Bertram, K. L., 2023, Preparing the physical modelling facility to simulate injection/storage of fluids and gases in complex stuctures: CREWES Meeting Poster, 35, no. 2.
Cai, X., 2023, 3D time-lapse reverse-time migration of DAS-VSP data: Snowflake data from Carbon Management Canada Newell County Facility: CREWES Meeting Poster, 35, no. 4.
Cai, X., 2023, Multi-parameter elastic full-waveform inversion base on the time-lapse VSP Snowflake data: CREWES Meeting Poster, 35, no. 5.
Cai, X., 2023, Single-source rapid-repeat time-lapse elastic FWI based on the DAS-VSP data: CREWES Meeting Poster, 35, no. 3.
Chen, H., 2023, A more accurate estimation of fracture weaknesses constrained using facies: CREWES Meeting Poster, 35, no. 6.
Chineke, C., 2023, Direct measurement of frequency-dependent phase velocities from Snowflake data: CREWES Meeting Poster, 35, no. 1.
Emery, D. J., 2023, Stratigraphical Consistent Seismic Profile for Geologically Informed Machine Learning Interpretation: CREWES Meeting Poster, 35, no. 7.
Fontes, P. H. L., 2023, A machine learning alternative to sparseness: CREWES Meeting Poster, 35, no. 8.
Hall, K. W., 2023, Multicomponent DAS sensing: smaller sensors and field testing: CREWES Meeting Poster, 35, no. 9.
Hess, S., 2023, Downhole acceleration detection of poor drilling performance related to bit damage: CREWES Meeting Poster, 35, no. 10.
Huang, S., 2023, Time-lapse data matching using neural networks with multiple reflections: CREWES Meeting Poster, 35, no. 11.
Innanen, K. A., 2023, Projective Geometric Algebra enabling FWI with sparse acquisitions & targeted updating: CREWES Meeting Poster, 35, no. 12.
Li, J., 2023, Ground roll interpolation and attenuation: CREWES Meeting Poster, 35, no. 19.
Li, J., 2023, Implicit Neural Representations for Unsupervised Seismic Data Processing: CREWES Meeting Poster, 35, no. 20.
Li, J., 2023, Robust Seismic data denoising via zero-shot unsupervised deep learning: CREWES Meeting Poster, 35, no. 18.
Li, J. L., 2023, Hamiltonian Monte Carlo in waveform inversion: CREWES Meeting Poster, 35, no. 16.
Li, J. L., 2023, Incorporating seismic interferometry and full waveform inversion: CREWES Meeting Poster, 35, no. 15.
Li, J. L., 2023, Machine Learning aids rapid assessment of aftershocks: Application to the 2022-2023 Peace River earthquake sequence, Alberta, Canada: CREWES Meeting Poster, 35, no. 14.
Li, J. L., 2023, Tuning Hamiltonian Monte Carlo in waveform inversion: CREWES Meeting Poster, 35, no. 17.
Liu, H., 2023, Mitigating elastic effects of acoustic full waveform inversion for VSP data via deep learning: CREWES Meeting Poster, 35, no. 21.
Pike, K., 2023, Targeted nullspace shuttles for full waveform time-lapse seismic monitoring and CO2 detection thresholds: CREWES Meeting Poster, 35, no. 22.
Qu, L., 2023, CO2 Interpretation from 4D Sleipner Seismic Images using Swin-Unet3D: CREWES Meeting Poster, 35, no. 23.
Sanchez, I., 2023, 3D-FDM for elastic wave modeling in the presence of irregular topography by using unstrictured index array representation on a GPU: CREWES Meeting Poster, 35, no. 24.
Su, Z., 2023, Simultaneous prediction of velocity and angle-dependent reflectivity in time domain FWI: CREWES Meeting Poster, 35, no. 25.
Trad, D. O., 2023, Towards realistic testing with RTM, FWI: CREWES Meeting Poster, 35, no. 26.
Wong, J., 2023, Picking and fitting first-break times on Gabor transforms of uncorrelated Vibroseis signals: CREWES Meeting Poster, 35, no. 27.
Wu, Y., 2023, Comparing the low-frequency content of seismic source-receiver combinations using surface-wave analysis: Afield case from Hussar, Alberta: CREWES Meeting Poster, 35, no. 28.
Zhang, T., 2023, Clifford Neural Operators for learning the horizontal and vertical elastic wavefield displacements: CREWES Meeting Poster, 35, no. 31.
Zhang, T., 2023, Implicit elastic full waveform inversion: application to the Snowflake dataset: CREWES Meeting Poster, 35, no. 30.
Zhang, T., 2023, Modeling error evaluation for the viscoelastic full waveform inversion: CREWES Meeting Poster, 35, no. 29.
Zhuang, K., 2023, 5D interpolation on GPUs using the non-uniformDiscrete Fourier Transform: CREWES Meeting Poster, 35, no. 32.