An Efficient Approach for Real-Time Prediction of Rate of Penetration in Offshore Drilling
Joint Authors
Shi, Xian
Liu, Gang
Gong, Xiaoling
Zhang, Jialin
Wang, Jian
Zhang, Hongning
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-11-06
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Predicting the rate of penetration (ROP) is critical for drilling optimization because maximization of ROP can greatly reduce expensive drilling costs.
In this work, the typical extreme learning machine (ELM) and an efficient learning model, upper-layer-solution-aware (USA), have been used in ROP prediction.
Because formation type, rock mechanical properties, hydraulics, bit type and properties (weight on the bit and rotary speed), and mud properties are the most important parameters that affect ROP, they have been considered to be the input parameters to predict ROP.
The prediction model has been constructed using industrial reservoir data sets that are collected from an oil reservoir at the Bohai Bay, China.
The prediction accuracy of the model has been evaluated and compared with the commonly used conventional artificial neural network (ANN).
The results indicate that ANN, ELM, and USA models are all competent for ROP prediction, while both of the ELM and USA models have the advantage of faster learning speed and better generalization performance.
The simulation results have shown a promising prospect for ELM and USA in the field of ROP prediction in new oil and gas exploration in general, as they outperform the ANN model.
Meanwhile, this work provides drilling engineers with more choices for ROP prediction according to their computation and accuracy demand.
American Psychological Association (APA)
Shi, Xian& Liu, Gang& Gong, Xiaoling& Zhang, Jialin& Wang, Jian& Zhang, Hongning. 2016. An Efficient Approach for Real-Time Prediction of Rate of Penetration in Offshore Drilling. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1112048
Modern Language Association (MLA)
Shi, Xian…[et al.]. An Efficient Approach for Real-Time Prediction of Rate of Penetration in Offshore Drilling. Mathematical Problems in Engineering No. 2016 (2016), pp.1-13.
https://search.emarefa.net/detail/BIM-1112048
American Medical Association (AMA)
Shi, Xian& Liu, Gang& Gong, Xiaoling& Zhang, Jialin& Wang, Jian& Zhang, Hongning. An Efficient Approach for Real-Time Prediction of Rate of Penetration in Offshore Drilling. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1112048
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112048