Characterization of fractured low <i>Q</i> zones at the Buena Vista Hills reservoir, California
Bibliographic record
Abstract
Abstract We show that attenuation of high-resolution interwell seismic and acoustic waves based on velocity dispersion analysis relates to fluid-flow effects in fractured and shale–sand sequence formations at the Buena Vista Hills reservoir, California. Fractured low quality factor (Q-factor) zones in the Brown Shale and Antelope Shale reservoir intervals in the Monterrey Formation correlate with a system of fractures having permeabilities of 2.5 to 5 md. Vertical fractures oriented at azimuths from 0° to 30° are detected in the frequency range of 1 to 10 kHz. We establish that a poroelastic model based on the Biot/squirt-flow (BISQ) mechanism can be used to relate the low Q-factor zones in the Brown and Antelope Shales. Because the Brown Shale has no sands, we use it to evaluate a fracture system's response to attenuation. We adapt the BISQ mechanism to simulate fluid flow in fracture-induced anisotropy, which provides flow properties parallel and perpendicular to fractures in the siliceous shale formations. The model assumes that the principal axes of the stiffness tensor are aligned with the axes of the permeability and squirt-flow tensors. We simulate the fracture system by assuming that (1) a squirt-flow length on the order of centimeters represents fluid flow in fractures and (2) a squirt-flow length < 1 mm represents flow in low-permeability shales. Two types of fractures at the site are joint-like tectonic fractures and sigmoidal vein fractures. Their fracture permeability (approximately 5 md) and squirt-flow lengths (between 1 and 2 cm) predict a Q-factor of about 20 that fits the observed Q-factor in the Brown Shale. We find that fractures associated with squirt-flow lengths ≥ 3 cm are sensitive to horizontal attenuation for a frequency range of 120 to 1000 Hz. In addition, the horizontal Q-factor derived from sonic and crosswell data is about five times less than the vertical Q-factor associated with waves originating from the earth's surface.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".