Logo do repositório

Development and Implementation of an IA-Based System to Automate Textual Classification on Daily Drilling Reports

dc.contributor.authorPerrout, S.
dc.contributor.authorRiente, A. F.
dc.contributor.authorVanni, G.
dc.contributor.authorAnjos, J.
dc.contributor.authorMendes, D. H.
dc.contributor.authorGuilherme, I. [UNESP]
dc.contributor.authorPedronette, D. C. [UNESP]
dc.contributor.authorRodrigues, R. B. [UNESP]
dc.contributor.authorPrivatto, P. I. [UNESP]
dc.contributor.authorMurari, R. P. [UNESP]
dc.contributor.authorPenteado, B. [UNESP]
dc.contributor.authorAfonso, L.C. Sugi [UNESP]
dc.contributor.institutionPetroleo Brasileiro
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2025-04-29T20:04:14Z
dc.date.issued2023-01-01
dc.description.abstractStructured daily drilling reports (DDRs) are a rich source of information that allows better planning, more accurate risk analysis, improved key performance indicators (KPIs), and contracts. However, such information is originally stored in a free-text and unstructured format, which becomes difficult for efficient data mining. With the advances of artificial intelligence (AI)-based technologies, particularly AI language models, applying such techniques over unstructured data became key in the digital transformation phenomenon. This paper presents an approach for automatic DDR classification, incorporating new techniques of artificial intelligence. The proposed classifier is already in use in Petrobras for offshore DDR classification.en
dc.description.affiliationPetrobras Petroleo Brasileiro
dc.description.affiliationSão Paulo State University UNESP
dc.description.affiliationUnespSão Paulo State University UNESP
dc.identifierhttp://dx.doi.org/10.4043/32978-MS
dc.identifier.citationOffshore Technology Conference Brasil, OTCB 2023.
dc.identifier.doi10.4043/32978-MS
dc.identifier.scopus2-s2.0-85175543614
dc.identifier.urihttps://hdl.handle.net/11449/305798
dc.language.isoeng
dc.relation.ispartofOffshore Technology Conference Brasil, OTCB 2023
dc.sourceScopus
dc.titleDevelopment and Implementation of an IA-Based System to Automate Textual Classification on Daily Drilling Reportsen
dc.typeTrabalho apresentado em eventopt
dspace.entity.typePublication

Arquivos

Coleções