3W Dataset 2.0.0: a realistic and public dataset with rare undesirable real events in oil wells
Ricardo Emanuel Vaz Vargas, Afr\^anio Jos\'e de Melo Junior, Celso Jos\'e Munaro, Cl\'audio Benevenuto de Campos Lima, Eduardo Toledo de Lima Junior, Felipe Muntzberg Barrocas, Fl\'avio Miguel Varej\~ao, Guilherme Fidelis Peixer, Igor de Melo Nery Oliveira

TL;DR
The paper presents the updated 3W Dataset 2.0.0, a comprehensive public multivariate time series dataset with rare undesirable oil well events, supporting AI-based early detection research.
Contribution
It introduces the latest version of the 3W Dataset with structural modifications and additional labeled data, fostering advancements in oil well event detection.
Findings
Dataset now includes more labeled data and structural improvements.
Supports development of robust AI methodologies for early event detection.
Encourages community collaboration and methodological improvements.
Abstract
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…
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