RESEARCH ARTICLE


The Basics of Noise Detection and Filtering for Borehole Drilling Data



Meen-Wah Gui*
Department of Civil Engineering (NTUT2656), National Taipei University of Technology, No 1, Sec 3, ZhongXiao E. Rd., Taipei 106, Taiwan.


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© 2008 Meen-Wah Gui.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Department of Civil Engineering (NTUT2656), National Taipei University of Technology, No 1, Sec 3, ZhongXiao E. Rd., Taipei 106, Taiwan; Tel: +886955154891; Fax: +886227814518; E-mail: mwgui@ntut.edu.tw


Abstract

A series of borehole instrumented drilling tests have been performed at two separate sites in London. However, these data contain noise which makes interpretation difficult. A study was thus carried out to explore the possibility of using signal processing techniques to remove noise from the instrumented borehole drilling data. The study began by examining the most common methods used to detect noise in a signal. Three types of filter: moving average, median and Butterworth filters were compared. Filtering weight for moving average filter, filtering order for median filter, and cut-off frequency for Butterworth filter were then proposed for each of the drilling parameters. The effects of standardized and non-standardized drilling procedures on the drilling data were also demonstrated by using cross-correlation functions for groups of standardized and non-standardized tests.