Using continuous microseismic records for hydrofracture diagnostics and mechanics
Bibliographic record
Abstract
Using continuous microseismic records is a novel technique for better understanding the mechanics of the fracture network evolution during a hydrofracture treatment, and to provide a tool for diagnostic evaluation of recorded microseismic data. Hydrofracture stimulations are widely used during well completions to optimize production volumes and extraction rates in petroleum reservoirs, enhanced geothermal systems and block‐caving mines. Microseismic monitoring is now becoming a standard tool for evaluating the position and evolution of a given treatment, principally by source locating microseismic hypocenters and visualizing these with respect to the treatment volume and infrastructure. The continuous microseismic amplitude record includes the full history of the seismic energy response of the rock mass recorded at a given geophone. We present case studies illustrating the use of this technique for supplementing microseismic locations to better understand the evolution of the fracture treatment, and to diagnose the condition of a given data set, so as to design criteria for more effective processing of the discrete microseismic events.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".