Research on water invasion performance of complex fracture-vuggy gas reservoirs based on classification modeling
Bibliographic record
Abstract
The complexity of the pore structure, spatial development, fractures, and pore distribution of fractured-vuggy carbonate reservoirs influences the water invasion dynamics of gas reservoirs, which is crucial in the dynamic research of strongly heterogeneous reservoirs. In this study, the collocation relationship of pore-vuggy fractures is described by the quantitative characterization of their attribute parameters. The discrete fracture network model is used to match and construct the fractures in different modes. The distribution classification method is used to model three-dimensional geological reservoirs in terms of their geometric and attribute characteristics. Bottom-water and edge-water gas reservoirs are constructed separately using numerical simulation, and the dynamic characteristics of water invasion are described. The results show that the proposed method is suitable for the geological modeling of fractured-vuggy gas reservoirs with strong heterogeneity and complexity. The modeling accuracy is improved because the gas reservoir heterogeneity and water invasion’s dynamic characteristics can be described accurately. Six stages of water invasion are identified from the numerical simulation of water invasion. This method provides theoretical guidance for the study of heterogeneous gas reservoirs with water. Cited as : Han, X., Tan, X., Li, X., Pang, Y., Zhang, L. Water invasion performance of complex fracture-vuggy gas reservoirs based on classification modeling. Advances in Geo-Energy Research, 2021, 5(2): 222-232, doi: 10.46690/ager.2021.02.11
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".