Effects of Fracture Properties on Numerical Simulation of a Naturally Fractured Reservoir
Bibliographic record
Abstract
Abstract Effects of Some of the fracture properties on numerical simulation of fractured reservoirs are usually not taken into consideration. Two important fracture properties, which are used in simulation, are fracture capillary pressure and fracture relative permeabilities. Engineers usually assume the first one to be zero and the second one to be a straight line without paying attention to their significant role in the simulation of fractured reservoirs. In addition, effects on these parameters on the behavior of fractured reservoir model when Dual Porosity Dual Permeability (DSDP) concept is used are not investigated yet. The present study investigates the effects of above mentioned properties through other fracture properties like fracture permeability and matrix- fracture transfer coefficient(shape factor) to analyze completely effects of the whole fracture characteristics on numerical simulation of a reservoir. The oil field under study is a highly fractured carbonate reservoir located in Southwest of Iran. This paper indicates when straight-line fracture relative permeabilities and zero fracture capillary pressure can be used in the simulation. Effect of reservoir heterogeneity was investigated on numerical simulation too. Sensitivity analysis also has been done to clearly indicate the behavior of the DSDP model by assuming /nonassuming zero fracture capillary pressure and straight line fracture relative permeabilities. Sensitivity analysis was done in three main production scenarios: natural depletion, water injection, gas injection. This sensitivity study will also show the magnitude of the error which simulation engineers are making if they use straight-line relative permeabilities and zero capillary pressure in the fractures.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".