Impedance Model Building

Inversion of Impedance (i.e the product of density and seismic velocity) using seismic data.

Used ML Approaches:

• Artificial Neural Networks

Used Neural Networks:

• CNN

• FC

• RNN

• GRU

• Autoencoder

• U-Net

• ResNet

• GAN

Used Learning Procedures:

• Unsupervised Learning

• Supervised Learning

• Transfer Learning

• Reinforcement Learning

• Semi-Supervised Learning

References:

1. Biswas, R., Sen, M. K., Das, V., & Mukerji, T. (2019). Prestack and poststack inversion using a physics-guided convolutional neural network. Interpretation, 7(3), SE161-SE174.

2. Das, V., Pollack, A., Wollner, U., & Mukerji, T. (2019). Convolutional neural network for seismic impedance inversion. Geophysics, 84(6), R869-R880.

3. Gao, Z., Pan, Z., Zuo, C., Gao, J., & Xu, Z. (2019). An optimized deep network representation of multimutation differential evolution and its application in seismic inversion. IEEE Transactions on Geoscience and Remote Sensing, 57(7), 4720-4734.

4. Alfarraj, M., & AlRegib, G. (2019). Semisupervised sequence modeling for elastic impedance inversion. Interpretation, 7(3), SE237-SE249.

5. Gao, Z., Li, C., Yang, T., Pan, Z., Gao, J., & Xu, Z. (2020). OMMDE-Net: A deep learning-based global optimization method for seismic inversion. IEEE Geoscience and Remote Sensing Letters, 18(2), 208-212.

6. Gao, Z., Li, C., Liu, N., Pan, Z., Gao, J., & Xu, Z. (2020). Large-Dimensional Seismic Inversion Using Global Optimization With Autoencoder-Based Model Dimensionality Reduction. IEEE Transactions on Geoscience and Remote Sensing, 59(2), 1718-1732.

7. Wang, Y., Ge, Q., Lu, W., & Yan, X. (2020). Well-logging constrained seismic inversion based on closed-loop convolutional neural network. IEEE Transactions on Geoscience and Remote Sensing, 58(8), 5564-5574.

8. Wang, Y., Wang, Q., Lu, W., & Li, H. (2021). Physics-Constrained Seismic Impedance Inversion Based on Deep Learning. IEEE Geoscience and Remote Sensing Letters.

9. Wu, B., Meng, D., Wang, L., Liu, N., & Wang, Y. (2020). Seismic impedance inversion using fully convolutional residual network and transfer learning. IEEE Geoscience and Remote Sensing Letters, 17(12), 2140-2144.

10. Wu, B., Meng, D., & Zhao, H. (2021). Semi-supervised learning for seismic impedance inversion using generative adversarial networks. Remote Sensing, 13(5), 909.

11. Zhang, J., Li, J., Chen, X., Li, Y., Huang, G., & Chen, Y. (2021). Robust deep learning seismic inversion with a priori initial model constraint. Geophysical Journal International, 225(3), 2001-2019.