Framework of Fracture Network Modeling using Conditioned Data with Sequential Gaussian Simulation

Yerlan Amanbek, Timur Merembayev, Sanjay Srinivasan

Research output: Contribution to journalArticlepeer-review

Abstract

The fracture characterization using a geostatistical tool with conditioning data is a computationally efficient tool for subsurface flow and transport applications. The main objective of the paper is to propose a framework of the geostatistical methods to model the fracture network. In the method, we have chosen a neighborhood area to apply the Gaussian Sequential Simulation in order to generate the fracture network in the unknown region. The angle was propagated from the seed where the neighborhood data guide direction. The Poisson procedure is used to distribute initial seeds. The method is applied for geological faults from Central Kazakhstan and for field data from Scotland, UK. The simulation results are compatible with the original fracture network in the flow and transport modeling setting. From the research that has been carried out, it is possible to conclude that the numerical simulation of fracture network is a valuable tool in subsurface flow and transport applications.
Original languageEnglish
Pages (from-to)219
Number of pages15
JournalArabian Journal of Geosciences
DOIs
Publication statusPublished - Mar 3 2023

Keywords

  • fracture network model
  • sequential Gaussian simulation
  • geostatistical method

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