{"title":"Real-time optimization of rate of penetration during drilling operation","authors":"D. Sui, Roar Nybø, V. Azizi","doi":"10.1109/ICCA.2013.6564893","DOIUrl":null,"url":null,"abstract":"The increase of drilling safety and the reduction of drilling operation costs, especially the improvement of drilling efficiency, are two important considerations. In general the rate of penetration (ROP) optimization means that the drilling parameters such as weight on bit (WOB) and rotary speed (RPM) are adjusted to drill the present formation most efficiently. In this paper, the Bourgoyne and Young ROP model had been selected to study the effects of several parameters during drilling operation. We present an advanced method for the ROP calculation and its optimization. A moving-horizon multiple regression method is proposed, which reduces the estimation error of the existing ROP models by continuously calibrating the model coefficients based on real-time data. Furthermore, a model predictive control (MPC) strategy is applied to achieve the ROP optimization to satisfy drilling requirements. The performance of the methodology is demonstrated by using realworld data from a North Sea well.","PeriodicalId":336534,"journal":{"name":"2013 10th IEEE International Conference on Control and Automation (ICCA)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 10th IEEE International Conference on Control and Automation (ICCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCA.2013.6564893","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
The increase of drilling safety and the reduction of drilling operation costs, especially the improvement of drilling efficiency, are two important considerations. In general the rate of penetration (ROP) optimization means that the drilling parameters such as weight on bit (WOB) and rotary speed (RPM) are adjusted to drill the present formation most efficiently. In this paper, the Bourgoyne and Young ROP model had been selected to study the effects of several parameters during drilling operation. We present an advanced method for the ROP calculation and its optimization. A moving-horizon multiple regression method is proposed, which reduces the estimation error of the existing ROP models by continuously calibrating the model coefficients based on real-time data. Furthermore, a model predictive control (MPC) strategy is applied to achieve the ROP optimization to satisfy drilling requirements. The performance of the methodology is demonstrated by using realworld data from a North Sea well.