The Intelligent field is the oil industry's new trend that enables continuous monitoring and optimization of individual wells and overall reservoir performance. This is achieved by integrating fields' real time data in the reservoir management business processes. The results from this integration are anticipated to increase production rates, identify opportunities for higher hydrocarbon recoveries and reduce operating costs and future capital expenditures.Saudi Aramco has embarked on implementing the Intelligent Field (I-Field) initiative through new pilot projects in Qatif and Haradh increment III fields. The objectives of the pilot projects are to provide real-time diagnostic capabilities, highlight and address implementation challenges, and develop a comprehensive architecture for I-Field implementation in Saudi Aramco fields.This paper discusses the implementation approach of the intelligent field initiatives in Saudi Aramco. It will shed light on the challenges encountered and will present the process and methodology of developing the roadmap of the "surveillance layer," the first building block of Saudi Aramco's I-Field architecture.

Successful intelligent field (I-Field) implementation relies on a robust real time field to desktop data acquisition and delivery system. Such systems should have the bandwidth and the resilience to meet I-Field data acquisition and delivery requirements including data type, frequency, resolution, security, integrity, quality and reliability. The system must also have a design that safeguards against loss of data.Saudi Aramco's earliest I-Field implementation projects were at Qatif and Haradh. These projects were instrumental in developing Saudi Aramco I-Field data acquisition and delivery requirements for reservoir and production engineers. The projects revealed limitations and challenges in the data acquisition and delivery infrastructure. Composed of several stages of interconnected systems supported by multiple organizations, these systems included surface and subsurface instrumentations, servers (data acquisition, control, database and applications) and various network protocols. System complexities and constraints dictated the need for developing an I-Field data acquisition and delivery infrastructure architecture that would meet Saudi Aramco's I-Field application requirements and overcome existing challenges and limitations. This paper presents Saudi Aramco's experience and methodology of assessing field-to-desktop data acquisition and delivery infrastructure of the pilot project fields. It also highlights examples of some of the inherited challenges and implementation of the newly adopted data acquisition and delivery architecture. The adopted architecture, methodology, and subsequent experience gained in overcoming these challenges now serve as a guide to further intelligent field implementation in other Saudi Aramco fields.

Following the success of the first installed intelligent completion system in Saudi Arabia in 2004, over 260 Intelligent Completion systems have been installed in a majority of Maximum Reservoir Contact (MRC) Multilateral (ML) wells. These intelligent completion systems have been successfully installed in openhole, expandable liners, expandable sand screen, Extended Reach Drilling (ERD) wells and also integrated with Electric Submersible Pumps (ESP). This technology has led enhanced oil recovery while reducing water production to surface. Water handling cost at surface is reduced by producing less water to surface and also shutting off downhole water production completely. This paper covers some of the case histories of over ten (10) years of design, planning, installation, testing and optimization of intelligent completion systems in Multilateral (ML) Maximum Reservoir Contact (MRC) wells within Saudi Arabia. Production optimization practices and enhancement of production life in carbonate multilateral wells in the world's largest oilfield are also documented. Case histories highlighting how water production was remotely choked back, shut-off and production optimized from identified lateral without any intervention in the well are reviewed. Advantages of intelligent completion technology for multilateral wells and the review of the downhole choke customization process that included design flow area after modelling well data for different flow rates and differential pressures are detailed. This is in addition to the integration of the surface control system to the production supervisory control and data acquisition (SCADA) system which provided real-time downhole pressure and temperature data and remote control of downhole flow control valves during the life cycle of the well. This paper also discusses a closed-loop approach which led to efficient real time production optimization. Performance review of how intelligent completion systems provide selective lateral control, delay water breakthrough, control water production, shut off wet lateral, reduce opex, optimize production, enhance recovery and reduce safety risks thereby minimizing future interventions are documented.