An extended finite element method model for carbon sequestration
Bibliographic record
Abstract
Summary A two‐phase flow eXtended Finite Element Method (XFEM) model is presented to analyse the injection and sequestration of carbon dioxide (CO2) in deep saline aquifers. XFEM is introduced to accurately approximate near‐injection well pressure behaviour with elements significantly larger than the injection well diameter. We present a vertically averaged multiphase flow model that combines XFEM to approximate the pressure field, with a Streamline Upwind/Finite Element Method/Finite Difference Method (SU‐FEM‐FDM) to approximate the distribution of CO2 in the aquifer. Near‐well enrichment functions are presented along with the solution procedure for the coupled problem. Two examples are presented: in the first, CO2 injection into a perfectly horizontal aquifer is modelled with both XFEM and FEM‐based methods. The results suggest that XFEM is able to provide low relative errors in the pressure near the well at a reduced computational cost compared with FEM. The impact and selection of the stabilization coefficient of the SU‐FEM‐FDM is also discussed. In the second example, the XFEM and SU‐FEM‐FDM model is applied to a more realistic problem of an inclined aquifer to demonstrate the ability of the model to capture the buoyancy‐driven migration of CO2 in a deep saline aquifer. Copyright © 2014 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".