Abstract:
In some embodiments, data from multiple vehicle-based natural gas leak detection survey runs are used by computer-implemented machine learning systems to generate a list of natural gas leaks ranked by hazard level. A risk model embodies training data having known hazard levels, and is used to classify newly-discovered leaks. Hazard levels may be expressed by continuous variables, and/or probabilities that a given leak fits within a predefined category of hazard (e.g. Grades 1-3). Each leak is represented by a cluster of leak indications (peaks) originating from a common leak sources. Hazard-predictive features may include maximum, minimum, mean, and/or median CH4/amplitude of aggregated leak indications; estimated leak flow rate, determined from an average of leak indications in a cluster; likelihood of leak being natural gas based on other indicator data (e.g. ethane concentration); probability the leak was detected on a given pass; and estimated distance to leak source.
Abstract:
Optical spectrometer apparatus, systems, and methods for analysis of carbon-14 including a resonant optical cavity configured to accept a sample gas including carbon-14, an optical source configured to deliver optical radiation to the resonant optical cavity, an optical detector configured to detect optical radiation emitted from the resonant cavity and to provide a detector signal; and a processor configured to compute a carbon-14 concentration from the detector signal, wherein computing the carbon-14 concentration from the detector signal includes fitting a spectroscopic model to a measured spectrogram, wherein the spectroscopic model accounts for contributions from one or more interfering species that spectroscopically interfere with carbon-14.
Abstract:
Optical spectrometer apparatus, systems, and methods for analysis of carbon-14 including a resonant optical cavity configured to accept a sample gas including carbon-14, an optical source configured to deliver optical radiation to the resonant optical cavity, an optical detector configured to detect optical radiation emitted from the resonant cavity and to provide a detector signal; and a processor configured to compute a carbon-14 concentration from the detector signal, wherein computing the carbon-14 concentration from the detector signal includes fitting a spectroscopic model to a measured spectrogram, wherein the spectroscopic model accounts for contributions from one or more interfering species that spectroscopically interfere with carbon-14.