Amundaray, N., and Innanen, K. A., 2020, Time domain FWI in Matlab with applications to inversion of simulated VSP data: CREWES Research Report, 32, 1, 10.
Amundaray, N., Innanen, K. A., Macquet, M., and Lawton, D. C., 2020, FWI time-lapse monitoring of CO2 injection using VSP at CaMI FRS: a feasibility study: CREWES Research Report, 32, 2, 17.
Bayati, F., and Trad, D. O., 2020, Adaptive rank reduction method for SSA to reconstruct seismic data: CREWES Research Report, 32, 3, 13.
Bertram, K. L., 2020, Adaptations for working in the year 2020: CREWES Research Report, 32, 4, 6.
Bertram, K. L., Wilson, T., Hall, K. W., Bertram, M. B., and Lauer, R., 2020, A brief overview of CREWES field work in 2020: CREWES Research Report, 32, 5, 12.
Bertram, K. L., and Wong, J., 2020, Enhanced receiver hardware for physical modeling: CREWES Research Report, 32, 6, 5.
Chen, H., and Innanen, K. A., 2020, Azimuthal PP and PS seismic amplitude variation with angle inversion for orthogonal fracture weaknesses: CREWES Research Report, 32, 7, 22.
Chen, H., and Innanen, K. A., 2020, Bayesian inversion of azimuthal seismic amplitude data for indicators of interconnected aligned cracks: CREWES Research Report, 32, 8, 16.
CREWES, 2020, Abstract Book: CREWES Research Report, 32, 86.
Eaid, M., Chaoshun, H., Zhang, L., Keating, S., and Innanen, K. A., 2020, Estimation of DAS microseismic source mechanisms using unsupervised deep learning: CREWES Research Report, 32, 9, 32.
Eaid, M., and Innanen, K. A., 2020, Analytic and finite-difference modeling of DAS fiber data from moment tensor sources: CREWES Research Report, 32, 10, 18.
Eaid, M., Keating, S., and Innanen, K. A., 2020, The role of fiber gauge length in FWI of data from coiled DAS fibers: CREWES Research Report, 32, 11, 12.
Eaid, M., Keating, S., Macquet, M., and Innanen, K. A., 2020, Elastic FWI of the CAMI FRS 3D walkaway-walkaround VSP fiber survey: a synthetic case study: CREWES Research Report, 32, 12, 22.
Fathalian, A., Guarido, M., Trad, D. O., and Innanen, K. A., 2020, Deep learning for 3D fault detection within virtual realityvisualization seismic volumes: CREWES Research Report, 32, 13, 13.
Fathalian, A., Trad, D. O., and Innanen, K. A., 2020, Numerical simulation of seismic wave propagation in attenuative transversely isotropic media: CREWES Research Report, 32, 14, 15.
Fu, X., and Innanen, K. A., 2020, A new parallel simulated annealing algorithm for 1.5D acousticfull-waveform inversion: CREWES Research Report, 32, 15, 13.
Fu, X., and Innanen, K. A., 2020, MCMC-based time-lapse full-waveform inversion: CREWES Research Report, 32, 16, 21.
Fu, X., Keating, S., Innanen, K. A., and Hu, Q., 2020, Double-wavelet Double-difference elastic full-waveform inversion: CREWES Research Report, 32, 17, 10.
Guarido, M., Emery, D. J., Macquet, M., Trad, D. O., and Innanen, K. A., 2020, The Pitfalls and Insights of Log Facies Classification for a Machine Learning Contest: CREWES Research Report, 32, 18, 15.
Guarido, M., Trad, D. O., and Innanen, K. A., 2020, Application of machine learning to the analysis of pipeline incidents in Canada: CREWES Research Report, 32, 19, 10.
Guarido, M., Trad, D. O., and Innanen, K. A., 2020, The effect of the COVID-19 pandemic to the WTI crude oil price using forecasting models: CREWES Research Report, 32, 20, 12.
Hall, K. W., Innanen, K. A., and Lawton, D. C., 2020, Field testing of multicomponent DAS sensing: CREWES Research Report, 32, 21, 10.
Hall, K. W., Wong, J., Bertram, K. L., and Innanen, K. A., 2020, Non-impulsive source waveforms for physical modelling: CREWES Research Report, 32, 22, 14.
Henley, D. C., 2020, A tale of two realities; reconciling physical and numerical modeling via 'bootstrap' processing: CREWES Research Report, 32, 23, 28.
Hu, Q., and Innanen, K. A., 2020, Elastic FWI with rock physics constraints: CREWES Research Report, 32, 24, 16.
Hu, Q., and Innanen, K. A., 2020, Rock physics properties from seismic attributes with global optimization methods: CREWES Research Report, 32, 25, 13.
Huang, S., and Trad, D. O., 2020, Full-wavefield migration in the frequency-wavenumber domain: CREWES Research Report, 32, 26, 14.
Innanen, K. A., 2020, A review of tensors in non-Cartesian coordinate systems: CREWES Research Report, 32, 27, 10.
Innanen, K. A., 2020, Application of misfit-based model space coordinate system design to seismic AVO inversion: CREWES Research Report, 32, 28, 13.
Innanen, K. A., 2020, Application of misfit-based model space coordinate system design to seismic FWI: CREWES Research Report, 32, 29, 17.
Innanen, K. A., 2020, Model re-parameterization via misfit-based coordinate transforms: CREWES Research Report, 32, 30, 6.
Innanen, K. A., 2020, Numerical procedures for computing constrained coordinate transformation matrices: CREWES Research Report, 32, 31, 13.
Keating, S., and Innanen, K. A., 2020, A tunneling approach to constrained full waveform inversion: CREWES Research Report, 32, 32, 10.
