Study on main controlling factors of tight gas reservoir productivity
Bibliographic record
Abstract
Abstract In this paper, a differential discrete numerical model is first established, taking into account the pore structure characteristics of tight reservoirs. Subsequently, a research framework for the rock compression coefficient is developed, and its influence on multi‐stage flow in tight reservoirs is investigated. Following this, the main geological controlling factors affecting productivity are analyzed. With porosity and permeability as the focus, a productivity analysis program for tight reservoirs is constructed, revealing the evolution patterns of production capacity under low‐porosity and low‐permeability conditions. The main findings are as follows: (a) In tight reservoir settings, different rock compression coefficients have a relatively limited impact on daily gas production. (b) Initial daily gas production shows little variation across different porosity values; however, as depletion development proceeds, lower porosity leads to a more rapid decline in gas production. (c) At permeability values of 0.03, 0.05, 0.07, and 0.1 mD, the initial daily gas production rates are 1528.578, 2547.596, 3566.587, and 5095.023 m 3 , respectively. Daily gas production gradually decreases throughout the depletion process.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".