Intelligent digital oilfield (iDOF) operations have gained momentum in the past few years, transformed from being merely a vision to real-world projects with quantifiable value. Challenges such as increased energy demand and diminishing new discoveries, coupled with a lack of specialist-domain expertise and trained personnel to efficiently operate assets, have forced operators to rethink the traditional way of asset management to increase productivity and operational efficiency.

The amount of information that asset managers now have to make decisions has increased dramatically in the last few years. More data about a problem can lead to improved decisions, but it also increases the complexity of the decision-making process. Asset teams need tools and technologies to help them quickly and efficiently analyze and understand all this data so they make better, faster decisions.

To help asset teams meet these challenges, a new generation of petroleum workflow automation integrates real-time data with asset models, helping team members to collaborate so they can better analyze data and more fully understand asset problems. We're calling this new generation of automated, intelligent workflows "smart flows."

This approach is cutting-edge, but also more complex. The complexity is addressed with the use of artificial intelligence technology, such as proxy models and neural networks, coupled with a visualization engine to provide an effective visual data mining tool. The objective of this new generation of petroleum workflow automation is to provide integrated solutions to asset opportunities and guide the operations with instructions based on smart analysis and integrated visualization.

This paper provides an overview of a workflow automation environment that is being implemented for a major operator.

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