Novel Environmentally Friendly Fluids to Remove Carbonate Minerals from Deep Sandstone Formations
Bibliographic record
Abstract
Abstract Carbonate minerals are present in sandstone formations. These minerals are either introduced to the formation during drilling/completion operations or naturally present in the rock. There is a need to remove these carbonates to enhance well performance. This especially true if there is a need to use HF-based fluids to prevent the precipitation of calcium and magnesium fluorides. In this study, we introduced GLDA (L-glutamic acid-N,N-diaceticacid) a new environmentally friendly chelate to remove carbonate minerals from sandstone formations. We also compared its performance with available chelates like EDTA (ethylenediaminetetraaceticacid) and HEDTA (hydroxyethylenediaminetriaceticacid). Berea (5 wt% clays) and Bandera (11 wt% clays) sandstone cores were used in the coreflood experiments. The concentration of the chelates used was 0.6M at pH values of 11 and 4. The coreflood experiments were run at a flow rate of 5 cm3/min and 300°F. Coreflood experiments showed that at high pH values (pH =11) GLDA, HEDTA, and EDTA were almost the same in increasing the permeability of both Berea and Bandera sandstone cores. GLDA, HEDTA, and EDTA were compatible with Bandera sandstone cores. The weight loss from the core was highest in case of HEDTA and lowest in case of GLDA at pH 11. At pH 4, 0.6M-GLDA performed better than 0.6M HEDTA in the coreflood experiments. The permeability ratio (final/initial) for Bandera sandstone cores was 2 in the case of GLDA and 1.2 in the case of HEDTA at pH of 4, and 300°F. At pH 11, HEDTA, EDTA, and GLDA almost were the same in enhancing the permeability of the Bandera sandstone cores. At pH value of 4, GLDA gave the best results in Berea and Bandera sandstone cores.
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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) | 0.000 | 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 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".