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首頁» 過刊瀏覽» 2021» Vol.6» Issue(3) 451-464???? DOI : 10.3969/j.issn.2096-1693.2021.03.036
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深水淺層淺水流災害風險評價與防災方法研究
申屠俊杰,,林伯韜,陸吉
1 中國石油大學(北京) 油氣資源與探測國家重點實驗室,,北京 102249 2 中國石油大學(北京) 石油工程學院,,北京 102249 3 中國石油大學(北京) 人工智能學院,北京 102249
Research on risk assessment and prevention methods of shallow water flow hazards in deep-water and shallow areas
SHENTU Junjie, LIN Botao, LU Ji
1 State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing 102249, China 2 College of Petroleum Engineering, China University of Petroleum-Beijing, Beijing 102249, China 3 College of Artificial Intelligence, China University of Petroleum-Beijing, Beijing 102249, China

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摘要? 隨著全球能源需求日益增加,,海洋油氣資源,,尤其是深水資源成為了新一輪的勘探開發(fā)熱點,。深水油氣 資源具有儲量高,、潛力大,、探明率低的特點,但同時也伴隨著淺層地質(zhì)災害等陸上鉆井不曾面臨的問題,。淺水 流災害是一種頻繁的淺層地質(zhì)災害,,其實質(zhì)為深水淺層發(fā)育的超壓砂體,主要由地層中快速沉積和不平衡壓實 作用形成,。淺水流災害破壞力大,、分布區(qū)域廣,對井壁,、套管,、井口等均有影響,嚴重破壞井筒完整性,。本文 首先闡述淺水流災害的概念,、危害及主要成因,,其次總結(jié)了淺水流的識別預測技術(shù),、風險評價方法及相關(guān)防控 措施,,最后提出了風險評價及綜合防災方法。淺水流的識別與預測方法主要有測井法和反射地震法兩種,,其中 反射地震法是最常用的方法,,主要通過Vp/Vs值的異常變化實現(xiàn)淺水流超壓砂體的識別。目前,,淺水流災害的風 險評價工作側(cè)重于鉆前預測,,以定性判斷為主,缺乏定量分析,,但近年來涌現(xiàn)的實驗及數(shù)值模擬研究正不斷填 補這塊空白,。淺水流的預防和控制作業(yè)主要包括井控措施和工作液體系優(yōu)化。本文綜合了現(xiàn)階段淺水流災害的 風險預測及評價工作,,提出一套新的風險評價體系,,并將風險評價體系與防災措施相結(jié)合,形成動態(tài)防災方法,。 該防災方法可合理規(guī)劃淺水流區(qū)域鉆井作業(yè)施工,,并將風險評價方案與應對機制有機結(jié)合,并且可在作業(yè)過程 中不斷優(yōu)化方案,,從而提高鉆井作業(yè)的靈活性和防災能力,。最后,本文展望了淺水流災害防災工作的發(fā)展趨勢,, 認為淺水流流動破壞機制的基礎(chǔ)研究,、地球物理識別技術(shù)的發(fā)展及人工智能技術(shù)的應用將是今后的研究熱點和 重點。
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關(guān)鍵詞 : 地質(zhì)災害;淺水流,;防災方法,;風險評價;機器學習
Abstract
With the continuous increase in global energy demand, offshore oil & gas resources, especially deep-water oil & gas
resources, have become new development hotspots. The deep-water oil & gas resources are characterized by high reserves, great  
potential and low exploration rates, but they are also accompanied by shallow geological hazards and other problems that onshore  
drilling works have never faced. Shallow water flow (SWF) is a common geological hazard, which is essentially the over-pres
sured sand section developed in the deep water and shallow areas and mainly formed by rapid deposition and unbalanced  
compaction in the formation. SWF hazards have large destructive power and wide distribution areas, which have influence on  
the borehole, casing and wellhead, and can seriously damage the integrity of the wellbore. In this paper, the concept, harm, and  
main causes of SWF hazards are firstly expounded. Then the identification and prediction technology, risk assessment methods,  
prevention, and control measures of SWF hazards are summarized. Finally, risk assessment and comprehensive prevention  
methods are put forward. It is concluded that the identification and prediction methods of SWF hazards mainly include logging  
and reflection seismic methods. Among these, the reflection seismic method is adopted more commonly in practice, which recog
nizes the overpressure sand body by the abnormal fluctuations of the value of V p / V s . At present, the risk assessment of the SWF  
hazards places more emphasis on the pre-drilling prediction and qualitative judgment but lacks quantitative analyses. However,  
experimental and numerical simulation studies have been constantly filling this gap in recent years. The prevention and control  
operations of SWF hazards include well control measures and working fluid system optimization. Based on current work of the  
risk prediction and assessment of the SWF hazards, a new risk assessment system is proposed and then combined with disaster  
prevention measures in this study, proposing a dynamic hazard prevention method. This hazard prevention method reasonably  
plans the drilling operations in SWF areas, combines the risk assessment scheme with the response mechanism, and continuously  
optimizes the drilling scheme during the drilling operation to improve the flexibility of drilling operations and enhances the  
hazard prevention ability. Finally, the development trends of SWF hazard prevention are examined. It is considered that basic  
research into the flow failure mechanism of the SWF hazards, the development of geophysical identification technology, as well  
as the application of artificial intelligence technology (AIT) will be the research emphases in the future.


Key words: geological hazard; shallow water flow; hazard prevention methods; risk assessment; machine learning
收稿日期: 2021-09-29 ????
PACS: ? ?
基金資助:國家科技重大專項(2017ZX05009-003) 和中國石油大學( 北京) 科研啟動基金項目(ZX20200120) 聯(lián)合資助
通訊作者: [email protected]
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申屠俊杰, 林伯韜. 深水淺層淺水流災害風險評價與防災方法研究. 石油科學通報, 2021, 03: 451-464 SHENTU Junjie, LIN Botao, LU Ji. Research on risk assessment and prevention methods of shallow water flow hazards in deep-water and shallow areas. Petroleum Science Bulletin, 2021, 03: 451-464.
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