Inversion and interpretation of seismic-derived rock properties in the Duvernay play
Bibliographic record
Abstract
We have developed an interpretive seismic workflow that incorporates multicomponent seismic inversion, guided by structural mapping, for characterizing low-permeability unconventional reservoirs. The workflow includes the determination of a calibrated time-depth relationship, generation of seismic-derived structural maps, poststack inversion, amplitude-variation-with-offset analysis, and PP-PS joint inversion. The subsequent interpretation procedure combines structural and inversion results with seismic-derived lithologic parameters, such as the Young’s modulus, Poisson’s ratio, and brittleness index. We applied this workflow to a 3D multicomponent seismic data set from the Duvernay play in the Kaybob area in Alberta, Canada. Subtle faults are discernible using isochron maps, horizontal time slices, and seismic stratal slices. Fault-detection software is also used to aid in the delineation of structural discontinuities. We found that seismic-derived attributes, coupled with structural mapping, can be used to map reservoir facies and thus to highlight zones that are most favorable for hydraulic-fracture stimulation. By imaging structural discontinuities and preexisting zones of weakness, seismic mapping also contributes to an improved framework for understanding the induced-seismicity risk.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".