3D hybrid mesh generation for reservoir simulation
Bibliographic record
Abstract
Abstract A great challenge for flow simulators of new generation is to gain more accuracy at well proximity within complex geological structures. For this purpose, a new approach based on hybrid mesh modelling was proposed in 2D by Balaven et al. ( Proceedings of the 7th International Conference on Numerical Grid Generation in Computational Field Simulations , Whistler, Canada, 2000; 407–416). In this hybrid mesh, the reservoir is described by a structured quadrilateral mesh and drainage areas around wells are represented by radial circular meshes. In order to generate a global conforming mesh, unstructured transition meshes constituted by convex polygonal elements satisfying finite volume properties are used to connect these two structured meshes. The hybrid mesh allows us to take full advantage of the simplicity and practical aspects of structured meshes, while complexity inherent to unstructured meshes is introduced only where strictly needed. This paper presents the 3D extension of the generation of such a hybrid mesh ( ECCOMAS , Jyväskylä, Finland, 2004). The proposed method uses 3D power diagrams to generate the transition mesh. Due to the round‐off errors, this mesh is modified in order to ensure the conformity with the structured meshes. In addition, some criteria are introduced to measure the mesh quality, as well as an optimization procedure to remove or to expand small edges of the transition mesh under finite volume properties constraints. Numerical results are given to show the efficiency of the approach. Copyright © 2005 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".