Chemomechanical effects of oxidizer‐ <scp> CO <sub>2</sub> </scp> systems upon hydraulically fractured unconventional source rock
Bibliographic record
Abstract
Abstract Carbon dioxide (CO 2 ) as supercritical (scCO 2 ) or foamed (CO 2 ‐Foam) fluid has been tested many times as a fracturing fluid, though it has not yet proven viable. Many challenges have been identified with scCO 2 as a fracturing fluid, including poor additive solubility, low viscosity, and limited accessibility. However, CO 2 is known to adsorb to organic matter (OM) and displace methane (i.e., enhanced coal bed methane [ECBM] operations), or to mobilize oil as in tertiary enhanced oil recovery. In this study we augment the efficacy of the kerogen control fluid (KCF) for stimulating unconventional rock formations by alternating aqueous oxidizing fracturing fluid with CO 2 injection or by combining oxidizers directly with CO 2 as a new additive. To this end, KCF‐CO 2 tests were designed to treat OM and extend the depth of permeability enhancement. We report the first attempt to combine oxidizer with CO 2 in the presence of source shale rocks at elevated temperature and pressure. Scanning electron microscopy imaging of the treated shale sample surfaces demonstrate potential porosity and permeability enhancement, though some mineral and organic deposits are also observed, which may prove to be detrimental. Meanwhile, alternating water‐based KCF with CO 2 provides a potential improvement to the KCF as predicted by early lab results on OM. The KCF‐CO 2 concept has no equivalent to date in unconventional hydraulic fracturing operations. This technology will contribute to reducing the footprint of anthropogenic CO 2 and enhancing its permanent sequestration in unconventional stimulated reservoirs, compliant with our global clean energy initiative of carbon capture, utilization, and storage.
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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 | 0.000 | 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) | 0.001 | 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".