Experimental Study on Solid Acid Systems for Acid Fracturing in Ultrahigh-Temperature Carbonate Reservoirs
Bibliographic record
Abstract
Acid fracturing is a key stimulation technique for carbonate reservoirs. However, current retarded acid systems face significant challenges in ultrahigh-temperature environments, such as overly rapid acid-rock reactions, poor postacidizing fracture conductivity, and severe tubing corrosion. To overcome these limitations, this study proposes a novel acidizing fluid system based on solid acids. A systematic evaluation of different solid acid types and combinations was conducted to determine the optimal formulation. A series of laboratory experiments, including dissolution testing, acid-rock reaction kinetics, etching characterization, and conductivity measurements, were performed to identify the optimal solid acid system for ultrahigh-temperature carbonate reservoirs. Twenty candidate solid acid formulations were evaluated at 453 K. Among them, EDTA, DTPA, and DTPA + HCl were identified as the most promising, demonstrating a high dissolution efficiency and minimal chelate formation. Kinetic tests further confirmed their slower reaction rates with carbonate rocks at elevated temperatures, indicating a strong retardation performance. Additionally, the optimized solid acid systems demonstrated effective fracture etching and superior conductivity at 453 K compared with conventional retarded acids. EDTA, DTPA, and DTPA + HCl exhibited high dissolution capacity, reduced reaction rates, and improved fracture conductivity, confirming their suitability for acid fracturing in ultrahigh-temperature carbonate reservoirs. The optimized solid acid system offers substantial potential for field application.
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) | 0.000 | 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".