论文详情
基于地表数据的井下振动识别与控制
石油钻采工艺
2016年 38卷 第2期
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Title
Identification and control of downhole vibration based on surface data
Authors
HAN Jiageng
WANG Haige
LIN Yuexiang
CUI Meng
单位
中国石油集团钻井工程技术研究院
中国石油勘探开发研究院
中国石油技术开发公司
Organization
CNPC Drilling Research Institute, Beijing 102206, China
PetroChina Research Institute of Petroleum Exploration &
Development, Beijing 100083, China
摘要
钻柱振动识别与控制对于减少钻井过程中事故复杂、防止钻头提前失效具有重要意义。全球每年与钻柱振动相关的失效和破坏的经济损失高达3 亿美元。若能实时监测钻头破岩状态,有效识别并控制钻柱有害振动,则能大大降低这种损失。调研了国内外对钻井振动问题的研究和应用情况,讨论了钻具振动的产生机理及其地表数据响应关系。在基于比能优化技术基础上,建立了一套根据地表数据实时识别并控制井下振动的方法。现场应用表明,振动识别与控制技术能够准确判断井下振动,通过不断优化钻井参数可以消除井下瓶颈因素,挖掘提速潜力,有望为钻井提速和降低成本探寻一条新途径。
Abstract
Identification and control of vibrations of drill strings are of great importance to eliminate drilling accidents and protect drilling bits from premature failure. Globally, economic losses related to failure and damages induced by drill string vibration are up to $300 million every year. Such losses can be reduced significantly as long as rock-breading conditions can be monitored in real time and hazardous vibration of drill strings can be identified and controlled effectively. In this paper, existing researches and applications related to drilling vibration both at home and abroad were reviewed, and mechanisms for generation of such drill-tool vibrations and their relationship with surface data were discussed. Based in energy density optimization, a package of techniques for identification and control of downhole vibration on the baisis of surface data were developed. Field application results show that the vibration identification and control techniques can accurately detect downhole vibration. Through continuous optimization of drilling parameters, the techniques can help to eliminate downhole bottleneck factors so as to fully explore the potential of improving drilling speed. These techniques may provide new alternatives to enhance drilling speeds and to minimize relevant costs.
关键词:
钻柱振动;
地表数据;
比能;
识别;
控制;
优化;
Keywords:
drill string vibration;
surface data;
energy density;
identification;
control;
optimization;
DOI
10.13639/j.odpt.2016.02.003