The Effect of Temperature on Flowback Data Analysis in Shale Gas Reservoirs: A Simulation-Based Study
Bibliographic record
Abstract
During hydraulic fracturing, there is a temperature difference between the injected water and formation rock for shale gas wells. The objective of this study is to investigate how this temperature difference changes with time, and how it affects multiphase-flow modeling during the shut-in and flowback periods. We conducted numerical simulations to investigate the behaviors of fracture temperature in shale gas wells. The results show a significant increase in fracture temperature during the shut-in and flowback periods. Sensitivity analysis suggests that this temperature increase is strongly related to the thermal conductivity of formation rock, matrix permeability, and initial reservoir temperature. Simulation scenarios were further compared to investigate the effect of temperature on flowback data analysis. Without considering the thermal effect, flowback data analysis may yield an earlier fracture cleanup and overestimated fracture volume. In addition, this study suggests that the thermal effect may also have implications for optimizing flowback operations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".