This inventor holds 1 USPTO granted patent. Top assignee: Landmark Graphics Corporation. Active years: 2025.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2025
Title: Bhaskar Jogi Venkata Mandapaka: Innovator in Reservoir Modeling
Introduction
Bhaskar Jogi Venkata Mandapaka is a notable inventor based in Bengaluru, India. He has made significant contributions to the field of reservoir modeling through his innovative use of machine learning and artificial intelligence. His work focuses on integrating seismic, well log, and production data to enhance the accuracy of reservoir predictions.
Latest Patents
Bhaskar holds a patent for "Automated reservoir model prediction using ML/AI integrating seismic, well log and production data." This patent describes methods and apparatus for generating one or more reservoir 3D models. The process involves training a machine learning model to create integrated enhanced logs based on an integrated data set, which includes seismic and well log data. The model then groups these logs into an ensemble to form a static reservoir 3D model, allowing for more accurate predictions of subterranean reservoirs.
Career Highlights
Bhaskar is currently employed at Landmark Graphics Corporation, where he applies his expertise in machine learning and data integration. His innovative approach has positioned him as a key player in the development of advanced reservoir modeling techniques. With 1 patent to his name, he continues to push the boundaries of technology in this field.
Collaborations
Bhaskar has collaborated with notable colleagues such as Sridharan Vallabhaneni and Samiran Roy. Their combined efforts contribute to the advancement of reservoir modeling and the application of machine learning in the industry.
Conclusion
Bhaskar Jogi Venkata Mandapaka is a pioneering inventor whose work in automated reservoir modeling showcases the potential of integrating machine learning with geological data. His contributions are shaping the future of reservoir predictions and enhancing the efficiency of resource management.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
