An Environmentally Friendly Stimulation Fluid for High-Temperature Applications
Bibliographic record
Abstract
Summary Matrix acidizing is used in carbonate formations to create flow channels from the formation to the wellbore; in sandstone formations, however, the goal is to dissolve materials that impair well performance. However, the use of acids in deep wells has some major drawbacks, including high reaction rate and corrosion to well tubulars. We have discovered a new stimulation chemical that can be used as a replacement for or in combination with acid treatments in deep wells. A polyacid whose structure allows for acidification is described. The polyacidic chelate L-glutamic acid, N, N-diacetic acid (GLDA) is manufactured from L-glutamic acid (MSG). The chelate-based fluid very effectively dissolves CaCO3, and it is less corrosive to the equipment and easy to handle. This paper discusses the reaction of the new chelate, GLDA, with calcite and compares its performance with other available chelates, including ethylenediaminetetraacetic acid (EDTA), hydroxy-ethylethylenediaminetriacetic acid (HEDTA), nitrilotriacetic acid (NTA), and ethanoldiglycine (EDG). GLDA dissolves calcite over a wide pH interval, although it is less effective than HEDTA at pH > 5. A unique property of GLDA is its high solubility; solutions exceeding 40 wt% can be achieved at a pH of approximately 2, whereas HEDTA solubility is limited to approximately 10 wt%. A mole of GLDA with a natural pH of approximately 1.5 is capable of dissolving up to two moles of CaCO3. Throughout the pH range, GLDA appears to be as thermally stable as HEDTA. As an additive to hydrochloric acid (HCl), GLDA is as effective as HEDTA in preventing precipitation of moderate levels of Fe3+ in spent acids. At high Fe3+ concentrations, GLDA is slightly less effective than HEDTA on a molar basis; but, to deal with high Fe3+ levels, GLDA may be better because significantly higher concentrations of it are possible in various acids. In 28 wt% HCl, HEDTA has limited solubility while GLDA's solubility exceeds 40 wt%. From an environmental standpoint, GLDA is readily biodegradable and is made from a renewable raw material, monosodium glutamate. GLDA has low toxicity and aquatic toxicity characteristics. As a replacement for HCl, GLDA is significantly safer and less corrosive.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".