Multi-Dimensional Control Rules and Assessment Methods for Surface Engineering Data Quality in Oil and Gas Field

The current digital delivery of surface engineering in oil and gas fields faces challenges such as difficulty in integrating multiple heterogeneous data sources, low efficiency in quality reviews, and a lack of unified evaluation standards, which seriously restrict the implementation of intelligent operation and maintenance. Based on this, this study constructs multi-dimensional control rules for data quality covering the entire lifecycle. Based on the characteristics of structured, semi-structured, and unstructured data, five-dimensional review criteria and quantification methods for normative, integrity, consistency, accuracy, and timeliness were developed. At the same time, by integrating the analytic hierarchy process (AHP) and the entropy weight method (EWM), a combined subjective and objective weight evaluation model was established to achieve scientific quantitative calculation of quality indicators. Verification with a project by Southwest Oil and Gas Field shows that the system effectively achieves quantifiable diagnosis and traceability of engineering data quality, revealing the differentiation characteristics of different data types in the quality dimension. The research results provide core methodological support for the establishment of an integrated data governance paradigm of “collection—review—operation and maintenance” in oil and gas fields, facilitating the implementation of intelligent operation and maintenance.