Effect of Fracture Compressibility on Gas-in-Place Calculations of Stress-Sensitive Naturally Fractured Reservoirs
Bibliographic record
Abstract
Abstract The tank material balance (MB) equation for gas reservoirs has been written taking into account the effective compressibility of matrix and fractures. The method has direct application on stress-sensitive naturally fractured reservoirs (nfr's). Under some conditions ignoring the effect of fracture compressibility (cf) can lead to over-estimating the volume of original gas in place using a cross-plot of p/z vs. Gp. The equation presented in this paper has been developed to overcome this weakness. The use of this MB is illustrated with an example. It is concluded that fracture compressibility can play an important role in the calculation of gas in place in naturally fractured reservoirs. The subject matter is significant because historically formation and water compressibilities have been neglected when carrying out MB calculations of conventional gas reservoir. This assumes that these compressibilities are negligible compared to gas. The assumption implies that the reservoir strata are static. When water influx is ignored, the assumption leads to a straight line in a cross-plot of p/z vs. cumulative gas production (Gp). However, this study shows that in those instances where fracture compressibility is large, the assumptions can lead to significant error.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".