Why the O&G Industry Needs a Digital Performance Model

Future Digital events create a vibrant space for collaboration, sharing and insights across industry, one where companies can collectively improve their understanding of how digital leads to a more effective, streamlined and value-generating industry. Find Kongsberg Digital at Future Oil and Gas Aberdeen.

At the recent Future Digital event in Houston, an interesting topic surfaced: defining the term ‘digital twin’. With more than 250 definitions, we are pleased to see that discussions are instead moving toward the value that digital twins bring and what elements are required for it to contribute to meaningful energy and digital transformation.

First things first: the data question

Let’s get the data question out of the way. While data remains a foundational ingredient for digital, companies are starting to see that a tactical large data approach is often long-winded, expensive and cost prohibitive. Bottom line, having more data does not lead to higher-quality decision-making but having the right data for decision-making does – especially since decision effectiveness drives 95 percent of company performance

What if the data is already in good shape?

That’s a good start. Maybe a good data architecture is already in place and it’s possible to add digital applications on top to help users find, manage and apply data through visual interfaces like dashboards. But is that enough? What even progressive digitalised companies lack is the ability to identify opportunities where digital applications – like a digital twin – can connect data to real value.

A strategic digital performance model approach

By evolving to a strategic approach that organises data in a digital twin into explicit performance model frameworks, companies can drive transparency around decision making to link from desired outcomes – like profit and loss factors or throughput capacity – to data patterns that can be analysed to determine the right decisions, actions and subsequent work execution. This way, savings offer hard ROI directly related to profit and loss. When leveraging this performance model, companies can continuously incorporate the latest technologies like generative AI and large language models (LLMs) to fill gaps in the data foundation, address specific use cases and services and provide full traceability into the reasoning behind recommended actions.

What is the digital performance model?

Put simply, a collection of key organisational components that deliver faster, transparent, higher quality decisions and stronger business performance at scale. It ties together processes, organisational structures, technologies and governance in an industrial work surface – a digital twin environment built on physics-based and datadriven models – that provides a digital interface where work can be done.

Value drivers of a digital performance model

The key to driving success with a digital performance model is selecting the right digital services in the coordinating layer of the business where operational decision-making takes place. This layer lies between the top-down strategic management layer and the bottom-up tactical execution layer, and it is where focusing on low- value, high-frequency events can bring both shortterm savings and long-term sustained, continuous improvement. By connecting these layers with digitally coordinated workflows, both business and operational goals are more transparent and achievable.

Some examples of low-value, high-frequency events in oil and gas:

Filter changes

Maintenance scheduling

• Changing between pumps during operation

Midstream metering

High-frequency events provide enough data to move from patterns to action and output, allowing for decision-making processes throughout the business to be digitalised and de-cluttered. The nature of being high frequency allows for faster automation and training of technologies like AI, ultimately freeing up decision-makers across the organisation to spend more time on key decisions and drive greater impact through the continuously optimised execution of business. When the low-value parts of a business are increasingly pushed towards autonomy and scaled, value drivers include asset support, cost savings and the condensation and automation of activity. Most importantly, a digital performance model approach accelerates faster high-quality decisions in real-time. Better throughput, less unplanned downtime and lower total cost of ownership –exactly what energy companies are after.

Three steps to success

Succeeding with the digital performance model requires three things: designing digitally, deploying optimally and delivering exponentially. First, designing digitally. This goes back to the initial stages of an operational digital twin where companies need to rethink how a digital thread will be embedded into operations – what are those high-frequency use cases and services that matter most? Then, deploying optimally. Making sure that the digital services in that coordination layer are grouped correctly according to resources or responses, and scalable enough that companies can push services towards autonomy across common asset classes. Finally, delivering exponentially by leveraging horizontal and vertical performance visibility for long-term returns on asset. The transparency of execution is essential for companies to close the gaps on understanding what actions drive the desired results.

The circle of trust

An important part of embedding digital is the explainability of how decisions are made, especially with increased use of Artificial Intelligence. With a digital performance model that deliberately includes data lineage and transparency, users can get a full understanding of 1st principles (the hybrid Machine Learning parts of the digital twin) and instant, updated transparency into the reasoning engine used by AI to provide insights and recommended actions.

Digital ways of working for future generations

When looking at the digital performance model, results from real-world use cases show that it can elevate individual performance for key operational roles and act as an enabler for collective organisation-wide improvement. The expectation for everything to be digital, connected, immediate and trustworthy is possible only with a digital performance model that aligns with the speed and scale required for true energy transition.

A holistic end-to-end digital approach that focuses on highly repeatable quality improvements can increase decision quality, speed and collaboration, resulting in alignment with the industry’s ultimate desire to achieve scalable impact and streamline datasets across operators and suppliers.