Effective VTI anisotropy for consistent monitoring of microseismic events
Bibliographic record
Abstract
The monitoring of induced or triggered microseismic events increasingly is being used to inform the efficient production of unconventional reservoirs. A key aspect of economic production in these low-permeability rocks is hydraulic fracture stimulation, usually in horizontal wells. To evaluate the success of the stimulation, engineers rely on monitoring the induced (or triggered) microseismic events that are then interpreted to map the stimulated reservoir volume and likely drainage area of the well. These microseismic events can be mapped either from downhole or surface monitoring arrays. In this study, we discuss a newly developed methodology that allows economic and consistent mapping of microseismic events from multiple stimulated wells across an entire field. This approach allows better comparison of stimulation techniques between wells in order to optimize long-term development of the reservoir. As well, the method enables a relatively robust observation of velocity anisotropy that leads to better wave-propagation modeling and more accurate event locations
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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".