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Deep learning for rapid and robust fluorescence lifetime imaging
Deep-learning approach has the potential to unlock fluorescent lifetime imaging for clinical applications. Fluorescence lifetime imaging microscopy (FLIM) is a widely used tool for biomedical imaging that offers many unique advantages over typical intensity-based fluorescence microscopy. FLIM is advancing fundamental biological research by enabling...
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An efficient codec for improved quality streaming video at low bitrates
Background
The ultimate goal of a successful video compression system is to reduce data volume while retaining the perceptual quality of the decompressed data. Standard video compression techniques, such as H.264, HEVC, VP9 and others, have well-known limits and tradeoffs between rate and distortion, especially at low bitrates. Better video compression...
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Real-time automated control and characterization of drilling fluid rheology
Problem statementDrilling is one of the most expensive activities in any oil and gas operation. Monitoring drilling and completion fluid and maintaining these at desired levels of viscosity and density is essential for optimum drilling fluid performance, efficient hole cleaning, and Equivalent Circulating Density (ECD) management, as well as preventing...
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FaultSeg3D: Fast and accurate 3D fault delineation
Problem statementAccurate 3D mapping of faults from seismic images is essential for seismic structural interpretation, reservoir characterization and well placement. Current methods for fault delineation depend on calculating attributes that estimate seismic reflection continuities and discontinuities. These methods are slow and can take days to process....
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RAPIDClean: fast, accurate real-time simulations for hole cleaning operations
Problem statementImproper hole cleaning is a major cause of non-productive time (NPT) in drilling. Current hole cleaning practices are mostly based on experience, rules of thumb and simplistic calculations, and do not necessarily work as expected in all scenarios. Available models do not include parameters such as fluid compressibility, pipe rotation...
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Automated real-time optimization of formation fluid sampling using artificial intelligence
BackgroundFor capital-intensive exploration and production projects, understanding the chemical and physical properties, phase behavior, compatibility, spatial distribution, and hydraulic connectivity of reservoir fluids is critical for long-term planning and operation. Often, reservoir fluid samples acquired via formation testing represent the only...
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