1887

Abstract

Summary

Machine Learning for CO2 resource assessment

Optimum storage sites

High resolution forward models for storage assessments

Merits of Machine Learning

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.202521167
2025-10-27
2026-01-14
Loading full text...

Full text loading...

References

  1. Improving Predictability by Drawing Comparisons between Geostatistical and Machine Learning Applications for Reservoir Modeling” Fourth EAGE Digitalization Conference & Exhibition, 2024Ahmad, A.; Rowan, D.
    [Google Scholar]
  2. Increasing Reservoir Predictability by Reducing Uncertainty by Using Learning Analytics with Forward Stratigraphic Simulations” 36th International Meeting of Sedimentology [Ims] (Dubrovnik, Croatia, 6/12–16/2023) Abstracts Book, 2023Ahmad, A.; Eder, K.
    [Google Scholar]
/content/papers/10.3997/2214-4609.202521167
Loading
/content/papers/10.3997/2214-4609.202521167
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error