Thermal Decomposition of Chelating Agents and a New Mechanism of Formation Damage
Bibliographic record
Abstract
Abstract Chelating agents are used in the oil and gas industry mainly to: remove inorganic scales, control iron during acid treatments, and stimulate carbonate/sandstone reservoirs. The main chelating agents used in the field, include: ethylenediaminetetraacetic acid (EDTA), N-(hydroxyethyl)-ethylenediaminetriaacetic acid (HEDTA), and recently glutamic acid-N, N diacetic acid (GLDA). As with all organic acids, one of the main concerns with using these chelates is their stability at elevated temperatures. Therefore, the objectives of the present study are to: 1) assess thermal stability of various chelates, and 2) examine the effect of thermal degradation products on the permeability of carbonate and sandstone cores. We prepared solutions (0.4 to 0.6 M) of HEDTA, GLDA, EDTA, and their salts. The solutions of these chelates were heated at various temperatures up to 400°F and times (2 to 12 hrs.). The thermal stability of these chelating agents was determined by measuring the concentration of the chelates before and after heating using a titration method utilizing FeCl3 as a titrant. Mass spectrometry was used to determine the degradation products. We injected GLDA to high permeability Indiana limestone, and investigated the effect of soaking of GLDA at high temperature on the final permeability of the core. Coreflood tests were conducted at 340°F and 5 cm3/min. Chelating agents degraded at temperatures greater than 350°F. The decomposition products included: iminodiacetic acid, acetic acid, and ⍰-hydroxy acids. The addition of salt and raising pH improved the thermal stability of chelates. Thus, careful design of the chelate-based treatment fluids can prevent loss of functionality at elevated temperatures in the field, enhancing the versatility of these solutions, and minimizing formation damage due to decomposition products.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".