Timelapse DAS VSP Viscoelastic FWI for CO2 Monitoring
Bibliographic record
Abstract
Summary Changes in reservoir properties resulting from the CO2 injection and migration can be monitored using time-lapse seismic data. Conventional analysis gives only qualitative information about the changes of the acoustic impedance contrasts in the reservoir. In order to differentiate the pore-pressure from CO2 saturation effects, it is necessary to evaluate the changes in the elastic properties. Borehole seismic data contain strong converted shear waves at the level of the reservoir that will allow determining S-velocity changes. FWI is an appropriate method to estimate elastic parameters. As CO2 saturation increases in the reservoir, P-waves undergo strong attenuation. Hence, it is necessary to estimate as well the bulk modulus Q-factor Q k . We demonstrate the feasibility of timelapse multi-Offset DAS VSP inversion for CO2 sequestration monitoring, by inverting synthetic seismic data based on a virtual CO2 injection site study. The timelapse FWI recovers P-wave and S-wave velocities for the baseline model; and, the perturbations of the velocity models associated to 3 years of CO2 injection are also well recovered for a distance of a few hundreds of meters from the well. The bulk modulus Q-factor Q k is not well recovered but it is needed for the correct estimation of the velocity models.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".