Improving oil and gas flowability in tight carbonates with a novel solid delayed acid
Bibliographic record
Abstract
The economic development of tight carbonate reservoirs requires hydraulic or acid fracturing stimulation. Acid fracturing better activates natural fractures, resulting in increased stimulated reservoir volume and improving oil and gas flowability. In order to solve the problem of excessive acid-rock reaction due to high temperature, this paper screened four kinds of solid forms of acid with the maximum quantity of acid and reaction rate as the index and formed a high temperature-resistant mixed solid acid system with solid organic acid as the main part and inorganic solid acid as the auxiliary part. The maximum quantity of acid produced and effective acid concentration of the system were greater than 50%, and no residue was precipitated after the complete reaction. Dynamic acid-rock rate tests were performed on different types of retarded acid at 140 °C. The test results show that the solid acid dissolves to form a low-viscosity acid solution, and the reaction rate is one order of magnitude lower than that of gelled and cross-linked acids at the same hydrogen ion concentration, and it is little affected by temperature. Moreover, the paper compares the treatment effect of micro-proppants and solid acids on micro-fractures. The results show that the core permeability improvement multiples up to 900 times under low dissolution of solid acid and the formation of oil and gas flow channels with the same scale as micro-proppants. The experimental results demonstrated the ability of solid delayed acid to transport the fracture leading edge at high temperatures and effectively activate micro-fractures.
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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) | 0.000 | 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".