A General Framework Model for Fully Coupled Thermal-Hydraulic-Mechanical Simulation of CO2 EOR Operations
Bibliographic record
Abstract
Abstract In this work, we present the development of a comprehensive mathematical formulation and reservoir simulator for thermal-hydraulic-mechanical simulation of CO2-EOR processes We adopt the integral finite difference method to simulate coupled thermal-hydraulic-mechanical processes during CO2-EOR in conventional and unconventional reservoirs. In our method, the governing equations of the multiphysical processes are solved fully coupled on the same unstructured grid. A multiscale algebraic linear solver is adopted to speed up the non-isothermal flow calculation. Inspired by the meshless method, the algebraic solver eliminates the low-frequency terms through smoothing on a coarse grid. In order to simulate the phase behavior of a three-phase system, a three-phase flash calculation module, based on direct minimization of Gibbs energy, is implemented in the simulator. We have investigated the impact of cold CO2 injection on injectivity as well as on phase behavior. We conclude that cold injection is an effective way to increase injectivity in tight-oil reservoirs. We have observed and studied the temperature decreasing phenomena near the production well, known as the Joule-Thomson effect, induced by expansion of in-situ fluids. The novelty of this work lies in the fully coupled simulation scheme, including non-isothermal effects on CO2-EOR processes and recoveries, which has been ignored in almost all modeling studies of CO2-EOR. The multiscale solution strategy and the unique phenomena of non-isothermal compositional modeling coupled with geomechanics are captured by our simulator.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".