Analyzing petroleum data from multi-source is a laborious and complex process, which often results in semantic and syntax conflicts. In this study, we take advantage of the knowledge representation and automatic reasoning of the ontology and propose an ontology-based multi-source petroleum information fusion framework. On the basis of this framework, ontology-based element similarity algorithm and fusion rules are proposed. Experimental results demonstrate that such framework improves the analysis efficiency of petroleum multi-source data.