Fast GPU-Based Seismogram Simulation from Microseismic Events in Marine Environments Using Heterogeneous Velocity Models
Not on the map. Why?
Abstract (arXiv)
A novel approach is presented for fast generation of synthetic seismograms due to microseismic events, using heterogeneous marine velocity models. The partial differential equations (PDEs) for the 3D elastic wave equation have been numerically solved using the Fourier domain pseudo-spectral method which is parallelizable on the graphics processing unit (GPU) cards, thus making it faster compared to traditional CPU based computing platforms. Due to computationally expensive forward simulation of large geological models, several combinations of individual synthetic seismic traces are used for specified microseismic event locations, in order to simulate the effect of realistic microseismic activity patterns in the subsurface. We here explore the patterns generated by few hundreds of microseismic events with different source mechanisms using various combinations, both in event amplitudes and origin times, using the simulated pressure and three component particle velocity fields via 1D, 2D and 3D seismic visualizations.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 May 2017.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 1; 2023: 2.
4 papers.
- 2022Adaptive Convolutional Dictionary Network for CT Metal Artifact Reductioncited by 17
- 2023Deep Unfolding Convolutional Dictionary Model for Multi-Contrast MRI Super-resolution and Reconstructioncited by 6
- 2021Towards fast machine-learning-assisted Bayesian posterior inference of microseismic event location and source mechanismcited by 1
- 2023Beckman Defensecited by 0
- 2023Deep Unfolding Convolutional Dictionary Model for Multi-Contrast MRI Super-resolution and Reconstruction3 Sep 2023
- 2023Beckman Defense4 Jan 2023
- 2022Adaptive Convolutional Dictionary Network for CT Metal Artifact Reduction16 May 2022
- 2021Towards fast machine-learning-assisted Bayesian posterior inference of microseismic event location and source mechanism12 Jan 2021