Beyond the dots in the box: Microseismicity-constrained fracture models for reservoir simulation
Bibliographic record
Abstract
Monitoring induced microseismic events usually results in locations for these events and a geometrical interpretation of these “dots in the box.” In this study, we show how additional information obtained from observed microseismic events, namely the source mechanisms, were used to generate a discrete fracture network. Using the wide aperture of a surface star-like array allows inversion for both shear- and nonshear-source mechanisms. Both volumetric and shear-only source mechanism inversion was done on microseismic events from the treatment of a shale gas reservoir in the continental United States. During the same hydraulic fracture stimulation treatment, both dip-slip and reverse faulting sources were active in this reservoir. The source mechanisms revealed fracture orientations more accurately than could be inferred from microseismic event locations alone. The activity of different mechanisms is interpreted as indicating reactivation of existing fractures in the rock, as well as suggesting generation of new fractures.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".