Big Data IAOM Project Management and Workflow Automation in a Giant Gas Field Digitization Drive

Integrated asset modeling, application of big data, and automation are among the top emerging trends in the oil and gas industry. The value associated with such implementation projects is very closely linked with the efficient use of the project management approach and a robust strategy to handle the technological challenges. This paper puts light on such initiatives implemented in a giant gas field. In this giant gas condensate field, a vast amount of data is generated and monitored on a daily basis. The frequent need to deliver the dynamic production target was driving this project implementation so that a value-driven system can be established while achieving the business KPIs. A phased approach was used to target multiple requirements into business deliverables where the early offline phases provided a robust base for full online integration. This project followed the agile approach focusing on getting insights from multiple stakeholders and domain experts and developing a lesson-learnt repository in all the project phases. The online integration solution is a critical differentiator in the workforce and process efficiency improvement. The multiple technical solution workflows helped in reducing manual efforts and streamlining the methodology in a standardized fashion. In addition, the standard project management practices, such as initializing the phases in a planned manner, followed by an interactive execution, monitoring, and controlling stages, ensured delivering project outcomes in an efficient way. This implementation also established a robust collaborative team effort to identify various different roles and responsibilities for stakeholders. This helped in the end phase when the project sustainability was essential. A strong team base maintained and updated the integrated system while delivering daily well and facility surveillance objectives and KPIs from users ranging from planning, engineering, operation, and management team. A special focus on IT team involvement throughout the project phase led to a successful data integration and diagnostic, as the core of the solution was a data-driven analytical framework integrated with multiple corporate and real-time data sources. In addition, this solution was equipped with various one-of-its-kind solution features such as business intelligence, advanced surveillance, dynamic-reservoir integration, manage-by-exception workflows, intelligence alerts, along with a strong digital framework and data architecture. The unique hybrid and agile project management approach focusing on delivering emerging trends and technologies to end-users in the most efficient way paved the way for achieving asset digitalization and standardization goals.