Picarro, Inc.

Lawrence Livermore National Security, LLC

Sze Meng Tan

Chris W Rella

Eric R Crosson

David Steele

Yonggang He

John Allen Hoffnagle

Michael R Woelk

Sean Patrick MacMullin

Aaron Van Pelt

Alejandro Dario Farinas

Tim Clark

Alex Balkanski

Barbara A Paldus

Anders Nottrott

Bernard G Fidric

Alexander Kachanov

Bruce A Richman

Kenneth W Turteltaub

James Ian Lee

Graham Bench

Ted Ognibene

Hongbing Chen

Benjamin Cohen-Stead

Derek Gregory Fleck

Alan Daniel McCartt

Nabil Saad

Chris W Relia

Gerald Thomas Sorensen

Improved cavity enhanced absorption spectroscopy is provided using a piecewise tunable laser by using a lookup table for laser tuning that is configured specifically for this application. In preferred embodiments this is done in combination with a laser control strategy that provides precise wavelength determination using cavity modes of the instrument as a reference.

Cavity enhanced absorption spectroscopy using a piecewise tunable laser and hierarchical wavelength determination

In some embodiments, at least one processor is employed to determine a boundary of a survey area. Data representative of the locations of measurement points adjacent to or outside of the survey area are received, as well as data representative of wind direction at the measurement points. The boundary of the survey area is determined according to the data representative of wind direction and a maximum detection distance value representative of an estimated maximum distance from a potential gas leak source at which a gas leak from the potential source can be detected.

Gas detection systems and methods using survey area indicators

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.

Leak detection event aggregation and ranking systems and methods

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 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. These methods can be practiced individually or in any combination.

Methods for gas leak detection and localization in populated areas having a distance estimate

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.

Interleaved data acquisition in optical spectroscopy is used to provide interference correction for time-varying interference. Measurements at a reference frequency are used to provide an estimate of the interference. These reference measurements are interleaved with the remaining measurements in order to provide estimates of the interference vs. time at relevant times. The interference being corrected can be spectrally structured or unstructured.

Cavity ring-down spectroscopy having interleaved data acquisition for interference mitigation

In some embodiments, data from a vehicle-borne gas leak detection survey are used to generate an aggregate leak indication search area (LISA) indicator for a plurality of leak indications (measurement peaks) characterizing a single leak or localized set of leaks. A clustering algorithm (e.g. Markov, DBScan) may be used to group a set of indications into a cluster characterizing the leak. Leak indications may be pre-filtered for quality control before assignment to a cluster according to a number of parameters including background gas level, inter-peak distance, peak shape, wind speed, wind direction and/or variability, vehicle speed and/or acceleration, and/or a lower detection threshold for leak flow rate.

Aggregate leak indicator display systems and methods

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.

Gas detection systems and methods using measurement position uncertainty representations

This work provides event selection in the context of gas leak pinpointing using mobile gas concentration and atmospheric measurements. The main idea of the present approach is to use a moving minimum to estimate background gas concentration, as opposed to the conventional use of a moving average for this background estimation.

Gas leak detection and event selection based on spatial concentration variability and other event properties

In some embodiments, a computer system generates display content indicating a likely direction and estimated distance to a potential gas leak source. The content includes a street map and at least one search area indicator on the map that indicates a search area suspected to have a gas leak source. The search area indicator has an axis indicating a representative wind direction relative to a geo-referenced location of at least one gas concentration measurement point. The search area indicator also has a width relative to the axis. The width is indicative of a wind direction variability associated with a plurality of wind direction measurements in an area of the gas concentration measurement point. The axis also preferably has a length indicating an estimated maximum distance to the potential gas leak source.

Gas detection systems and methods using search area indicators

In some embodiments, at least one processor is employed to determine a boundary of a survey area. Data representative of the locations of measurement points adjacent to or outside of the survey area is received, as well as data representative of wind direction at the measurement points. The boundary of the survey area is determined according to the data representative of wind direction and a maximum detection distance value representative of an estimated maximum distance from a potential gas leak source at which a gas leak from the potential source can be detected.

Systems and methods for determining a survey area for gas leak detection

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.

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Sunnyvale, CA, United States of America

Sze Meng Tan