The Energy Industry Remains Subject to Disruption
It comes as little surprise that there is still an opportunity to improve when it comes to challenging the status quo of the Energy industry. In addition to top-down pressure on commodity pricing as seen through the last cycle, along with margin compression and related ecosystem challenges, whether you are an operator or service company, we also have to govern macro elements such as moving toward “net zero emissions” and lowered overall consumption. Operators and partners find themselves challenged.
Some of the challenges observed in the industry are:
- Trapped and “Contextless” information: there is no shortage of data, but data is only meaningful when it has context. Trapped information without context prevails, and companies find themselves needing to make sense of data through context.
- Limited cross-functional collaboration: the need for niche expertise in the energy industry has over time led to the formation of information siloes, leading to limited cross-functional collaboration
- Reactive model: The prevailing operating model is rigid and often reactive, and this covers everything from operations, service models to how individual assets on facilities are maintained.
- Siloed improvement approaches: Companies try to improve, but due to the siloed status quo, the improvement measures are often confined to those siloes.
- High expectations: Coupled with the historical ROI related challenges, the energy industry remains an arena of both opportunity and frustration.
There are material opportunities, still. Improvement potential ranging from 30% on cost and time to production uplift and cost-takeout in operations prevails but provided the appropriate approach.
The relevance of digital is at an all-time high in 2020, where it has been called upon both for addressing the remote worker scenario imposed by COVID-19, and as a measure to understand how to handle demand destruction and rapid margin compression.
Answering the sustainability demand
In addition, the green narrative is becoming more pronounced.
Companies seek to
- lower the power consumption on their facilities;
- to enable reduced manning and thus indirectly affect emissions related to supply chain and logistics;
- to increase the flexibility of their operations ecosystems, allowing the operating cost curve to move relative to commodity price and demand;
- and to support efficient carbon capture to support broad net-zero emissions related commitments.
The traditional way of thinking
How do we collectively address this as an industry? We believe it begins with challenging the traditional way of thinking.
It is our observation that, at the fundamental level, orchestration of how we go about our business in oil and gas is very much based on existing conventions:
- In terms of the people aspect, organizations have similar shapes as they have always had, with little radical change. Organizational roles, job descriptions and titles remain similar.
- In terms of processes, they are still largely sequential and role-based by design, in a world where advanced systems to an increasing degree augment our human capabilities.
- This also lends itself to application in how we engage with suppliers, apply technology and utilize the service provider ecosystem.
We are in essence describing a push of methodologies and approaches based on convention, rather than actual needs. As a result, workloads remain high and efficiency gains are inherently limited.
Kognitwin Energy – Unify data, knowledge and people. Enable the best decision every time. Learn more about our solution
Inherently, we believe that needs should dictate the surrounding ecosystem of services, people and methodologies. In terms of solutions, we consider the digital twin as the driver to determine not only the current state of a facility but also to determine its needs.
Digital twins’ possibilities include, for example:
- Predict maintenance needs based on condition-based maintenance approaches;
- Performance monitoring to determine bottlenecks on throughput, and identify mitigation actions;
- Advance what-if simulation to understand operating conditions that may or may not require the presence or allocation of expertise to resolve scenarios.
All of this contributes to a proactive model, that reduces the workload and thus reduces costs, as well as the need for supply chain and logistics activities, thereby reducing the carbon footprint.
In essence, the digital twin becomes a shared vehicle to enable operational flexibility and efficiency.
Beyond being a virtual replica of your industrial facility, Kognitwin Energy, our dynamic digital twin delivers a rich framework for advanced digitalization and analytics, including a range of solutions that can be customized to attend your needs. Learn more
Most operators find themselves with a host of business systems across the IT and OT categories that deliver valuable insights; however, there is little to no holistic cross-integration. As a first step, we find that connecting information as seen here, including industrial 3D models, engineering documentation, sensor data, ERP information and other transactional data, is vital. In addition, more advanced twins take it a step further in providing contextualization, simulation and prediction possibilities.
As data is integrated and contextualized, operators can take advantage of new possibilities, like:
- Simulation of facility behavior – through first principle physics, steady-state and dynamic;
- Integration of transactional data and business information;
- Intuitive visualization, 2D, 3D, and rich P&ID views that engineers can navigate in;
- Access to real-time performance data from sensors;
- And, data-driven models, combining the above to increase calculation speed and deliver rapid outcomes.
Delivering value to stakeholders
The combination of all possibilities mentioned above create value to the pertinent stakeholders, enabling:
- Improved understanding of data and operations;
- Access to optimization opportunities;
- Contribution to POB or manning reduction;
- Scaling cross assets, elevating management to the portfolio-level;
- Confidence in predictions, leading to the desired increased flexibility.
rom our experience, unlocking value and creating organizational momentum often begins with enabling cross-functional teams in accessing information and facilitating collaboration.
The sentiment in the market is that we by doing so can unlock up to 70% reduction in time spent searching for information and staging information for decision making. This sentiment comes from roles across organizations, ranging from engineering to management, with true belief in the potential. Potentially even more importantly, creating initial momentum drives organizations to become true owners of their digital initiatives, making companies inherently more digital by design. This is key.
The implementation of scaling digital twins can also provide relevant organizational impact, such as:
- Increasing share of remote personnel, as more can be done through digital access
- Leaner facility teams, as they are augmented by remote support and technology
- Leaner and more advanced remote teams as they are augmented by technology
The digital twin approach can be transformational
This is a journey, but if approached correctly, operators can achieve substantial progress and drive transformation. Companies find themselves having different ambition levels. While some aim for autonomy, some pragmatically focus on remote operations and cost-efficiency. We can observe consistency across the journey required, and we see two parallel tracks:
- One that starts with asset data connectivity across systems, integration of real-time data driving the company up the ladder of advanced analytics, from descriptive through predictive, prescriptive and autonomous
- And one that starts with the fundamentals: How we work together. Here we leverage the inertia of collaboration to drive scaled remote support and leaner manning
This two-prong approach is of course dependent. You must have an operating model that supports the vision and the technology must support the operating model.
With this in mind, we would like to ask the energy industry community: are you ready to disrupt the old way of thinking and start creating value through more efficient solutions? Want to pick up the old tools, or look to the future when you consider how you operate your assets?
Kongsberg Digital has leveraged its position within dynamic production simulation to build Kognitwin® Energy, a dynamic digital twin that enable operators to achieve their overarching goals, from decreasing carbon footprint to optimising production and condition monitoring.
Beyond creating a virtual replica of industrial facilities, Kognitwin Energy delivers a rich framework for advanced analytics, including a range of applications, like Kognitwin Unify – the exclusive data contextualization engine – and the Hybrid ML technology, that can be customised to meet the operator’s needs.
Haavard Oestensen is Head of Growth in the Digital Energy team at Kongsberg Digital. Based in Houston (USA), he has 15 years of experience in the Oil & Gas industry and extensive consulting experience covering the areas of production, commercial management and global hydrocarbon management system deployments.