by Dr. Diana Shigapova, Industry Sr Manager for Upstream, AspenTech
In an era where the upstream oil and gas industry confronts unprecedented challenges, the role of digitalisation has become more crucial than ever. This technological shift is not just a response to the evolving landscape of operational demands and environmental concerns but also a strategic move to address the looming skills gap in the sector. A recent survey by the International Energy Agency (IEA) with 160 energy firms globally found that skilled labour shortages are a key barrier to ramping up activity, with supply failing to keep pace with demand. Comprehensive digital solutions that integrate both subsurface and surface operations, enhancing efficiency and pinpointing opportunities for continuous improvement can help to fill the void.
Advanced geophysical, geological, and engineering solutions are revolutionising how geoscientists and engineers approach subsurface exploration. These tools aid in investment prioritisation, exploration programmes, drilling, and field development by reducing risks associated with forecast uncertainties.
From feasibility analysis to advanced 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 is time-consuming and often results in missing the most effective production projections. Herein, the complexity of the subsurface dynamics intersects with the challenge of accurately modelling a broad spectrum of scenarios and their economic implications.
For instance, designing wells for near-field expansion requires intricate trajectory planning to maximise recovery from a single well while maintaining a safe distance from existing wellbores. The complexities of drilling in these 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 support a new generation of experts.
Optimising production
Solving one of the actual challenges – the use of existing facilities for a new production regime – necessitates 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, facilitated by integrated flow assurance and production modeling software, helps enable operations to quickly anticipate the impact of a new tie-in on the process facility in the short and longer term.
Building a fieldwide model enables collaboration between multiple teams, allowing them to optimise the whole system, define operational best practices and reduce tie-in time. The capability to quickly achieve steady-state operations can result in a net savings of at least four days of production.
A production network simulator is critical to ensuring the safe and cost-effective transportation of fluids. Such a simulator can assess 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 used to ensure optimal flow over the entire lifecycle and improve margins.
Through the use of advanced simulation software, organisations can reduce their dependency on a small pool of experts.
Leveraging digital twins
Rigorous process simulation-based digital twins deliver accurate insights into a wide range of process parameters, often in real time, which typically cannot be directly measured in an operating facility. More importantly, these insights are displayed in easily-readable and accessible user interfaces and dashboards, allowing 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 helps operators identify opportunities for production enhancement and minimise the risk of additional exploration and production. A fieldwide simulation model, capturing the producing field’s intricacies, can result in 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 additional productivity and profitability gains. Such integration, grounded in advanced data analytics and AI, can support an additional 5-10% increase in operational yield, unlocking further potential from existing assets.
The integration of advanced data analytics and artificial intelligence (AI) into geoscience and production optimisation necessitates the use of 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 skillset within the industry.
Looking to the future
In conclusion, the integration of digital technologies and data analytics, including AI, is a game-changer for the upstream oil and gas industry. It addresses critical challenges such as the skills gap and environmental concerns while unlocking new levels of efficiency and profitability. As the industry continues to evolve, embracing these technologies will be pivotal in empowering a skilled workforce and fostering sustainable growth.
