Preprints
https://doi.org/10.5194/gmd-2022-22
https://doi.org/10.5194/gmd-2022-22
Submitted as: model description paper
19 May 2022
Submitted as: model description paper | 19 May 2022
Status: this preprint has been withdrawn by the authors.

DFN Generator v2.0: A new tool to model the growth of large-scale natural fracture networks using fundamental geomechanics

Michael John Welch, Mikael Lüthje, and Simon John Oldfield Michael John Welch et al.
  • Danish Hydrocarbon Research and Technology Centre, Danish Technical University, Kgs. Lyngby, 2800, Denmark

Abstract. In this paper we present a new code to build geologically realistic models of natural fracture networks in geological formations, by simulating the processes of fracture nucleation, growth and interaction, based on geomechanical principles and the geological history of the formation. This code implements the fracture modelling algorithm described in Welch et al. (2020), developed to generate more accurate, better constrained models of large fracture networks than current stochastic techniques. It can efficiently build either implicit fracture models, explicit DFNs, or both, across large (km-scale) geological structures such as folds, major faults or salt diapirs. It will thus have applications in engineering and fluid flow modelling, including CO2 sequestration and geothermal energy, as well as in understanding the controls on the evolution of fracture networks.

The code is written in C Sharp and is provided with two interfaces: a standalone interface with text file input and output, that can be compiled in standard C Sharp and can run simple models, and a plug-in interface for the Petrel geomodelling package from Schlumberger, that can run more complex models of real geological structures. The standalone version has been used to run extensive sensitivity analyses, which studied the influence of various mechanical and physical parameters (e.g. layer thickness, applied strain, Young’s Modulus, etc.) on the fracture evolution and geometry, by varying the parameters individually in simple models. The Petrel plug-in has been used to evaluate the code applicability by running simulations of actual fractured layers in outcrops and in the subsurface, and comparing the results with observed fracture patterns.

This preprint has been withdrawn.

Michael John Welch et al.

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2022-22', Anonymous Referee #1, 01 Jul 2022
  • RC2: 'Comment on gmd-2022-22', Anonymous Referee #2, 04 Jul 2022

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2022-22', Anonymous Referee #1, 01 Jul 2022
  • RC2: 'Comment on gmd-2022-22', Anonymous Referee #2, 04 Jul 2022

Michael John Welch et al.

Data sets

Test models (models used for code verification) Michael Welch https://github.com/JointFlow/DFNGenerator/tree/main/DFNGenerator_StandaloneProgram/Test_models

Model code and software

DFNGenerator Michael Welch, Mikael Lüthje https://github.com/JointFlow/DFNGenerator

Michael John Welch et al.

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This preprint has been withdrawn.

Short summary
This code can build geologically realistic models of natural fracture networks by simulating the nucleation, growth and interaction of fractures based on geomechanical principles. It uses the algorithm of Welch et al. (2020) to generate more realistic models of large fracture networks than stochastic techniques. It can build either implicit fracture models, explicit DFNs, or both, and will have applications in engineering and fluid flow modelling, as well as in understanding fracture evolution.