分析管體和螺紋的檢測結(jié)果,然后斷定鉆桿級別并自動送入相應(yīng)的管架臺存放。
[Abstract]:The drill string is subjected to stress alternating load, temperature, environmental medium, friction between drill string and well wall, high frequency impact, corrosion and hydrogen embrittlement, etc. It is easy to occur a variety of drilling failure accidents. Once the failure accident occurs, the loss is very serious. It is very important to take effective measures to prevent the drilling tool failure. It is convenient for us to use and maintain the drill tool by making clear the main reason and mechanism of drilling tool failure, and by means of the corresponding testing technology to judge the position of drilling tool failure in advance and to determine the use state of drill tool. Thus it can prevent downhole drilling tool failure, reduce accident loss and enhance drilling competitiveness. Firstly, this paper makes statistics and research on drilling tool failure in Liaohe oil area. The results show that fatigue is the main reason that affects the failure of drilling tools, and fatigue failure is easy to occur at the stress concentration on the surface of drilling tools. The data show that the failure accidents of drill pipes and drill collars account for 84.7% of the total number. The thread part is the key accident point. And most of these failure accidents are related to fatigue. Then, the effect and adaptability of five kinds of testing methods in Liaohe oil area are studied. . The thread inspection mainly adopts the ultrasonic testing method, the tube body inspection mainly uses the whole magnetic flux leakage testing equipment to carry on the inspection, but these methods also have the certain experience to the testing personnel. And ultrasonic can not automatically detect the shape of the thread. Based on this situation, this paper proposed the design of a drill pipe automatic detection system. The detection system consists of six parts: the first part is the drilling tool recovery table. The drill pipe of different size type can be stored separately, which is convenient for the later detection; The second part is the automatic straightening drill pipe to realize the straightness detection and automatic straightening of drill pipe. The third part is the tube body magnetic flux leakage detection, which is the same as the current detection system. 4th part is automatic cleaning thread, designed a thread cleaning device, can carry on the drilling tool thread cleaning treatment, removes the thread surface sludge and other dirt, makes the thread tooth surface smooth; 5th part is thread detection, the image detection system based on digital processing is put forward, which can quickly and accurately judge the thread situation and complete the shape detection. Finally, the drill pipe is classified into different grades, which is controlled by PLC, and the test results of pipe body and thread are synthetically analyzed, and then the drill pipe grade is determined and automatically sent to the corresponding pipe stand for storage.
【學位授予單位】：東北石油大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TE921.2

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