In recent times, i-field, e-field, digital oilfield of the future etc. have dominated discussions focusing on increasing the recovery from both shallow and deep water assets using electronic technologies. The common theme is the ability to integrate tested and emerging information and communication technologies (ICT) with asset management workflows for improved recovery, collaborative decision making and prompt intervention thereby increasing the asset's bottom-line.
A methodology adopted for implementation of i-field in one of Chevron's mega projects is presented in this paper. The Agbami field, located in deepwater offshore Nigeria is a subsea development incorporating crestal gas and peripheral water injection. It is located in ~ 5000 ft of water and consists of a 38 well development program to be implemented in 3 phases. The first phase involves 22 wells – 12 producers, 6 water and 4 gas injectors. The well completion incorporates intelligent well completion (IWC) – downhole flowmeters, pressure & temperature gauges and interval control valves (ICVs). These downhole accessories will be controlled using electric and hydraulic controls/instrumentation with Subsurface, Subsea and Topsides data acquired and transmitted to a central data historian on the FPSO in relevant time.
The implementation of a robust architecture for Data and Information Management System involving acquisition, processing, storage and replication (from offshore to onshore) is conceived to be the bedrock of the other main focus areas namely: Production Optimization, Reservoir Management & Surveillance, Facilities & Equipment Reliability, and Asset Decision Environment. The impacts of these four focus areas and the methodology engaged in identification, prioritization and generation of the relevant workflows have been discussed.
The expected gains from implementing i-field include improved well and facilities uptime resulting in increased efficiency and reliability, increased production, improved ultimate recovery, and better overall performance from automation of several routine activities. This will ultimately increase the expected value (EV) of the asset through better and prompt decision making using appropriate collaborative tools. In addition, best practices and lessons learned for development and deployment of i-field initiatives in a green field environment are presented with possible applications to mature brown fields.