In the upstream oil and gas sector, companies are rapidly adapting to key challenges, with digitalization at the forefront. This transformation, essential for operational efficiency, emissions reduction, and field expansion, is crucial in an industry facing a significant skills shortage.
Accenture analysis predicts a deficit of up to 40,000 competent workers by 2025, compounded by an aging workforce. Comprehensive digital solutions that integrate both subsurface and surface operations, enhancing efficiency and identifying opportunities for continuous improvement help to fill the void.
Organizations can leverage advanced geophysical, geological, and engineering solutions that empower geoscientists and engineers to gain unprecedented insight into subsurface knowledge, delivering accurate models for complex reservoirs and optimizing production. These technologies aid in investment prioritization, exploration programs, drilling, and field development by reducing risks associated with forecast uncertainties.
From providing feasibility studies to enhancing well construction
One of the most significant 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 may result in missing the most effective production projections. Herein, the complexity of the subsurface dynamics intersects with the challenge of accurately modelling a range of scenarios and their economic implications.
For instance, designing wells for near-field expansion requires intricate trajectory planning to maximize recovery from a single well while maintaining a safe distance from existing wellbores. The complexities of drilling in these kinds of scenarios requires geo-mechanical modeling and real-time data utilization, 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 help deliver a new generation of experts.
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 a new tie-in will have on the process facility in the short and longer term.
Building a fieldwide model enables collaboration between multiple teams, allowing them to optimize the entire system, define operational best practices and reduce tie-in time. The capability to quickly achieve steady-state operations can result in net savings of at least four days of production.
Accelerating project delivery
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 optimization software can be made use of to ensure optimal flow over the entire lifecycle and improve margins.
By utilizing advanced simulation software in this manner, organizations 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 small group of experts.
Leveraging digital twins
Rigorous process simulation-based digital twins provide 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 intuitive, 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 to identify opportunities for production enhancement and minimize the risk of additional exploration and production. A fieldwide simulation model, capturing the producing field’s intricacies, can result in a ten to 15 percent reduction in CO2 emissions and energy consumption, contributing to sustainability goals while boosting operational efficiency.
A fully integrated model that harmonizes reservoir engineering objectives with production, gathering, and processing operations can help deliver extra productivity and profitability gains. Such integration, grounded in advanced data analytics and AI, can support an additional five to ten percent increase in operational yield, unlocking untapped potential from existing assets.
The integration of advanced data analytics and artificial intelligence (AI) into geoscience and production optimization necessitates the use of individuals with expertise in data science and AI technologies. Organizations will have 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’s shift to digital technologies and data analytics is essential for addressing the skills gap, workforce shortages, and enhancing profitability. As the industry evolves, integrating these advanced technologies will be crucial for empowering the workforce and driving sustainable growth.
For a list of the sources used in this article, please contact the editor.
Dr. Diana Shigapova is Industry Sr Manager for Upstream, at Aspen Technology (AspenTech), a global software leader. AspenTech solutions address complex environments where it is critical to optimize the asset design, operation, and maintenance lifecycle. Through its unique combination of deep domain expertise and innovation, customers in asset-intensive industries can run their assets safer, greener, longer and faster to improve their operational excellence.