Quantifying non-steady state natural gas leakage from the pipelines using an innovative sensor network and model for subsurface emissions - InSENSE

Abstract

Detecting and quantifying subsurface leaks remains a challenge due to the complex nature and extent of belowground leak scenarios. To address these scenarios, monitoring and evaluating changes in gas leakage behavior over space and time are crucial for ensuring safe and efficient responses to known or potential gas leaks. This study demonstrates the capability of linking environmental and gas concentration data obtained using a low-cost, near real-time methane (CH₄) detector network and an inverse gas migration model to capture and quantify non-steady state belowground natural gas (NG) leaks. The Estimating Surface Concentration Above Pipeline Emission (ESCAPE) model was modified to incorporate the impact of soil properties on gas migration. Field-scale controlled NG experiments with leakage rates ranging from 37 to 121 g/h indicate that elevated belowground near-surface (BNS) gas concentrations persist long before elevated surface concentrations are observed. On average, BNS CH₄ concentrations were 20%-486% higher than surface CH₄ concentrations within the monitoring radius of 4 m from the leak location. An increase in the BNS CH₄ concentration was observed within 3 h as the leak rate increased from 37 to 89 g/h. However, due to the atmospheric fluctuations, any changes in surface CH₄ concentrations could not be confirmed within this period. The plume area of the BNS CH₄ extended approximately two times farther than that of the surface CH₄ as the gas leak rate increased from 37 to 121 g/h. The estimated NG leak rates by the modified ESCAPE model agreed well with the experimental NG leak rates (m = 0.99 and R² = 0.77), demonstrating that including soil characteristics and BNS CH₄ measurements can advance estimations of non-steady NG leak rates in low and moderate NG leak rate scenarios. The CH₄ detector network and model show potential as an innovative tool to improve operators' risk assessment and NG leakage response.

Keywords: Leak detection and quantification; Methane; Natural gas; Pipeline safety; Surface; Underground.