Enhancing fracture network characterization: A data-driven, outcrop-based analysis

Zhu, Weiwei; He, Xupeng; Santoso, Ryan; Lei, Gang; Patzek, Tadeusz W; Wang, Moran

doi:10.1016/j.compgeo.2022.104997

Cited by 7 publications

(3 citation statements)

References 90 publications

(112 reference statements)

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“…A water‐gas flow simulation in a discrete fracture matrix system is conducted with UNCONG (Li et al., 2015). Detailed settings of the simulation, such as the relative permeability curve in the matrix and fractures, and boundary conditions, are consistent with previous work (Zhu, He, Li, et al., 2022). The fracture permeability is five orders of magnitude larger than that of the matrix to mimic a low‐permeable formation.…”

Section: Resultssupporting

confidence: 82%

“…The key procedure to obtain the individual term is to find the T , X , and I ‐type nodes in the natural fracture outcrop, which is done by a novel pixel‐based fracture detection algorithm (Zhu, He, Santoso, et al., 2022). Intersection nodes in the outcrop map are identified and classified into different node types based on the number of branches.…”

Section: Methodsmentioning

confidence: 99%

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A Novel Connectivity Metric of Identified Multi‐Cluster Fracture Networks in Permeable Formations

Zhu,

He,

Patzek

et al. 2024

Geophysical Research Letters

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Complex natural fracture networks typically consist of multiple clusters, whose connectivity is rarely quantified. Therefore, for each identified fracture network, we propose a connectivity metric that accounts for individual fracture clusters and their interactions. This metric evaluates contributions from all fracture clusters, considering their relative sizes and interactions among the isolated clusters, which in turn depend on the hydraulic conductance of the interconnecting rock matrix. Furthermore, we investigate how the system connectivity depends on fracture sealing, alterations of central clusters, and cluster linkage. Fracture sealing strongly impacts overall fracture connectivity, with 5 percent of sealed fractures reducing connectivity by 20 percent. The connectivity reduction is small when transitioning the central cluster from the largest to the smallest one. However, the largest cluster significantly contributes to overall connectivity, while the smallest one contributes minimally. Natural fracture networks increase connectivity by linking more clusters, with heterogeneity and anisotropy playing pivotal roles.

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Section: Resultssupporting

confidence: 82%

Section: Methodsmentioning

confidence: 99%

A Novel Connectivity Metric of Identified Multi‐Cluster Fracture Networks in Permeable Formations

Zhu,

He,

Patzek

et al. 2024

Geophysical Research Letters

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“…Just as understanding superposed folding helps unravel the deformation history of a region (e.g., Ray, 1974; Ramsay & Huber, 1987), understanding superposition in fracture networks helps determine the evolution of that network. Rather than analysing the final fracture network as a single entity (e.g., Zhu et al , 2022), it is necessary to distinguish the different fracture types present and determine the sequence of development of the components of the network (e.g., Katternhorn et al , 2000; Gillespie et al , 2001), if the geometric and topological development of the network is to be understood. This involves using geometric and topological characteristics to define different classes or ages of fracture that are appropriate for the study (e.g., Peacock & Sanderson, 2018; Andrews et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Superposed fracture networks

Peacock,

Sanderson,

Magán

2023

Geol. Mag.

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The concept of superposed fracture networks consisting of different generations, and often types, of fractures that have developed sequentially is discussed. Superposed networks can consist of different types of extension or shear fractures, and each fracture may abut, cross or follow (reactivate) earlier fractures. An example of a superposed fracture network in Liassic limestones in Somerset, UK, is presented, which comprises two sets of veins and a later joint network. The veins develop as damage zones around faults, with veins of the later set crossing or trailing along the earlier set. The later joints either cross-cut the earlier veins or reactivate them, the latter being common for the thicker (more than about 5 mm) veins. The veins and joint networks have markedly different geometries and topologies. The veins are spatially clustered and are typically dominated by I-nodes, while the joints are more evenly distributed and tend to be dominated by Y-nodes. The combined network of veins and joints at Lilstock is dominated by X-nodes because so many joints cross-cut the earlier veins. Understanding the development of superposed fracture networks leads to better understanding of the kinematic, mechanical, tectonic and fluid flow history of rocks.

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Hydrogeologic and geomorphic processes in a karst landscape and seasonably-cold climate: Linking spatial distribution and morphometric dynamics of closed depressions to bedrock fractures in a wastewater spray irrigated agricultural and forest system located at the site of the Living Filter in Central Pennsylvania, United States

Daniel

Richendrfer

Falta

et al. 2023

Agricultural Water Management

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Enhancing fracture network characterization: A data-driven, outcrop-based analysis

Cited by 7 publications

References 90 publications

A Novel Connectivity Metric of Identified Multi‐Cluster Fracture Networks in Permeable Formations

A Novel Connectivity Metric of Identified Multi‐Cluster Fracture Networks in Permeable Formations

Superposed fracture networks

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