Bertram, K. L., and Wong, J., 2023, Preparing the physical modelling facility to simulate injection/storage of fluids and gases in complex stuctures: CREWES Research Report, 35, 1, 17.
Cai, X., Innanen, K. A., Hu, Q., and Lawton, D. C., 2023, Multi-parameter elastic full-waveform inversion based on the time-lapse VSP Snowflake data: CREWES Research Report, 35, 2, 10.
Cai, X., Innanen, K. A., and Lawton, D. C., 2023, Single-source rapid-repeat time-lapse elastic FWI based on the DAS-VSP data: CREWES Research Report, 35, 3, 12.
Cai, X., Innanen, K. A., Su, Z., and Lawton, D. C., 2023, 3D time-lapse reverse-time migration of DAS-VSP data: Snowflake data from Carbon Management Canada NewellCounty Facility: CREWES Research Report, 35, 4, 8.
Chen, H., Han, J., and Innanen, K. A., 2023, A more accurate estimation of fracture weaknesses constrained using fracture facies: CREWES Research Report, 35, 5, 17.
Chineke, C., and Innanen, K. A., 2023, Direct measurement of frequency-dependent phase velocities from Snowflake data: CREWES Research Report, 35, 6, 16.
Emery, D. J., and Trad, D. O., 2023, Stratigraphical Consistent Seismic Profile for Geologically Informed Machine Learning Interpretation: CREWES Research Report, 35, 7, 11.
Fontes, P. H. L., and Trad, D. O., 2023, A machine learning alternative to sparseness: CREWES Research Report, 35, 8, 20.
Hall, K. W., Innanen, K. A., and Lawton, D. C., 2023, Testing smaller permanent multicomponent optical fibre sensors: CREWES Research Report, 35, 9, 13.
Hess, S., Shor, R., Vetsak, A., and Innanen, K. A., 2023, Downhole acceleration detection of poor drilling performance related to bit damage: CREWES Research Report, 35, 10, 12.
Hu, Q., Eaid, M., Keating, S., Innanen, K. A., and Cai, X., 2023, Estimation of rock physics properties via FWI of VSP data recorded by accelerometer and fiberoptic sensors: CREWES Research Report, 35, 11, 20.
Hu, Q., Zhang, T., and Innanen, K. A., 2023, Uncertainty quantification in rock physics full waveform inversion: CREWES Research Report, 35, 12, 9.
Huang, S., and Trad, D. O., 2023, Time-lapse data matching using neural networks with multiple reflections: CREWES Research Report, 35, 13, 39.
Innanen, K. A., 2023, A tutorial on the adjoint-state method: CREWES Research Report, 35, 14, 22.
Innanen, K. A., 2023, Projective geometric algebra as an enabler of FWI with sparse acquisitions and targeted updating: CREWES Research Report, 35, 15, 17.
Ji, H., Park, S., Oh, J., and Innanen, K. A., 2023, 3D full waveform inversion of the Snowflake CO2 injection VSP data: CREWES Research Report, 35, 16, 14.
Kolkman-Quinn, B., Lawton, D. C., Bertram, M. B., and Macquet, M., 2023, Sparse seismic monitoring at CMC’s Newell County CO2 storage facility: CREWES Research Report, 35, 17, 13.
Li, J. L., and Innanen, K. A., 2023, Hamiltonian Monte Carlo in full waveform inversion: CREWES Research Report, 35, 18, 23.
Li, J. L., and Innanen, K. A., 2023, Incorporating seismic interferometry and full waveform inversion: CREWES Research Report, 35, 19, 11.
Li, J. L., and Innanen, K. A., 2023, Tuning Hamiltonian Monte Carlo in full waveform inversion: CREWES Research Report, 35, 20, 14.
Li, J. L., Rojas-Parra, J., Salvage, R. O., Eaton, D. W. S., Innanen, K. A., and Sun, W., 2023, Machine Learning aids rapid assessment of aftershocks: Application to the 2022-2023 Peace River earthquake sequence, Alberta, Canada: CREWES Research Report, 35, 21, 13.
Li, J., and Trad, D. O., 2023, Ground roll interpolation and attenuation: CREWES Research Report, 35, 22, 20.
Li, J., and Trad, D. O., 2023, Implicit Neural Representations for Unsupervised Seismic Data Processing.: CREWES Research Report, 35, 23, 17.
Li, J., and Trad, D. O., 2023, Robust Seismic data denoising via zero-shot unsupervised deep learning: CREWES Research Report, 35, 24, 27.
Liu, H., Qu, L., Trad, D. O., and Innanen, K. A., 2023, Mitigating elastic effects of acoustic full waveform inversion for VSP data via deep learning: CREWES Research Report, 35, 25, 16.
Pike, K., Innanen, K. A., and Keating, S., 2023, Targeted nullspace shuttles for full waveform time-lapse seismic monitoring and CO2 detection thresholds: CREWES Research Report, 35, 26, 14.
Qu, L., and Innanen, K. A., 2023, Advanced CO2 Interpretation from 4D Sleipner Seismic Images using Swin-Unet3D: CREWES Research Report, 35, 27, 13.
Russell, B. H., 2023, Repeatability indicators in time lapse seismology and their application to the Sleipner CO2 storage project: CREWES Research Report, 35, 28, 19.
Sanchez, I., Agudelo, W. M., Trad, D. O., and Sierra, D., 2023, 3D-FDM for elastic wave modeling in the presence of irregular topography by using unstructured index array representation on a GPU: CREWES Research Report, 35, 29, 29.
Sanchez, I., Agudelo, W. M., Trad, D. O., and Sierra, D., 2023, Numerical modelling of near-surface seismic scattering by the partitioned domain method: CREWES Research Report, 35, 30, 18.
Shor, R., 2023, Geothermal Initiatives at the University of Calgary: CREWES Research Report, 35, 31, 3.
Su, Z., Trad, D. O., and Li, D., 2023, Simultaneous prediction of velocity and angle-dependent reflectivity in time domain FWI: CREWES Research Report, 35, 32, 18.
Trad, D. O., and Sanchez, I., 2023, Towards realistic imaging and FWI testing: CREWES Research Report, 35, 33, 26.
Wong, J., 2023, Picking and fitting of first-break times measured on Gabor transforms of uncorrelated Vibroseis VSP signals: CREWES Research Report, 35, 34, 10.
Wu, Y., and Stewart, R. R., 2023, Comparing the low-frequency content of seismic source-receiver combinations using surface-wave analysis: A field case from Hussar, Alberta: CREWES Research Report, 35, 35, 16.
Zhang, T., Cai, X., and Innanen, K. A., 2023, Implicit elastic full waveform inversion for the VSP data: snowflake data from Carbon Management Canada Newell County Facility: CREWES Research Report, 35, 36, 12.
Zhang, T., Innanen, K. A., and Trad, D. O., 2023, A specific type of modeling error evaluation for viscoelastic full waveform inversion: CREWES Research Report, 35, 37, 20.
Zhang, T., Innanen, K. A., and Trad, D. O., 2023, Using Clifford Neural Operators for learning the horizontal and vertical elastic wavefield displacements.: CREWES Research Report, 35, 38, 16.
Zhuang, K., and Trad, D. O., 2023, Methods and High Performance Computing Optimizations of 5D interpolation: CREWES Research Report, 35, 39, 10.