Abstract
As a conventional energy industry, the petroleum industry is responsible for supplying over half of the world’s energy. Facilitating sustainable development for petroleum energy production remains crucial. Data methods have emerged as powerful tools to advance sustainability by enabling efficient resource management and risk mitigation. However, the reliable implementation of data-driven methods relies on high-quality data, necessitating the verification of data integrity on substantial data volumes. To this end, this poster paper presents our ongoing research, leveraging ontologies and knowledge graphs as shared knowledge representation, and provides preliminary results on data integrity verification. Based on the ontologies, we formulate domain knowledge integrity constraints and test three technologies of integrity verification: Python, PySpark, and SPARQL, for exploring future potential industrial adoption.