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井壁稳定问题的不确定性分析方法探讨 被引量:9

Discussion on uncertainty analysis method for wellbore stability
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摘要 井壁稳定性失效是钻井工程中主要的复杂情况之一,给钻井作业带来了很大的困难和安全隐患。针对井壁稳定性问题,文中探讨了4种不确定性分析方法:蒙特卡洛(Monte-Carlo)模拟法、统计误差分析法、一次二阶矩法及一次可靠度法。分析发现,基于蒙特卡洛模拟法得到的结果更为保守,更有利于保持井壁稳定性。同时,对影响井壁问题的各个因素进行了敏感性分析,获取了井壁稳定性计算模型中最为敏感的因素:对于坍塌压力最为敏感的因素是最大水平地应力,对于破裂压力最为敏感的因素是最小水平地应力。研究结果有助于确定影响井壁稳定可靠度最为敏感的因素,并运用一定方法提高敏感因素的准确程度,最终减少坍塌及破裂压力预测结果的不确定性,从而提高井壁稳定的可靠度。 Failure of wellbore stability is one of the main complex situations in drilling engineering, which brings great difficulties and security risks to the drilling operation. In this paper, the wellbore stability reliability was analyzed based on the Monte-Carlo simulation, S.E.A.M, F.O.S.M, and F.O.R.M methods. The outcomes of this study show that wellbore instability risks based on Monte- Carlo simulation were more conservative. Therefore, the Monte Carlo simulation is more conducive to the wellbore stability reliability. In addition, sensitivity of random variables of wellbore stability reliability was analyzed based on the Monte-Carlo simulation method. The results show that the maximum horizontal stress is the most sensitive parameter for collapse pressure; the minimum horizontal stress has the largest effects on formation fracture pressure. The outcomes of this study made it possible for risk reducing analysis by focusing on the most sensitive parameters which are critical for the wellbore stability. The accuracy of sensitive parameters is improved to reduce the uncertainties of the collapse and fracture pressure prediction, and the reliability of wellbore stability is improved.
作者 胜亚楠 管志川 许玉强 王庆 张波 SHENG Yanan;GUAN Zhichuan;XU Yuqiang;WANG Qing;ZHANG Bo(College of Petroleum Engineering, China University of Petroleum, Qingdao 266580, Chin)
出处 《断块油气田》 CAS 北大核心 2017年第6期847-850,866,共5页 Fault-Block Oil & Gas Field
基金 国家自然科学基金面上项目"隔水管内气液两相流声传播特性与深水钻井气侵监测方法"(51574275) 长江学者及创新团队发展计划资助项目(IRT_14R58)
关键词 井壁稳定性 不确定性分析 蒙特卡洛模拟法 统计误差分析法 一次二阶矩法 一次可靠度分析法 敏感性分析 wellbore stability uncertainty analysis Monte-Carlo simulation S.E.A.M F.O.S.M F.O.R.M sensitivity analysis
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