EXPLORATION • DRILLING • FIELD SERVICES
RIGHT: “A step change in seismic
imaging” – how S-Cube’s founder describes it
technology was able to fill. “Cloud native seismic processing and in particular full waveform inversion (FWI) had not been tackled by the industry service sector,” he recalls. “Te gap existed for an entirely data-driven earth model, building on the cloud with real-time monitoring of the job to enhance accuracy and automation.” In layman’s terms, what Shah’s company,
W
LEFT: S-Cube aims to reduce driling model build times to three weeks BELOW: Seismic measurements can be predicted in the smart software BELOW RIGHT: The technology is fundamentally changing how drilling operations are conducted
S-Cube, essentially does is translate seabed geophysical survey data into precise and highly accurate 3D models of the subsurface to pinpoint the best locations where operators should drill for oil and other natural resources.. Shah, now COO, launched the business when his team developed an adaptive waveform inversion (AWI) algorithm that has since gone on to fundamentally alter how petroleum exploration is approached. It’s enabled global energy firms, such as Ineos and Tullow Oil, to use artificial and automated intelligence intelligence to mimic field data with numerical
hen he was preparing to launch his company in 2015, Dr Nikhil Shah was confident he’d spotted a gap in the market that his
simulations to reduce risk and uncertainty in identifying profitable deep-sea deposits.
HOW DOES THE AWI WORK? Shah describes AWI as, “a smart optimisation cost function within the XWI next- generation waveform inversion framework that searches for the rock 3D velocity model that best predicts seismic measurements leveraging the full recorded wavefield.” He explains that, “AWI provides an
adaptive way of scoring the prediction using a mathematical mapping between field data and model predicted data. Following through the multivariable calculus, this generates more accurate model updates when starting further from true answers. It was the breakthrough on which S-Cube was founded.” Shah firmly believes that his approach is superior to traditional methods. “XWI on AWS (Amazon Web Services) is unique to the industry. It encompasses the most sophisticated waveform inversion techniques with the largest compute facility on the planet. Tis combines to give verifiable accuracy and more automation,” he states. He also points out that, “Our additional
advantage comes from having machine learning capability built into our platform to automatically identify patterns that optimise job performance and settings. Te more data and user projects the framework sees, the more it self-improves.” S-Cube’s solution is cutting-edge in terms of technology and it’s entered a sector that’s known for being technically conservative and risk-averse – and been highly successful. How did Shah’s team accomplish this? “Tere were two partnerships we struck early that were key to overcome hurdles of being a new player,” reveals Shah. Tese partnerships saw Tullow Oil becoming the pilot user (working with S-Cube directly) and the AWS cloud
www.engineerlive.com 9
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60
