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November 1, 2025Water Resources ResearchOpen Access

Post‐Constrained Conditional Sedimentary Facies Simulation From a Single Training Image Using a Concurrent Multi‐Stage Generative Adversarial Network

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Authors

CZCe ZhangGLGang LiuQCQiyu Chen

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Overview

This analysis demonstrates that a novel conditional simulation method improves geological consistency in sparse data scenarios, highlighting natural resource optimization.

Key Points

  • The CMS‐PCSinGAN approach maintains diversity in generated models, enabling effective sedimentary facies characterization while utilizing limited data.
  • Results show improved geological consistency and applicability when compared to traditional conditional generative adversarial networks for modeling sedimentary facies.
  • Assessment through variogram analysis confirmed that the proposed method meets conditional requirements without sacrificing quality or richness of results.
  • This technique highlights the potential for enhanced efficiency in the development of natural resources using advanced simulation methods.

Cite This Study

Zhang et al. (2025) studied this question.

synapsesocial.com/papers/69254371c0ce034ddc3587dchttps://doi.org/10.1029/2025wr040582
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