Initial 4D seismic results after CO<sub>2</sub> injection start-up at the Aquistore storage site
Bibliographic record
Abstract
The first post-[Formula: see text]-injection 3D time-lapse seismic survey was conducted at the Aquistore [Formula: see text] storage site in February 2016 using the same permanent array of buried geophones used for acquisition of three previous pre-[Formula: see text]-injection surveys from March 2012 to November 2013. By February 2016, 36 kilotons of [Formula: see text] have been injected within the reservoir between 3170 and 3370 m depth. We have developed time-lapse results from analysis of the first post-[Formula: see text]-injection data and three pre-[Formula: see text]-injection data sets. The objective of our analysis was to evaluate the ability of the permanent array to detect the injected [Formula: see text]. A “4D-friendly simultaneous” processing flow was applied to the data in an effort to maximize the repeatability between the pre- and post-[Formula: see text]-injection volumes while optimizing the final subsurface image including the reservoir. Excellent repeatability was achieved among all surveys with global normalized root-mean-square (G nrms) values of 1.13–1.19 for the raw prestack data relative to the baseline data, which decreased during processing to G nrms values of approximately 0.10 for the final crossequalized migrated data volumes. A zone of high normalized root-mean-square ( nrms) values (0.11–0.25 as compared with background values of 0.05–0.10) is identified within the upper Deadwood unit of the storage reservoir, which likely corresponds to approximately 18 kilotons of [Formula: see text]. No significant nrms anomalies are observed within the other reservoir units due to a combination of reduced seismic sensitivity, higher background nrms values, and/or small quantities of [Formula: see text] residing within these zones.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 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".