Efficient and Scalable Methods for Dual-Porosity/Permeability Models in Fractured Reservoir Simulations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In this paper, the multi-stage preconditioners are modified and applied to dual-porosity/permeability (DPDK) model problems. Employed as the first step of the multi-stage preconditioning processes, two modified decoupling processes for DPDK problems are developed. In a DPDK model, mass transfer both between fractures and between matrices is allowed, which means that the pressure both in fractures and matrix behaves as an elliptic property, so it is natural to employ two preconditioning stages solving the fracture pressure system and the matrix pressure, respectively, which draws the first type of a multi-stage preconditioner in this paper. Since the transmisibility between fracture blocks is much higher than that between matrices, the elliptic property of the fracture pressure is much stronger. Hence, we remove the stage of solving the matrix pressure system in the second type of a multi-stage preconditioner. Moreover, an extra stage of the ILU preconditioning process is added to the above multi-stage preconditioners in order to improve their efficiency, which results in another two multi-stage preconditioners. Combination of the modified decoupling processes and four new multi-stage preconditioners are studied and compared by large-scale reservoir simulation problems. Based on these numerical experiments, the optimal method to solve the DPDK model problems is concluded.
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.
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 | 0.000 |
| 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 it