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    Systems and methods for likelihood-based detection of gas leaks using mobile survey equipment
    2.
    发明授权
    Systems and methods for likelihood-based detection of gas leaks using mobile survey equipment 有权

    公开(公告)号：US09599597B1

    公开(公告)日：2017-03-21

    申请号：US14139348

    申请日：2013-12-23

    Applicant: Picarro Inc.

    Inventor： David Steele ,  Sze M. Tan ,  Chris W. Rella

    IPC: G01N31/00 ,  G01N33/00

    CPC classification number: G01N33/0004 ,  G01M3/04 ,  G01N33/0075

    Abstract: In some embodiments, vehicle-based natural gas leak detection methods are used to generate 2-D spatial distributions (heat maps) of gas emission source probabilities and surveyed area locations using measured gas concentrations and associated geospatial (e.g. GPS) locations, wind direction and wind speed, and atmospheric condition data. Bayesian updates are used to incorporate the results of one or more measurement runs into computed spatial distributions. Operating in gas-emission plume space rather than raw concentration data space allows reducing the computational complexity of updating gas emission source probability heat maps. Gas pipeline location data and other external data may be used to determine the heat map data.

    Methods for gas leak detection and localization in populated areas using two or more tracer measurements
    3.
    发明申请
    Methods for gas leak detection and localization in populated areas using two or more tracer measurements 审中-公开
    使用两次或多次示踪剂测量的人口稠密地区气体泄漏检测和定位方法

    公开(公告)号：US20160216172A1

    公开(公告)日：2016-07-28

    申请号：US15088885

    申请日：2016-04-01

    Applicant: Picarro, Inc.

    Inventor： Chris W. Rella ,  Eric R. Crosson ,  Michael R. Woelk ,  Sze Meng Tan ,  Yonggang He ,  David Steele

    IPC: G01M3/04 ,  G01N33/00

    CPC classification number: G01N33/0009 ,  G01M3/22 ,  G01M3/38 ,  G01N21/01 ,  G01N21/3504 ,  G01N21/39 ,  G01N2021/0314 ,  G01N2201/025

    Abstract: Improved gas leak detection from moving platforms is provided. Automatic horizontal spatial scale analysis can be performed in order to distinguish a leak from background levels of the measured gas. Source identification can be provided by using two or more tracer measurements of isotopic ratios and/or chemical tracers to distinguish gas leaks from other sources of the measured gas. Multi-point measurements combined with spatial analysis of the multi-point measurement results can provide leak source distance estimates. Qualitative source identification is provided. These methods can be practiced individually or in any combination.

    Abstract translation: 提供了从移动平台改进的气体泄漏检测。 可以进行自动水平空间尺度分析，以区分泄漏与被测气体的背景水平。 可以通过使用两个或更多个同位素比率和/或化学示踪剂的示踪剂测量来提供源识别，以区分气体泄漏与测量气体的其他来源。 多点测量结合多点测量结果的空间分析可以提供泄漏源距离估计。 提供定性来源识别。 这些方法可以单独或以任何组合实施。

    Leak detection event aggregation and ranking systems and methods
    4.
    发明授权
    Leak detection event aggregation and ranking systems and methods 有权

    公开(公告)号：US11933774B1

    公开(公告)日：2024-03-19

    申请号：US18060111

    申请日：2022-11-30

    Applicant: Picarro Inc.

    Inventor： Sean MacMullin ,  Chris W. Rella ,  Aaron Van Pelt ,  Alex Balkanski ,  Yonggang He ,  Sze M. Tan ,  David Steele ,  Tim Clark

    IPC: G01N33/00 ,  G01M3/04

    CPC classification number: G01N33/0075 ,  G01M3/04 ,  G01N33/0047

    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 source. 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.

    Systems and methods for likelihood-based detection of gas leaks using mobile survey equipment
    5.
    发明授权
    Systems and methods for likelihood-based detection of gas leaks using mobile survey equipment 有权

    公开(公告)号：US10444108B1

    公开(公告)日：2019-10-15

    申请号：US16350419

    申请日：2018-11-12

    Applicant: Picarro Inc.

