Chris Ayres explained how Opex Group is using operational data to ‘unlock’ carbon emissions savings. This is achieved using its flagship ‘Emissions.ai’, digital solution that helps carbon intensive companies decarbonize ops and reduce emissions, energy and fuel. It contextualises operational emissions and leverages engineering first principles, analytics and AI to identify hidden operational inefficiencies, improvements and opportunities to lower emissions and costs.
Alan Bibb (Neptune Energy) observed that the ‘Digital Twin’ is ‘too wide a topic to cover in general terms’ and that the term means different things to different users. Neptune’s digital twin journey has been ‘incremental, tactical and pragmatic’ with a focus on value generation. Ideally a twin should support as-built verification, virtual surveys, clash detection and other management of change tasks. Expected asset behaviour should be compared to actual behaviour in real-time. Contextual access to asset data generates insights and liberates data silos. While the digital twin is achievable (and can be funded) in the design and construction phases, the shift to operations is proving more challenging. Operations require richer data, contextualisation and transformation of ‘business as usual’ tasks. Finding funds for such activities can be hard. There are multiple barriers to overcome from limited search of tag-based data to cultural issues. Users want simple tools and workflows adapted to a range of activities including engineering and offshore operations. Data quality and governance is also problematic. However, the opportunity for value generation is good, particularly if there is buy-in from EPC/contractors. Ideally the twin should be an ‘agnostic and open solution’.
David Lecore (North Sea Transition Authority) recalled with satisfaction his earlier study (co-authored with Steve Hawtin) on the Value of Data (reviewed in Oil IT Journal in 2011), now seen from the standpoint of the regulator (Lecore was previously with Common Data Access). In the ‘Value’ study folks were asked about how long seismic data was likely to hold value. Most opined that value would disappear after less than 10 years. In fact, of the approx. 4,000 seismic surveys on the UKCS, some 3,700 are pre Y2K. Far from having little or no value such surveys are seeing re-use. One source of this unexpected value is the mooted use of depleted Southern North Sea fields for carbon dioxide sequestration or gas storage. If the value of data is now accepted, what’s all the fuss today, why are we still talking about data management? Industry had unfortunately a record of unscalable pilot projects, poor resourcing (people and funding) and a failure to appreciate how hard data projects are. More generally, there is too much focus on digital and not enough on data quality and governance.
Steve Hawtin, (White Turret) is the author of the book ‘The Management of Oil Industry Exploration and Production Data’ which we reviewed back in 2013. Hawtin reflected on what has changed since 2013 to conclude that the key data issues are not technical, there are no silver bullets and that management of change is critical. This involves getting people to adopt new ways of working, achieving agreement and focus and overall, clarifying what is required. The first step to improving the data situation is to define how things ought to work, by documenting context, uses and processes. On the topic of data standards, Hawtin illustrated his approach with a fictional ‘Umbrella Oil’ company with and a slide showing a shelf full of data standards and a compendium of such available as a huge tome. After the event Hawtin explained to Oil IT Journal, ‘I have actually implemented exactly this approach in a number of real companies (some quite big ones), each one has applied the basic concept in a completely different way. In my view there is no chance of developing an ‘industry standard’ set of data standards. Rather, what I have developed is a standard way to explain the benefits of actually writing this stuff down, and a set of steps to establish an internal team with the tools and contacts to start doing that. The standards that those teams have then produced have varied wildly in scope, content and application from one company to the next, each focused on the aspects that their organisation sees as the most important. It is hard enough to establish a consensus within a single company.’
Steve Johnson’s company, contracting engineer Petrofac, has extensive experience of data collection and use and is able to realize some of the ‘unharnessed potential’ of data. Data gathered over a multitude of projects has enabled a probability analysis of completion times and likely delays. Analysis of previously siloed data revealed that the assumptions on the time to complete certain activities were ‘questionable’. In many cases there was a greater than 50% chance that the task would take longer than anticipated. Many assets possess a potential wealth of machinery data but this is often ‘stranded’ and only accessible locally. Stranded data represents a lost opportunity, restricting the ability to manage the performance and health of the equipment. ‘Embracing digital is the enabler that will unlock the value. A virtuous cycle between digital and data will happen when digital adoption promotes increased recognition of the importance of data. Johnson also advocated the use of a ‘cognitive search engine’ to source key data and information in large volumes of documentation. Other enablers are IIOT/LoRaWan type communications that connect the workforce, providing insights that improve construction management and enhance workforce safety and productivity. Johnson is also keen on using data science to improve asset management with proactive intervention.
More from OEUK.
© Oil IT Journal - all rights reserved.