Open source software for simulations and inversions of airborne electromagnetic data

Lindsey J. Heagy, Seogi Kang, Rowan Cockett and Douglas W. Oldenburg

Inversions of airborne EM data are often an iterative process, not only requiring that the researcher be able to explore the impact of changing components such as the choice of regularization functional or model parameterization, but also often requiring that forward simulations be run and fields and fluxes visualized in order to build an understanding of the physical processes governing what we observe in the data. In the hope of facilitating this exploration and promoting reproducibility of geophysical simulations and inversions, we have developed the open source software package, SimPEG. The software has been designed to be modular and extensible with the goal of allowing researchers to interrogate all of the components and to facilitate the exploration of new inversion strategies. We present an overview of the software in its application to airborne EM and demonstrate its use for visualizing fields and fluxes in a forward simulation as well as its flexibility in formulating and solving the inverse problem. We invert a line of airborne TDEM data over a conductive vertical plate using a 1D voxel-inversion, a 2D voxel inversion and a parametric inversion, where all of the forward modelling is done on a 3D grid. The results in this paper can be reproduced by using the provided Jupyter notebooks. The Python software can also be modified to allow users to experiment with parameters and explore the physics of the electromagnetics and intricacies of inversion.

Presented at the 2018 conference on Airborne Electromagnetics (http://www.conferencemanager.dk/AEM2018). The abstract and notebooks used to generate the examples are available at: https://github.com/simpeg-research/heagy-2018-AEM/blob/master/Heagy_etal_2018_aem_workshop.pdf

Transcript

1. Open source software for simulations and inversions of airborne electromagnetic data Lindsey Heagy, Seogi Kang, Rowan Cockett, Doug Oldenburg & the SimPEG Team June 19, 2018
2. context
3. building for researchers • Flexibility to experiment ◦ Prioritize organization and flexibility • Integration of information ◦ Geologic ◦ Multiple physics • Reproducible and transparent
4. • Modular: building blocks ◦ organized in a framework ◦ pieces available to manipulation • Declarative: express intent ◦ write what you mean ◦ looks like the math • Extensible: new research ◦ quantitative communication ◦ built in feedback loops • Open: for the future ◦ reproducible ◦ opportunities for collaboration building for researchers
5. building for researchers • Modular: building blocks ◦ organized in a framework ◦ pieces available to manipulation • Declarative: express intent ◦ write what you mean ◦ looks like the math • Extensible: new research ◦ quantitative communication ◦ built in feedback loops • Open: for the future ◦ reproducible ◦ opportunities for collaboration
6. 6 inversion
7. (Cockett et al., 2015)
8. Implemented in Python! framework
9. forward simulation Survey: Data collection and geometry Physics: PDE to solve
10. finite volume
11. create a mesh
12. discretize & solve continuous discrete
13. framework
14. Data Misfit Regularization Inverse Problem inversion elements
15. inversion as optimization
16. 16 (does it work?)
17. a few questions • Understanding responses ◦ How does magnetic permeability or chargeability affect my data? • Survey design ◦ Which system should be used to excite / detect the target of interest? ◦ Would adding another receiver orientation improve detection / recovery of the target? • Inversion ◦ Where is a 3D inversion needed? ◦ Can a parametric inversion be used? 17
18. example: conductive plate 18
19. example: conductive plate 19
20. 20 conductive plate: current density
21. 21 conductive plate: magnetic flux
22. fields, fluxes and data Current density Magnetic flux
23. inverse problem 23 subject to mlower < m < mupper
24. framework
25. what is your model? • Subsurface log conductivity • 1D, 2D, 3D voxel model • Parametric model • … 25 • Need to map to forward simulation mesh • Keep track of derivatives for inversion
26. 1D inversion • Model: 1D subsurface conductivity at each sounding location • Forward simulation mesh: 2D cylindrical mesh • Recent developments: SimPEG EM1D ◦ includes lateral and spatial constraints 26
27. 2D voxel inversion • 2D model (tensor mesh) • Forward simulation mesh: 3D tensor mesh ◦ Map 2D section to 3D space 27
28. 2D parametric inversion 28
29. 2D parametric inversion • 6 parameters describing model • Forward simulation mesh: 3D tensor mesh ◦ Map parameters to 2D mesh à fill 3D space 29
30. building for researchers • Modular: building blocks ◦ organized in a framework ◦ pieces available to manipulation • Declarative: express intent ◦ write what you mean ◦ looks like the math • Extensible: new research ◦ quantitative communication ◦ built in feedback loops • Open: for the future ◦ reproducible ◦ opportunities for collaboration 1D inversion 2D inversion Parametric inversion
31. framework • Electromagnetics: ◦ FDEM, TDEM, EM1D (analytic) • Vadose zone flow • Gravity • Magnetics • DC / IP • EMIP 31 In one consistent, modular framework
32. open development versioned, peer reviewed, issue tracking 32 docs.simpeg.xyz tested available for industry, academic use
33. coming soon… 33 • Large scale problems with OcTree meshes and domain decomposition • Efficiency improvements including parallelization • Joint and cooperative inversions with petrophysical information • …
34. contributing
35. Thank you! 35 simpeg.xyz slack.simpeg.xyz github.com/simpeg-research/heagy2018-aem This work is licensed under a Creative Commons Attribution 4.0 International License > pip install SimPEG