Acosta, C., Innanen, K. A., and Hall, K. W., 2024, Geometrical model for the “Croissant” multi-component DAS sensor: CREWES Research Report, 36, 1.
Bertram, K. L., and Wong, J., 2024, Physical modelling over a fluid injection model; 4D acquisition and preliminary analysis: CREWES Research Report, 36, 2.
Cai, X., Innanen, K. A., Trad, D. O., and Wong, J., 2024, FWI of Synthetic Data from a Physical Modelling Facility Channel Model: CREWES Research Report, 36, 3.
Cai, X., Zhang, T., Innanen, K. A., and Trad, D. O., 2024, Simultaneous inversion of velocity and reflectivity based on the neural network method: CREWES Research Report, 36, 4.
Chen, H., and Innanen, K. A., 2024, Extended Azimuthal Elastic Impedance (EAEI) calculation for estimating fluid indicator in fractured reservoirs: CREWES Research Report, 36, 5.
Emery, D. J., Guarido, M., and Trad, D. O., 2024, Estimating geological stacking patterns using seismic waveform detection - A gateway to using large language models for seismic interpretation of geological facies: CREWES Research Report, 36, 6.
Emery, D. J., and Trad, D. O., 2024, Estimating Elastic Logs and Mineralogy: CREWES Research Report, 36, 7.
Guarido, M., Emery, D. J., and Innanen, K. A., 2024, AI assistant using retrieval-augmented generation to extract data from mud-logging reports: CREWES Research Report, 36, 8.
Guarido, M., and Innanen, K. A., 2024, Creating a CREWES AI chat assistant using gpt-4o-mini and retrieval-augmented generation: CREWES Research Report, 36, 9.
Guarido, M., and Innanen, K. A., 2024, Intelligence chat copilot app for well-log processing and analysis: CREWES Research Report, 36, 10.
Guarido, M., and Innanen, K. A., 2024, Methods of forecasting Alberta's energy demand: CREWES Research Report, 36, 11.
Hall, K. W., Innanen, K. A., and Lawton, D. C., 2024, 9C DAS acquisition on the Pretzel and Croissant multi-component sensors: CREWES Research Report, 36, 12.
Hernández, A. R., Zhang, T., and Innanen, K. A., 2024, Using Fourier Neural Operators to generate multi-resolution seismic wavefields: CREWES Research Report, 36, 13.
Innanen, K. A., 2024, Programming an Ising computer for seismic tomography: CREWES Research Report, 36, 15.
Innanen, K. A., and Hall, K. W., 2024, Identifying clustering behaviour in EFWI via t-distributed stochastic neighbourhood embedding (t-SNE): CREWES Research Report, 36, 16.
Innanen, K. A., Trad, D. O., Lawton, D. C., Lauer, R., and Ezekiel, C. J., 2024, NSERC Alliance Grant Proposal: Low Cost Seismic Monitoring: CREWES Research Report, 36, 14.
Karpiah, A., Trad, D. O., and Guarido, M., 2024, Deep Learning for Depth Registration of DAS Channels in Vertical Seismic Profiling: CREWES Research Report, 36, 17.
Li, J. L., and Innanen, K. A., 2024, 3D frequency-domain acoustic full waveform inversion: CREWES Research Report, 36, 18.
Li, J. L., and Innanen, K. A., 2024, Hamiltonian Monte Carlo based time-lapse seismic FWI and uncertainty quantification in CO2 monitoring: a VSP feasibility study: CREWES Research Report, 36, 19.
Li, J. L., and Innanen, K. A., 2024, Uncertainty quantification in time-lapse full waveform inversion with Stein Variational Gradient Descent: CREWES Research Report, 36, 20.
Li, J. L., Pike, K., Innanen, K. A., and Hall, K. W., 2024, 4D synthetic time-lapse FWI experiments for CO2 monitoring configured for the Snowflake dataset: CREWES Research Report, 36, 21.
