Microseismic Data Processing, Modeling and Interpretation in the Presence of Coals: A Falher Member Case Study
Bibliographic record
Abstract
Low-velocity, low-density coal units are prevalent throughout the Cretaceous section of the Western Canadian Sedimentary Basin. Their elastic properties differ considerably from the surrounding clastic units, resulting in complex seismic propagation paths and interference patterns. This thesis presents a case study evaluating the implications these coal units have on the processing, finite-difference modeling and interpretation of a borehole microseismic dataset recorded in the Falher Member of western Alberta's Deep Basin. Seismic energy generated during hydraulic fracturing of the Falher Member manifests as low-velocity, high-amplitude channel waves. A Matlab-based processing workflow is developed to analyze the data set, with emphasis on velocity model calibration, receiver orientation and hypocentre location in the presence of coals. Finite-difference modeling is used to evaluate the propagation of seismic energy through the monitoring interval, leading to the identification of complex P- and S-wave arrival patterns which significantly complicate microseimsic processing. Alternative acquisition geometries are evaluated via finite-difference modeling and offer improvements to the original acquisition design. The resulting hypocentre distribution suggests that the completion design effectively stimulated the reservoir along the wellbore. Systematic error introduced by the coal layers may contribute to distance-dependant uncertainty in the final hypocentre 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".