The promise of an "Intelligent Energy" initiative is premised both on the availability of real-time data, and on improving real-time communications between the field and the office. However, acquiring, organizing, and making sense of real-time data for field production management poses a number of challenges for any individual surveillance engineer. For an asset team working collaboratively, the challenge of efficient and effective data monitoring and the performance of optimization workflows can be even more demanding. Many production workflows require an engineer to coordinate data flows between numerous, diverse, and frequently siloed systems and applications. Studies have shown that approximately 50-70% of an engineer’s time is spent finding, gathering, and managing data for use in these different applications1. This non-productive time can be drastically reduced by defining standard production workflows, by implementing an automated system to execute these prescribed workflows, and by ensuring that the data sources are well defined and accessible.

A well-designed, thoughtfully implemented, and automated workflow ensures that all the relevant data is available "at the fingertips" of each member of the asset team, reduces the likehood of input errors, and removes the burden of data management from engineering personnel. These automated workflows allow knowledge workers to focus on value-added engineering tasks. In addition, the design and implementation of automated and configurable workflows creates a transparency and consistency in work processes that can be customized to the unique needs of each asset.

This paper presents an asset-based collaborative project that includes:

  • Initial needs assessment

  • Design of well data required for advanced surveillance

  • Workflow design

  • Implementation methodology

  • Value realization review

The core enabling technology that allows these automated workflows is a vendor-neutral integration platform that dynamically links diverse data sources and software applications currently in use for production monitoring and optimization.

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