Hydraulic fracturing using liquefied hydrocarbon gases or light hydrocarbons. Technology prospects in the Russian Federation
Bibliographic record
Abstract
One of the most effective methods of development of oil and gas fields with complicated hydrocarbon production conditions is hydraulic fracturing.However, utilization of the most commonly used water-based fracturing fluids is not always expedient, for instance, in unconventional formations, reservoirs with low formation pressure containing water-sensitive minerals, low-permeable or unconsolidated rocks.American and Canadian literature indicates that the most suitable and modern frac fluid is hydrocarbon one based on liquefied petroleum gas or light hydrocarbons.The use of such fluids in the fields of the Russian Federation is perspective.The main reason to face the new technology is the presence of one of the most promising production targets in Russia -the Bazhenov formation.It is nowadays one of the most desirable objects, and at the same time one of the most difficult to be developed.Enormous reserves of oil in this formation suggest its desirability.The government has for a long time stimulated exploitation of these deposits by introducing a tax credit.Today, there is no universal approach to the development of this target.A new advanced integrated approach will address this problem and pave the way for the development of this rich source of hydrocarbons containing million tons of oil.Another promising task for the implementation of this technology may be the use of associated petroleum gas, which according to the Russian regulations must be disposed of, but the technologies currently in use in Russia do not allow this to be done sufficiently.When developing the proposed technology, it is planned to start with the use of liquefied petroleum gas (propane-butane mixture) as the main hydraulic fracturing fluid and switch to petroleum gas as the technology develops.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".