    Inventor： David Steele ,  Sze M. Tan ,  Chris W. Rella

    IPC: G01M3/04 ,  G01N33/00 ,  G01W1/02 ,  G01N25/20

    Abstract: In some embodiments, vehicle-based natural gas leak detection methods are used to generate 2-D spatial distributions (heat maps) of gas emission source probabilities and surveyed area locations using measured gas concentrations and associated geospatial (e.g. GPS) locations, wind direction and wind speed, and atmospheric condition data. Bayesian updates are used to incorporate the results of one or more measurement runs into computed spatial distributions. Operating in gas-emission plume space rather than raw concentration data space allows reducing the computational complexity of updating gas emission source probability heat maps. Gas pipeline location data and other external data may be used to determine the heat map data.

    Leak detection event aggregation and ranking systems and methods
    6.
    发明授权
    Leak detection event aggregation and ranking systems and methods 有权

    公开(公告)号：US10948471B1

    公开(公告)日：2021-03-16

    申请号：US15996069

    申请日：2018-06-01

    Applicant: Picarro Inc.

    Inventor： Sean MacMullin ,  Chris W. Relia ,  Aaron Van Pelt ,  Alex Balkanski ,  Yonggang He ,  Sze Tan ,  David Steele ,  Tim Clark

    IPC: G01N33/00 ,  G01M3/04

    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.

    Gas detection systems and methods using measurement position uncertainty representations
    7.
    发明授权
    Gas detection systems and methods using measurement position uncertainty representations 有权

    公开(公告)号：US10598562B2

    公开(公告)日：2020-03-24

    申请号：US14948287

    申请日：2015-11-21

    Applicant: Picarro Inc.

    Inventor： David Steele ,  Chris W. Rella ,  Sze M. Tan ,  Aaron Van Pelt

    IPC: G01M3/22 ,  G01P13/02 ,  G01P5/02 ,  F17D5/02 ,  G01M3/04 ,  G01C21/36

    Abstract: In some embodiments, a natural gas leak detection system generates display content including indicators of remote and local potential leak source areas situated on a map of an area of a gas concentration measurement survey performed by a vehicle-borne device. The remote area may be shaped as a wedge extending upwind from an associated gas concentration measurement point. The local area graphically represents a potential local leak source area situated around the gas concentration measurement point, and having a boundary within a predetermined distance (e.g. 10 meters) of the gas concentration measurement point. The local area may be represented as a circle, ellipse, or other shape, and may include an area downwind from the measurement point. Size and/or shape parameters of the local area indicator may be determined according to survey vehicle speed and direction data, and/or wind speed and direction data characterizing the measurement point.

    Scanned 1-D Gas Plume Profile and Flux Measurements Using Multiple Analysis Instruments
    10.
    发明申请
    Scanned 1-D Gas Plume Profile and Flux Measurements Using Multiple Analysis Instruments 审中-公开
    使用多个分析仪器扫描1-D气体波形和通量测量

    公开(公告)号：US20150047416A1

    公开(公告)日：2015-02-19

    申请号：US14532999

    申请日：2014-11-04

    Applicant: Picarro, Inc.

    Inventor： Chris W. Rella ,  Eric R. Crosson ,  David Steele ,  Marc L. Fischer

    IPC: G01N33/00

    CPC classification number: G01N33/0031 ,  G01F1/704

    Abstract: A gas concentration image (i.e., concentration vs. position data) in a cross section through a gas plume is obtained. Such measurements can be obtained by moving a 1D array of gas sample inlets through the gas plume. By combining a gas concentration image with ambient flow information through the surface of the gas concentration image, the leak rate (i.e., gas flux) from the leak source can be estimated. Multiple gas analysis instruments can be employed in connection with sweeping a 1-D array of measurement ports through the gas plume in order to reduce analysis time.

    Abstract translation: 获得通过气体羽流的横截面中的气体浓度图像（即，浓度与位置数据）。 这样的测量可以通过将气体样品入口的1D阵列移动通过气体羽流来获得。 通过将气体浓度图像与通过气体浓度图像的表面的环境流量信息组合，可以估计来自泄漏源的泄漏速率（即，气体通量）。 多个气体分析仪器可用于通过气体羽流扫描测量端口的1-D阵列，以减少分析时间。

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