Mehran Hassanpour

Title: Innovations of Mehran Hassanpour in Geological Property Modeling

Introduction

Mehran Hassanpour is an accomplished inventor based in Houston, TX. He has made significant contributions to the field of geological property modeling through his innovative use of machine learning algorithms. With a total of 3 patents, his work has advanced the understanding and prediction of rock properties.

Latest Patents

One of his latest patents is titled "Building scalable geological property models using machine learning algorithms." This invention provides a method for predicting rock properties at a selectable scale. It involves receiving coordinates of sample points, measurement data, and scales associated with each sample point. A deep neural network (DNN) is trained using this data to generate rock property information for request points based on their coordinates and scales.

Another notable patent is "Geological property modeling with neural network representations." This patent describes a process where a neural network trainer estimates secondary data at locations within a geological formation where such data is unknown. The trained neural networks use input from known locations to estimate the unknown secondary data, thereby reducing memory footprint and enhancing efficiency.

Career Highlights

Mehran Hassanpour is currently employed at Landmark Graphics Corporation, where he continues to develop innovative solutions in geological modeling. His expertise in machine learning and geological sciences has positioned him as a key figure in his field.

Collaborations

Throughout his career, Mehran has collaborated with notable colleagues such as Genbao Shi and Gaetan Bardy. These collaborations have further enriched his work and contributed to the advancement of geological property modeling.

Conclusion

Mehran Hassanpour's innovative patents and contributions to geological property modeling demonstrate his expertise and commitment to advancing technology in this field. His work continues to influence the way geological data is analyzed and utilized.