Published: 08/19/2025
Published: 08/19/2025
The world faces an unprecedented challenge in mitigating the devastating effects of global warming on our planet. This is why, in the oil and gas sector (and many others), reducing greenhouse gas emissions can no longer be a distant goal—it must be a real and urgent action instead.
The only caveat is that the planning for emissions reduction is far from simple for such heavy and complex industries. Industry players must balance multiple factors if they wish to remain viable. This means choosing to invest in decarbonization projects that not only have a measurable impact on emissions but also a positive business impact, such as providing a new revenue stream, reducing costs, or lowering tax liability.
Until now, decarbonization planning has usually been very manual, relying heavily on spreadsheets to record project information, costs, and abatement potential. Companies will then typically plot marginal abatement cost curves (MACCs), a common tool used to show the relative cost of abatement across different decarbonization projects.
These MACCs, however, represent a snapshot in time and are not suitable for multiyear planning where investment costs, operating costs, and abatement potential may change annually. To truly kickstart decarbonization journeys and bring emissions reduction into a business’s decision-making cycle, leaders must address the pain points created by the tedious and time-consuming planning workflows that many struggle with today.
In addition, planning cannot begin without first forecasting how emissions may change over the coming years given the business’s expected activity. Given that it provides the top line from which future emission abatement will be measured, this forecast needs to be as accurate as possible. How else can business leaders develop realistic plans that account for the potential emission increases their companies will see as they grow
A new frontier of low-carbon planning needs a new approach. Multiyear decarbonization planning needs to balance both economics and emissions abatement, making this process ideal for flexible, scalable, and realistic optimization. As we better understood the challenges facing oil and gas operators when planning their decarbonization pathways, we began identifying several areas where optimization could help future-proof their strategies.
1. Flexibility
Optimization has the advantage of enabling companies to improve what is most important to them. One company may want to maximize their emissions reduction based on an allocated budget and will use the optimization methodology to identify the best project mix and deployment order to do so. Another company’s top priority might be minimizing cost, in which case optimization constructs a roadmap of projects that meet its reduction target for the lowest overall cost possible. Being able to change the objectives and constraints of the optimization strategy based on priorities removes a lot of the heavy lifting that comes from doing these analyses manually.
2. Scalability
Companies can generally take one of two approaches when planning their emissions reduction. The first is a top-down approach by which reduction targets and ideas for meeting these targets are federated through the organization from the corporate level. The second is a bottom-up approach, in which the lower levels of the organization, such as individual plants and facilities, define the technology and equipment they need to install to reduce their emissions. The results of these projects are then aggregated at the corporate level.
Optimization solutions can be built for a wide range of complexity levels and corporate hierarchies and can, therefore, fit both types of planning. The same optimization solution can be applied at a facility, country, region, or enterprise level, for example, depending on the planning approach taken.
Modeling bottom-up planning is essential for some oil and gas operators, particularly in areas with an intense focus on reducing the methane emitted during operations. This includes mitigating emissions from the flaring of excess natural gas, venting unburnt gas directly into the atmosphere, and preventing gas from escaping through leaks in equipment and pipeline networks. These three areas alone can be costly to address, which shows why it’s critical to plan emissions reduction that is economically viable, reduces the impact of potential methane emission fees, and facilitates efficient natural gas production at the facility or site level.
3. Representing realistic projects
Open-source energy system modeling has been used for several decades to build optimization problems—representing how energy is sourced, produced, and consumed. Many of these frameworks have been extended in recent years to account for the emissions associated with each building block.
Each block behaves according to a set of rules; for example, as older power plants shut down, new ones can be added. These rule sets work well for modeling dynamic energy systems, but they’re not suitable for modeling organizations that are reducing the emissions associated with their operations. Why? Because decarbonization projects don’t have the same flexibility as other initiatives. They can’t be scaled up and down or simply turned on and off.
These limitations inspired the development of our scalable modeling framework, which aims to represent decarbonization projects more realistically within the optimization problem. Such frameworks help ensure that multiyear roadmaps reflect the realities of oil and gas operations, so that companies better understand where problematic emissions sources can be tackled to meet their reduction or budget goals.
The appetite for a low-carbon future is evident, not just in heavy industry but also across investors, regulators, and the public. But the only way to collectively reduce the impact of greenhouse gas emissions is to break down the barriers to effective mitigation, including efficient and comprehensive business planning for decarbonization. This is where data and digital solutions play a key role by ensuring that realistic and achievable reduction roadmaps can be easily built.
Throughout our own decarbonization journey, we’ve learned firsthand just how difficult and uncertain this planning process can be. It’s what gave rise to our goal of bringing innovative energy tech and solutions to hard-to-abate industries (e.g. CCUS and many other areas), thereby enabling more organizations to realize their low-carbon ambitions. And as we continue to refine our approach, we’re excited to see how it empowers our customers and partners to turn their decarbonization goals into tangible realities, driving a more sustainable future for all.
Stephanie Lee
Product Champion Plan Workflow
Stephanie Lee is the Digital Sustainability Product Champion for SLB, based in Houston, Texas, where she develops sustainability and climate change solutions using advanced digital and AI technologies.
She earned a PhD in Earth Science from the University of Waikato in 2013 and a bachelor's in Geological and Earth Sciences from the University of Leeds. Stephanie holds the SLB Product Management Badge of Distinction from UC Berkeley Executive Education (2024) and a Professional Education Certificate in Clean Energy Solutions from MIT. Her expertise includes sustainability, climate change, digital technologies, product management, and agile methodologies.