Fast Assessment of the Impact of Multi-Scale Geological Heterogeneities on Flow Behaviour in Complex Carbonate Reservoirs
Bibliographic record
Abstract
Summary We discuss the application of the new open-source Rapid Reservoir Modelling software (RRM) to create a suite of 3D reservoir models of a complex carbonate formation where each model is increasingly more refined such that progressively more small-scale geological structures are preserved. Using flow diagnostics we then calculate key metrics for the dynamic reservoir behaviour to quantify the similarities and dissimilarities of the flow behaviour across the different models. This analysis allows us to identify at which scale geological heterogeneities need to be resolved in the reservoir model to capture the essential flow behaviours. The workflow presented in this study hence allows us to efficiently and effectively test different geological concepts and analyse how multi-scale geological heterogeneities that may need to be represented in a reservoir model impact the predicted dynamic response, so as to design more reliable and robust reservoir models for a broad range of geoenergy applications.
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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".