Thermal Stability of Oilfield Aminopolycarboxylic Acids/Salts
Bibliographic record
Abstract
Summary Chelating agents are used to remove various inorganic scales, including sulfates and carbonates. They are also used as standalone stimulation fluids and as iron-control agents during acidizing treatments. The main chelating agents used in the oil field include ethylenediaminetetraacetic acid (EDTA), nitrilotriacetic acid (NTA), N-(hydroxyethyl)-ethylenediaminetriacetic acid (HEDTA), and glutamic acid diacetic acid (GLDA). (Note that the abbreviations for these chelating agents will be used throughout the rest of the paper.) One of the concerns with these chelants is their thermal stability at elevated temperatures. Chelant solutions (0.7 to 0.8 M) of HEDTA, GLDA, NTA, EDTA, and their mono-/disalts were prepared. The aqueous solutions of these chelants were heated at various temperatures (300 to 400°F) and times (2 to 12 hours). The concentration of chelant was measured with a titration method that uses FeCl3 solutions. The products of thermal decomposition of chelants were determined with mass spectrometry (MS) and gas-chromatography/MS techniques. Most chelants decomposed at temperatures greater than 350°F. At 400°F and after 12 hours of heating, diammonium salt of GLDA degraded more quickly than diammonium salt of EDTA chelant. Analyses of NH4H3GLDA with MS techniques after heating highlighted that the decomposition products included iminodiacetic acid, hydroxyacetic acid, and α-hydroxyglutaric acid. Studying the kinetics of aqueous solutions of NaH3GLDA, NaH2HEDTA, and (NH4)2H2EDTA showed that their thermal-degradation kinetics followed a pseudofirst-order reaction. The Arrhenius equation can be used to predict the activation energy that is necessary for the degradation mechanisms of chelants.
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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) | 0.002 | 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".