SLB has launched a carbon storage screening and ranking solution that increases confidence in site selection decisions based on scientific analysis of the long-term integrity and economic potential of an asset.
The solution helps customers avoid suboptimal storage sites with risk factors that can waste valuable time and resources as well as decrease the probability of a carbon capture, utilization and storage (CCUS) project reaching final investment decision (FID).
“CCUS is one of the most immediate opportunities to reduce emissions, but it must scale up by 100–200 times in less than three decades to have the expected impact on global net zero ambitions,” said Frederik Majkut, senior vice president of Carbon Solutions for SLB’s New Energy business. “Ensuring that a storage site is both safer and economical is crucial for the speed, scale and investment needed to meaningfully drive CCUS growth for a low carbon energy ecosystem.”
The screening and ranking solution uses both technical and nontechnical data to provide a detailed assessment of the capacity and economic viability of storage sites, while identifying potential risks. A benchmark comparison, pulling from successful storage projects globally, is created to provide a relative basis for ranking each site.
SLB uses proprietary tools, augmented by advanced digitally enabled workflows, to provide a fast, traceable and consistent process to validate the data, with an emphasis on risk identification using sensitivity and uncertainty analysis.
In Trinidad and Tobago, SLB collaborated with a customer to screen and rank potential storage sites, ahead of a scheduled offshore exploration and production and carbon storage licensing round. SLB evaluated storage sites in three geographic provinces, using 67 key criteria from SLB's proprietary workflow to evaluate potential sites. It then performed a sensitivity analysis to understand the influence of varied attributes and site properties on the ranking outcomes. The sites’ performance was benchmarked against the attributes of carbon storage basins in the United States and Europe.
Using Monte Carlo simulations to evaluate more than 2,000 iterations, SLB ranked the sites for the customer from best to worst. The process empowered the customer to prioritize areas with prime subsurface and surface characteristics, as well as high grading zones for more detailed evaluation and investment.