Company Filing History:
Years Active: 2021
Title: Arrian M Brantley: Innovator in Seismic Inversion Technologies
Introduction
Arrian M Brantley is a notable inventor based in Spring, TX (US). He has made significant contributions to the field of seismic inversion technologies, particularly through his innovative patent that addresses the challenges of scheduling in complex computational environments.
Latest Patents
Brantley's most recent patent is titled "Scalable scheduling of parallel iterative seismic jobs." This patent describes a system and method for scalable and reliable scheduling of iterative seismic full wavefield inversion algorithms. The invention focuses on alternating parallel and serial stages of computation on massively parallel computing systems. The workers in this system operate independently, initiating actions without awareness of each other, and are provided with limited information. This design enables the application of optimal scheduling, load-balancing, and reliability techniques that are specific to seismic inversion problems. The central dispatcher plays a crucial role by specifying the structure of the inversion, including task dependencies, and tracking the progress of work. Additionally, management tools are integrated to allow users to make performance and reliability improvements during the execution of the seismic inversion.
Career Highlights
Arrian M Brantley is currently employed at ExxonMobil Upstream Research Company, where he applies his expertise in seismic technologies. His work has been instrumental in advancing the efficiency and reliability of seismic data processing.
Collaborations
Brantley collaborates with talented professionals in his field, including Aleksandar Bobrek and Anoop A Mullur. Their combined efforts contribute to the innovative solutions being developed at ExxonMobil.
Conclusion
Arrian M Brantley is a distinguished inventor whose work in seismic inversion technologies has the potential to transform the industry. His innovative approaches to scheduling and computation are paving the way for more efficient seismic data processing.