Shifting from Reactive to Predictive in Energy: Driving Valuable Outcomes in a New Digital Landscape Part 2

Technology and Digital

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May 16, 2018

For the Oil and Gas industry to succeed in making the digital shift from reactive to predictive maintenance, their industrial processes and technology applications need to evolve. In this three-part blog series, we will discuss the following:

  • Incorporating Data Analysis into Operations Processes, Part 1
  • Human and IT impacts, Part 2
  • Managing Digitalization Programs, Part 3

The digital transformation will bring necessary changes to the Oil and Gas industry: new ways of working and new functions will appear. The routine inspections of a field technician won’t be the same as before, as new sensors will replace walk-around routines with the analysis directly performed on the equipment via sensors. Maintenance crews will see a significant shift in work orders to predictive and preventative efforts and away from corrective maintenance. Field operators will have more information at their fingertips through mobile toolsets, wearables and will be provided additional autonomy in their daily efforts. New roles for data scientists will be created to build, maintain, and optimize operations analysis models. According to a McKinsey study, oil and gas companies could employ more data scientists with Ph.D.’s than geologists in the next 10 years.

A changing industry workforce will also include automation and robotics, including remotely operated aerial drones and AUVs. Soon, automated underwater vehicles (AUVs) will be enabled to perform routine inspections on various subsea equipment from a self-sufficient base powered by solar energy, relinquishing the need for vessels to move ROVs to and from the inspection site. Other automated systems such as pipeline drone inspections can be controlled almost entirely by a small team of skilled employees, hundreds of miles away. Presently, offshore oil rigs typically employ 100–200 workers, a figure that may decrease due to automation initiatives, although people remain indispensable for critical safety roles that require complex decision-making.

Operational processes will become increasingly attractive for future recruitment as tasks achieved by humans will become less tactical and more focused on added value. However, change management and organizational concerns should always be kept in mind as human involvement is crucial for a successful transformation.

Beyond the human impact, this transformation has a strong effect on the IT organization. The addition of an “Internet of Things” and “Big Data” layer into the IT architecture will imply more communication required between operations and IT management. The entire communication chain needs to be considered: from the implementation of sensors to final data analysis tools. Data repositories, application integration, connectivity and interactions with other systems need to be reconsidered. For example, sensors implementation will be integrated with existing API’s and with mobility tools: the analysis of sensors for equipment or live-streamed inspection activities should be available for operators, in real-time, to their own PDA.

The main digital impacts on IT and data management:

  • A new cross-application structure (with relevant applications, for example: CMMS, ERP, PLM…) integrated with master data management is necessary
  • Regarding data intelligence systems, a relevant design should be created in line with enterprise architecture
  • Data will grow significantly, and efficient real-time analysis will be critical. The technical infrastructure needs to be adapted to be responsive and consistent with the new technologies.

As an organization adopts an enhanced technology infrastructure to support and enable cross applications dynamics, optimized use of data intelligence systems and operational real-time analysis – the engagement of both new and existing users and organizations will require a strategy that enhances the user experience and provides ease of access to analytics and insights. Managing a transformation of this size will be discussed in the Part 3 of this series.

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