ANALYSIS OF TIME-LAPSE 3-D VSP DATA FOR SEISMIC MONITORING OF CO2 FLOOD IN WEYBURN FIELD, SASKATCHEWAN
Bibliographic record
Abstract
This study explores the potential of VSP data in reservoir studies and particularly in separating the effects of CO2 pore pressure and saturation after fluid injection into the reservoir. It helps establishing robust and reliable links between physical properties of hydrocarbon reservoirs and seismic data. It also reduces the uncertainties of the AVA analysis through constructing a detailed model of first-arrival amplitude decay combining geometric spreading, scattering, and inelastic dissipation. The inversion of seismic data reveals anisotropic variations of geometric attenuation (wavefront curvatures and scattering, denoted ) and the effective attenuation parameter () with depth. Statistical analysis of model uncertainties quantitatively measures the significance of these results. This model correctly predicts the observed frequency-dependent first-arrival amplitudes at all frequencies and can be used for reflected waves. Scattering and geometric spreading (focusing and defocusing of wave fronts) significantly affect seismic amplitudes at lower frequencies and shallower depths. Using of complete well logs, a model of P- and S-wave scattering is derived from direct-wave attenuation observations by numerical and analytical methods. Both approaches reveal fluctuations in the transmitted-energy flux within different depth intervals, and particularly at frequencies above 60 Hz. A randomization of well logs suggests that the upper envelope of the transmitted energy flux (corresponding to strongest transmission) is a reasonable estimate for random scattering. The lower envelope corresponding to the strongest reflectivity appears to be a useful characteristic of the fluctuations in the scattered wavefields. Once these ‘random’ and ‘fluctuation’ attenuations are modeled, they can be isolated from the intrinsic and geometric effects. Finally, three amplitude-based methods are used to separate the effects of CO2 pressure and saturation in the Weyburn reservoir. Based on these results, an area close to an injection well within the southern part of the study area is interpreted as having the highest pressure, and the area between the northern and eastern wells show the highest CO2 saturation. Near the center of the study area, the effects of CO2 saturation and pressure appear to be the weakest.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 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".