Improvement of Wired Drill Pipe Data Quality via Data Validation and Reconciliation

doi:10.1007/s11633-017-1068-9

CASIA OpenIR > 学术期刊 > Machine Intelligence Research

	Improvement of Wired Drill Pipe Data Quality via Data Validation and Reconciliation
	Dan Sui; Olha Sukhoboka; Bernt Sigve Aadnøy
发表期刊	International Journal of Automation and Computing
ISSN	1476-8186
	2018
卷号	15 期号:5 页码:625-636
摘要	Wired drill pipe (WDP) technology is one of the most promising data acquisition technologies in todays oil and gas industry. For the first time it allows sensors to be positioned along the drill string which enables collecting and transmitting valuable data not only from the bottom hole assembly (BHA), but also along the entire length of the wellbore to the drill floor. The technology has received industry acceptance as a viable alternative to the typical logging while drilling (LWD) method. Recently more and more WDP applications can be found in the challenging drilling environments around the world, leading to many innovations to the industry. Nevertheless most of the data acquired from WDP can be noisy and in some circumstances of very poor quality. Diverse factors contribute to the poor data quality. Most common sources include mis-calibrated sensors, sensor drifting, errors during data transmission, or some abnormal conditions in the well, etc. The challenge of improving the data quality has attracted more and more focus from many researchers during the past decade. This paper has proposed a promising solution to address such challenge by making corrections of the raw WDP data and estimating unmeasurable parameters to reveal downhole behaviors. An advanced data processing method, data validation and reconciliation (DVR) has been employed, which makes use of the redundant data from multiple WDP sensors to filter/remove the noise from the measurements and ensures the coherence of all sensors and models. Moreover it has the ability to distinguish the accurate measurements from the inaccurate ones. In addition, the data with improved quality can be used for estimating some crucial parameters in the drilling process which are unmeasurable in the first place, hence provide better model calibrations for integrated well planning and realtime operations.
关键词	Data quality wired drill pipe (WDP) data validation and reconciliation (DVR) drilling models.
DOI	10.1007/s11633-017-1068-9
引用统计	被引频次：7[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/42439
专题	学术期刊_Machine Intelligence Research
作者单位	Petroleum Engineering Department, University of Stavanger, Stavanger 4036, Norway
推荐引用方式 GB/T 7714	Dan Sui,Olha Sukhoboka,Bernt Sigve Aadnøy. Improvement of Wired Drill Pipe Data Quality via Data Validation and Reconciliation[J]. International Journal of Automation and Computing,2018,15(5):625-636.
APA	Dan Sui,Olha Sukhoboka,&Bernt Sigve Aadnøy.(2018).Improvement of Wired Drill Pipe Data Quality via Data Validation and Reconciliation.International Journal of Automation and Computing,15(5),625-636.
MLA	Dan Sui,et al."Improvement of Wired Drill Pipe Data Quality via Data Validation and Reconciliation".International Journal of Automation and Computing 15.5(2018):625-636.

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