Reliability of microseismic source mechanisms recorded in the Pembina field, Alberta
Bibliographic record
Abstract
Source mechanisms of microseismic events, obtained using moment tensor inversion (MTI), can provide valuable information for monitoring hydraulic fracturing treatments. MTI is carried out for a dataset of 470 microseismic events recorded on two vertical monitoring wells in the Pembina Field, Alberta, Canada. Synthetic tests are carried out to investigate the reliability of moment tensor (MT) solutions, especially with respect to the seismic source location relative to the two monitoring wells. The tests show that a narrow region of unreliable solutions, exhibiting high bias and variance, intersects the two monitoring wells. The real dataset shows two regions of MT solutions, one with predominantly shear mechanisms and one with predominantly tensile mechanisms. However, the region of tensile mechanisms correlates strongly with the unreliable region identified in the synthetic tests. Therefore these results are inferred to be unreliable and mechanisms within the reservoir are interpreted to be predominantly shear in nature. This study shows the importance of accounting for the reliability of MTI when interpreting solutions. Presentation Date: Wednesday, September 27, 2017 Start Time: 4:20 PM Location: 362D Presentation Type: ORAL
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".