Coupled Hydraulic Fracture and Proppant Transport Simulation
Bibliographic record
Abstract
This paper focuses on the study of proppant transport mechanisms in fractures during frac-packing operation. A multi-module, numerical proppant, reservoir and geomechanics simulator has been developed, which improves the current numerical modeling techniques for proppant transport. The modules are linked together and tailored to capture the processes and mechanisms that are significant in frac-pack operations. The proposed approach takes advantage of a robust and sophisticated numerical smeared fracture simulator and incorporates an in-house proppant transport module to calculate propped fracture dimensions and concentration distribution. In the development of software capability, the propped fracture geometry and proppant concentration, which are the output of the proppant module, are imported to the hydraulic fracture simulator through mobility modification. Complex issues of proppant transport in fractures that are addressed in the literature and captured by the current model are: hindered settling velocity (terminal velocity of proppant in the injection fluid), the effect of fracture walls, proppant concentration and inertia on settling (due to extra drag forces applied on particles, compared to single-particle motion in Stokes regime in unbounded medium), possible propped fracture porosity and also mobility change due to the presence of proppant, and fracture closure or extension during proppant injection. A sensitivity analysis is conducted using realistic parameters to provide guidelines that allow more accurate predictions of the proppant concentration and fluid flow. The main objective of this study is to link a numerical hydraulic fracture model to a proppant transport model to study the fracturing response and proppant distribution and to investigate the effect of proppant injection on fracture propagation and fracture dimensions.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".