Determination of Gas Well Productivity by Logging Parameters
Bibliographic record
Abstract
The prediction and evaluation of reservoir productivity is a comprehensive index of the dynamic characteristics of gas reservoirs, which can provide a reasonable basis for the design and rational distribution of gasfield development plan. Proration of gas well is an important procedure in the development process, Absolute open flow as a key indicator of rational production of gas well. It is very important to determine the absolute open flow of the gas well. The Permian in Ordos Basin is a typical tight sandstone gas reservoir. The paper analyses correlation relations between different logging parameters and absolute open flow, and get the four parameters, porosity, permeability, storage coefficient（the product of porosity and effective thickness）with better correlation relations and effective thickness with best correlation relation by combining a large amount of gas logging data and static logging data and means of linear regression analysis, Then on the basis of this, a new empirical formula for calculating the absolute open flow of gas wells is obtained by using the method of multiple linear regression. The example shows that the result of this method is reasonable and reliable and the method can provide scientific basis for the prediction of natural gas absolute open flow of tight sandstone gas reservoirs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".