This special issue invites paper contributions that focus on improving seismic tomography and imaging with both physics- and data-driven approaches and their applications to derive high-resolution Earth models.
High resolution subsurface models are demanded for a broad range of geophysical applications, including but not limited to subsurface channels detection, hydrological modeling for groundwater contaminations and environmental sustainability analysis, hydrocarbon reservoirs explorations, and carbon sequestration monitoring. Building an Earth model from seismic data typically involves two main steps: (1) using seismic tomography method to invert for Earth attributes (e.g., velocity, anisotropy, attenuation, etc.), and (2) applying seismic imaging method to migrate the time-domain reflection signals to map the depth-domain boundaries and discontinuities. In recent decades, seismic methods including ray- and wave-equation-based tomography and imaging have been developed with numerous case studies, which successfully improve our understanding of hydrocarbon characteristics and carbon storage. However, as the data volume increases rapidly, nowadays it’s continuously challenging to derive reliable Earth models efficiently and accurately from seismic data. At the same time, the estimation of model uncertainties, both prior and posterior, and tracking the dynamic changes of subsurface properties become increasingly attractive. All these applications require algorithm development that can consider more complex physics to enhance the resolution and fidelity of subsurface seismic models with high computational efficiency. Besides the physics-driven methods, the machine learning methods that incorporate human experiences to train the models using big data also show their great potential in overcoming the bottlenecks of traditional seismic tomography and imaging.
We encourage the submission of papers covering different topics, from pure, fundamental research to more applied demonstrations and integrated case studies, including, but not limited to:
- Full waveform inversion
- Reverse time migration
- Least-square migration
- Ray-based tomography and migration
- Time-lapse imaging
- Attenuation modeling
- Application of machine learning in seismic tomography and imaging
- Field data case studies for hydrocarbon exploration and CCS monitor
Manuscripts should be prepared according to the author’s and submitted using the online submission webpage.
Contributed papers are welcome to be submitted to Geophysical Prospecting by the normal procedure via Research Exchange, taking care on the online submission form to select the drop-down menu for the Special Issue: Frontiers in Seismic Tomography and Imaging. To ensure the manuscript is processed timely, we request the authors to clearly state in the cover letter that the manuscript is submitted to this specific Special Issue, and notify the Editor Sizhuang Deng and GP editorial team via email with the subject line ‘GP Special Issue submission on Frontiers in Seismic Tomography and Imaging’, so that it is appropriately tagged.
- Submission starts: 1 November 2023
- Paper submission deadline: 1 April 2024
- Acceptance/rejection notification: 1 August 2024
- Paper publication: October 2024