Evaluation of produced water quality by using water quality indices in Heglig area, Sudan
Bibliographic record
Abstract
Abstract The rate of produced water production of oilfields increases as oilfields age. This study aims to evaluate water quality of produced water from oilfields in the Heglig area using various water quality evaluation indices and study the significance of evaporation for cumulative pollutants after bioremediation in Heglig oilfield. Produced water samples were collected and analyzed for three locations in Heglig and Neem oilfields in order to determine the physicochemical, radioactivity, and heavy metal variables. The data obtained were used to determine the heavy metal pollution index, heavy metal evaluation index, weighted arithmetic water quality index, and Canadian water quality index (CCME WQI). The study revealed very poor water quality and high heavy metals at Neem oilfield. In addition, produced water quality at Heglig oilfield before the bioremediation was very poor and after the bioremediation was found to be poor, also the heavy metals were low before the bioremediation and medium after the bioremediation. Low levels of chemical oxygen demand (COD) oil in water, and total suspended solids (TSS) are mainly responsible for improvement of water quality after the bioremediation. Variation in the heavy metals before and after the bioremediation was a result of cumulative effect in the evaporation ponds.
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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 | 0.022 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".