MODELING AND RHEOLOGICAL CHARACTERIZATION OF SLUDGE BASED DRILLING OIL
Bibliographic record
Abstract
Abstract: When the drilling mud is in contact with more or less permeable walls of the well, the liquid filter part in the formation by depositing on the walls of the solid part is called the cake (silty clay film). Among the main functions of drilling fluid include keeping the walls of the well due to the hydrostatic pressure exerted by the flowing fluid. Also, the mastery of the rheological properties of the mud used is required.. The rheological characterization focus on the drilling mud used for drilling the 121/4 phase in the well AY (Hassi Messaoud) is an invert emulsion mud with oil report / water 85/15 and its density is 2.04, consisting essentially of gas oil, organophilic clay, two emulsions, sodium chloride and barite. It would define the rheological model of drilling fluid used and seek the most suitable rheological model. The rheological tests were carried out using a Fann viscometer 6-speed (3, 6, 100, 200,300 and 600 rpm) to determine the rheological properties of the mud as the yield value or yield stress, the plastic viscosity and apparent viscosity. Other rheological parameters such as the consistency index (k) and the behavior index (n) of the mud were estimated. The results show that the Herschel-Bulkley model is a minimal deviation from other models (model Bingham and Ostwald de Waele or Power).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".