In 2008, Cairn Energy India, Ltd. (CEIL) recognized the importance of tackling unstructured data across the drilling and petroleum engineering group, where significant use of a proper workflow and a state-of-the-art data management application system have been promoted within the organization. The project rollout was aimed to achieve absolute integration of drilling and completion information into one centralized database system.

Over the last 10 years, the drilling and well services group has used the knowledge management system to achieve targeted maturity involving the conversion of a large volume of data into a reliable, yet simple, synchronized and structured data form. Collaboration between departments and vendor's application was needed for the CEIL process to remain effective following the company's aggressive growth.

This system was initially designed to generate schematics, reports, and queries. A specific workflow and process culture was required to ensure that all critical data, including operation-related information, are being captured meticulously during the lifecycle of a well.

Factual integration between the drilling and completion system was only possible after combining the thousands of reports into a centralized data management system. CEIL initiated the data management project to achieve reliable and accessible information across this domain, thus improving the group's productivity and operational efficiency.

This integration further facilitated the common access point for engineering personnel. In addition, it minimized the data entry workflow and effective use of decisive historical data. Data, once recorded, can be used by multiple applications intended for engineering, well-planning analysis, and operational monitoring. This integration has improved data quality and facilitated timely and cost-effective decision making.

This paper explains the methodology, strategy, and technology implemented in the data management project.

You can access this article if you purchase or spend a download.