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.

As part of the implementation of its strategic goals, Saudi Aramco effectively leverages intelligent field (I-Field) processes and technologies. The I-Field initiative (development architecture) includes four levels: Surveillance, Integration, Optimization and Innovation, with a vision for full implementation and coverage of all producing fields within the medium term. The accomplishment of this ambitious goal requires a well coordinated approach company-wide to truly benefit and extract value from the I-Field approach and practices.The value proposition of the I-Field program includes increasing production potential, recovery factor and efficiency with the most safe and environmentally sound practices. One facet of achieving this corporate objective is through enhanced reservoir management strategies and integrated multidisciplinary collaborations. One of the contributing initial elements is the creation of Intelligent Field Centers (IFCs) that will enable and facilitate collaborative decision making around reservoir management processes and tasks.The first established IFCs had emphasis on reservoir management tasks with a longer vision and a wider objective of optimizing the company's assets and operations in achieving its expanding goals. This first group of IFCs is foreseen as nuclei for a growing contemporary practice in managing the company's assets.In order to come up with the optimum design of these centers and to ensure that they meet the objectives set out by the company, a rigorous, multistage methodology was utilized that started by a comprehensive assessment study. The results of this assessment revealed several high priority workflows being performed by the reservoir management groups, which, once implemented in the IFCs, should deliver improvements in efficiency and, therefore, impacting production and ultimately increasing recoverable reserves.The assessment and design results showed critical cross-functional and I-Field requirements, such as collaboration, change management, integration, interoperability and openness, automation and knowledge capture. This paper will detail the methodology followed in assessing the requirements and designing the use of the IFCs.

The drive to implement the latest and optimal Intelligent Field Infrastructure (IFI) is a continuous aim for Oil & Gas operators. This requires the right balance between technology, business drivers, and evolving implementation requirements. A successful Intelligent Field implementation relies on a robust real time field to desktop data acquisition and delivery system designed with clearly defined data acquisition requirements. The data acquisition requirements definition should include data type, acquisition frequency, resolution, integrity, quality and reliability. The data acquisition and delivery system requires built in dynamics from design, technology selection, and deployment to operational maintainability. The challenge in achieving such an objective exuberates by the different variables that must be considered when addressing IFI integrated solution. The variables to be considered in the solution shall include network coverage, hardware selection, software solutions, and feature functionalities. The solution shall be able to integrate different technologies: surface and subsurface gauges and subsystems; forming data collection, for real-time reservoir management and production operation, such as temperature, pressure, flow characteristic, etc. This paper presents Saudi Aramco's experience and methodology of developing IFI, field-to-desktop data acquisition and delivery infrastructure, for new fields. It highlights critical components for the IFI building blocks and the most optimal approach in addressing them. Reflection on previous case studies is used to illustrate concepts and to outline best practices and lesson learned.

Digital Field capability is at the leading edge of the Oil & Gas industry. This capability is a result of continual advancements and integration of well technologies, communications, process control, and E&P computing technologies. Digital Field capabilities enable the integration and use of surface and subsurface real time data, to optimize upstream assets and profitability. This capability has been given different names, such as Intelligent Fields, Smart fields, Digital Oil Field of the Future, integrated field and Integrated Operations. In Saudi Aramco, this capability is being leveraged through four major projects: "Real-time Drilling Operations" for optimal drilling; "Geosteering" for optimal well placement within the reservoir; "Intelligent Fields" for optimizing reservoir management, production and production operations; and "Event Solutions" for optimal field development. Throughout this paper, the term "Digital Field" will be used as the nomenclature for this capability. This paper provides an introduction and background on Digital Field capabilities and presents Saudi Aramco's experience in leveraging them in key upstream business processes. The paper also highlights areas of applications, challenges, lessons learned, values attained and the opportunities that this brings to the industry as experienced through Saudi Aramco implementations.