Abstract: A digital twin is a system framework tightly attached to a physical production plant conceived for monitoring the operation in real time. This framework integrates data from distinct sources and supports data analytics and predictive evaluation of the petroleum flow and the maintenance schedule. The scenario’s difficulty includes multiple data suppliers, diverse data sources and platforms, heterogeneous data types and formats, data or unit transformation needs, and multifaceted data semantics. These requirements demand an innovative semantic solution for data integration and processing in the digital twin environment. The PeTwin project looks to define the best practices and software solutions for the development of digital twins for petroleum production plants. The project’s central objective is to deal with the semantic complexity of the information and offer a functional framework for machine learning and data analytics to support engineering daily operations in petroleum production surveillance. We have developed a network of BFO-based domain ontologies, an associated knowledge graph, and an application layer that implements the semantic treatment of information in a real scenario of petroleum production wells.

Keywords: Digital Twin, Ontology, Semantic Data Access and Integration, Petroleum Production

Authors: Mara Abel, João Cesar Netto, Fabrício Henrique Rodrigues, Nicolau Oyhenard dos Santos, Rafael Humann Petry, Haroldo Rojas de Souza Silva

Journal/Conference:  Joint Ontology Workshops (JOWO) – Formal Ontology in Information Systems (FOIS) 2024

Publication: https://ceur-ws.org/Vol-3882/projects-3.pdf