Experimental Studies to Determine CO2 Storage Potential via Natural Adsorption in Shale Samples – A Proof-Of-Concept Study
Bibliographic record
Abstract
Abstract With an increased interest in carbon capture and storage (CCS), many current studies focus on CO2 storage sites in depleted fields and saline aquifers. While these storage sites are promising with high-capacity storage, they are sometimes uneconomical due to the extended distance from the high CO2 fields. As shales are widely distributed with reduced risk for induced seismicity relative to CO2 storage, shale formations can be an alternative to the uneconomical storage sites. To unlock the storage potential of shale formation in Malaysia, experimental studies using actual samples are required. Shale samples from the Montney Formation are used for a proof-of-concept study since Malaysian shale samples can only be obtained later from field works. Samples from the Montney Formation in Western Canada were selected because the formation is known as unconventional hydrocarbon play with multiple hydrocarbon phases. A total of five samples underwent X-ray Diffraction analysis (XRD), where the bulk minerals and clay weight percentages were determined. Later, the same set of samples was analysed using a laser particle size analyser (LPSA) for grain size determination, followed by sorption analysis via accelerated surface area and porosimetry system to find out the samples’ specific surface area, pore size distribution, and adsorption quantities. Interestingly, the results showed that the samples are dominated by quartz and plagioclase, with only traces of clay minerals. The samples are also classified as siltstones because the silt content exceeded 60 % of the total grain size distribution. Nevertheless, we were able to prove relationships between adsorption capacity with mineralogy, grain size distribution, pressure, and specific surface area at the laboratory scale. The results from the proof-of-concept study are used as preliminary inputs for numerical modelling as part of upscaling efforts. Moving forward, we will replicate the analysis using Malaysian shale samples, with additional adsorption capacity experiments at varying temperature and pressure conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".