Practice and Exploration of Data Governance for Drilling Completion

Drilling and completion is the core of energy production and plays an irreplaceable role in improving oil and gas exploration and development and increasing crude oil recovery. Similarly, drilling data is of great significance in drilling optimization, perforation, hydraulic fracturing, and oil and gas production. However, in actual production, data quality and application often fall short, making it difficult to further enhance and optimize oilfield engineering technology. Therefore, effective data governance to address data quality and application problems has become an urgent and critical issue. Additionally, the scale, quality, complexity, and security of data are essential issues that must be considered in data governance processes. To address these issues, this paper proposes an engineering technology data governance approach covering data quality control, data standardization, data modeling, and data mining. These methods and tools have been applied in production practices, and have achieved good results. Additionally, this paper explores the application of intelligent data governance, which aims to quickly and efficiently manage data. This paper compares the advantages and disadvantages of existing data governance algorithms in data governance, providing reference application scenarios for more efficient, reliable, and accurate drilling data governance. In summary, the proposed data governance approach and techniques provide the foundation for further improvements in oilfield engineering technology and management, as well as enhancing data utilization and decision-making for the petroleum service industry. Effective methods and tools must be used to address the challenges of data governance, including data scale, quality, complexity, and security. The proposed data governance approach for engineering technology, along with its applications and exploration in intelligent data governance, provides significant support for the exploration and implementation of data governance in the petroleum industry.