Multi-constraint dynamic fusion characterization of CT images of fracture networks in hydrate reservoir cores

Abstract

Fracture networks are the primary fluid migration conduits in geological reservoirs. Their spatial connectivity, geometric morphology, and dynamic evolution patterns directly influence the concentration of resources such as natural gas hydrates. Traditional core analysis techniques are unable to accurately characterize the three-dimensional topological structure of fractures, leading to significant deviations in the predictions of fundamental physical reservoir parameters. This study addresses the challenge of identifying fractures and reconstructing their connections in X-ray computed tomography (CT) images of natural gas hydrate reservoir cores. Based on interactive processing modules and morphological operation mechanisms, the top-hat transformation method is introduced to extract microfractures in the core, thereby avoiding local detail masking by global thresholds. A multi-constraint dynamic fusion method for characterizing fracture connections is proposed. Principal component analysis (PCA) is used to extract fracture direction features, which are then combined with geometric collinearity verification and spatial proximity screening to effectively identify connections in damaged fracture networks. Based on this fracture network optimization, numerical simulation was used to obtain the absolute permeability parameters of the rock core. This method can effectively address the difficulty caused by CT image noise and insufficient resolution in identifying microfractures, making the extracted core fracture network’s geometric topology characteristics more closely resemble the actual reservoir. This provides microscopic data support for natural gas hydrate reservoir flow and stability assessments. The research findings are important for promoting the exploration and development of natural gas hydrates.

Keywords

Natural gas hydrate / Fracture network / Top-hat transformation / Fracture connection / Absolute permeability

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Funding

National Natural Science Foundation of China(42476231)

Marine Geological Survey Program(DD20221704)

RIGHTS & PERMISSIONS

The Author(s)