When Should We Use Chelating Agents in Carbonate Stimulation?
Bibliographic record
Abstract
Abstract Carbonate reservoir stimulation has been carried out for years using HCl-based fluids. High HCl concentrations should not be used when the well completion has Cr-based alloy in which the protective layer is chrome oxide, which is soluble in HCl. HCl or its based fluids are not recommended either in shallow reservoirs where the fracture pressure is low (face dissolution) or in deep reservoirs where it will cause severe corrosion problems. Different chelating agents have been proposed to be used as alternatives to HCl in the cases that HCl cannot be used. Chelating agents such as HEDTA (hydroxyethylenediaminetriaceticacid), and GLDA (L-glutamic acid −N, N-diacetic acid) have been used to stimulate carbonate cores. The benefits of chelating agents over HCl are the low reaction and corrosion rates. In this study, the effect of core length on the volume required to create wormhole was investigated using Indiana limestone cores of an average permeability 3 md and core lengths from 1 to 20 in. Chelating agents were tested at pH value of 4 and a concentration of 0.6M and their performance was compared with that of 15 wt% HCl. Experimental results showed that the volume of HCl required to create wormholes increased when core length was 20 in. This effect was different from that noted when chelating agent were used. Increasing the core length for chelating agents decreased the volume required to create wormholes in the carbonate cores at the same conditions. This is because of the increased contact time by increasing the core length. Chelating agents can be used to stimulate shallow reservoirs where HCl causes face dissolution. They can be used in deep reservoirs where HCl can cause severe corrosion to well tubulars.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".