This series of jupyter notebooks demonstrates features of the Chevron Optimization Framework for Imaging and Inversion
.
20_marmousi_model_setup
, and used in subsequent notebooks. 00_add_packages
adds and precompiles all packages used in these demos.10_jets_basics
introduction to Jets
and DistributedJets
.20_marmousi_model_setup
download the Marmousi model.
20_marmousi_model_setup
.30_forward_modeling
static and dynamic scheduled modeling.40_sensitivity
generation of FWI sensitivity kernels, single trace and wavefield separation examples. 50_fwi
01_fwi_L2.ipynb
contains a brute force Marmousi time domain FWI example using the LBFGS
algorithm from Optim.jl
, includes upsampling and downsampling models, data analysis, illumination compensation, very simple box constraints, and nonlinear optimization using Optim.jl
. 02_fwi_L2_dynamic.ipynb
contains a "cloud native" implementation of the previous notebook on the Azure cloud.10_add_slim_packages.ipynb, 11_constrained_fwi_pqn.ipynb, 12_constrained_fwi_spg.ipynb
contain constrained FWI examples that demonstrate interoperability with Georgia Tech SLIM group's julia software. 60_rtm
brute force RTM of the Marmous FWI results, including data processing like applying a temporal mute, and image processing like a Laplacian filter to remove backscattered noise. Both static and dynamic scheduled examples are provided.