音頻信號在氣體鉆井?dāng)y巖狀態(tài)監(jiān)測中的應(yīng)用研究
本文選題:氣體鉆井 + 大顆粒巖屑 ; 參考:《西南石油大學(xué)》2017年碩士論文
【摘要】:近年來,氣體鉆井作為一項(xiàng)應(yīng)對復(fù)雜地質(zhì)的高效鉆井方式得到了越來越多的應(yīng)用,但使用氣體作為鉆井循環(huán)介質(zhì)易發(fā)生井壁坍塌、井底巖爆等狀況,急需一種安全監(jiān)測系統(tǒng)保障氣體鉆井的安全運(yùn)行。當(dāng)氣體鉆井發(fā)生異常狀況時(shí),排砂管內(nèi)返出巖屑的流量會(huì)突然變化,大顆粒巖屑明顯增多,及時(shí)、準(zhǔn)確地監(jiān)測大顆粒巖屑的流量變化,可為判斷、預(yù)防井下事故的發(fā)生提供依據(jù)。本文在分析大顆粒巖屑撞擊音頻信號特征的基礎(chǔ)上,開展了氣體鉆井返出大顆粒巖屑的監(jiān)測方法研究。首先,根據(jù)對異常狀況發(fā)生時(shí)巖屑大小的調(diào)研,設(shè)計(jì)了音頻信號采集方案用于采集巖屑撞擊聲和干擾聲;然后,根據(jù)短時(shí)能量的大小尋找聲音段的起止點(diǎn),分析聲音段特征,選定以梅爾倒譜系數(shù)為主的混合參數(shù)組成模板庫,利用人工神經(jīng)網(wǎng)絡(luò)算法排除干擾聲音;最后,分析不同大小巖屑撞擊聲的狀態(tài)特征,分別利用隱馬爾科夫模型和能量法計(jì)算巖屑的大小,并在MATLAB平臺(tái)上驗(yàn)證了方法的可用性。在理論研究的基礎(chǔ)上,設(shè)計(jì)了排砂管線返屑狀態(tài)的安全監(jiān)測系統(tǒng)。系統(tǒng)硬件部分主要由PC機(jī)、外置聲卡、音頻信號線、拾音器、隔音材料組成;軟件部分采用C#語言編寫監(jiān)控界面、SQLServer數(shù)據(jù)庫存儲(chǔ)監(jiān)測信息。通過測試,系統(tǒng)能夠達(dá)到實(shí)時(shí)性、準(zhǔn)確性的要求。通過大量實(shí)驗(yàn)結(jié)果表明,采用聲音處理技術(shù)排除干擾聲,繼而識(shí)別巖屑大小的二級判斷方法,適用于排砂管線返屑狀態(tài)的監(jiān)測,可為氣體鉆井的安全運(yùn)行提供有力保障,有較高的實(shí)用價(jià)值。
[Abstract]:In recent years, gas drilling has been used more and more as an efficient drilling method to deal with complicated geology.A safety monitoring system is urgently needed to ensure the safe operation of gas drilling.When abnormal condition occurs in gas drilling, the flow rate of the back cuttings in the sand discharge pipe will change suddenly, and the large granular cuttings will increase obviously. It can be judged that the flow rate of the large granular cuttings can be monitored in time and accurately.To prevent underground accidents from happening.Based on the analysis of the characteristics of the large particle cuttings impact audio signal, the monitoring method of the large grain cuttings from gas drilling is studied in this paper.First of all, according to the investigation of the debris size when the abnormal condition occurs, the audio signal acquisition scheme is designed to collect the cuttings impact sound and interference sound, and then, according to the size of the short time energy, the starting and ending points of the sound segment are found, and the characteristics of the sound segment are analyzed.The template library is composed of mixed parameters based on Mel cepstrum coefficient, and the interference sound is eliminated by artificial neural network algorithm. Finally, the state characteristics of cuttings impact sound of different sizes are analyzed.The size of cuttings is calculated by using hidden Markov model and energy method respectively, and the availability of the method is verified on MATLAB platform.On the basis of theoretical research, a safety monitoring system for the state of sand discharge pipeline is designed.The hardware part of the system is mainly composed of PC, external sound card, audio signal line, pick-up, soundproof material, and the software part uses C # language to compile the monitor interface and SQL Server database to store monitoring information.Through testing, the system can meet the requirements of real-time and accuracy.Through a large number of experimental results, it is shown that the two-stage judgment method of eliminating interference sound by sound processing technology and then identifying the size of cuttings is suitable for monitoring the sawback state of sand discharge pipeline, and can provide a strong guarantee for the safe operation of gas drilling.It has higher practical value.
【學(xué)位授予單位】:西南石油大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2017
【分類號】:TE242
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