When Obinna Joshua Ochulor appeared on my screen during a Zoom call from his Aberdeen flat, the relief of having just submitted his MSc project was evident, but so was the determination. His dissertation, “Modelling and Simulation of Torque and Drag in Extended-Reach Wells,” completed at Robert Gordon University’s School of Engineering, had taken months of painstaking work. He spoke about it less as an academic hurdle cleared and more as a data-driven contribution to one of the oil and gas industry’s most persistent challenges. “This was never about writing for a grade,” he told me. “It was about creating a model that could help engineers calculate forces more precisely, cut costs, and improve safety in extended-reach drilling. If the numbers are right, the wells are safer and the money saved is real.”
Extended-reach wells are becoming longer, deeper, and more complex as companies push to access difficult reservoirs. A conventional vertical well may extend a few thousand feet, but extended-reach wells can exceed 30,000 feet horizontally. Industry benchmarks show that such wells can save operators up to 30 percent in surface infrastructure costs by reaching multiple reservoirs from a single platform. Yet the engineering risks grow exponentially. Torque, the rotational force applied to the drillstring, and drag, the resistance encountered as the string moves, must be predicted with precision. If torque exceeds design limits, drill pipes twist and fail. If drag is underestimated, the pipe gets stuck, halting operations. The International Association of Drilling Contractors estimates that stuck pipe incidents account for nearly 25 percent of non-productive rig time worldwide, with costs ranging from $500,000 to over $1 million per event. Ochulor’s model tackled this exact problem. “Even reducing non-productive time by 10 hours could save half a million dollars on a North Sea project,” he explained. “That’s why getting the simulation right matters so much.”
His approach relied on advanced simulation software calibrated with real wellbore parameters. By applying mathematical models to torque and drag equations and validating against known datasets, he created a digital environment where different drilling scenarios could be tested. His sensitivity analysis showed, for instance, how changes in well inclination angles of just five degrees significantly altered drag forces, or how variations in lubricant properties could reduce torque by nearly 15 percent. These are not abstract numbers. They are operational insights that can prevent expensive downtime and extend the working life of drilling equipment. “What excites me,” Ochulor said on the call, “is not just that the model works, but that it shows clear cause-and-effect relationships. Engineers can see how small changes in parameters impact performance before they commit millions to mobilising a rig.”
Aberdeen was the perfect place for such work. The North Sea remains one of the most mature and technically demanding oil basins in the world, and torque and drag problems are a daily reality for drilling teams. Reports from the UK Oil and Gas Authority note that extended-reach wells are critical to maximising recovery, yet they also account for some of the most expensive failures. With daily rig rates in the North Sea averaging $200,000 to $300,000, time literally is money. Ochulor’s project demonstrated that predictive modelling could shave off non-productive time and make operations more reliable. “In this industry, an error margin of even 10 percent can be the difference between success and failure,” he remarked. “By narrowing that margin, my model gives decision-makers more confidence.” His project joins a growing movement to bring digital simulation deeper into drilling planning, blending academic research with industry imperatives.
The project was demanding both technically and personally. Ochulor described nights spent recalibrating equations when simulations did not align with expected patterns. He explained how integrating real-world variables, such as friction factors, drilling fluid properties, and casing designs, added both complexity and realism. “There were days when I felt like the model would never converge,” he admitted with a laugh. “But once it started producing results that matched field data, the effort made sense. It meant I wasn’t just solving equations, I was replicating the physics of the wellbore.” His supervisors encouraged him to balance theoretical accuracy with operational practicality, ensuring his model could be understood and applied by drilling engineers, not just academics. That balance between theory and real-world application became the hallmark of his work.
Beyond equations and simulations, the project had personal resonance. Nigeria, where Ochulor grew up, remains one of Africa’s largest oil producers yet suffers from inefficiencies and costly downtime in drilling operations. Studies by Nigeria’s National Petroleum Corporation show billions lost annually due to non-productive rig time and miscalculations in well planning. For him, the Aberdeen project was more than academic training. “I kept thinking about how much my country has lost over the years because of poor planning or inadequate modelling,” he told me. “If we had better predictive tools, many of those losses could have been prevented. This project was my way of contributing, even in a small way, to solving that problem.” The idea that a model developed in Aberdeen could find application in West Africa gave him a sense of purpose that extended far beyond the submission deadline.
Feedback from academic reviewers and informal discussions with industry professionals validated the significance of his work. One drilling consultant noted that while commercial torque-and-drag software exists, much of it is proprietary, expensive, and sometimes too rigid for custom scenarios. Ochulor’s model, by contrast, was adaptable and transparent, allowing engineers to test specific conditions. “That feedback was encouraging,” he said. “It made me realise this was not just an exercise to get a degree. With further refinement, it could be integrated into real projects.” The ability to make his findings accessible, rather than buried in academic jargon, also stood out. As he explained, “Engineers don’t want black-box outputs. They want to know why the numbers are what they are. My model tries to give them that visibility.”
As our Zoom call drew to a close, Ochulor reflected on what submission meant. “It’s a milestone, yes, but not the end,” he said. “I see it as the beginning of bigger questions. How do we test this in more complex wells. How do we integrate it with digital twin technologies. And how do young engineers like me ensure we’re not just following industry trends but shaping them with data.” His voice carried both the exhaustion of months of work and the excitement of possibilities ahead. Whether his torque and drag model becomes a widely adopted tool is still to be seen, but what is certain is that on a September day in Aberdeen, a young Nigerian researcher submitted more than a project. He submitted a challenge to the industry to think smarter, plan better, and trust in the power of data to drill safer and more efficient wells.
