PTQ Q3 2025 Issue

A Alex Sorokin, Business Consulting Engineer, Imubit, alex.sorokin@imubit.com As facilities become more complex and integrated, busi- nesses become commensurately more vulnerable to gaps in institutional and technical expertise. On one hand, decades of know-how, experiential intuition, and mental models vanish as a generation reaches retirement age. A newer console operator may not know how to handle a sticky control valve, a fouled heat exchanger, or a rarely seen feedstock. In the field, he may not recognise a pump’s sound as abnormal, potentially missing much-needed pre- ventive maintenance. Likewise, a newer engineer may not yet know how to weigh different pieces of compelling information, such as catalyst deactivation, feedstock impurities, and fractionator flooding, to make an actionable recommendation to opera - tions, planning, or the capital projects team. Of course, new operators and engineers do become more effective, but over weeks, months, and years. To preserve and promote operating excellence in the face of a generational workforce transition, the industry must preserve and develop institu- tional expertise faster than ever before. Experienced personnel also face new challenges. To a greater extent than previously, they must be fast, flexible, and inventive to optimise tradeoffs in intricate, system-wide challenges rather than individual process units. Engineers and planners must compensate for abnormal operations not only at a single reactor or distillation column but within these interconnected networks. Today, downstream production may be constrained by intermediate qualities, and selectivity is preferable to the upstream plant rate. However, these limits may ease tomorrow, or the market incentive for high-grade products may drop, and the rate will be more valuable than selectiv- ity. With tight cost control and tighter margins, it is impera- tive that these opportunities are identified continuously and attained quickly. To do so, traditional approaches use linearised or first-principles models, which, while powerful, become prohibitively difficult to tune, maintain, and trust due to the large number of parameters, assumptions, and scenarios that describe a multi-unit system. Many sites seek an alternative in novel technologies, but most lack the technical expertise to implement new methods in a cen- tury-old industry. These bespoke human and technical knowledge gaps are connected and can form an intimidating feedback loop, but can also be addressed simultaneously. For example, histori- cal plant data intrinsically contains the cause and effect of every operator move. AI models trained on this data pre- serve a career’s worth of human experience and transfer it to the next generation. Some refiners now integrate AI-based models into operator training. Furthermore, engineers use these models to assess oper- ating strategies and explore alternatives, building expertise and generating value quickly. New technologies with a low barrier to entry help personnel to develop hybrid skillsets, providing the technical expertise that sites need to tackle complex problems. Dozens of refineries and chemical plants now use AI optimisers to achieve a truly global optimum,

even as incentives, qualities of intermediate products, and production constraints shift that optimum hour to hour and day to day. A Dave Loubser, Senior Staff Consultant, KBC, dave. loubser@kbc.global Expanding refinery and petrochemical integration presents significant opportunities for value creation, but also reveals critical knowledge gaps that must be addressed within the oil and gas industry. As integration deepens and asset com- plexity increases, traditional operational competencies are no longer sufficient. One key gap lies in the limited cross- disciplinary understanding between refining and petro - chemical operations. Engineers and planners often spe- cialise in one domain, leading to suboptimal integration strategies and underutilised synergies across the value chain. Another major gap is in digital and data analytics capabil- ities. Integrated sites generate massive amounts of process data, yet many organisations lack the advanced analyt- ics, AI, and machine learning expertise needed to extract actionable insights for real-time optimisation. Additionally, there is a need for better modelling and simulation tools that can bridge refining and petrochemical operations, Teams must better understand market dynamics, product flexibility, and logistic constraints across both refining and petrochemical sectors to maximise profitability accurately reflecting feedstock behaviour, energy integra - tion, and complex reaction kinetics in an end-to-end digital twin environment. Workforce competency also needs to evolve. The shift towards integrated complexes demands a workforce skilled in systems thinking, lifecycle emissions manage- ment, and multi-unit optimisation. There is a gap in training programmes that build these competencies across opera- tions, planning, and technology functions. Furthermore, sustainability and regulatory expectations add another layer of complexity. Integrated facilities must balance profitability with emissions targets and circular economy goals, requiring expertise in carbon accounting, renewable feedstock qualification, and life cycle analysis – areas where current capabilities are still developing. Finally, commercial and supply chain integration is often overlooked. Teams must better understand market dynam- ics, product flexibility, and logistic constraints across both refining and petrochemical sectors to maximise profitability. Bridging these gaps will require targeted training, invest- ment in digital tools, and stronger collaboration across functional and organisational boundaries. The companies that succeed will be those that embrace integration, not just in assets but in knowledge and culture.

PTQ Q3 2025