Dmitry Mikhailov

Title: Innovations in Subsurface Property Reconstruction by Dmitry Mikhailov

Introduction

Dmitry Mikhailov is an innovative inventor based in Otuz-Adyr, Kyrgyzstan. He has made significant contributions to the field of seismic exploration through his groundbreaking patent. His work focuses on enhancing the accuracy and efficiency of subsurface property reconstruction using advanced deep learning techniques.

Latest Patents

Dmitry holds a patent for a "Full waveform inversion algorithm for subsurface physical property reconstruction using generative deep learning approach." This patent addresses the inverse problem in seismic exploration by leveraging both the Radon transform and deep learning techniques. The method employs Generative Adversarial Networks (GANs) and specialized neural network architectures known as R-nets. The first R-net efficiently handles hyperbolic Radon Transform, aiding in data preprocessing, while the second R-net generates detailed subsurface models. The reconstructed properties include the velocity of pressure wave propagation, velocity of shear wave propagation, impedance, and density. This novel approach significantly enhances the accuracy and efficiency of the reconstruction process, particularly beneficial for pre-stack depth migration.

Career Highlights

Dmitry Mikhailov is associated with Engiscent Pte. Ltd., where he applies his expertise in seismic data analysis and deep learning. His innovative methods have the potential to revolutionize the way subsurface models are constructed, leading to faster and more accurate results.

Collaborations

Dmitry collaborates with Alexander Vlasov, contributing to the advancement of technologies in seismic exploration and subsurface modeling.

Conclusion

Dmitry Mikhailov's contributions to the field of seismic exploration through his innovative patent demonstrate the power of combining traditional methods with modern deep learning techniques. His work is paving the way for more efficient and accurate subsurface property reconstruction.