Sergey Fomel

Title: Innovations of Sergey Fomel

Introduction

Sergey Fomel is a prominent inventor based in Austin, Texas, known for his contributions to the field of machine learning and seismic data analysis. With a total of three patents to his name, Fomel has made significant strides in utilizing technology to enhance the understanding of subsurface formations.

Latest Patents

One of Fomel's latest patents is titled "Using synthetic data sets to train a neural network for three-dimensional seismic fault segmentation." This innovative machine learning system efficiently detects faults from three-dimensional seismic images by treating fault detection as a binary segmentation problem. The system employs a balanced loss function to optimize model parameters, addressing the heavily biased distribution of fault and non-fault samples. By training the machine learning system with synthetic seismic and fault volumes, the technology can accurately detect faults from real-world seismic data acquired from different surveys.

Another notable patent is "S-wave anisotropy estimate by automated image registration." This patent provides a system and method for estimating fracture density within subsurface formations using S-wave seismic data. The process involves separating the S-wave seismic data into fast and slow components, utilizing a computer to compute local similarity and cumulative time-differences. This innovative approach allows for accurate estimation of fracture density in subsurface formations.

Career Highlights

Throughout his career, Sergey Fomel has worked with notable companies such as Z Terra Inc. and Aramco Services Company. His experience in these organizations has contributed to his expertise in seismic data analysis and machine learning applications.

Collaborations

Fomel has collaborated with esteemed colleagues, including Alexander M Popovici and Nicolay Tanushev, further enhancing his research and development efforts in the field.

Conclusion

Sergey Fomel's innovative work in machine learning and seismic data analysis has led to significant advancements in understanding subsurface formations. His patents reflect a commitment to leveraging technology for practical applications in the industry.