Research on New Method of Clastic Reservoir Permeability Interpretation
Bibliographic record
Abstract
Reservoir permeability is an important parameter in reservoir evaluation and the research on surplus oil distributing regularities. However, it is difficult to calculate it accurately in the process of reservoir interpretation. The ordinary interpretation model uses the rough linear relationship between porosity and permeability within a semi-log coordinate system, resulting in much error. In this paper the permeability calculating formula, including three parameters, porosity, pore-throat radius and pore tortuosity, was deduced from the unity of Poiseuille Capillary Model and Darcy’s Law. Based on that, data of core physical properties analysis, mercury injection and well logging were used to construct the empirical relationship between pore tortuosity and pore-throat radius, thus realizing the transformation of permeability calculation from the solo empirical model to the semi-theoretical and semi-empirical model. The calculated results showed that the relative error of the new model was 20.26%, with 22.46 percentage points lower than the error of the traditional empirical model.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".