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

Autor: Welch, Michael J., Lüthje, Mikael, Oldfield, Simon J.
Předmět:
Zdroj: Geoscientific Model Development Discussions; 5/19/2022, p1-42, 42p
Abstrakt: 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. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index