基于案例推理技术的井漏风险识别方法
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摘要
井漏风险造成的危害严重,钻井过程中如果发生井漏风险,就容易造成储层污染及更为严重的次生危害。要降低井漏造成的损失,提高钻井效率,就必须对井漏风险进行实时识别,以便及时采取防漏堵漏措施。由于井漏风险因素有很多,如果仅采用一个或几个风险因素通过对比对井漏风险进行识别,容易造成误判。采用案例推理方法为理论依据,通过对井漏风险因素进行研究,选取了总池体积、出入口流量、地层孔隙压力当量密度等11个风险因素,运用多信息融合技术,建立了基于案例推理技术的井漏风险识别模型,从而避免了单因素对比识别造成的偏差,为井漏风险实时识别提供更可靠的分析方法。研究结果表明,该方法可以对井漏风险进行识别。
Lost circulation risk can cause serious damage. If lost circulation risk happens during drilling, it can easily cause pollution to reservoir and more serious secondary damages. In order to reduce losses caused by lost circulation and improve drilling efficiency, the identification of lost circulation risk and real time leak resistance and sealing measures must be made. There are many lost circulation risk factors, so comparing only one or several factors to identify lost circulation may easily cause miscarriage. Based on case-based reasoning method, through the study on the related risk factors of lost circulation, we choose 11 risk factors such as tank volume change, mud flow-out, pore pressure and so on, to establish lost circulation identification model, so as to avoid the error caused by single factor risk identification and provide a more reliable method for lost circulation risk identified in real time. The research result showed this method can identify the risk of lost circulation.
Lost circulation risk can cause serious damage. If lost circulation risk happens during drilling, it can easily cause pollution to reservoir and more serious secondary damages. In order to reduce losses caused by lost circulation and improve drilling efficiency, the identification of lost circulation risk and real time leak resistance and sealing measures must be made. There are many lost circulation risk factors, so comparing only one or several factors to identify lost circulation may easily cause miscarriage. Based on case-based reasoning method, through the study on the related risk factors of lost circulation, we choose 11 risk factors such as tank volume change, mud flow-out, pore pressure and so on, to establish lost circulation identification model, so as to avoid the error caused by single factor risk identification and provide a more reliable method for lost circulation risk identified in real time. The research result showed this method can identify the risk of lost circulation.
引文
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[4] 杨立平,杨进.现代综合录井技术基础及应用[M].北京:石油工业出版社,2008.
[5] 刘金华.工程参数录井在钻井工程中的应用[J].断块油气田,2003,10(5):87-88.
[6] 李凤霞,崔茂荣,王丽华,等.综合录井技术在实时监测钻井事故中的应用[J].断块油气田,2007,14(4):66-68.
[7] 金聪,戴上平,郭京蕾,等.人工智能教程[M].北京:清华大学出版社,2007.
[8] 罗忠良,王克运,康仁科,等.基于案例推理系统中案例检索算法的探索[J].计算机工程与应用,2005,41(25):230-232.
[9] 郭建明,李琪,徐英卓.基于实例和规则集成推理的钻井事故诊断处理系统[J].石油钻探技术,2007,35(3):15-18.
[10] 张树杰,黄勇,王静滨,等.基于熵值和TOPSIS法的装备体系方案优选方法[J].兵工自动化,2016,35(1):20-22.
[11] Hayes-Roth F,Lenat D,Water man D,et al.Building Expert Systems [M].Addison-Wesley,1983.
[12] Raja, H, S?rmo, F. and Vinther, M.L. Case-Based Reasoning: Predicting Real-Time Drilling Problems and Improving Drilling Performance. Paper SPE 141598-MS presented at the SPE Middle East Oil and Gas Show and Conference held in Manama Bahrain, 25-28 September, 2011.
[13] Dean Le. Case-Based Reasoning Technology Used to Provide Early Indications of Potential NPT-Related Problems While Drilling the Viking. Paper SPE 162866-MS presented at the SPE Canadian Unconventional Resources Conference, Calgary, Alberta, Canada, 30 October-1 November, 2012.
[14] Shokouhi, S.V., Skalle,P., S?rmo, F. Integration of Real-time Data and Past Experiences for Reducing Operational Problems. Paper SPE 13969-MS presented at the International Petroleum Technology Conference, Doha, Qatar, 7-9 December, 2009.
[15] 柳玉, 贲可荣.案例推理的故障诊断技术研究综述[J].计算机科学与探索,2011,5(10):5-19.
[16] 侯玉梅,许成媛.基于案例推理法研究综述[J].燕山大学学报(哲学社会科学版),2011,12(4):108-114.
[17] 朱群雄, 刘光. CBR 技术在Multi-Agent 故障诊断中的应用[J]. 计算机工程与应用, 2004, 12(1): 111-113.