Using Linear Flow Parameter Initial Rate Method to Optimize Completion Design of Western Canada’s Montney Tight Gas Reservoir
Bibliographic record
Abstract
Since 2007, the horizontal well staged fracturing technology has been widely used in the development of tight sandstones in the Deep Basin Montney reservoir of Western Canada Basin. The horizontal length of the horizontal well, the amount of proppant added to the fracturing and completion, the frac stage spacing, and the choice of open-hole completion or casing completion have become important factors in the optimization of completion design. LFPIR (Linear Flow Parameter Initial Rate) is observed through the double logarithmic curve of the natural gas production data of the well. After the development enters the stable linear flow stage, the linear flow corresponding to the ideal situation can be obtained when the initial production rate in this stage is inversely extended to tD≈0. The LFPIR depends on the stimulated volume of the reservoir after fracturing, and the completion effect directly affects the size of the stimulated reservoir. The completion quality of the well can be judged by studying the LFPIR of the developed Montney horizon well in the Heritage area. By comparing the LFPIR of wells with different completion designs, optimize the completion design in the tight 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".