Experimental Investigation on the Evolution of Physicochemical Properties and Dissolution Mechanism of High-Siliceous Shale with Acid Treatment
Bibliographic record
Abstract
Summary The investigation of the influence of acidification conditions on the modification patterns of shale and the mechanisms of shale acidification processes is an indispensable aspect of further development within the field of shale acidizing theory. Prior research on shale acidizing has predominantly used hydrochloric acid (HCl) and carbonate-rich shale, which has restricted the scope of application for shale acidizing techniques and has not thoroughly examined the reaction kinetics of acid-rock interactions under reservoir conditions. This study focuses on siliceous shale, utilizing hydrogen fluoride (HF) in rotating disk experiments to assess the kinetic parameters of acid-rock reactions under varying acidification conditions, including duration, concentration, temperature, bedding direction, and acid flow velocity. Key influencing factors such as time, temperature, concentration, and experimental methods were selected for a comprehensive analysis, incorporating mineral composition [X-ray diffraction (XRD) and scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS)], microstructure (SEM), pore medium characteristics [mercury intrusion porosimetry (MIP) and low-temperature nitrogen adsorption (LNA)], surface morphology (3D laser scanning), and nanoindentation testing (NIT). The findings confirm the positive role of acid treatment in enhancing the permeability of shale oil and gas and in softening the reservoir rock, while also indicating potential negative impacts on hydrocarbon extraction, such as the formation of precipitated byproducts and the exfoliation of rock layers. This paper investigates the patterns of influence of HF acidizing parameters on siliceous shale and elucidates the mechanisms of action in shale acidification transformations, thereby providing a theoretical foundation for the modification of shale oil and gas reservoirs.
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How this classification was reachedexpand
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 | 0.000 |
| 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 teacher head, 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".