Simulação numérica de fraturamento hidráulico em um reservatório arenítico da Bacia Sergipe-Alagoas
Bibliographic record
Abstract
Hydraulic fracturing consists of a technique capable of stimulating oil wells that have suffered a decline in production over time, as well as allowing the production of reservoirs that have low permeability, through the creation of a network of channels in the rock, promoting the connection between the pores in the rocky environment. The hydraulically induced fracture in the formation is generally created and propagates at great depths in the reservoir rock. There are several models of fractures that have been developed until then. These models aim to get as close to the real as possible and determine the geometry that the fracture forms in the formation. Currently, some softwares have been developed and used for this type of study. This dissertation aims to numerically simulate the hydraulic fracturing applied in an arenite reservoir according to data extracted from an oil well that has suffered a decline in production over time and also to simulate hydraulic fracturing in the same reservoir with different permeabilities for serve as sensitivity data. The reservoir has a permeability equivalent to 30 mD. For sensitivity data, simulations were performed for different permeabilities, maintaining the same input data regarding the reservoir, also varying the type of propant to be added to the fracture fluid. For this, the software Stimplan-3D was used for the hydraulic fracture simulation of a real well already drilled in the Aracaju City field of the Sergipe-Alagoas Basin. With the input data a geological model of the reservoir was generated. Subsequently, a fracture of controlled form was created in the rock-sandstone reservoir. The geometry of this fracture follows the Perkins and Kern model in that the crack is long and at the same time narrow, presenting an increasing length over time with a constant height. The first simulation was performed for the case where the rock-reservoir has a permeability of 30 mD, and the fractured fluid is used as the propellant type of 30 # X-Link and Bauxite. For sensitivity data, a few more simulations were performed considering that the rock-reservoir had the following permeabilities: 1 mD, 10 mD, 20 mD and 30 mD. For these, the same type of fluid was maintained, but another type of propeller, the Ottawa Sand was used. The results showed that the fracture takes a satisfactory proportion in the rock-reservoir with good accommodation of the granular material inside the fracture for all the cases. The fracture reached a greater penetration depth in the reservoir rock for the cases where the permeability was 1 mD and 30 mD than for the permeabilities of 10 mD and 20 mD. The injection pressure behaved as expected for all simulations, initially high and subsequently suffered decline caused by the addition of certain proppant concentrations. The fracture conductivity was higher for the permeability of 1 mD and lower for the permeability of 30 mD. However, for all cases with different permeabilities, the fracture created in the rock formation, behaved according to the Perkins and Kern fracture model.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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; both teacher heads agree on what is shown here.
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".