Permanent Seismic Reservoir Monitoring for Real-time Surveillance of Thermal EOR at Peace River
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Summary Permanent seismic reservoir monitoring (PSRM) solutions, if of high enough sensitivity and low enough cost, can be used to tackle the many known problems faced by seismic monitoring onshore and thereby increase the profitability of such developments. Here we focus on thermal EOR monitoring using continuous seismic, as provided by SeisMovie®, a registered trademark of CGG. We review the PSRM staircase that Shell has climbed since 2009, introduce the most areally extensive deployment at Peace River in Alberta, Canada, and discuss some of the initial findings and plans ahead. We show progress with PSRM to generate better onshore data that will lead to higher recovery, higher production, and safer and cleaner operations. Significant steps were made towards on-demand, lower footprint PSRM, and next steps are set towards cheaper, non-intrusive automated systems that are required for broad application.
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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 | 0.001 | 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 | 0.000 | 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) | 0.000 | 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 it