How has the Oil & Gas (O&G) industry changed over the years in terms of process automation and enhanced control systems?
Looking back, it all started very simply and gradually, but the last ten years or so, have seen a tremendous boost to overall plant automation systems, use of data and interest in digital technologies
In different regions and industries, there is much talk about this new incoming era whilst others say that it is already here. The latest trends seen in the hydrocarbon sector are very promising; in terms of using interesting state-of-art developments related to Process Automation.
Since 2015 terms such as digitalisation, innovation, sustainability, Big Data, Industry 4.0 are attracting real interest from leading VIOGC/NOC and technology or solution providers alike – the reason is the understanding that in order to remain competitive it will be important to apply state of the art systems in their business processes and as a result securing their place in the market.
Many industry experts admit that downstream companies were not the first to buy into the idea of digital transformation and are now jumping on a bandwagon of existing technologies and solutions - however in comparison to other industries, the O&G sector has already come a long way and the pace of change is really significant.
We note that the leading companies with regards to growth margin and operational efficiency (Pacesetters) are doing things differently. In addition to using the latest process automation systems they have built state of the art complexes, created JVs with different partners sharing knowhow and experience. It should also be highlighted that they are not only using ‘ready-made’ solutions that are available on the market, but looking to develop custom-made solutions and further stimulating R&D in this area – proceeding in this manner has helped many interesting solutions see the light of day over the past few years.
Running through the topics that have been ‘hot’ in the areas where automation is concerned:
- Drones & Robots – Artificial Intelligence & Machine Learning
- Smart & Digital from a well to a method, we’re now talking Smart Refineries & Smart Corporate Systems
- Cloud / Big Data / E-mobility
- 3D-printing for any type of purpose starting from a building to equipment manufacturing with this technology makes the process cost-effective by up to 75% & up to 90% faster compared to traditional methods)
- Industry 4.0 / APC / IIOT
- Agile / Lean Principles
- Modeling / Visualization / Simulation (for safety, for Operator Training – OTS, etc.) – models become more precise & accurate which helps understand process flows better, construction issues, etc., which has a positive impact on many indexes used to measure efficiency.
The most modern designs in the abovementioned areas share several common features: they are generally quite expensive, sophisticated & complex, highly selective, flexible & adaptive. The latter characteristics being key for any solution to ‘win the favour’ of a client -- since the requirements & limits today become more stringent, clients are more demanding and competition between providers is fiercer than ever before.
What can digital solutions be used for?
Well, essentially speaking, practically everything – there is almost not a single work process in production today that cannot benefit from such solutions and applications and there is a whole network of developments that can take the process to the next level - these include:
- Measurement (online)
- Analysis, Evaluation & Prediction (multi-parameter)
- HSE management
- Benchmarking & Troubleshooting
- Risk / Change Management
- Quality Management
- Process Control
- Data: Collection, Transfer, Management, Reporting, etc.
- Optimization, incl. Energy Efficiency
- Setting & Monitoring KPIs, Planning
Today we are familiar with different types of automation in processes in relation to E&P, downstream process units, and more recently in relation to equipment, maintenance, inspections programmes and now it is possible to use advanced solutions in areas such as petrochemicals, pipelines, shipping, tanks & terminals, etc.
What was deemed impossible yesterday, is today an option, and tomorrow will be a must, a routine practice.
With these numerous opportunities, a whole array of subsequent challenges has emerged related to Data Management, i.e. how and where to store enormous amounts of data, how to ensure access in a timely manner, make it reliable & safe (cyber security is another trend that companies must focus on), choose the useful information and – most importantly – use it in the right way.
It is not the data itself that matters, but knowledge, understanding & correct interpretation
As some experienced industry professionals say, ‘you can cover a column / unit with sensors that cost huge amounts of money, but in case you don’t know what they measure and what to do with these readings, they’re absolutely useless and will never increase level of safety, operational readiness, product quality, or any other important parameter’.
In reality, if not maintained properly, these advanced techniques can show wrong numbers and this ‘fake data’ can lead to potential incidents or accidents – one can remember at least a couple of incidents that were the result of human factor coupled with automation failure. Another issue is that some operators learn to work in an automated mode, meaning that they only follow and monitor the data on their screens, but will forget to double-check or question the rationale of everyday routine.
This particular issue is the one that many workers have against further digitalisation – what if we are unable to keep it under control? Will it leave me unemployed? Top managers with one voice state that this evolution (or rather a revolution?) should not be looked upon as a threat: yes, some job positions will eventually be replaced with others, but haven’t we seen the same story in the past when previous industrial revolutions took place in every economy?
The result will be that fewer people may be needed for certain tasks, but these specialists will need to be experienced, highly qualified and motivated.
This can be achieved in the future by combining the best features of the millennial generation that are soon to step in the industry and whom feel comfortable in this quasi-digital reality, along with experts with 20-30+ years of industry experience that have worked their way through the process and know exactly how every machine works along with the core principles of facilities that younger specialists lack.
Corporations shall pay greater attention to their human capital (& every industry worker shall take care of his own as well) – with continuous training, stimulation of a mindset open to changes, modern organisational structure
Reluctance to change is to be expected, but these global trends & evolution cannot be stopped -- in this highly-volatile and almost unpredictable world any missed beat or step back can be costly with market share, result in significant losses and - in some cases – company closures if companies are not ready to change.
The problem is that now many are afraid to be outperformed by others and these trends have transformed from hype to a kind of hysteria. Quite often decision-makers do not understand (& to be honest, few non-specialists in this area do) the whole concept under IIOT or Industry 4.0, but they feel that it is better to try it rather than wait a little longer to see how it develops; today some state-run companies are starting to implement blockchain models, not always being 100% sure whether they need it or not.
Change & evolution may happen slower than we want, but the right approach here is to assess all options carefully & thoroughly, choose the ones that are right for this moment and develop those that have high potential for the future, and then build a different business model that incorporates essential interfaces within the company using available resources – both technical & intellectual.