Advances in thermo-hydro-mechanical-chemical modelling for CO2 geological storage and utilization
Bibliographic record
Abstract
Geological storage and utilization of CO 2 involve complex interactions among Thermo-hydro-mechanical-chemical (THMC) coupling processes, which significantly affect storage integrity and efficiency. To address the challenges in accurately simulating these coupled phenomena, this paper systematically reviews recent advances in the mathematical modeling and numerical solution of THMC coupling in CO 2 geological storage. The study focuses on the derivation and structure of governing and constitutive equations, the classification and comparative performance of fully coupled, iteratively coupled, and explicitly coupled solution methods, and the modeling of dynamic changes in porosity, permeability, and fracture evolution induced by multi-field interactions. Furthermore, the paper evaluates the capabilities, application scenarios, and limitations of major simulation platforms, including TOUGH, CMG-GEM, and COMSOL. By establishing a comparative framework integrating model formulations and solver strategies, this work clarifies the strengths and gaps of current approaches and contributes to the development of robust, scalable, and mechanism-oriented numerical models for long-term prediction of CO 2 behavior in geological formations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".