Former University of Cambridge graduate, Dr Nikhil Shah, cofounder of S-CUBE, a technology company that evolved from Imperial College London, has revolutionised seismic imaging data processing techniques for the petroleum exploration and production industry. Rapidly growing oil and gas sectors are taking notice of these techniques.
Dr Shah told Asian Voice, "Data processing is highly scalable and new start ups with novel algorithmic breakthroughs can optimise processes in the most the capital intensive industries in the world.” Before completing a PhD at Imperial College London (Earth Science & Engineering), he then worked for Chevron USA as a Project Manager.
He is the son of Koolesh Shah, Managing Director and owner of London Town Group of Companies, which has successfully developed into an established hotel and residential property company with assets in excess of £125 million since being founded in 1988. He opened Intercontinental Hotel Group’s first Hotel Indigo branded boutique hotel outside America in central London. On the residential property side, Koolesh owns and manages a substantial portfolio in London.
Shah cofounded Sub-Salt in 2013 to revolutionise seismic analysis by automatically deriving the most detailed velocity models in the industry. The biggest risk facing oil and gas companies is the optimal placement of drilling locations in exploration and production. Key to resolving this risk is obtaining the best possible seismic image; the most important step in this process being the creation of an accurate seismic velocity model. Such a model enables making better drilling decisions and identifying subsurface resources.
S-CUBE revolutionises seismic analysis by automatically deriving the most detailed velocity models in the industry. It supersedes hand velocity picking and interpretation-based tomography, considerably speeding up the process and providing a much superior velocity model and subsequent subsurface imaging.
S-CUBE has developed and patented a technique called Adaptive Waveform Inversion (AWI™), which is arguably the most accurate and efficient algorithm in the world to determine the final velocity model from a highly inaccurate starting model.
