Experimental Investigation of Possibility of Replacing Oil-Based Muds with Environmentally Friendly Water-Based Glycol Muds in Maroon Oil Field
Bibliographic record
Abstract
Abstract Oil-based muds have been used widely in Iranian oil fields to drill pay zones and shaly formations. However, their applications have become more restricted because of high initial cost and prices of handling. The other important aspect is the environmental concerns that become more stringent in Iran. Therefore, an environmental friendly mud replacement having a good performance has become Iranian oil companies' demand. Water-based glycol muds seem to be good alternatives for oil-based muds. These environmental friendly muds can inhibit shaly formations, lubricate drill stem, clean the hole, and deposit a thin and impermeable filter cake which reduce the risk of differential pipe sticking and damage, respectively. Moreover, initial and handling expenses are reduced, and these lead to the reduction in the overall costs of drilling the well. In this study, rheological property of the water-based glycol mud was assessed and compared with the oil-based one. Cutting integrity test was performed in order to evaluate the performance of shale inhibition. This test was conducted on bottom hole samples of Kazhdumi, Daryan, and Asmari, three different problematic shaly formations of Maroon oil field. Formation damage caused by water-based glycol and oil- based muds was measured and compared. It was found that the water-based mud has a comparable rheological property with respect to oil-based mud. The cuttings recovery percentage was within the excellent range. Formation damage caused by water- based glycol mud was more than oil-based mud. The results show that this mud system is a very good alternative to oil-based muds in Iranian oil fields.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".