In January 2019, ExxonMobil announced a partnership with IBM to advance the potential use of quantum computing in developing next-generation energy and manufacturing technologies. This collaboration made ExxonMobil the first energy company to join the IBM Q Network, a worldwide community of Fortune 500 companies, startups, academic institutions, and national research labs working to advance quantum computing and explore practical applications for science and business.

The Energy Sector Challenges

ExxonMobil faced several complex computational challenges that exceeded the capabilities of traditional computing systems. The company needed to address what they termed the “dual challenge” of providing reliable and affordable energy to a growing global population, projected to reach 9.2 billion by 2040, while simultaneously reducing environmental impacts and the risks of climate change.

Specific challenges included optimizing maritime shipping routes for cleaner fuels like natural gas, which emits up to 60% less greenhouse gases than coal, managing complex electric power grids, and developing more effective carbon capture technologies. These problems involve vast numbers of variables and constraints, creating optimization scenarios that are extremely difficult or impossible to solve exactly with classical computing approaches.

Additionally, ExxonMobil needed more accurate ways to simulate molecular interactions for applications such as developing new catalysts, improving carbon capture materials, and creating more efficient chemical manufacturing processes. Simulating these quantum-scale interactions accurately requires computational resources that exceed the capabilities of even the most powerful supercomputers.

Quantum Solutions

The IBM-ExxonMobil partnership focused on several quantum computing applications designed to address these energy sector challenges:
Maritime Inventory Routing Optimization

Teams from IBM Research and ExxonMobil Corporate Strategy Research collaborated to model maritime inventory routing on quantum devices. This involved developing quantum algorithms to optimize the routing of ships transporting natural gas and other cleaner fuels, analyzing the strengths and trade-offs of different strategies for vehicle and inventory routing.

The approach aimed to provide more efficient solutions to routing problems than possible with classical computing methods, potentially reducing fuel consumption, lowering emissions, and improving the economics of cleaner energy transportation.

Power Grid Optimization The partnership explored quantum computing applications for optimizing country-level power grids, a computationally intensive challenge that involves balancing supply, demand, transmission constraints, and other factors across vast networks. By developing quantum algorithms for grid optimization, the partnership aimed to enable more efficient integration of renewable energy sources and improve overall grid reliability and performance.

Quantum Chemistry for Carbon Capture

Researchers focused on developing quantum algorithms to perform more accurate quantum chemistry calculations, enabling the discovery of new materials for efficient carbon capture. This work leveraged quantum computing’s natural advantage in simulating quantum systems, potentially allowing for the design of materials with specific properties that could dramatically improve carbon capture efficiency.

Implementation

The implementation of these quantum solutions involved close collaboration between ExxonMobil’s research team and IBM’s quantum computing experts within the IBM Q Network framework.

Collaborative Research Structure

ExxonMobil assembled a quantum team composed of applied mathematicians, optimization experts, computational chemists, and other scientists with both the fundamental research capabilities needed for algorithm development and practical knowledge of energy industry challenges. This team worked directly with IBM’s quantum computing specialists to develop and test algorithms on IBM’s quantum hardware.

The collaboration also extended to the broader IBM Q Network community, creating opportunities for knowledge exchange and collaboration with other quantum computing pioneers across various industries.

Maritime Routing Implementation

For the maritime inventory routing challenge, the teams developed quantum algorithms that could represent the complex constraints of shipping operations and find optimized solutions. This implementation required translating real-world shipping constraints into mathematical formulations compatible with quantum processing.

The researchers analyzed different strategies for encoding these problems for quantum processing, evaluating how various quantum approaches compared to classical methods and identifying the types of routing problems where quantum computing might offer the greatest advantages.

Materials Science Implementation

ExxonMobil later joined IBM’s Materials Science Working Group, which kicked off in March 2023 and included members from Oak Ridge National Lab, RIKEN, the University of Chicago, Boeing, and Bosch. This group focused on implementing quantum algorithms for simulating materials at a fundamental level, with particular emphasis on determining the ground state properties of materials—a key to understanding how they behave during chemical reactions.

Results and Business Impact

While the partnership was still in its early stages and quantum computing technology continued to mature, several important outcomes and potential business impacts emerged:

Foundation for Future Quantum Applications

The collaboration established a strong foundation for quantum computing applications in the energy sector, laying the groundwork for future advances as quantum hardware continues to improve. ExxonMobil positioned itself at the forefront of quantum computing adoption in the energy industry, developing the expertise and capabilities needed to leverage this technology as it matures . GlobucExxonMobil

Insights into Maritime Routing Optimization

The maritime routing work provided insights into how quantum computing could eventually handle previously insoluble routing problems. As IBM’s quantum hardware scaled from small prototype systems to larger devices, these early algorithms and implementations created a pathway toward practical quantum-enhanced shipping optimization . IBM

Environmental Modeling Advancements

The quantum chemistry research offered potential for more accurate environmental modeling and materials design for carbon capture, addressing a critical aspect of ExxonMobil’s dual challenge of providing energy while reducing environmental impact. Even in these early stages, the quantum approach demonstrated potential advantages over classical simulation methods for certain types of molecular modeling.

New Algorithmic Approaches

The partnership inspired “different ways of thinking that are uniquely suited to [quantum computing’s] specific powers,” according to Dr. Vijay Swarup, ExxonMobil Vice President of Research and Development . IBM This led to the development of new algorithmic approaches that could benefit not just ExxonMobil but the broader quantum computing community.

Future Directions

Building on their initial collaboration, IBM and ExxonMobil outlined several directions for future quantum computing research and applications:

Scaling Quantum Algorithms

As quantum hardware capabilities continued to advance, the partners planned to scale their quantum algorithms to address larger and more complex energy optimization problems. This scaling effort aimed to prepare for the day when quantum computing becomes “utterly disruptive,” as Dr. Swarup put it.

Expanding to New Application Areas

Beyond the initial focus areas, the partnership identified additional potential applications for quantum computing across ExxonMobil’s operations, including developing new catalysts for low-energy chemical processing, simulating complex chemical reactions, and optimizing manufacturing processes.

Integration with Classical Computing Infrastructure

The future vision included integrating quantum computing with ExxonMobil’s existing high-performance computing resources, creating hybrid quantum-classical workflows that leverage the strengths of both computing paradigms. This approach recognized that quantum processors would likely serve as specialized accelerators for specific computational tasks rather than replacements for classical systems . IBM

Industry Standards and Best Practices

Through their participation in the IBM Q Network and various working groups, ExxonMobil and IBM aimed to help establish industry standards and best practices for quantum computing applications in the energy sector, encouraging broader adoption of quantum approaches to energy challenges.