Laboratory Study of the Heavy Weight Reversible Invert Emulsion Drilling Fluid
Bibliographic record
Abstract
A novel reversible invert emulsion drilling fluid which is useful in resolving the contradiction between drilling efficiency, cementing and environmental effect has been invented based on the protonation reversibility of amine. The new drilling fluid has reversible emulsion-phase behavior. The formulation of the reversible invert emulsion drilling fluid was: white oil (5)+25% CaCl 2 brine+50% weight agent ZFU-3+1.5% organoclay+0.5% lime +4.5% reversible emulsifier UPSG-1+1% wetting agent DYSL-3+an appropriate amount barite, oleaginous fluid to non-oleaginous fluid-ratio was 50/50, drilling fluid density was 1.9 kg/L, weight agent ZFU is sodium formate. Comprehensive performance evaluation with laboratory test showed that the new drilling fluid could be readily and reversibly converted from a water-in-oil emulsion to an oil-in water emulsion and back to a water-in-oil emulsion using an acid-based chemical switch. And before and after converting the emulsion mud maintains good performance, with emulsion-breaking voltage of 900-1,100 V, resistance to temperature of 150℃, HEHP filter loss of less than 6 ml. Additionally, the filter cake and oily cuttings could be treated easily. This suggests that the reversible invert emulsion drilling fluid has both merits of oil-based fluid and water –based fluids, and all properties are excellent. The reversible invert emulsion drilling fluid is capable of resolving the problems with the application of conventional oil-based drilling fluid. The density of the reversible invert emulsion is 1.9 kg/L, which is also better than the traditional reversible invert emulsion drilling fluid.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".