Production Analysis of Multi-Stage Hydraulically Fractured Horizontal Wells in Tight Gas Reservoirs
Bibliographic record
Abstract
Activities in exploitation and developing tight gas reservoirs grown tremendously in recent years. The horizontal well with multi-stage hydraulic fracture stimulation has proven to be an effective strategy of developing these unconventional resources. However, to evaluate the fracturing treatment and predict the long-term production behavior of wells in gas recovery it is important to estimate the effective half-length and spacing of created hydraulic fractures and the extent of the stimulated reservoir volume (SRV). In this paper, a simplified linear model is presented to represent the relationship between fractures and matrix rock. Four flow regimes are identified with this model which exhibits the production dynamics of multi-stage fractured horizontal wells (MFHW). Rate-normalized gas pseudopressure is derived from production data and used to interpret flow regimes with corresponding calculation equations. We illustrate the analysis procedure with two field cases from a tight gas reservoir in Northeast China. The results prove that the proposed method works well in analyzing production data from tight gas wells in their early life. The potential in further developing this technique for practical application is obvious and looks very promising.
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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 | 0.001 | 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 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".