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Applied Geophysics

Presentations

Exploring the influence of various transfer functions on airborne magnetotelluric inversion

Presentation given at IMAGE 2025

Devin C. Cowan, Lindsey J. Heagy, and Douglas W. Oldenburg
8/28/2025
Applying Segmentation Methods In Geophysical Inversion to Improve The Recovery of Structural Features

Presentation given at AEGC 2025 in the Inverse Problems sessions.

Johnathan C. Kuttai and Lindsey J. Heagy
8/28/2025
Inverting for arbitrarily shaped targets using parameterized radial basis functions

Presentation given at IMAGE 2025

Parth Pokar and Lindsey J. Heagy
8/28/2025
SimPEG: an open-source framework for simulation and parameter estimation in geophysics

Presentation in the session: Recent Advances on PDE-constrained optimization packages and libraries: Part II

Lindsey J. Heagy, Santiago Soler, Joseph Capriotti et al.
7/21/2025
3D geophysical inversions to characterize carbon sequestration potential of ultramafic rocks

Poster presented at EGU2025

Santiago Soler, Joseph Capriotti, Douglas W. Oldenburg et al.
5/1/2025
Airborne Natural Source Electromagnetics for an Arbitrary Base Station

Presented at Geotech RoundUp Symposium 2024 session

Devin C. Cowan, Lindsey J. Heagy, and Douglas W. Oldenburg
4/1/2025
Leveraging Convolutional Neural Networks for implicit regularization in DC resistivity inversions

Talk presented in session NS33C-07

Anran Xu, Lindsey J. Heagy, and John Weis
3/25/2025
Comparing strategies for assessing uncertainty with geophysical inversions for mineral exploration

Talk presented in session SY41A-1036

Johnathan C. Kuttai and Lindsey J. Heagy
3/25/2025
Exploring why the implicit regularization effects provided by neural networks can be effective for geophysical inversions

Talk presented at Canadian Exploration Geophysical Society (KEGS) Symposium 2025

Anran Xu and Lindsey J. Heagy
3/1/2025
Modelling and inversion of electromagnetic data

Presentation given at the 2025 workshop on Ground and Borehole Electromagnetics at RoundUp

Lindsey J. Heagy
1/19/2025
Leveraging Neural Fields for Geophysical Inverse Problems

Talk presented at Society for Industrial and Applied Mathematics (SIAM) Conference on Mathematics of Data Science (MDS24)

Anran Xu and Lindsey J. Heagy
10/25/2024
Inversion, visualization, and open-source tools

Introduction to inversion presented at the Geophysics Day at the Student-Industry Mineral Exploration Workshop (S-IMEW)

Lindsey J. Heagy
5/6/2024
Using convolutional neural networks to classify UXO with multicomponent electromagnetic induction data

Summit on Geophysical Detection of Explosive Remnants of War- Solving Current Challenges of Unexploded Ordnance (UXO) and Demining

Jorge Lopez-Alvis, Lindsey J. Heagy, Douglas W. Oldenburg et al.
4/1/2024
Geophysical electromagnetics: imaging the subsurface from shallow to deep

Colloquium for the Department of Physics at the University of Alberta

Lindsey J. Heagy
3/22/2024
Electromagnetic geophysics across the scales

Talk presented in SAGA 2024 session

Lindsey J. Heagy
3/16/2024
Comparison of magnetic vector inversion with sparse norm susceptibility inversion accounting for demagnetization

Talk presented at 2023 Third International Meeting for Applied Geoscience & Energy Expanded Abstracts

John M. Weis, Lindsey J. Heagy, and Douglas W. Oldenburg
12/14/2023
Joint inversions with the SimPEG framework

Talk presented at 2023 Third International Meeting for Applied Geoscience & Energy Expanded Abstracts

Joseph Capriotti, Lindsey J. Heagy, and Santiago Soler
12/14/2023
Using convolutional neural networks to classify UXO with multicomponent electromagnetic induction data

Talk presented in NS43A-09 2023 session

Jorge Lopez-Alvis, Lindsey J. Heagy, Douglas W. Oldenburg et al.
12/14/2023
Processing potential fields data with Fatiando a Terra

Invited talk presented in session NS33C-05

Santiago Soler, Lu Li, and Lindsey J. Heagy
12/13/2023
Using convolutional neural networks to classify UXO with multicomponent electromagnetic induction data

Talk presented at 2023 SERDP-ESTCP-OEC symposium

Jorge Lopez-Alvis, Lindsey J. Heagy, Douglas W. Oldenburg et al.
11/28/2023
Using convolutional neural networks to classify UXO with multicomponent electromagnetic induction data

Talk presented at 2023 SERDP-ESTCP-OEC symposium

Jorge Lopez-Alvis, Lindsey J. Heagy, Douglas W. Oldenburg et al.
11/28/2023
Impacts of magnetic permeability on electromagnetic data collected in settings with steel-cased wells

We consider a vertical wellbore and simulate time and frequency domain data on 3D cylindrical meshes.

Lindsey J. Heagy and Douglas W. Oldenburg
11/13/2023
Accelerating research with community-driven open-source software for geophysical inversions

Talk presented at 2023 Third International Meeting for Applied Geoscience & Energy Expanded Abstracts

Lindsey J. Heagy, Seogi Kang, Joseph Capriotti et al.
8/29/2023
A convolutional neural network for the classification of UXO in marine settings

Talk presented SERDP project MR22-3487

Jorge Lopez-Alvis, Lindsey J. Heagy, Douglas W. Oldenburg et al.
4/2/2023
A decade of SimPEG connecting research & industry through open-source software

Talk presented at the 2023 Geotech symposium

Lindsey J. Heagy
1/27/2023
Linking open source tools for geophysical simulation and inversion in rugged topographies

Talk presented at NS35B-0388 2022 session

Joseph Capriotti, Johnathan Kuttai, Dominique Fournier et al.
12/14/2022
Monitoring CO2 sequestration with electromagnetics in the presence of steel-cased wells

Talk presented at GC12E-0483 session

Lindsey J. Heagy and Douglas W. Oldenburg
12/12/2022
Accelerating geophysics research in a changing climate

Talk presented at Bay Area Geophysical Society

Lindsey J. Heagy
10/19/2022
Computational geophysics in a changing climate

Seminar presented to the University of Tasmania

Lindsey J. Heagy
4/1/2022
Geophysics in a changing climate

Talk presented in BCGS Roundup Breakfast in 2022

Lindsey J. Heagy
2/1/2022
Machine learning methods for the classification of UXO from electromagnetic data in marine setting

Talk presented at SERDP 2022

Jorge Lopez-Alvis, Lindsey J. Heagy, Douglas W. Oldenburg et al.
1/20/2022
Machine learning for the classification of unexploded ordnance (UXO) from electromagnetic data

Presenting an approach for using convolutional neural networks to classify unexploded ordnance directly from time-domain electromagnetic data

Lindsey J. Heagy, Douglas W. Oldenburg, Fernando Pérez et al.
9/30/2020
Modelling electromagnetic problems in the presence of cased wells

Revisiting numerical modelling strategies to investigate the role of various properties and complexities due to the casing, and present a modelling and inversion strategy.

Lindsey J. Heagy, Rowan Cockett, Douglas W. Oldenburg et al.
8/19/2015
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