Solidification/Stabilization Treatment for organic oil immobilization in Algerian Petroleum Drill Cuttings: Optimization and Acceptance Tests for Landfilling
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Bibliographic record
Abstract
Hassi Messaoud oil field is one of the most important fields in Algeria and the world, because it covers an important quantity of total Crude Oil Production in Algeria. Furthermore, two-thirds of this oil field is underexplored or not explored. Therefore, the drilling process of petroleum wells in this field is a continuous process that results in significant drilling waste. This implies that enormous noxious quantities of drilling waste are produced daily that require treatment via solidification/stabilization (S/S) process before being landfilled. These types of wastes have pollution concentration that significantly exceeds the safety standards. In this study, we focus on the factors affecting the solidification/stabilization treatment of the drill cuttings obtained from Hassi Messaoud oil field and the process optimization. The solidification/stabilization is performed using the cement as binder, and sand, silicate, organophilic clay and activated carbon as additives.The study has been divided into two steps: (i) Determining the optimum ratio of each element used in the S/S process for the organic element (hydrocarbon) elimination, (ii) Combining the optimum ratios found in the previous step to determine the optimal mixture. The obtained results in the first step showed that the optimum ratio for the cement-to-drill cuttings mass ratio is 0.09:1. For the additives-to-drill cuttings mass ratios are 0.04:1, 0.006:1, 0.013:1 and 0.013:1 for the sand, sodium silicate, organophilic clay and activated carbon, respectively. An optimum formula is found whose main finding shows that the hydrocarbon content of our sample is dropped from 9.40 to 1.999%. Many tests’ results such as matrix permeability, resistance to free compression and heavy metals rate before and after S/S process were investigated before landfilling. Besides that, in the light of outcomes achieved by this assessment, these harmful cuttings can be converted into a useful product that helps in reducing the environmental foot prints.
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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 it