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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sui, D. Nybo, R. Azizi, V. |
| Copyright Year | 2013 |
| 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. |
| Starting Page | 357 |
| Ending Page | 362 |
| File Size | 201557 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467347075 |
| ISSN | 19483449 |
| e-ISBN | 9781467347082 |
| DOI | 10.1109/ICCA.2013.6564893 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-06-12 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Mathematical model Optimization Real-time systems Kalman filters Equations Trajectory Data models |
| Content Type | Text |
| Resource Type | Article |
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