Enhanced Reservoir Characterization Using Hydraulic Fracture Microseismicity
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Microseismic measurements were integrated with seismic reservoir characterization and injection data to investigate variability in the hydraulic fracture response between three horizontal wells in the Montney shale in NE British Columbia, Canada. When wells were close enough, hydraulic fractures were found to interact with pre-existing faults, which acted as a barrier to fracture growth, and resulted in relatively large-magnitude microseismicity. Pre-existing faults were identified by edge detection/ant tracking algorithms applied to seismic reflection data, as well as from advanced analysis of the microseismicity, including microseismic deformation levels, magnitude-frequency characteristics and composite failure mechanism analysis. In cases where the wells were far from pre-existing faults simple, planar hydraulic fractures were observed, although there was a tendency to grow towards regions of low Poisson’s ratio based on amplitude versus offset inversion of the seismic reflection data. The tendency for the hydraulic fractures to be asymmetric and grow preferentially towards the low Poisson’s ratio region is attributed to material property changes and associated lower stresses in these regions. Insight from the enhanced reservoir characterization with integrated microseismic and treatment data is being used for better well placement, improved completion designs and increased production.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 it