Qian Sang

Title: Qian Sang: Innovator in Digital Core Permeability Prediction

Introduction

Qian Sang is a prominent inventor based in Qingdao, China. He has made significant contributions to the field of digital core analysis, particularly in predicting permeability using advanced deep learning techniques. His innovative approach has the potential to enhance the efficiency of resource extraction processes.

Latest Patents

Qian Sang holds a patent titled "Method for predicting permeability of multi-mineral phase digital core based on deep learning." This patent discloses a method for predicting the permeability of a multi-mineral phase digital core. The process involves constructing a three-dimensional digital core and randomly generating a pore structure. By performing image segmentation on the digital core, multiple multi-mineral digital core images are acquired. The permeability corresponding to each image is simulated using multi-physics field simulation software, leading to the creation of a multi-mineral digital core data set. A convolutional neural network, specifically SE-ResNet18, is then trained with this data set to predict the permeability of new multi-mineral core images.

Career Highlights

Qian Sang is affiliated with the China University of Petroleum, where he continues to advance research in digital core analysis. His work is characterized by a strong emphasis on integrating machine learning techniques with traditional geological studies. This innovative approach has positioned him as a leader in his field.

Collaborations

Some of Qian Sang's notable coworkers include Hai Sun and Liang Zhou. Their collaborative efforts contribute to the ongoing research and development in the area of digital core permeability prediction.

Conclusion

Qian Sang's contributions to the field of digital core analysis through his innovative patent demonstrate the intersection of technology and geology. His work not only advances academic research but also has practical implications for resource extraction industries.