Intelligent Field upstream operations in the Oil & Gas industry encompass infrastructure that provides real-time data for monitoring and enabling informed and efficient decision-making leading to improved field operations. Therefore, it is vital to ensure that the infrastructure is reliable and that the data obtained is managed properly to make it available to end users. This paper proposes an integral approach to measure Intelligent Field Infrastructure (IFI) and data communications reliability and explains its applications and reachability on field performance.

This innovative method supports engineers to tackle issues in timely manner. In addition, a robust IFI optimizes production strategy by exploiting available data to improve well rate compliance, monitor well integrity and reduce field surveillance activities. Furthermore, a reliability index requires a consistent asset inventory supported by an effective maintenance strategy that is perceptible to all involved organizations.

Six sigma methodology tools are to be implemented to address reliability. To conduct a root-cause analysis leads to identify the flaws in data communications and infrastructure. Then, data is to be compiled within a process mapping structure that can be used to generate performance plots ranked upon Failure Mode and Effect Analysis (FMEA). Building a reliability index powered by visualization tools lead to expose hidden areas of opportunities to improved field operations. This integrative approach provides different organizations with one platform to overcome reliability issues and reduce equipment downtime; hence, maintaining asset value and capitalizing its capability.

The approach presented in this study is relevant to Oil & Gas industry professionals involved in IFI for understanding the impact of asset integrity on remote operations capability. It also sheds light on understanding the role of information-driven analytics on optimizing field performance.

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