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Abstract

Summary

In response to global efforts to reduce CO emissions, the oil and gas industry is advancing techniques to identify viable storage areas, with 4D evaluation playing a crucial role. Forward stratigraphic modeling is particularly effective in data-limited scenarios, enabling geologically consistent subsurface models to characterize potential CO storage zones. Synthetic seismic generation complements this process by simulating seismic wave propagation through reservoirs, revealing geological properties and fluid dynamics. This simulation helps track CO distribution changes over time and supports validation of dynamic reservoir models. Integrating forward stratigraphic modeling with synthetic seismic generation establishes a robust workflow for assessing CCUS storage potential. The approach combines facies property modeling, sedimentary architecture representation, and fluid dynamics analysis with seismic impedance contrast evaluation. This integration accounts for CO distribution and saturation changes caused by injection and storage, creating a comprehensive method for optimizing storage zone identification.

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/content/papers/10.3997/2214-4609.202521227
2025-10-27
2026-01-19
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References

  1. Daly, C., 2021, An Application of an Embedded Model Estimator to a Synthetic Nonstationary Reservoir Model With Multiple Secondary Variables: Frontiers in Artificial Intelligence, v. 4, doi:10.3389/frai.2021.624697.
    https://doi.org/10.3389/frai.2021.624697 [Google Scholar]
/content/papers/10.3997/2214-4609.202521227
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