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  • 标题:CALCULATION MODEL OF DEEP-WATER DRILLING FLUID EQUIVALENT CIRCULATION DENSITY AND ANALYSIS OF INFLUENCING FACTORS BASED ON MULTIPLE REGRESSION METHOD
  • 本地全文:下载
  • 作者:Lei Li ; Hexing Liu ; Liangbin Dou
  • 期刊名称:Fresenius Environmental Bulletin
  • 印刷版ISSN:1018-4619
  • 出版年度:2020
  • 卷号:29
  • 期号:11
  • 页码:10118-10127
  • 语种:English
  • 出版社:PSP Publishing
  • 摘要:During the drilling of deep-water formations,the density of drilling fluid is affected by the large temperature difference in the wellbore which is difficult to accurately predict.The deep water drilling could cause drilling difficulties such as narrow safety density windows,which seriously affects the safe and rapid drilling of deep water formations.In order to better control the pressure distribution in the wellbore,based on the multiple regression analysis method,a calculation model of drilling fluid equivalent density in the wellbore was established.The model comprehensively considers the influence of drilling fluid rheological parameters with formation temperature and pressure changes.At the same time,combining the influence of engineering factors such as annulus flow pattern,borehole size,and circulation displacement,the model is solved using iterative numerical calculation methods.The effects of water depth,geothermal gradient and borehole size on drilling fluid rheological parameters and equivalent density were analyzed.Sensitivity analysis results show that the increase in water depth reduces the bottom hole temperature and increases the viscosity and yield point of the drilling fluid,resulting in an increase in the equivalent circulation density.The increase in the geothermal gradient increases the temperature in the wellbore,causing the equivalent circulation density to gradually decrease.The borehole size mainly affects the equivalent circulation density of drilling fluid through the circulation pressure loss,which has little effect on the rheological parameters of drilling fluid.
  • 关键词:Deep-water oil and gas;equivalent circulation density;numerical simulation;multiple regression sensitivity analysis
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