Roman Shor
Assistant Professor
Research Interests
Explore related searches
Contact this professor
Get a free first email built on one of their papers, ready for you to edit and send yourself.
About
Roman Shor is an Assistant Professor at the University of Calgary, Canada. His research areas include energy technology, nanocomposite materials, and seismic data analysis. He has recently published articles focusing on solar-assisted heating systems, wastewater treatment technologies, and mechanical properties of hydrogels. Additionally, he explores advanced control strategies in drilling and the dynamics of colloidal suspensions.
Articles (16)
Year:
2024
Year:
2024
Year:
2024
Year:
2024
Year:
2024
Full-waveform inversion (FWI), as an optimization-based approach to estimating subsurface models, is limited by incomplete acquisition and illumination of the subsurface. The incorporation of additional data from new and independent raypaths should be expected to result in significant increase in the accuracy of FWI models. In principle, seismic-while-drilling (SWD) technology can supply these additional raypaths; however, it introduces a new suite of unknowns, namely precise source locations (i.e., drilling path), source signature, and radiation characteristics. A new FWI algorithm is formulated in which the source radiation patterns and positions join the velocity and density values of the grid cells as unknowns to be determined. Several numerical inversion experiments are then conducted with different source settings using a synthetic model. The SWD sources are supplemented by explosive sources and multicomponent receivers at the surface, simulating a conventional surface acquisition geometry. The subsurface model and SWD source properties are recovered and analyzed. The analysis is suggestive that SWD involvement can enhance the accuracy of FWI models, with varying degrees of enhancement depending on factors such as trajectory inclination, source density, and drill path extension. The impact of SWD-FWI over standard FWI is reduced when low-frequency data are missing, but improvements over the models constructed with no subsurface sources remain. This formulation permits general source information, such as position and moment tensor components, to be independently obtained. This inversion scheme may lead to a range of potential applications for which medium properties and source information are required.
Year:
2023
Year:
2022
Year:
2022
Year:
2022
Year:
2022
Year:
2021
Year:
2021
Year:
2021
Year:
2021
Year:
2021
Year:
2021
Collaborators (5)
Giovanniantonio Natale
Associate Professor
University of Calgary
Keekyoung Kim
-
Nasser Kazemi
Université de Montréal
Silviu Niculescu
Université Paris-Saclay
Aggrey Mwesigye
Assistant Professor
University of Calgary
Make your next move.
Prepare your application
Review drafts before you send them.