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This sensing technology is capable of recording substantial data volumes at multiple depths within an oil well, giving unprecedented insights into production behaviour. However the technology is also prone to recording periods of anomalous behaviour, where the same physical features are concurrently observed at multiple depths. Such features are called \u2018stripes\u2019 and are undesirable, detrimentally affecting well performance modelling. This paper focuses on the important challenge of developing a principled approach to identifying such anomalous periods within distributed acoustic signals. We extend recent work on classifying locally stationary wavelet time series to an online setting and, in so doing, introduce a computationally-efficient online procedure capable of accurately identifying anomalous regions within multivariate time series.<\/jats:p>","DOI":"10.1007\/s10618-018-00608-w","type":"journal-article","created":{"date-parts":[[2019,2,20]],"date-time":"2019-02-20T08:14:19Z","timestamp":1550650459000},"page":"748-772","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Dynamic detection of anomalous regions within distributed acoustic sensing data streams using locally stationary wavelet time series"],"prefix":"10.1007","volume":"33","author":[{"given":"Rebecca E.","family":"Wilson","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9957-2460","authenticated-orcid":false,"given":"Idris A.","family":"Eckley","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4719-2690","authenticated-orcid":false,"given":"Matthew A.","family":"Nunes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Timothy","family":"Park","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,2,20]]},"reference":[{"issue":"6","key":"608_CR1","doi-asserted-by":"publisher","first-page":"1355","DOI":"10.1109\/TSP.2002.1003060","volume":"50","author":"PL Ainsleigh","year":"2002","unstructured":"Ainsleigh PL, Kehtarnavaz N, Streit RL (2002) Hidden Gauss\u2013Markov models for signal classification. 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