Domain Decomposition Methods Applied to Coupled Flow-Geomechanics Reservoir Simulation
Bibliographic record
Abstract
Abstract In this work, well established Domain Decomposition techniques have been studied in order to carry out efficient simulations of coupled flow/geomechanics problems by taking full advantage of current parallel computer architectures. Different solution schemes can be defined depending upon transmission conditions among sub-domain interfaces. Three different schemes, i.e. Dirichlet-Neumann, Neumann-Neumann and Mortar-FEM, are tested and the advantages and disadvantages of each of them identified. This work will focus in the coupling of different meshes and/or physics on different domains by means of the Mortar-FEM plus the above DD-Schemes. Several examples of coupling of elasticity and poroelasticity in the context of reservoir compaction and subsidence are presented. In order to facilitate the implementation of complex workflows, we have implemented an advanced Python wrapper interface that allows programming capabilities. We have applied this platform to a variety of problems ranging from near-wellbore applications to field level subsidence calculations.
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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 | 0.000 |
| 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".