@article{Xie2026, 
author = {Jin-Yang Xie and Bing Hou and Yong-Chun Wu and Le He and Ju-Hui Zhu and Wei Gong and Cai-Bao Wang},
title = {Competitive fracture propagation in Da’an deep shale: A study based on multi-adjacent well collaborative distributed optical fiber monitoring},
year = {2026},
journal = {Petroleum Science},
volume = {23},
number = {9},
pages = {5593-5609},
keywords = {Distributed optical fiber monitoring, Multi-cluster fracturing, Competitive fracture propagation, True tri-axial hydraulic fracturing, Da’an deep shale gas},
url = {https://www.sciopen.com/article/10.1016/j.petsci.2026.04.053},
doi = {10.1016/j.petsci.2026.04.053},
abstract = {The competitive propagation of hydraulic fractures during multi-cluster stimulations poses a critical challenge to achieving effective reservoir stimulation in deep shale formations. To address this, our study integrates true triaxial physical simulations with an innovative multi-adjacent well collaborative distributed fiber-optic monitoring strategy. Applied to the deep Longmaxi shale, this approach facilitates full three-dimensional, dynamic tracking of strain evolution, thereby elucidating the mechanisms that govern fracture competition under in-situ stress conditions. The results delineate two distinct fracture architectures dictated by the prevailing stress regime. When the maximum horizontal stress dominates, a cross-shaped network of orthogonal transverse and bedding fractures develops. Conversely, under vertical stress dominance, the combined effects of stress shadowing and geological discontinuities promote the formation of step-like main fractures alongside backward-extending inclined branches. The synchronized interpretation of distributed strain-rate signals—characterized by distinctive patterns such as asymmetric heart-shaped and V-shaped fingerprints—and pump pressure curves elucidates the dynamic process of cluster interaction. This transforms fiber-optic sensing from a monitoring tool into a quantitative diagnostic platform for competitive fracturing. The findings establish a theoretical foundation for designing three-dimensional monitoring frameworks, optimizing cluster spacing, and enabling adaptive pumping strategies, directly supporting the efficient development of deep shale gas resources.}
}