PREDICT: PeRmEability DIstributions of Clay-smeared faulTs [Github]

Computes upscaled fault permeability distributions using a parameter-based, probabilistic description of clay and sand smears. Written in MATLAB.

Generates multiple realizations of the fault core materials in shallow (depth < ~3km), poorly-lithified siliciclastic sequences, using a high-resolution grid (fine grid). The computation of fault permeability is performed in a given throw window, and the code can be run in 2D or 3D.

Outputs the directional components of the fault permeability tensor (dip-normal, kxx; strike-parallel, kyy; and dip-parallel, kzz) in an upscaling (coarse) grid defined by the user (3D version). For example, this flexibility is useful to assign fault permeability in subsequent flow simulation models.

The fault permeability is obtained via flow-based upscaling of the fine grid permeability. PREDICT uses MRST to perform permeability upscaling (finite volume method)

Incorporates uncertainty in the geological variables that control the fault material distribution and their properties. Therefore, the output permeability is given as a set of probability distributions.

Mostly vectorized where possible and can be run in parallel using MATLAB's parfor, so it is fast and scales well with the number of computing cores available.

Convergence of output probability distributions vs number of realizations performed, for five different example sequences (A to E). N = 1000 realizations are enough.

Computing times for an example sequence vs cores available

Example of output probability distributions of fault permeability for each directional component, and their correlation.