Promise Longe Unveils Breakthrough in CO₂-EOR and Carbon Storage for a Net-Zero Future

By Tosin Clegg

In the race toward a carbon-neutral future, one researcher is bridging the gap between cutting-edge science and practical energy solutions. A groundbreaking study by Promise O. Longe, a PhD researcher in Chemical and Petroleum Engineering at the University of Kansas, has unveiled the transformative potential of CO₂-Enhanced Oil Recovery (CO₂-EOR) and carbon storage initiatives in supporting both emissions reduction and sustainable energy production.

Longe’s research, themed “Turning Emissions into Energy: The Role of CO₂-EOR and CO₂ Storage Initiatives in a Carbon-Neutral Future,” provides a forward-thinking blueprint for converting carbon emissions into viable energy assets through advanced numerical modeling, machine learning, and field-scale simulations. His work was presented at the various SPE Energy conferences and disseminated in reputable journals.

He explained that CO₂-EOR is a method where captured carbon dioxide is injected into aging oil fields to push out more oil, making use of CO₂ that would otherwise be released into the atmosphere. CCS, or Carbon Capture and Storage, involves collecting CO₂ emissions from industrial sources and safely storing them underground. Together, they reduce emissions, boost energy production, and help fight climate change—turning a major environmental challenge into an energy opportunity.

Drawing from extensive simulations performed at the Stewart Field Unit in Kansas, Longe’s research explores how captured CO₂ from ethanol plants can be effectively stored in subsurface formations while enhancing oil recovery. This dual-use approach maximizes environmental and economic benefits, offering a scalable solution to the global decarbonization challenge. “The future of clean energy lies in converting our greatest threat—CO₂—into an asset,” Longe stated in an interview. “My research is focused on making that vision practical through computational models, field validation, and novel predictive systems.” Longe explained that his work seeks to optimize the dual potential of CO₂—as a permanent storage medium and as a displacement agent in enhanced oil recovery. He emphasized that CO₂-EOR is one of the most economically viable and technically mature pathways for large-scale carbon sequestration, especially when reinforced by predictive modeling. “These methods allow us to accurately predict CO₂ trapping efficiency, migration behavior, and long-term stability in subsurface formations,” he noted.

At the core of this research is a machine-learning model designed to predict CO₂ trapping efficiency in a variety of subsurface geological settings. He affirmed that this model helps design more efficient injection strategies and reduces the operational uncertainty that often hinders CCS deployment. In his recent peer-reviewed article in Geoenergy Science and Engineering, he presented a full-field reservoir simulation study on CO2-EOR projects of the Stewart Field Unit. The study evaluated multiple CO₂-WAG (Water-Alternating-Gas) scenarios and proposed a recommendation for implementation of the optimal scenario: “Clean energy solutions will only scale if they make economic sense,” he reiterated. “This model helps ensure that carbon management isn’t just environmentally beneficial—but commercially sustainable too.”

Longe also presented a companion paper at the SPE Energy Transition Symposium, titled “An Overview of Stewart Field Unit Project: A Field Case Study of CO₂ Capture, Utilization, and Storage.” This technical presentation explored real-world deployment challenges, simulation outcomes, and strategic lessons from the Kansas field pilot. “The Stewart Field project allowed us to test advanced simulation tools in a real-world context—validating both the performance of CO₂-EOR and its storage permanence in shallow fluvial reservoirs,” he explained. He emphasized the importance of integrating field data to refine and validate predictive modeling tools, ensuring their reliability for broader CCS applications. He affirmed that projects like Stewart Field are instrumental in building the technical and economic case for widespread CCS deployment across geologically diverse regions.

A graduate of Federal University of Petroleum Resources Effurun (FUPRE) in Nigeria, Longe’s journey from the Niger Delta to the U.S. Midwest is a testament to international collaboration and scholarly persistence. His early career included roles at Laser Engineering and the Department of Petroleum Resources (DPR) Nigeria, where he gained valuable field experience. “My early exposure to the complexities of Nigerian oilfields shaped my problem-solving instincts. Those challenges became the seedbed for my innovations in reservoir simulation and machine learning,” he explained.

As a rising global researcher at a leading U.S. institution, Longe brings a unique perspective to energy transition science. He emphasized the urgent need for inclusive, equitable solutions that incorporate the capabilities and needs of developing nations. “We cannot afford to exclude developing nations from the clean energy conversation,” he said. “Solutions must be global in scale and equitable in impact.” Longe currently did serves as the Vice President of the Society of Petroleum Engineers (SPE) at KU and as the Research Chair for the Graduate Engineering Association, extending his impact beyond the lab through mentoring, outreach, and leadership.

Longe’s work is increasingly shaping policy-relevant discussions, with invited talks and conference presentations at global forums like the International Petroleum Technology Conference in Saudi Arabia. “Policy frameworks that incentivize CO₂ reuse and storage are essential,” he stated. “They accelerate innovation and create long-term certainty for investors and operators.” His expertise bridges academia and industry, with a focus on delivering field-ready solutions informed by data science, simulation, and economic modeling.

From developing production rate models for Niger Delta oil wells to designing gas solubility algorithms for brine-CO₂ systems, Longe’s work is rooted in field application. “Everything I work on has a field application in mind. That’s how we bridge the gap between theory and transformation,” he affirmed. His tools are actively used in Kansas-based projects and inform industry and government-funded initiatives focused on both enhanced oil recovery, carbon and hydrogen storage.

Longe has co-authored articles in prestigious and high impact factor journals such as Applied Energy, Journal of Molecular Liquids, Energies, ACS Energy & Fuels, and Journal of Alloys and Compounds. His accolades include the SPE Egbert Imomoh Scholarship, NSBE Legacy Scholarship, Chevron/Agbami Award of Excellence, and multiple departmental awards at KU.

From simulation labs to sandstone reservoirs, Promise O. Longe is leading the next generation of carbon science. His integration of machine learning, techno-economic modeling, and reservoir engineering is shaping the conversation around practical, scalable decarbonization strategies. “We’re not just storing carbon—we’re reimagining it,” he concluded. “By transforming emissions into energy and embedding intelligence into our storage systems, we can unlock a net-zero future that is both practical and powerful.”

References:

Longe, P.O. et al. (2025). Techno-economic Evaluation of CO₂-EOR and Carbon Storage in a Shallow Incised Fluvial Reservoir Using Captured CO₂ from an Ethanol Plant. Geoenergy Science and Engineering. https://doi.org/10.1016/j.geoen.2024.213559
Longe, P.O. et al. (2024). An Overview of Stewart Field Unit Project: A Field Case Study of CO₂ Capture, Utilization, and Storage. SPE Energy Transition Symposium.