Long Term Conductivity of Narrow Fractures Filled with a Proppant Monolayer in Shale Gas Reservoirs
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Bibliographic record
Abstract
The primary goal of hydraulic fracturing is to create a high conductive pathway. Gas shale is mainly fractured by slick-water. A complex network of narrow secondary fractures is created in slick water fracturing. These narrow fractures without proppants maintain low conductivity. A partial monolayer of proppant can be used to enhance the conductivity of these fractures and then improve the production. Due to the interaction between proppants and fracture surface under confining stress, the proppants will embed into the formations, which results in a decrease in fracture width and conductivity. Researches available in literature have addressed the problem. However, the shale reveals varying amounts of creep deformation in response to applied stress, which will continuously enhance the proppant embedment and reduce fracture width. The influence of this time dependent effect on the long-term conductivity of partial monolayer proppant is not well understood. The study of the characteristics and controlling factors of the long-term change in conductivity can benefit to the production analysis and hydraulic fracturing optimization. Therefore, models combining numerical and analytical methods are developed in this paper. A finite element model is developed to simulate the long-term change in fracture width. Then a simplified model based on Carman-Kozeny equation is used to calculate the long-term conductivity. Simulation results show that after considering long term creep effects, there is still an optimal proppant concentration, which remains the maximum residual conductivity after proppant embedment. The simulation results also indicate that the optimal concentration depends on stress, rock mechanical properties, proppant mechanical properties and time.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it