Keating, S., and Innanen, K. A., 2020, Simultaneous recovery of source locations, moment tensors and subsurface models in 2D FWI: CREWES Research Report, 32, 33, 14.
Kolkman-Quinn, B., and Lawton, D. C., 2020, Time-lapse VSP results from the CaMI Field Research Station: CREWES Research Report, 32, 34, 14.
Lamoureux, M. P., Li, D., and Vestrum, R.J., 2020, GPU tools for seismic wave modelling: CREWES Research Report, 32, 35, 12.
Law, B. K., and Trad, D. O., 2020, The application of stereotomography to Hussar 2D survey: CREWES Research Report, 32, 36, 13.
Lawton, D. C., Bertram, M. B., Hunter, T., Maidment, G., and Kolkman-Quinn, B., 2020, Squid: An innovative new ground-coupled electric seismic source for seismic monitoring: CREWES Research Report, 32, 37, 11.
Li, D., Lamoureux, M. P., and Liao, W., 2020, Incorporating multiple a priori information for full waveform inversion: CREWES Research Report, 32, 38, 19.
Liu, H., and Innanen, K. A., 2020, A first-order qP-wave propagator in 2D VTI media: CREWES Research Report, 32, 39, 10.
Liu, H., Trad, D. O., and Innanen, K. A., 2020, Acoustic full waveform inversion in time domain using blended data: CREWES Research Report, 32, 40, 14.
Macquet, M., Lawton, D. C., and Isaac, J. H., 2020, Microseismicity detection and seismic ambient noise correlation at the CaMI Field Research Station, Newell County, Alberta: CREWES Research Report, 32, 41, 20.
Monsegny, J. E., Hall, K. W., Lawton, D. C., and Trad, D. O., 2020, Least Squares DAS to geophone transform: CREWES Research Report, 32, 42, 12.
Monsegny, J. E., Lawton, D. C., and Trad, D. O., 2020, A comparative study of different DAS vendors data: CREWES Research Report, 32, 43, 15.
Monsegny, J. E., Lawton, D. C., and Trad, D. O., 2020, Depth calibration of DAS VSP data at CaMI Field Research Station: CREWES Research Report, 32, 44, 9.
Monsegny, J. E., Lawton, D. C., and Trad, D. O., 2020, Reverse time migration approaches for DAS VSP: CREWES Research Report, 32, 45, 12.
Niu, Z., and Trad, D. O., 2020, Experiments on constructing seismic using generative adversarial network: CREWES Research Report, 32, 46, 11.
Pan, W., 2020, Waveform Q tomography with central-frequency shifts: CREWES Research Report, 32, 47, 14.
Pan, W., and Innanen, K. A., 2020, Sensitivity kernel analysis for time-domain viscoelastic full-waveform inversion based on the GSLS model: CREWES Research Report, 32, 48, 22.
Qu, L., Innanen, K. A., and Dettmer, J., 2020, Sensitivity analysis of surface wave dispersion curves for various subsurface parameters: CREWES Research Report, 32, 49, 9.
Qu, L., Innanen, K. A., Dettmer, J., and Pan, W., 2020, 2D surface wave inversion on the DAS data at CaMI Field Research Station: Multi-offset MASW vs FWI: CREWES Research Report, 32, 50, 12.
Russell, B. H., 2020, Unsupervised seismic faces classification using K-means and Gaussian Mixture Modeling: CREWES Research Report, 32, 51, 20.
Su, Z., and Trad, D. O., 2020, Deblending in common receiver and common angle gathers: CREWES Research Report, 32, 52, 15.
Sun, J., Innanen, K. A., and Huang, C., 2020, Physics-guided deep learning for seismic inversion: hybrid training and uncertainty analysis: CREWES Research Report, 32, 53, 29.
Trad, D. O., 2020, A multigrid approach for time domain FWI: CREWES Research Report, 32, 54, 20.
Woźniakowska, P., Guarido, M., Trad, D. O., Emery, D. J., and Eaton, D. W. S., 2020, Fault Detection using Residual Neural Networks: CREWES Research Report, 32, 56, 6.
Wong, J., Bertram, K. L., Zhang, H., Hall, K. W., and Innanen, K. A., 2020, Enhanced source hardware and tank for physical modelling: CREWES Research Report, 32, 55, 24.
Yao, Z., 2020, Fast Sweeping Method with Adaptive Finite Difference Scheme Eikonal Solver: CREWES Research Report, 32, 63, 5.
Zhang, H., Akram, J., and Innanen, K. A., 2020, Physics-guided neural network for velocity calibration using downhole microseismic data: CREWES Research Report, 32, 57, 14.
Zhang, H., Dettmer, J., Wong, J., and Innanen, K. A., 2020, Simultaneous Bayesian inversion for effective anisotropic parameters and microseismic event locations: A physical modelling study: CREWES Research Report, 32, 58, 29.
Zhang, H., and Innanen, K. A., 2020, Bayesian inversion for source mechanisms of microearthquakes: CREWES Research Report, 32, 59, 11.
Zhang, H., Innanen, K. A., and Eaton, D. W. S., 2020, Inversion for shear-tensile focal mechanisms using an unsupervised physics-guided neural network: CREWES Research Report, 32, 60, 17.
Zhang, T., Sun, J., Innanen, K. A., and Trad, D. O., 2020, A deep learning formulation of viscoelastic VTI full waveform inversion: CREWES Research Report, 32, 61, 15.
Zhang, T., Sun, J., Innanen, K. A., and Trad, D. O., 2020, Elastic TTI full waveform inversion based on theory guided neural network: CREWES Research Report, 32, 62, 16.
Zhuang, K., and Trad, D. O., 2020, Comparison of high performance computing methods for high resolution Radon transform and deblending: CREWES Research Report, 32, 64, 9.