3D reservoir simulation of CO <sub>2</sub> injection in a deep saline aquifer of the Lower Paleozoic Potsdam Sandstone of the St Lawrence Platform, Gentilly Block, Quebec
Bibliographic record
Abstract
Increasing demand in carbon dioxide storage volumes to reduce greenhouse gas emissions to net zero by 2050 implies assessment of CO 2 storage capacity, including deep saline aquifers, even in tight sandstone reservoirs. 3D reservoir simulations of supercritical CO 2 injection were carried out in the Lower Paleozoic Potsdam Sandstone of the St Lawrence Platform (Gentilly Block), Quebec to predict safe CO 2 injection rates, evaluate reservoir pressure build-up in the presence of sealing and permeable faults, and estimate the gas injection cumulative. 3D one-way coupled reservoir–geomechanical modelling helped to analyse the interaction between reservoir pressure build-up and changes in in situ stresses, and estimate the risk of top and bottom seal failure and fault shear-slip reactivation. It is shown that a safe CO 2 injection rate per well for 20 years of continuous injection is estimated to range from 0.7 kg s −1 (22.1 kt a −1 ) to 10 kg s −1 (315.4 kt a −1 ) depending on the porosity and permeability of the Potsdam Sandstone varying from core-derived matrix values to ‘fracture-enhanced’ values. The corresponding injection CO 2 cumulative for 20 years ranges from 432.2 to 6013.5 kt per well. The implementation of a multiple-well injection plan will help to increase the injection CO 2 cumulative, given the considerable thickness and basin-scale dimensions of the Potsdam reservoir (3440 km 3 ).
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".