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Title: FInd Gas Source

Abstract

FIGS is a neural network software that ingests real time synchronized field data on environmental flow fields and turbulence and gas concentration variations at high frequency and uses an error minimization algorithm to locate the gas source and quantify its strength. The software can be interfaced with atmospheric, oceanic and subsurface instruments in a variety of platforms stationary or mobile (e.g. cars, UAVs, submersible vehicles or boreholes) and used to find gas sources by smart use of data and phenomenology. FIGS can be trained by phenomenological model of the flow fields in the environment of interest and/or be calibrated by controlled release. After initial deployment the FIGS learning will grow with time as it accumulates data on source quantification. FIGS can be installed on any computer from small beagle-bones for field deployment/end-use to PC/MACs/main-frame for training/analysis. FIGS has been trained (using LANL's high resolution atmospheric simulations) and calibrated, tested and evaluated in the field and shown to perform well in finding and quantifying methane leaks at 10-100m scales at well pads by ingesting atmospheric measurements. The code is applicable to gas and particle source location at large scales.

Authors:
 [1];  [2];  [3]
  1. Planetary Science Institute
  2. University Corporation for Atmospheric Research
  3. LANL
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
Contributing Org.:
Los Alamos National Laboratory (LANL)
OSTI Identifier:
1405117
Report Number(s):
FIGS; 005503MLTPL00
C16132
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Software
Software Revision:
00
Software Package Number:
005503
Software CPU:
MLTPL
Source Code Available:
Yes
Other Software Info:
FIGS is a general gas source/leak detection algorithm that has been developed by LANL and customized for an ARPA-E project on methane detection at well pads.
Country of Publication:
United States

Citation Formats

Travis, Bryan, Sauer, Jeremy, and Dubey, Manvendra. FInd Gas Source. Computer software. Vers. 00. USDOE. 24 Feb. 2017. Web.
Travis, Bryan, Sauer, Jeremy, & Dubey, Manvendra. (2017, February 24). FInd Gas Source (Version 00) [Computer software].
Travis, Bryan, Sauer, Jeremy, and Dubey, Manvendra. FInd Gas Source. Computer software. Version 00. February 24, 2017.
@misc{osti_1405117,
title = {FInd Gas Source, Version 00},
author = {Travis, Bryan and Sauer, Jeremy and Dubey, Manvendra},
abstractNote = {FIGS is a neural network software that ingests real time synchronized field data on environmental flow fields and turbulence and gas concentration variations at high frequency and uses an error minimization algorithm to locate the gas source and quantify its strength. The software can be interfaced with atmospheric, oceanic and subsurface instruments in a variety of platforms stationary or mobile (e.g. cars, UAVs, submersible vehicles or boreholes) and used to find gas sources by smart use of data and phenomenology. FIGS can be trained by phenomenological model of the flow fields in the environment of interest and/or be calibrated by controlled release. After initial deployment the FIGS learning will grow with time as it accumulates data on source quantification. FIGS can be installed on any computer from small beagle-bones for field deployment/end-use to PC/MACs/main-frame for training/analysis. FIGS has been trained (using LANL's high resolution atmospheric simulations) and calibrated, tested and evaluated in the field and shown to perform well in finding and quantifying methane leaks at 10-100m scales at well pads by ingesting atmospheric measurements. The code is applicable to gas and particle source location at large scales.},
doi = {},
year = {2017},
month = {2},
note =
}

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