Rapid microbial methanogenesis during CO2 storage in hydrocarbon reservoirs
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Carbon capture and storage (CCS) is a key technology to mitigate the environmental impact of carbon dioxide (CO 2 ) emissions. An understanding of the potential trapping and storage mechanisms is required to provide confidence in safe and secure CO 2 geological sequestration 1,2 . Depleted hydrocarbon reservoirs have substantial CO 2 storage potential 1 , 3 , and numerous hydrocarbon reservoirs have undergone CO 2 injection as a means of enhanced oil recovery (CO 2 -EOR), providing an opportunity to evaluate the (bio)geochemical behaviour of injected carbon. Here we present noble gas, stable isotope, clumped isotope and gene-sequencing analyses from a CO 2 -EOR project in the Olla Field (Louisiana, USA). We show that microbial methanogenesis converted as much as 13–19% of the injected CO 2 to methane (CH 4 ) and up to an additional 74% of CO 2 was dissolved in the groundwater. We calculate an in situ microbial methanogenesis rate from within a natural system of 73–109 millimoles of CH 4 per cubic metre (standard temperature and pressure) per year for the Olla Field. Similar geochemical trends in both injected and natural CO 2 fields suggest that microbial methanogenesis may be an important subsurface sink of CO 2 globally. For CO 2 sequestration sites within the environmental window for microbial methanogenesis, conversion to CH 4 should be considered in site selection.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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