For decades, upstream personnel have struggled to efficiently gather offshore data and effectively analyze it to make better business decisions. One internal audit conducted by an oil and gas company found its upstream employees spent up to 80 percent of their time just looking for, then converting the data because the data historically has not been housed in one place within one platform. Traditionally, employees must collect large volumes of information from multiple data sources, including spreadsheets, data streams or tacit knowledge. Alone, the Internet of Things (IoT) sensors connected to equipment in the field can send 1,000 readings a minute to engineers, resulting in an insurmountable data for engineers to assess critically. All of this effort results in underutilized time and loss of money.

The paper's topic addresses the digital twin technology solution which solves energy company's Big Data problems and recoups the wasted time and associated costs of field workers looking for data. Specifically, FutureOn's FieldTwin technology offers a cloud-based, comprehensive and secure platform with the ability to break up the barriers of the data silos built by legacy systems, creating accessible data across the company. Employees spend less time searching for data, and more time identifying trends and innovative ways to exploit the data, i.e., smarter drilling, greater field automation or improved safety.

FieldTwin technology also provides a real-time, data-driven visual representation of the field that creates actionable data, whether it is an operator using the visualization of its subsea assets for field expansions or a renewable company utilizing the digitalization of its offshore wind projects for more effective planning. Studies show humans respond to and process visual data better than any other type of data. The human brain processing images 60,000 times faster than text, and 90 percent of information transmitted to the brain is visual. FieldTwin exploits this reality to enhance data processing and organizational effectiveness spanning project management to risk management in the field.

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