Digital is not a new concept for Oil & Gas, however, it is only in the last few years that organisations have begun to understand the full potential of digitalisation

“Digitalisation the use of data & technology to gain additional insight, support better decision making, reduce risk and improve efficiency across an organisation. Supported by an agile culture and a focus on innovation, it represents a fundamentally different way of working.”

A substantive increase in the use of Digital Technology is highlighted through the OGA Stewardship Survey, demonstrating that organisations have a growing realisation toward digitalisation.

The TLB in a collaboration between five organisations, prompted the UKCS Data & Digital Maturity Survey - Understanding attitudes, progress and challenges in Digital Transformation for the UK Oil & Gas industry.

Through this enhanced understanding, the Offshore Digital Landscape is now better placed to set cohesive priorities addressing opportunities associated with the Four Areas of Digital.

The TLB along with partner organisations plays a leadership role, in championing Digital Transformation, a cultural change, as much as the integration of technology into business.


Four areas of digital


Data is the foundation of digital. Governed, accessible and connected datasets provide the basis for digital to add value


Without digital capability and culture through the organisation, the impact that digital can make is limited


An innovation process ensures that a pipeline of “ideas” is driving transformation, with the support mechanism to invest, pilot and scale


Technology transforms data into tangible value, but must be focussed on solving the right problems, and properly deployed

Four Areas Digital


The first hour of a “Maintenance & Inspection Lead’s Day” in 2021 captures the vision that the Industry must have for both digital transition and accompanying data. We should be all capable to imagine a user’s experience within an organisation that gets full value from its data.

An organisation that:

Governed Data

Has well governed high-quality data

Data Process

Uses that data, modern digital architecture and models to process natural language query requests, customises reports automatically for users and allow them to combine, compare and contrast disparate data sets quickly and easily


Takes advantage of data being captured through mobile/autonomous devices which automatically upload to the cloud for automated image recognition

Digital Twin

Has a digital twin, with the ability to return the relevant information for a specific component in a machine or system

Future use case Example

The first hour of the day starts from here...

It’s Wednesday the 1st September 2021. The Maintenance and Inspection lead on Asset X arrives at work at 07:30 as usual. She turns on her laptop, scans her emails and Teams chats on her primary screen and glances at her second screen which displays the automatically selected KPIs and reports based on a balance of her role, colleagues and contact ‘likes’ and her own report viewing history. She doesn’t dwell on this since she had already seen the KPIs on her iPhone over breakfast. She had been sent a specific alert that there was a new potential single point of failure which impacted more than 75% of production in the gas export system, the failure prediction model detected there was a greater than 50% likelihood of a stoppage within the next 48 hours due to a seal fault. She activates voice query and asks her PC to display the failure history of the at-risk export pump and then to highlight seal failure – she then asks this to be correlated with historic shortfalls. The system suggests there is a greater than 0.8R2 correlation between seal failure and lost production.

She asks the PC to return the 3D exploded view of the compressor with the specific seal highlighted and also the maintenance record of the package with only those activities that mention seals highlighted. The system returns a series of images automatically tagged against this seal that were taken by the tech during the last maintenance activity. They clearly showed marking on the face of the seal which had been detected by the image recognition AI at the time and a PM had been recorded with medium priority as a result.

She refers to the offshore work plan and sees that maintenance is planned on this, the back-up compressor, in two months’ time. She asks Power BI to return the likelihood of failure within the next two months and the expected time to repair given the current stock levels and supply vessel availability. She triggers an expedited repair request and the AI automatically reschedules the offshore work program, stock replenishment, logistics manifest and Field Ops Manager approval request, with a report automatically generated indicating the probability of failure, the estimated protected production as a result of acting now. It’s 08:30 now so she has her first coffee of the day…

Integrating sector vision INTEGRATING THE SECTOR VISION

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Digital Systems Circle

Digital Systems

“Digital Systems” seeks to identify and address the elements necessary within Core Business

Analytics Circle

Shared Analytics

“Shared Analytics” facilitates a cohesive digital culture, to define an expectation, for Machine Learning& Machine Vision

Data Infrastructure_circle

Data Infrastructure

“Data Infrastructure” sets a Modern Digitalised Energy System expectation, that empowers decision makers with real-time, actionable information, by combining the power of global data networks.