Seismic Migration

Relocating seismic events to the position they occurred in the subsurface by removing acquisition effects.

Used ML Approaches:

• Artificial Neural Networks

Used Neural Networks:

• RNN

• CNN

• FC

• AlexNet

• VGG

• U-Net

• GAN

Used Learning Procedures:

• Unsupervised Learning

• Supervised Learning

References:

1. Vamaraju, J., & Sen, M. K. (2019). Unsupervised physics-based neural networks for seismic migration. Interpretation, 7(3), SE189-SE200.

2. Lu, Y., Sun, H., Wang, X., Liu, Q., & Zhang, H. (2020). Improving the image quality of elastic reverse-time migration in the dip-angle domain using deep learning. Geophysics, 85(5), S269-S283.

3. Cheng, Q., Zhang, J., & Liu, W. (2021). Extracting Fresnel zones from migrated dip-angle gathers using a convolutional neural network. Exploration Geophysics, 52(2), 211-220.

4. Liu, W., Cheng, Q., Liu, L., Wang, Y., & Zhang, J. (2020). Accelerating High-Resolution Seismic Imaging by Using Deep Learning. Applied Sciences, 10(7), 2502.

5. Liu, Z., Chen, Y., & Schuster, G. (2020). Deep convolutional neural network and sparse least-squares migration. Geophysics, 85(4), WA241-WA253.

6. Kaur, H., Pham, N., & Fomel, S. (2020). Improving the resolution of migrated images by approximating the inverse Hessian using deep learning. Geophysics, 85(4), WA173-WA183.

7. Vamaraju, J., Vila, J., Araya-Polo, M., Datta, D., Sidahmed, M., & Sen, M. K. (2021). Minibatch least-squares reverse time migration in a deep-learning framework. Geophysics, 86(2), S125-S142.