Regional Assessment of Suitability of Organic-Rich Gas Shales for Carbon Sequestration
Bibliographic record
Abstract
Abstract In gas shales, natural gas occurs both as free gas in intergranular and fracture porosity and as an adsorbed phase onto the surfaces of clays and organic matter, analogous to natural gas storage in coalbeds. The adsorption capacity of shales from Kentucky, Indiana, and West Virginia was estimated using drill cuttings and sidewall cores to determine both CO 2and CH 4adsorption isotherms. Elemental capture spectroscopy logs were analyzed to investigate possible correlations between adsorption capacity and mineralogy. The maturity of the shale was characterized using average random vitrinite reflectance data yielding values ranging from 0.78 to 1.59 (upper oil to wet gas and condensate hydrocarbon maturity values). Total organic carbon (TOC) content ranges from 0.69 to 14%. Calculated CO 2adsorption capacities at 2.75 MPa range from a low of 0.4 m 3/t (14.1 ft 3/t) to more than 4.2 m 3/t (148.3 ft 3/t). A direct linear correlation between measured TOC and the adsorption capacity of the shale has been determined; CO 2adsorption capacity increases with increasing TOC. Data also suggest that CO 2is preferentially adsorbed (5.3:1) and would displace CH 4, leading to a potential method for enhancing natural gas recovery in gas shales. Initial estimates of the volume of CO 2sequesterable in the shale based on these data indicate a capacity of as much as 25 billion t in the deeper and thicker parts of the Devonian shales across Kentucky. Discounting the uncertainties in reservoir volume and injection efficiency, these results indicate that gas shales could provide a potentially large geologic sink for CO 2. Moreover, the extensive occurrence of gas shales in Paleozoic and Mesozoic basins across North America makes them an attractive regional target for economic CO 2storage and enhanced natural gas production.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".