Feng Xiao
About Feng Xiao
Feng Xiao is an Advanced Wells Engineer at ExxonMobil Engineering and Technology Company, with a background in petroleum engineering and significant experience in research and industry roles.
Current Role at ExxonMobil
Feng Xiao is currently employed as an Advanced Wells Engineer at ExxonMobil Engineering and Technology Company. He has been in this role since 2013, operating out of the Houston, Texas area. In his position, he leads the development of digital-twin solutions to optimize flow performance in deep-water well-flowline-riser systems. Additionally, Feng applies machine learning for offshore gas lift optimization and identifies casing failure in cyclic steam stim wells.
Previous Experience
Prior to his current role at ExxonMobil, Feng Xiao held multiple positions in research and engineering. In 2013, he was a Visiting Scholar specialized in Supercomputing at Argonne National Laboratory for one month. He also completed internships at Shell as a Geomechanics Intern and at ExxonMobil as an Engineering Research Intern in 2012, each for three months respectively. Earlier in his career, Feng served as a Research Assistant at both Colorado School of Mines and the University of Tulsa.
Educational Background
Feng Xiao has a strong academic background in petroleum engineering and business. He earned a PhD in Petroleum Engineering with a minor in Geoscience from Colorado School of Mines. He also completed a program in Business Strategy from Harvard Business School Online. Feng holds a Master's degree in Petroleum Engineering from the University of Tulsa and a Bachelor's degree from Southwest Petroleum Institute. Additionally, he studied at China University of Petroleum, Beijing.
Special Projects and Responsibilities
During his tenure at ExxonMobil, Feng Xiao has undertaken significant projects and responsibilities. He facilitated specialist network meetings in transient flow modeling to advance next-generation production optimization technologies. As ExxonMobil's technical representative, Feng interfaced with Joint Industry Projects (JIPs) and developed workflows for the Production Surveillance and Optimization platform, which has been deployed to top tier assets.