Boosting Reaction Rate of Acids for Better Stimulation of Dolomite-Rich Formations
Bibliographic record
Abstract
Abstract Carbonate formations are often stimulated using acid systems to enhance production rates. The reaction rate between acid and dolomite is known to be much slower than that between acid and calcite. Accordingly, for some acid fracturing treatments in dolomitic formations, it has been observed that the injected acid system could not adequately react with the rock to render desirable etching patterns on the fracture faces. This can be a direct result of the slow reactivity between dolomite-rich formations and acids. Developing an acidizing fluid that can accelerate the dissolution of dolomite will be beneficial to maximize the results of stimulation treatments in dolomite-rich formations. In the current study, advancements were made toward accelerating the reaction rate of dolomite with acids through an additive-driven chemical approach based on careful surfactant selection. Static dissolution testing of dolomite core samples in the presence of 28 wt% hydrochloric acid (HCl), both with and without additives, were performed at ambient conditions. The weight loss was calculated, and the efficiency of the added chemicals was evaluated to select the formulation for evaluation at reservoir conditions. A comprehensive reaction kinetics study was performed at a pressure of 3000 psi, across a temperature range of 175 to 350 °F. Guelph Dolomite samples were cut into 1.5" diameter by 0.5" thick disks. Powder X-Ray diffraction (PXRD) was used to determine the mineralogy and purity of the dolomite core samples. The ion concentrations in the effluent samples during the dissolution was measured by ICP in the effluent samples. Several acid/surfactant formulations were screened and characterized in the current work where several suitable surfactants were identified. It was found that the rate of dissolution of dolomite rocks in hydrochloric acids (28 wt%) could be increased by up to 30%. These results are consistent with the kinetics data collected at both 200 and 300 °F, where the rotating disk apparatus (RDA) showed that the reaction rate of dolomite with one of the developed formulations can be improved by 30 to 50% over hydrochloric acid alone. The acid/surfactant formulations developed in the current study are aqueous-based formulations. There were no incompatibilities observed after the fluid preparation. The developed acid systems showed an improvement in the dolomite and acid reaction rate which paved the road to apply these formulations in the field to improve the outcome of acid fracturing treatments.
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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".