New Environmentally Friendly Oil-Based Stimulation Fluids
Bibliographic record
Abstract
Abstract The lab and field development of an environmentally friendly liquid diesel substitute-based (DiSub) system for completion and stimulation, with properties similar to or exceeding those achieved with diesel, will be discussed. The chemical evolution of the DiSub system and properties of the fluid including rheology, break and conductivity testing, and toxicity data will be presented. The application of the system in a field situation is described. Since the inception of hydraulic fracturing, oil-based fracturing and completion fluids have been used. Motivations for using these systems include: formation sensitivity to water; water retention by the formation, such as water blocks; and the inability of low-pressure oil productive formations to unload water. Oil-based fracturing designs have historically required complicated procedures to successfully execute a fracturing operation. Fluid compositions used did not consistently produce stimulation fluids with optimum viscosity or transport properties. Drilling and completion activities in the North Sea, deepwater Gulf of Mexico, Alaska, and Canada provided the impetus to develop innovative environmentally-friendly completion techniques and chemistries. The DiSub system provides a cost effective and environmentally-friendly stimulation fluid. The system is within most global environmental standards and has been approved and used in the North Sea due to its excellent properties, like zero aromatic content, low aquatic toxicity and excellent biodegradability. This makes it a major improvement over the use of diesel and mineral oils, for both humans and the environment. Exposure hazards and the variability of the previously used diesel and/or lease crude are eliminated.
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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".