Digitalising the value chain

Online Editor

Dr Jillian Davidson explains how digitalising the upstream mitigates skills shortages and drives profitability

Companies operating across the upstream oil and gas sector are confronted with pressing challenges that demand immediate attention. Central among these is the imperative to embrace digitalisation across the value chain. This shift is being driven by the need for operational excellence, emissions reduction, enhanced asset production, and the expansion of reserves. Yet, the urgency of this digital transformation is compounded by a scarcity of skilled resources within the industry.

According to analysis by Accenture, the energy industry will experience a lack of up to 40,000 competent workers by 2025. The research also shows that Upstream Petrotechnical Professionals (PTPs) older than 55 made up 19% of the total oil and gas workforce in 2015. By 2025, their numbers will drop to just 7%. To effectively address this skills shortage while optimising the value chain, firms must implement end-to-end digital solutions that seamlessly integrate subsurface and surface operations.

To bridge the skills gap, organisations can leverage advanced seismic imaging solutions that empower geoscientists to gain unprecedented insight into subsurface knowledge. These visualisation tools deliver highly accurate images from beneath complex structures, such as shallow low-velocity anomalies such as gas pockets, subsalt, sub-basalt and high-velocity carbonate rocks.

They optimise reservoir characterisation, and fracture detection, and help companies prioritise investment, accurately delineate stratigraphic features of formations to decide on placement of future wells. They reduce time to first production, and mitigate the risks associated with inaccurate predictions.

Inaccuracies in predicting rock types and fluid distribution within reservoirs are another critical challenge. Reservoir properties' inherent variability generates geological uncertainties that hinder accurate well placement, and there is a scarcity of experts across the industry with the necessary skills to address the problem.

Moreover, the prospect of mitigating this challenge through integrated analysis, incorporating multi-scale geological, geophysical, and seismic information, raises questions of both data accuracy and the expertise to interpret. That’s especially the case given that there is a lack of professionals today who are proficient in data acquisition and analysis techniques such as seismic interpretation, well log analysis, and reservoir modelling.

From delivering feasibility studies to enhancing well construction

One of the greatest challenges in oil and gas exploration and production is to forecast recoverable volumes of hydrocarbons and drive production scenarios amid pervasive subsurface uncertainty. The traditional multidisciplinary approach to scenario iteration, though valuable, is fraught with time inefficiencies and the potential for flawed production projections. Herein, the complexity of the subsurface dynamics intersects with the challenge of accurately modeling various scenarios and their economic implications.

Designing wells for near-field expansion necessitates intricate trajectory planning to maximise recovery from a single well while maintaining a safe distance from existing wellbores. The complexities of drilling in such scenarios requires geo-mechanical modeling and real-time data utilisation, both of which are contingent on skilled human intervention. To address this challenge, the industry may need to invest in workforce development and training initiatives to nurture a new generation of experts.

Optimising production

Using existing facilities for a new production regime requires a holistic overview of the system to incorporate all the constraints when planning the tie-in of new production wells. The tight integration of subsurface and surface assets, enabled using integrated flow assurance and production modelling software, helps fill skill gaps by enabling any operator to quickly anticipate the impact a new tie-in will have on the process facility in the short and longer term.

Building a fieldwide model allows collaboration between multiple teams, enabling them to optimise the entire system, define operational best practices and reduce tie-in time. The ability to quickly achieve steady-state operations can result in a net savings of at least four days of production.

Accelerating project delivery

A production network simulator is key to ensuring the safe and cost-effective transportation of fluids. Such a simulator can consider the multiphase network response of multiple wells feeding into a common production system, where the response of one well will affect the flow rate of another. From complex individual wells to a vast network, AspenTech’s production modelling and optimisation software can be leveraged to ensure optimal flow over the entire lifecycle and improve margins.

By utilising advanced simulation software in this way, organisations can reduce their dependency on a small pool of experts. This widens the talent pool for operating and maintaining these networks, making it less reliant on a handful of experts.

Leveraging digital twins

Rigorous process simulation-based digital twins provide accurate insights into a spectrum of process parameters, often in real time, which typically cannot be directly measured in an operating facility. More importantly, these insights are displayed in intuitive, easily readable and easily accessible user interfaces and dashboards, enabling stakeholders across the enterprise to make informed decisions that reduce risk, while improving the efficiency and agility of their operations to increase profitability and advance sustainability efforts.

Integration is key

Leveraging subsurface engineering solutions empowers operators to identify opportunities for production enhancement and minimise the risk of further exploration and production. A fieldwide simulation model, capturing the producing field's intricacies, can lead to a 10–15% reduction in CO2 emissions and energy consumption, contributing to sustainability goals while boosting operational efficiency.

A fully integrated model that harmonises reservoir engineering objectives with production, gathering, and processing operations can help deliver further productivity and profitability gains. Such integration, grounded in advanced data analytics and AI, can drive an additional 5-10% increase in operational yield, unlocking untapped potential from existing assets.

The integration of advanced data analytics and artificial intelligence (AI) into subsurface engineering and production optimisation requires individuals with expertise in data science and AI technologies. Organisations will need to hire or train professionals with these skills, contributing to the development of a more diversified skill set within the industry.

Looking to the future

In conclusion, the upstream oil and gas sector faces not only technical challenges but also a critical skills shortage. Embracing digitalisation and optimising operations across the value chain is not just a strategic move for profitability; it's a path to addressing the skills gap. As the industry evolves, those who strategically integrate technology and data analytics will stand at the forefront, nurturing a skilled workforce and propelling their organisations towards a more productive, prosperous future.

 Dr Jillian Davidson is industry director for Energy at AspenTech

Recent Issues