Extended Kalman filters and piece-wise linear segmentation for the processing of drilling data

This research is oriented to the development and implementation of signal processing techniques for the analysis of drilling data with a focus on adaptive filters and segmentation schemes. The thesis is divided into two distinct parts; the first part deals with the use of extended Kalman filters to...

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Main Author: Soroush, Amirali
Format: Thesis
Published: Curtin University 2012
Online Access:http://hdl.handle.net/20.500.11937/57584
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author Soroush, Amirali
author_facet Soroush, Amirali
author_sort Soroush, Amirali
building Curtin Institutional Repository
collection Online Access
description This research is oriented to the development and implementation of signal processing techniques for the analysis of drilling data with a focus on adaptive filters and segmentation schemes. The thesis is divided into two distinct parts; the first part deals with the use of extended Kalman filters to estimate in real-time the instantaneous angular velocity of the drilling bit using downhole measurements, while the second part is devoted to a novel method for the segmentation of piece-wise linear signals corrupted with noise.
first_indexed 2025-11-14T10:09:48Z
format Thesis
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T10:09:48Z
publishDate 2012
publisher Curtin University
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repository_type Digital Repository
spelling curtin-20.500.11937-575842017-11-16T04:59:10Z Extended Kalman filters and piece-wise linear segmentation for the processing of drilling data Soroush, Amirali This research is oriented to the development and implementation of signal processing techniques for the analysis of drilling data with a focus on adaptive filters and segmentation schemes. The thesis is divided into two distinct parts; the first part deals with the use of extended Kalman filters to estimate in real-time the instantaneous angular velocity of the drilling bit using downhole measurements, while the second part is devoted to a novel method for the segmentation of piece-wise linear signals corrupted with noise. 2012 Thesis http://hdl.handle.net/20.500.11937/57584 Curtin University fulltext
spellingShingle Soroush, Amirali
Extended Kalman filters and piece-wise linear segmentation for the processing of drilling data
title Extended Kalman filters and piece-wise linear segmentation for the processing of drilling data
title_full Extended Kalman filters and piece-wise linear segmentation for the processing of drilling data
title_fullStr Extended Kalman filters and piece-wise linear segmentation for the processing of drilling data
title_full_unstemmed Extended Kalman filters and piece-wise linear segmentation for the processing of drilling data
title_short Extended Kalman filters and piece-wise linear segmentation for the processing of drilling data
title_sort extended kalman filters and piece-wise linear segmentation for the processing of drilling data
url http://hdl.handle.net/20.500.11937/57584