Sponsors Meeting Posters 2024
Acosta, C., 2024, Geometrical model for the "Croissant" multi-component DAS sensor: CREWES Meeting Poster, 36, no. 1.
Bertram, K. L., 2024, Physical modelling over a fluid injection model; 4D acquisition and preliminary analysis: CREWES Meeting Poster, 36, no. 2.
Cai, X., 2024, FWI of Synthetic Data from a Physical Modelling Facility Channel Model: CREWES Meeting Poster, 36, no. 3.
Cai, X., 2024, Simultaneous inversion of velocity and reflectivity based on the neural network method: CREWES Meeting Poster, 36, no. 4.
Chen, H., 2024, Extended Azimuthal Elastic Impedance (EAEI) calculation for estimating fluid indicator in fractured reservoirs: CREWES Meeting Poster, 36, no. 5.
Emery, D. J., 2024, Estimating Elastic Logs and Mineralogy: CREWES Meeting Poster, 36, no. 6.
Guarido, M., 2024, CREWES Large-Language Models APPs powered by GPT: CREWES Meeting Poster, 36, no. 7.
Guarido, M., 2024, Methods of forecasting Alberta's energy demand: CREWES Meeting Poster, 36, no. 8.
Hall, K. W., 2024, 9C DAS acquisition on the Pretzel and Croissant multi-component sensors: CREWES Meeting Poster, 36, no. 9.
Hernández, A. R., 2024, Using Fourier Neural Operators to generate multi-resolution seismic wavefields: CREWES Meeting Poster, 36, no. 10.
Innanen, K. A., 2024, Identifying clustering behaviour in EFWI via t-distributed stochastic neighbourhood embedding (t-SNE): CREWES Meeting Poster, 36, no. 11.
Karpiah, A., 2024, Deep Learning for Depth Registration of DAS Channels in Vertical Seismic Profiling: CREWES Meeting Poster, 36, no. 12.
Li, J., 2024, Seismic data denoising by diffusion model: CREWES Meeting Poster, 36, no. 13.
Li, J., 2024, Unsupervised 3D ground roll attenuation via continuous learning: CREWES Meeting Poster, 36, no. 14.
Li, J., 2024, Unsupervised DAS noise attenuation via double INR networks: CREWES Meeting Poster, 36, no. 15.
Li, J. L., 2024, 3D frequency-domain acoustic full waveform inversion: CREWES Meeting Poster, 36, no. 16.
Li, J. L., 2024, Hamiltonian Monte Carlo based time-lapse seismic FWI and uncertainty quantificationin CO2 monitoring: a VSP feasibility study: CREWES Meeting Poster, 36, no. 17.
Li, J. L., 2024, Numerical experiments on 4D monitoring based on Snowflake data and settings: CREWES Meeting Poster, 36, no. 18.
Li, J. L., 2024, Uncertainty quantification in time-lapse full waveform inversion with Stein Variational Gradient Descent: CREWES Meeting Poster, 36, no. 19.
Liu, H., 2024, A fast data-matching approach for Snowflake DAS VSP data at CaMI: CREWES Meeting Poster, 36, no. 20.
Liu, H., 2024, High-Resolution Time-Lapse Monitoring of CO2 Sequestration in a Seven-Meter Reservoir Using Walkaway VSP and Full-Waveform Inversion: CREWES Meeting Poster, 36, no. 21.
Liu, H., 2024, Time-lapse data matching, strategy and FWI of Snowflake DAS VSP data at CaMI: CREWES Meeting Poster, 36, no. 22.
Macquet, M., 2024, CMC-CaMI Field Research Station: Advancing Technologies for Carbon Storage Monitoring: CREWES Meeting Poster, 36, no. 23.
Perrin, R., 2024, Spatial-temporal fault movement analysis around a propagator wake on the Juan de Fuca plate: CREWES Meeting Poster, 36, no. 24.
Pike, K., 2024, Time-lapse nullspace shuttles: VSP vs surface acquisition, shuttling to zero, and sparse monitoring prospects: CREWES Meeting Poster, 36, no. 25.
Sanchez, I., 2024, Surface wave dispersion analysis and inversion from 3D complex land seismic exploration data: CREWES Meeting Poster, 36, no. 26.
Schumacher, C., 2024, Optimizing seismic survey designs and configurations for full waveform inversion: a study using physical modeling data and an industry software package: CREWES Meeting Poster, 36, no. 27.
Su, Z., 2024, Time domain FWI imaging in acoustic variable-density media: CREWES Meeting Poster, 36, no. 28.
Trad, D. O., 2024, Computational frameworks for modelling, RTM and FWI: CREWES Meeting Poster, 36, no. 29.
Wong, J., 2024, Fast depth migration of data acquired over a channel physical model: CREWES Meeting Poster, 36, no. 30.
Zhang, T., 2024, A comparison of FWI uncertainty quantification methods: conventional versus machine learning: A case study in Alberta, Canada: CREWES Meeting Poster, 36, no. 31.
Zhang, T., 2024, Effective boundary RNN-based 3D acoustic FWI: CREWES Meeting Poster, 36, no. 32.
Zhang, T., 2024, Neural network joint implicit inversion for seismic and gravity data: CREWES Meeting Poster, 36, no. 33.
Zhuang, K., 2024, Simultaneous Deblending and Interpolation using Radon: CREWES Meeting Poster, 36, no. 34.
Ziegon, A. H., 2024, Effects of frequency-dependent DAS and geophone data inclusion in elastic FWI: CREWES Meeting Poster, 36, no. 35.
Ziegon, A. H., 2024, Model entropy constraints in multi-parameter FWI: A promising tool for time-lapse FWI: CREWES Meeting Poster, 36, no. 36.
Ziegon, A. H., 2024, Pseudo-3D elastic FWI: Structurally coupled inversions of intersecting 2D planes: CREWES Meeting Poster, 36, no. 37.