Stochastic fault network simulation with the FaultMod plugin: Application to a compartmentalized reservoir affected by large structural uncertainties.

Charline Julio and Guillaume Caumon and Mary Ford. ( 2014 )
in: Proc. 34th Gocad Meeting, Nancy

Abstract

Stochastic modelling of fault networks aims at generating a set of models conditioned by spatial constraints interpreted from well or seismic data. This set samples the uncertainty space related to the fault network geometry and topology. We propose to apply this stochastic approach to a highly-uncertain and complex fault network. The used dataset is composed of 13 wells and a seismic cube that poorly images the reservoir. In this paper, we discuss the two main challenges raised by the use of a stochastic approach on a real dataset: (1) the consideration of geological and conceptual knowledge, and (2) the uncertainty evaluation about the algorithm parameters and its numerical management. Within the framework of our case study, we explain how the tectonic history and the structural style can be conveyed to a stochastic fault modelling system in order to ensure the simulation of geologically-consistent 3D fault networks. Moreover, we propose strategies to evaluate the uncertainties from statistical analyses. This results in a set of structural models that can be used to describe the diversity of the possible fault network geometries and topologies.

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BibTeX Reference

@INPROCEEDINGS{Julio2GM2014,
    author = { Julio, Charline and Caumon, Guillaume and Ford, Mary },
     title = { Stochastic fault network simulation with the FaultMod plugin: Application to a compartmentalized reservoir affected by large structural uncertainties. },
 booktitle = { Proc. 34th Gocad Meeting, Nancy },
      year = { 2014 },
  abstract = { Stochastic modelling of fault networks aims at generating a set of models conditioned by spatial constraints interpreted from well or seismic data. This set samples the uncertainty space related to the fault network geometry and topology. We propose to apply this stochastic approach to a highly-uncertain and complex fault network. The used dataset is composed of 13 wells and a seismic cube that poorly images the reservoir. In this paper, we discuss the two main challenges raised by the use of a stochastic approach on a real dataset: (1) the consideration of geological and conceptual knowledge, and (2) the uncertainty evaluation about the algorithm parameters and its numerical management. Within the framework of our case study, we explain how the tectonic history and the structural style can be conveyed to a stochastic fault modelling system in order to ensure the simulation of geologically-consistent 3D fault networks. Moreover, we propose strategies to evaluate the uncertainties from statistical analyses. This results in a set of structural models that can be used to describe the diversity of the possible fault network geometries and topologies. }
}