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Using Statistical Techniques to Improve the QC Process of Swell Noise FilteringNormal access

Authors: A. Spanos and M. Bekara
Event name: 75th EAGE Conference & Exhibition incorporating SPE EUROPEC 2013
Session: Noise Attenuation
Publication date: 10 June 2013
DOI: 10.3997/2214-4609.20130884
Organisations: EAGE
Language: English
Info: Extended abstract, PDF ( 369.17Kb )
Price: € 20

Summary:
The current approach for the quality control (QC) process of the swell noise filtering phase carries significant drawbacks. This abstract investigates the use of statistical techniques to improve the QC process. The main approach of this analysis is to combine attributes that capture properties of the filtering process and plot them against each other in order to identify “outliers”. It is shown that cases which have been “badly” or not “properly” filtered will cluster away from the main group and may be detected using statistical methods such as clustering algorithms. Statistical techniques may potentially play an important role in the development of a data-driven automated QC platform.


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