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FAST Calibration

version 2.0 (4.69 MB) by Tirom
Fast Automatic Stress Tensor Calibration for 3D geomechanical-numerical modelling

4 Downloads

Updated 04 May 2021

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The 3D geomechanical-numerical modelling aims at a continuous description of the stress state in a subsurface volume. The model is fitted to the model-independent stress data records by adaptation of the displacement boundary conditions. This process is herein referred to as model calibration. Depending on the amount of available stress data records and the complexity of the model the calibration can be a lengthy process of trial-and-error to estimate the best-fit boundary conditions.
The tool FAST Calibration (Fast Automatic Stress Tensor Calibration) is a Matlab script that facilitates and speeds up this calibration process. By using a linear regression it requires only three test model scenarios with different displacement boundary conditions to calibrate a geomechanical-numerical model on available stress data records. The differences between the modeled and observed stresses are used for the linear regression that allows to compute the displacement boundary conditions required for the best-fit estimation.
The influence of observed stress data records on the best-fit displacement boundary conditions can be weighted. Furthermore, FAST Calibration provides a cross checking of the best-fit estimate against indirect stress information that cannot be used for the calibration process, such as the observation of borehole breakouts or drilling induced fractures.

Manual available: http://doi.org/10.48440/wsm.2021.002

Cite As

Ziegler, Moritz O., and Oliver Heidbach. Matlab Script FAST Calibration V.2.0. GFZ German Research Center for Geosciences, 2021, doi:10.5880/WSM.2021.002.

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MATLAB Release Compatibility
Created with R2020a
Compatible with R2020a and later releases
Platform Compatibility
Windows macOS Linux

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To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.