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| Main Authors: | , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.01048 |
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| _version_ | 1866908994598076416 |
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| author | Vargas, Ricardo Emanuel Vaz Junior, Afrânio José de Melo Munaro, Celso José Lima, Cláudio Benevenuto de Campos Junior, Eduardo Toledo de Lima Barrocas, Felipe Muntzberg Varejão, Flávio Miguel Peixer, Guilherme Fidelis Oliveira, Igor de Melo Nery Barbosa Jr., Jader Riso Cadena, Jaime Andrés Lozano de Araújo, Jean Carlos Dias Carneiro, João Neuenschwander Escosteguy Lopes, Lucas Gouveia Omena de Gouveia, Lucas Pereira Fernandes, Mateus de Araujo Scramignon, Matheus Lima Ciarelli, Patrick Marques Branco, Rodrigo Castello Pinto, Rogério Leite Alves |
| author_facet | Vargas, Ricardo Emanuel Vaz Junior, Afrânio José de Melo Munaro, Celso José Lima, Cláudio Benevenuto de Campos Junior, Eduardo Toledo de Lima Barrocas, Felipe Muntzberg Varejão, Flávio Miguel Peixer, Guilherme Fidelis Oliveira, Igor de Melo Nery Barbosa Jr., Jader Riso Cadena, Jaime Andrés Lozano de Araújo, Jean Carlos Dias Carneiro, João Neuenschwander Escosteguy Lopes, Lucas Gouveia Omena de Gouveia, Lucas Pereira Fernandes, Mateus de Araujo Scramignon, Matheus Lima Ciarelli, Patrick Marques Branco, Rodrigo Castello Pinto, Rogério Leite Alves |
| contents | In the oil industry, undesirable events in oil wells can cause economic losses, environmental accidents, and human casualties. Solutions based on Artificial Intelligence and Machine Learning for Early Detection of such events have proven valuable for diverse applications across industries. In 2019, recognizing the importance and the lack of public datasets related to undesirable events in oil wells, Petrobras developed and publicly released the first version of the 3W Dataset, which is essentially a set of Multivariate Time Series labeled by experts. Since then, the 3W Dataset has been developed collaboratively and has become a foundational reference for numerous works in the field. This data article describes the current publicly available version of the 3W Dataset, which contains structural modifications and additional labeled data. The detailed description provided encourages and supports the 3W community and new 3W users to improve previous published results and to develop new robust methodologies, digital products and services capable of detecting undesirable events in oil wells with enough anticipation to enable corrective or mitigating actions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_01048 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | 3W Dataset 2.0.0: a realistic and public dataset with rare undesirable real events in oil wells Vargas, Ricardo Emanuel Vaz Junior, Afrânio José de Melo Munaro, Celso José Lima, Cláudio Benevenuto de Campos Junior, Eduardo Toledo de Lima Barrocas, Felipe Muntzberg Varejão, Flávio Miguel Peixer, Guilherme Fidelis Oliveira, Igor de Melo Nery Barbosa Jr., Jader Riso Cadena, Jaime Andrés Lozano de Araújo, Jean Carlos Dias Carneiro, João Neuenschwander Escosteguy Lopes, Lucas Gouveia Omena de Gouveia, Lucas Pereira Fernandes, Mateus de Araujo Scramignon, Matheus Lima Ciarelli, Patrick Marques Branco, Rodrigo Castello Pinto, Rogério Leite Alves Machine Learning In the oil industry, undesirable events in oil wells can cause economic losses, environmental accidents, and human casualties. Solutions based on Artificial Intelligence and Machine Learning for Early Detection of such events have proven valuable for diverse applications across industries. In 2019, recognizing the importance and the lack of public datasets related to undesirable events in oil wells, Petrobras developed and publicly released the first version of the 3W Dataset, which is essentially a set of Multivariate Time Series labeled by experts. Since then, the 3W Dataset has been developed collaboratively and has become a foundational reference for numerous works in the field. This data article describes the current publicly available version of the 3W Dataset, which contains structural modifications and additional labeled data. The detailed description provided encourages and supports the 3W community and new 3W users to improve previous published results and to develop new robust methodologies, digital products and services capable of detecting undesirable events in oil wells with enough anticipation to enable corrective or mitigating actions. |
| title | 3W Dataset 2.0.0: a realistic and public dataset with rare undesirable real events in oil wells |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2507.01048 |