Emulsified Chelating Agent: Evaluation of an Innovative Technique for High Temperature Stimulation Treatments
Bibliographic record
Abstract
Abstract Acid treatments in wells drilled in carbonate reservoirs aim to remove the damage, and increase the permeability in the area around the wellbore. Regular HCl used to be the main stimulation fluid; however at high temperatures, HCl causes excessive corrosion, rapid acid spending and face dissolution. For high temperature treatments, the alternatives are limited; including chelating agents, such as GLDA (glutamic acid-N,N-diacetic acid) and HEDTA (N-hydroxyethyl-ethylenediamine-triacetic acid). This paper discusses the evaluation of an innovative technique to formulate a new emulsified chelating agent that can be used for high temperature stimulation treatments. GLDA (pH = 3.8) of 38 wt% initial concentration was selected to formulate the emulsified GLDA (EGLDA). The EGLDA was formulated using a cationic emulsifier, with final GLDA concentration and volume fraction of 20 wt% and 0.7, respectively. The viscosity of the new EGLDA was measured at temperatures up to 300°F using an HPHT rheometer. The reaction of the EGLDA and limestone rock was studied using a rotating disk apparatus at temperature of 230°F. Coreflood experiments were performed using low permeability Indiana limestone core samples and emulsified GLDA at a temperature of 300°F and injection rate of 2.0 cm3/min. EGLDA is a non-Newtonian shear-thinning fluid, where the viscosity can be represented by the power-law model. The emulsified GLDA achieved a viscosity of 57.5 cp at 100 s-1 and 75°F. The EGLDA was stable up to 300°F, and the apparent viscosity at 10 s-1 shear was found to be 40 cp. The reaction rates of EGLDA with calcite were in the range of 6.2×10-8 to 1.2×10-7 gmole/cm2.s, less by 2 orders of magnitude than those of 15 wt% HCl emulsified acid formulated by 1.0 vol% emulsifier and reacted with calcite at a temperature of 230°F. The coreflood experiments performed using EGLDA and Indiana limestone cores, indicated that emulsified GLDA was able to enhance the permeability of the core by a factor of 3.7 times. From the work done, the EGLDA achieved low reaction rates with no face dissolution at high temperature, and this will results in better stimulation treatments, especially in high temperature wells.
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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".