Li, J., and Trad, D. O., 2024, Seismic data denoising by diffusion model: CREWES Research Report, 36, 22.
Li, J., and Trad, D. O., 2024, Unsupervised 3D ground roll attenuation via continuous learning: CREWES Research Report, 36, 23.
Li, J., and Trad, D. O., 2024, Unsupervised DAS noise attenuation via double INR networks: CREWES Research Report, 36, 24.
Liu, H., Fu, X., Cai, X., Trad, D. O., and Innanen, K. A., 2024, A fast data-matching approach for Snowflake DAS VSP data at CaMI: CREWES Research Report, 36, 25.
Liu, H., Fu, X., Cai, X., Trad, D. O., and Innanen, K. A., 2024, High-Resolution Time-Lapse Monitoring of CO2 Sequestration in a Seven-Meter Reservoir Using Walkaway VSP and Full-Waveform Inversion: CREWES Research Report, 36, 26.
Liu, H., Fu, X., Cai, X., Trad, D. O., and Innanen, K. A., 2024, Time-lapse data matching, strategy and FWI of Snowflake DAS VSP data at CaMI.FRS: CREWES Research Report, 36, 27.
Perrin, R., Beeson, J., Trehu, A., Lauer, R., Spinelli, G., and Harris, R., 2024, Spatial-temporal fault movement analysis around a propagator wake on the Juan de Fuca plate: CREWES Research Report, 36, 28.
Pike, K., Innanen, K. A., and Keating, S., 2024, Time-lapse nullspace shuttles: VSP vs surface acquisition, shuttling to zero, and sparse monitoring prospects: CREWES Research Report, 36, 29.
Russell, B. H., and Innanen, K. A., 2024, Boolean logic and Machine Learning: CREWES Research Report, 36, 30.
Sanchez, I., Trad, D. O., and Agudelo, W. M., 2024, Surface wave dispersion analysis and inversion from 3D complex land seismic exploration data: CREWES Research Report, 36, 31.
Schumacher, C., Innanen, K. A., Trad, D. O., and Wong, J., 2024, Optimizing seismic survey designs and configurations for full waveform inversion: a study using physical modeling data and an industry software package: CREWES Research Report, 36, 32.
Su, Z., and Trad, D. O., 2024, Time domain FWI imaging in acoustic variable-density media: CREWES Research Report, 36, 33.
Trad, D. O., Zhang, T., and Sanchez, I., 2024, Computational frameworks for modelling, migration and inversion: CREWES Research Report, 36, 34.
Wong, J., 2024, PSPI depth-migration of data acquired over a channel physical model: CREWES Research Report, 36, 35.
Zhang, T., Cai, X., Hall, K. W., and Innanen, K. A., 2024, Assessing the value of combined use of distributed acoustic sensing (DAS) and multicomponent vertical seismic profiling (VSP) data with network-based full waveform inversion and uncertainty quantification: A case study in Alberta, Canada: CREWES Research Report, 36, 36.
Zhang, T., and Innanen, K. A., 2024, Neural network joint implicit inversion for seismic and gravity data: CREWES Research Report, 36, 37.
Zhang, T., Trad, D. O., and Innanen, K. A., 2024, Time domain 3D effective boundary method RNN-based FWI: CREWES Research Report, 36, 38.
Zhuang, K., and Trad, D. O., 2024, Simultaneous Deblending and Interpolation using the High-Resolution Radon Transform: CREWES Research Report, 36, 39.
Ziegon, A. H., and Innanen, K. A., 2024, Effects of frequency-dependent DAS and geophone data inclusion in elastic FWI: CREWES Research Report, 36, 40.
Ziegon, A. H., and Innanen, K. A., 2024, Model entropy constraints in multi-parameter FWI: A promising tool for time-lapse FWI: CREWES Research Report, 36, 41.
Ziegon, A. H., and Innanen, K. A., 2024, Pseudo-3D elastic FWI: Structurally coupled inversions of intersecting 2D planes: CREWES Research Report, 36, 42.