Abstract
Abstract
ABSTRACT Fracture conductivity constitutes a pivotal parameter for assessing the efficacy of hydraulic fracturing stimulation in unconventional reservoirs. Owing to the heterogeneous distribution of proppants within the fracture, proppant placement characteristics critically govern stress transmission pathways under closure stress, thereby exerting a direct influence on both fracture width and conductivity. To address the current limitation of insufficient consideration of the effects of proppant distribution characteristics and embedment behaviour on fracture conductivity. The distribution of proppants in fractures is hypothesized to assume a hexagonal close‐packed configuration, and a dimensionless distance coefficient was incorporated to address the increased porosity in the proppant pack, arising from heterogeneous distribution relative to an ideal hexagonal close‐packed configuration, thereby enabling the development of a porosity–permeability model. By integrating the relationship between proppant embedment depth and closure stress, a fracture conductivity model accounting for proppant embedding behaviour and distribution characteristics has been developed. The proposed model was further validated through laboratory experiments, yielding results that demonstrate its capability to accurately characterize the evolution of fracture conductivity in response to closure stress. When the distribution concentration is larger than 13 kg/m 2 , increasing the proppant concentration has no effect on improving the porosity of the propped pack. Under closure stresses exceeding 20 MPa, higher proppant concentrations effectively mitigate proppant embedment‐induced degradation of fracture conductivity, thereby preserving elevated conductivity over operational timeframes.
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@article{Yang2026Study,
title = {Study on Fracture Conductivity Model Incorporating Proppant Distribution Characteristics and Embedment Behaviour},
author = {Yadong Yang and YE KAIRUI and Zou Longqing and Yongxin Che and He Bo},
journal = {Geological Journal},
year = {2026},
doi = {10.1002/gj.70382},
url = {https://doi.org/10.1002/gj.70382}
}
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