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Review Article

The Application of Downhole Vibration Factor in Drilling Tool Reliability Big Data Analytics - A Review

[+] Author and Article Information
Yali Ren

Department of Computer Science, Georgia Institute of Technology, North Avenue, Atlanta, GA 30332 USA
yren78@gatech.edu

Ning Wang

Department of Electrical and Computer Engineering, University of Houston, Engineering Bldg 1, 4726 Calhoun Rd, Houston, TX 77204 USA
nwang@uh.edu

Jinwei Jiang

Department of Mechanical Engineering, University of Houston, Engineering Bldg 1, 4726 Calhoun Rd, Houston, TX 77204 USA
jjiang7@uh.edu

Junxiao Zhu

Department of Mechanical Engineering, University of Houston, Engineering Bldg 1, 4726 Calhoun Rd, Houston, TX 77204 USA
jzhu10@uh.edu

Gangbing Song

Department of Mechanical Engineering, University of Houston, Engineering Building 2, 4726 Calhoun Rd, Houston, TX 77204 USA
gsong@uh.edu

Xuemin Chen

Department of Engineering, Texas Southern University, Houston, Leonard H. O. Spearman Technology Building, 3100 Cleburne Ave, TX 77004 USA
chenxm@tsu.edu

1Corresponding author.

ASME doi:10.1115/1.4040407 History: Received September 01, 2017; Revised May 23, 2018

Abstract

In the challenging downhole environment, drilling tools are normally subject to high temperature, severe vibration and other harsh operation conditions. The drilling activities generate massive field data, namely Field Reliability Big Data (FRBD), which includes downhole operation, environment, failure, degradation and dynamic data. FRBD has large volume, high variety and extreme complexity. FRBD presents abundant opportunities and great challenges for drilling tool reliability analytics. Consequently, as one of the key factors to affect drilling tool reliability, downhole vibration factor plays a critical role in the reliability analytics based on FRBD. This paper reviews the important parameters of downhole drilling operations, examines the mode, physical and reliability impact of downhole vibration, and presents the features of reliability big data analytics. Specifically, this paper explores the application of vibration factor in reliability big data analytics covering tool lifetime/failure prediction, prognostics/diagnostics, condition monitoring, and maintenance planning and optimization. Moreover, the authors highlight the future researches about how to better utilize the downhole vibration in reliability big data analytics to further improve tool reliability and optimize maintenance planning.

Copyright (c) 2018 by ASME
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