Development of a Scalable Parallel Compositional Simulator for Thermo-Hydromechanical Coupling in Fractured Rocks Using an Embedded Discrete Fracture Model
Bibliographic record
Abstract
Summary Numerical simulation of thermo-hydromechanical (THM) coupling in practical complex fractured rocks is an essential but challenging issue for the evaluation and optimization of underground energy production. In this study, we present our work on a scalable parallel compositional simulator for THM coupling, which is suitable for massive 3D polygonal fractures. In addition, we also present the improvements, parallel implementation, and optimization of an embedded discrete fracture model (EDFM). A unified cell-centered grid system based on the finite volume method (FVM) is used for all governing equations, and an extended stencil is adopted for mechanical equations to resolve the low-resolution defect of the traditional FVM. The deformation of both matrix rock and fractures is considered. A sequential fully implicit (SFI) method is adopted to solve THM coupling. This simulator is validated against three analytical solution models. Finally, we apply the simulator to two cases including a multilayered shale gas reservoir with massive natural fractures and a fractured geothermal model using CO2 as a working fluid. We also test the performance and parallel scalability on 1,024 CPU cores with up to 50 million matrix gridblocks and 5.5 million fracture gridblocks. The results show that this simulator can efficiently solve the THM coupling problem in practical massive fractures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".