Did you know the oil and gas sector is responsible for over 40% of industrial CO₂ emissions? Decarbonizing this sector isn’t just urgent, it’s one of the toughest challenges we face.
Every barrel refined and every stack scrubbed still leaves behind a quiet challenge: what do you do with the carbon captured? For industries under pressure to decarbonize, CCS (Carbon Capture and Storage) offers hope, but complexity accompanies that hope.
Capturing carbon is only half the battle. What happens after the CO₂ is compressed, dehydrated, and pushed through a pipeline is where your real challenges and opportunities begin, as shown in Figure 1.
When you're dealing with carbon mitigation, purity is more than a footnote in your lab report. Even tiny amounts of impurities in a CO₂ stream such as hydrogen, nitrogen, sulfur compounds, or water can throw off your entire system. These trace elements may seem trivial, but they can change how the gas behaves, wear down equipment, and make transport far more complicated.
And in the future where CCS is expected to cut at least 15% of global emissions by 2050, ignoring these effects is no longer an option.
Let’s start with the physics. Unlike methane or hydrogen, CO₂ has a high Joule-Thomson coefficient, meaning it cools rapidly when expanded and heats quickly when compressed. This property becomes a liability in your pipeline systems where pressure and temperature fluctuate, especially when impurities are introduced.
That cooling can trigger:
Each of these risks not only compounds over time but also gets worse as CO₂ pressure builds and reservoirs fill. Even more concerning? These effects often go undetected until performance drops or maintenance is needed.
You can’t afford to treat carbon transport as an afterthought. Instead, you need a predictive, performance-focused approach. That’s where Integrated Asset Modeling (IAM) comes in.
Figure 2 shows how through an IAM approach, you can simulate your entire CCS chain from dehydration to subsurface store. It’s not a one-off study; it’s a digital twin with a working brain. Unlike traditional black oil models, which fall short in CO₂ applications, IAM accounts for:
It’s not just simulation; it’s planning for real-world scenarios.
IAM turns unknowns into options. Before making changes in the field, you can test multiple feed compositions, predict failure points, and fine-tune pressure, temperature, and dehydration targets. IAM can help your team assess the cost-benefit trade-offs of purification vs. operational risks, so you’re optimizing not just for carbon but for cost, too.
CCS won’t succeed on vision alone. You need to implement the right infrastructure behind it. As impurities, assets’ evolution over the life of the field and potential upsets emerge as key challenges in transport performance, your focus must expand beyond capture.
IAM makes that shift possible. It’s not just about flow rates and total injected volumes —it’s about building a system that lasts longer, runs cleaner, and adapts as conditions change.
Beyond performance, IAM helps your team weigh purification costs, compression requirements, pipeline sizing and more, against maintenance and downtime risks - critical for long-term financial sustainability. And as CCS adoption grows, continued advances in impurity removal, materials science, and modeling will be essential to scale these systems efficiently.
Want to see the technical strategies behind this approach? Read the full article.