Assessment of the Limitations on the Seismic Detectability of Injected CO2 within a Deep Geological Reservoir
Bibliographic record
Abstract
Aquistore is a deep saline CO2 storage research and demonstration project located near Estevan, Saskatchewan where CO2 is transported via pipeline and injected into a sandstone reservoir ∼3200 m below the surface. A pre-injection time-lapse analysis performed on two sparse 3D seismic datasets was used to characterise the background time-lapse signal-to-noise level at the storage site. The time-lapse analysis revealed that the lowest global nRMS was 0.07 which was taken to represent the level above which CO2 would be detectable in the reservoir. We investigate the conditions under which the injected CO2 can be detected above the defined minimum noise level through Gassmann fluid substitution and 3D seismic forward modelling. Additionally, Wave Unix was used to simulate the seismic response of the reservoir due to the injected CO2 by generating the synthetic surface reflection seismic data from an explosive surface P-wave source. We generated noise-free synthetic seismograms for the baseline model as well as for the 2-phase fluid replacement of brine with CO2 for CO2 concentrations up to 100% within the target zone – the monitors. The baseline and monitor traces from the 3D seismic survey at Aquistore are used as the noise traces in this study, and were added to their respective baseline and monitor synthetic traces. The nRMS within the reservoir was then computed for the noisy baseline and various noisy monitor surveys and was used in the assessment of the limitation to the detection of the injected CO2 in the reservoir under the background noise level at the site. We are able to conclude that the time-lapse repeatability will not limit the ability to monitor the CO2 induced changes in the reservoir at the Aquistore storage site.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".