Methane leak detection and sizing over long distances using dual frequency comb laser spectroscopy and a bootstrap inversion technique Journal Article uri icon

Overview

abstract

  • Abstract. Advances in natural gas extraction technology have led to increased activity in the production and transport sectors in the United States, and, as a consequence, an increased need for reliable monitoring of methane leaks to the atmosphere. We present a statistical methodology in combination with an observing system for the detection and attribution of fugitive emissions of methane from distributed potential source location landscapes such as natural gas production sites. We measure long (> 500 m), integrated open path concentrations of atmospheric methane using a dual frequency comb spectrometer and combine measurements with an atmospheric transport model to infer leak locations and strengths using a novel statistical method, the non-zero minimum bootstrap (NZMB). The new statistical method allows us to determine whether the empirical distribution of possible source strengths for a given location excludes zero. Using this information, we identify leaking source locations (i.e., natural gas wells) through rejection of the null hypothesis that the source is not leaking. The method is tested with a series of synthetic data inversions with varying measurement density and varying levels of model-data mismatch. It is also tested with field observations of 1) a non-leaking source location and 2) a source location where a controlled emission of 2.1 E-5 kg s−1 of methane gas is released over a period of several hours. This series of synthetic data tests and outdoor field observations using a controlled methane release demonstrate the viability of the approach for the detection and sizing of very small (;

publication date

  • October 16, 2017

has restriction

  • green

Date in CU Experts

  • February 3, 2018 10:59 AM

Full Author List

  • Alden CB; Ghosh S; Coburn S; Sweeney C; Karion A; Wright R; Coddington I; Prasad K; Rieker GB

author count

  • 9

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