In production engineering, managing a mature field, where cost and job complexity increases as the reservoirs further deplete, analyzing a vast amount of data from different sources is required to understand the well and reservoir performance on a timely basis. Analyzing the full picture of the production system behavior and planning timely interventions is the key in managing these fields. As the E&P organizations go through the production lifecycle, it is increasingly difficult to keep this data in a structured format and a place where it can be easily accessed by the end users for their day-to-day workflows. More and more production data end up in Excel spreadsheets and other repositories creating what is known as data entropy. Legacy corporate data archives become a bottleneck in efficient production data management as they cannot scale efficiently.

On the data analytics side, production and reservoir engineers often rely on Excel spreadsheets or inefficient home-grown systems which restrict their ability to derive more insights from the data. Then there is the collaboration aspect. Emails and shared-drives become the de-facto form of exchanging analysis and data, but these resources are time consuming and error-prone due to misplacement, duplication and different vintage of several data files.

It is contradictory that the E&P industry despite its steady advances with digitalization and adoption of the latest technologies such as Artificial Intelligence and Machine Learning (to mention a few) continues to struggle with these fundamental data management issues. The implementation of a robust production data management system and basic analysis workflows are key to enabling effective digital tools and must be a top priority for any oil and gas organization consolidating their digital journey.

This paper talks about the success case of implementing a production data management system for the mature assets of a National Oil Corporation, encompassing 37 years of production data from various scattered archives. The implementation of the system was customized to suit the requirement of the end-users to enable maximum utilization and faster adoption of the technology. The conceptualization, implementation, customization and development of this digital transformation initiative along with lessons learnt and future development possibilities is demonstrated in this case study.

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