Fluid flow and heat transfer during staged multi-cluster fracturing treatments along horizontal wells — Application for hydraulic fracture characterization using distributed temperature sensing
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Bibliographic record
Abstract
We present a technique for quantitatively characterizing fracture parameters during fracturing operation using temperature information recorded by distributed temperature sensing (DTS). A coupled thermo-hydraulic forward model is first developed to describe the fluid flow and heat transfer in the wellbore, fracture, and reservoir. The developed model is solved using the finite-difference approach for both injection and shut-in periods of staged multi-cluster fracturing treatments along horizontal wells. Then, the DTS temperature behavior is studied by conducting a sensitivity analysis of essential parameters. The results show that temperature signals capture changes in the fracture, reservoir, wellbore, and operation parameters, demonstrating DTS temperature data's feasibility in diagnosing fracture properties. The results also indicate that the temperature response at fracture locations shows a V-shape characteristic for both injection and shut-in periods, aiding in identifying the locations of the created fractures. The proposed model integrated with the Genetic Algorithm is applied to interpret DTS data from a shale gas reservoir, providing parameters like injection volume, fracture locations, fracture half-length, and leak-off coefficient at one particular time. These results enhance new insights on utilizing temperature data for fracturing optimization and further improve energy extraction performance from the stimulated reservoirs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it