In-Fracture Explosive Hydraulic Fracturing Fluid and Its Rheological Study
Bibliographic record
Abstract
Abstract Low permeability reservoirs take a large portion of the newly discovered hydrocarbon reservoirs. Stimulating low and ultra low permeability reservoirs faces more technical challenges. Unlike other stimulation techniques such as "well shooting", "nuclear explosion", and "high energy fracturing", the concept of in fracture explosion (IFE) is to create a fracture hydraulically, convey solid explosives deep into the fracture and place them in the fracture. Then ignite the explosives in the fracture to generate crushed zones or shear fractures near the main fracture while keeping the well bore intact. In such a way, the well productivity is increased. For complex tight gas reservoirs, especially those that tend to develop multi fractures and shear fractures by conventional hydraulic fracturing making the placement of proppant difficult, this technology has irreplaceable advantage. Fracturing fluid for in fracture explosion has two functions -to carry solid explosives while create hydraulic fractures, and to propagate ignition. This study has found such a fluid system that can meet both general requirements for hydraulic fracturing fluid and the realization of lighting, transmit fire, ignition, and propagate explosion under simulated reservoir conditions. The fluid system was tested successfully in a narrow fracture simulator. Expected explosion realized in this simulation. The simulated fracture has a length of 2300 mm with variable width of 0–50 mm. The process of squeezing, igniting, and explosion of 300g TNT equivalent was tested. This fluid system has the following properties: Rheology at reservoir temperature can be adjusted according specific requirement. Viscosity ranges from 10 to 50 mPa.s. Wall building leak off coefficient is 3.6×10−4 m/min0.5 and spurt loss is 0.25 ml/cm2. Combined with a regular fracturing fluid as a lead (pad), such properties allow the fluid to satisfy the requirements of generating deep fractures and transport/place explosives in the fractures. This paper will provide details of the study and discuss the potential applications for tight gas reservoir stimulation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".