The Application of Face Direction Perforating in Unconventional Reservoirs
Bibliographic record
Abstract
Abstract The types of reservoirs are more and more complex with the deepening of the exploration and development, and it comes up with a new challenge for perforation completion technology. A new perforating technology is urgent to match up with the reservoirs to improve oil and gas well productivity or create channel conditions for well stimulation, and it is a new requirement to the emergence of unconventional reservoirs. As the middle part of this kind of reservoir development, perforation must be to create a better channel condition for well stimulation, to reduce the rock fracture pressure, induce fracture extension direction, and perfect reservoirs fracture network system. Face direction perforating adopt extra large perforation diameter bullet and special hole arrangement, multi-holes are formed in the same cross section which is perpendicular to the axial of the casing, it can form stress concentration along the wellbore's cross direction, and can effectively control the trend of the fracture, reduce formation fracture pressure, avoid cross collusion of fractures between different segments, and improve the perfect degree of fracture network system. The casing damage research and parameter matching optimizing between casing and face direction perforating are completed by establishing casing damage mathematical model of face direction perforating under different working conditions, the initiation and extend direction of hydraulic fracture after face direction perforating was studied as well, and then it is implemented in the field. Test showed that face direction perforating can reduce formation fracture pressure by 15% or more, oil production increased more than 20% after hydraulic fracture compare with conventional perforating and fracture.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".