Natural Gas Compressor Stations Research Articles

Experimental and numerical study on natural gas explosion evolution in open space under different initial conditions

The vapor cloud explosion in open space are greatly affected by the initial conditions of gas cloud and the surrounding environment, while in the gas compressor station, these factors are ubiquitous. While the researches of external influencing factors like the obstacle and initial turbulence effect on natural gas explosion in open space are rare. In this paper, a series of natural gas explosion experiments were conducted and a long-distance natural gas pipeline compressor station was taking as an example to simulate the natural gas leakage and explosion in the typical location. Results showed that the greater the initial turbulence, the greater the peak overpressure of gas explosion. When the initial wind speed is 5 m/s, the peak overpressure can promote 73.4 % higher than that without initial turbulence. However, the overpressure doesn't linearly increase with the increasing of initial wind speed. What's more, the flame speed showed the same law with the overpressure, and the effect of concentration on overpressure is lower than that of initial turbulence and obstacle density. The explosion damaging range in the condenser area is larger than that in the separator area, and the maximum overpressure can reach about 21 kPa and the temperature can reach above 2280K, which provides an important basis for the safety prevention and personnel protection in natural gas compressor station.

Assessment of current methane emission quantification techniques for natural gas midstream applications

Abstract. Methane emissions from natural gas systems are increasingly scrutinized, and accurate reporting requires quantification of site- and source-level measurement. We evaluate the performance of 10 available state-of-the-art CH4 emission quantification approaches against a blind controlled-release experiment at an inerted natural gas compressor station in 2021. The experiment consisted of 17 blind 2 h releases at a single exhaust point or multiple simultaneous ones. The controlled releases covered a range of methane flow rates from 0.01 to 50 kg h−1. Measurement platforms included aircraft, drones, trucks, vans, ground-based stations, and handheld systems. Herewith, we compare their respective strengths, weaknesses, and potential complementarity depending on the emission rates and atmospheric conditions. Most systems were able to quantify the releases within an order of magnitude. The level of errors from the different systems was not significantly influenced by release rates larger than 0.1 kg h−1, with much poorer results for the 0.01 kg h−1 release. It was found that handheld optical gas imaging (OGI) cameras underestimated the emissions. In contrast, the “site-level” systems, relying on atmospheric dispersion, tended to overestimate the emission rates. We assess the dependence of emission quantification performance on key parameters such as wind speed, deployment constraints, and measurement duration. At the low wind speeds encountered (below 2 m s−1), the experiments did not reveal a significant dependence on wind speed. The ability to quantify individual sources degraded during multiple-source releases. Compliance with the Oil and Gas Methane Partnership's (OGMP 2.0) highest level of reporting may require a combination of the specific advantages of each measurement technique and will depend on reconciliation approaches. Self-reported uncertainties were either not available or were based on the standard deviation in a series of independent realizations or fixed values from expert judgment or theoretical considerations. For most systems, the overall relative errors estimated in this study are higher than self-reported uncertainties.

Quantitative risk estimation of CNG station by using fuzzy bayesian networks and consequence modeling

As one of the potential explosions and inflammation, compressed natural gas (CNG) stations in urban areas cause irreparable losses and casualties. Estimating risk assessment in gas stress based on coherent uses can reduce accidents in urban areas. The purpose of the present study was to estimate a small risk estimation at one of the CNG multipurpose stations, LPG, using combined models of the Fuzzy Bayesian Network, Bow-tie Diagram, and consequence modeling. This study was conducted based on the basic and 25 intermediate events. This study formed a seven-person safety team to identify the primary events and build the Bow-tie diagram. Then, because of the lack of a proper database, fuzzy theory was used to determine the probability of significant events. Bayesian networks were drawn based on the Bow-tie model using GeNLe software. Finally, the main events of the two Bow-tie, Bayesian network modeling, and risk estimation were performed with the help of PHAST/SAFETI (V8.22). The geographical information system software was used to zone the explosion effects. The Risk assessment result showed that the social risks and the Bayesian network model are more than Bow-tie, and the Bow-tie diagram is unacceptable. Therefore, using incompatible land uses in the vicinity of the CNG stations gives rise to the effects of accident scenarios in particular residential and administrative land uses, which decision-makers and city managers should consider. Based on the findings of this study, the obtained results can be utilized to implement effective control measures. These measures encompass devising a response plan tailored to address specific emergency conditions and conducting comprehensive training programs for the individuals and residents residing within the study area.

Community Health Impacts From Natural Gas Pipeline Compressor Stations.

Compressor stations maintain pressure along natural gas pipelines to sustain gas flow. Unfortunately, they present human health concerns as they release chemical pollutants into the air, sometimes at levels higher than national air quality standards. Further, compressor stations are often placed in rural areas with higher levels of poverty and/or minority populations, contributing to environmental justice concerns. In this paper we investigate what chemical pollutants are emitted by compressor stations, the impacts of emitted pollutants on human health, and local community impacts. Based on the information gained from these examinations, we provide the following policy recommendations with the goal of minimizing harm to those affected by natural gas compressor stations: the Environmental Protection Agency (EPA) and relevant state agencies must increase air quality monitoring and data transparency; the EPA should direct more resources to monitoring programs specifically at compressor stations; the EPA should provide free indoor air quality monitoring to homes near compressor stations; the EPA needs to adjust its National Ambient Air Quality Standards to better protect communities and assess cumulative impacts; and decision-makers at all levels must pursue meaningful involvement from potentially affected communities. We find there is substantial evidence of negative impacts to strongly support these recommendations.

Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution

Abstract. Reducing oil and gas methane emissions is crucially important for limiting the rate of human-induced climate warming. As the capacity of multi-scale measurements of global oil and gas methane emissions has advanced in recent years, including the emerging ecosystem of satellite and airborne remote sensing platforms, a clear need for an openly accessible and regularly updated global inventory of oil and gas infrastructure has emerged as an important tool for characterizing and tracking methane emission sources. In this study, we develop a spatially explicit database of global oil and gas infrastructure, focusing on the acquisition, curation, and integration of public-domain geospatial datasets reported by official government sources and by industry, academic research institutions, and other non-government entities. We focus on the major oil and gas facility types that are key sources of measured methane emissions, including production wells, offshore production platforms, natural gas compressor stations, processing facilities, liquefied natural gas facilities, crude oil refineries, and pipelines. The first version of this global geospatial database (Oil and Gas Infrastructure Mapping database, OGIM_v1) contains a total of ∼ 6 million features, including 2.6 million point locations of major oil and gas facility types and over 2.6×106 km of pipelines globally. For each facility record, we include key attributes – such as facility type, operational status, oil and gas production and capacity information, operator names, and installation dates – which enable detailed methane source assessment and attribution analytics. Using the OGIM database, we demonstrate facility-level source attribution for multiple airborne remote-sensing-detected methane point sources from the Permian Basin, which is the largest oil-producing basin in the United States. In addition to source attribution, we present other major applications of this oil and gas infrastructure database in relation to methane emission assessment, including the development of an improved bottom-up methane emission inventory at high resolution (1 km × 1 km). We also discuss the tracking of changes in basin-level oil and gas activity and the development of policy-relevant analytics and insights for targeted methane mitigation. This work and the OGIM database, which we anticipate updating on a regular cadence, help fulfill a crucial oil and gas geospatial data need, in support of the assessment, attribution, and mitigation of global oil and gas methane emissions at high resolution. OGIM_v1 is publicly available at https://doi.org/10.5281/zenodo.7466757 (Omara et al., 2022a).

Optimisation of the operating parameters of the natural gas compressor station

Optimisation of the operating parameters of the natural gas compressor station

A Pilot Demonstration of Flaring Gas Recovery during Shale Gas Well Completion in Sichuan, China

Summary As one of the largest emitters in the world, the oil and gas industry needs to apply more effort to greenhouse gas (GHG) reduction. Methane, as a potent GHG, could largely determine whether natural gas could serve as a bridging energy toward a sustainable future. In the past decade, oil and gas companies in China have significantly enhanced casing gas recovery and reduced large volume flaring (>2×104 m3/d). However, the remaining low- to mid-volume flaring gas was left for further recovery. Shale gas production in China has met a surge in the number of drilling wells. Those new wells were characterized by a relatively low gas production rate (<1×106 m3/d) in comparison with shale gas wells in the US. As a result, flaring gas during well completion needs to be recycled or used to enhance the gas recovery rate. In this study, we carried out a pilot demonstration project of flaring gas recovery to reduce GHG emissions in the Weiyuan shale gas region in Sichuan Province, China. We adopted the technical route of dehydration and natural gas compression. The recycled natural gas was transformed into compressed natural gas (CNG) and transported to the nearest CNG station for further use. The inlet gas pressure was between 2.85 and 5.82 MPa, and the outlet pressure was kept stable at around 20 MPa to meet the standard of CNG. The manufactured device also showed sound flexibility with the recovery rate between 523.22 and 1224.38 m3/h, which was 28–157% of the designed capacity. The combination of the molecular sieve with high capacity, post low-pressure dehydration, and the application of hydraulic piston in the compression system have guaranteed the equipment to meet the designed performance. The equipment applied in the pilot demonstration has well matched with the local transportation, gas composition, and surface engineering of the well completion. It has the potential of popularization and application in the shale gas tight gas regions in China. Other technical routes, such as small-scale gas to chemicals or natural gas hydrate, should be considered for industrial application for gas flowing rate less than 2×104 m3/d to ensure a further drive down of methane emission along the value chain.

Pulmonary function tests in compressed natural gas pump workers in Surat city

Background: Various studies have known abatements in lung function and several other health problems associated with longstanding air pollution exposure. One of the most cost-effective and environmental alternative of conventional fuels (petrol and diesel) is compressed natural gas (CNG). The increasing use of CNG as a fuel (as it is safe and cheap as compare to the conventional fuels) can add one more bug to the list of work-related disease. Aims and Objectives: This study is to evaluate the respiratory functions of CNG pump workers. Materials and Methods: The present study was held on 82 male subjects. The study group included of non-smoking healthy adult males, age group of 20–40 years working in different CNG stations in Surat city for >6 months and 8 h per day. The control group included of non-smoking healthy adult males, age group of 20–30 years working or studying in the Surat Municipal Institute of Medical Education and Research (SMIMER). Results: Out of 82 male subjects, 30 subjects were control and 52 subjects were CNG station workers. The study group comprised of 52 healthy non-smokers in the age group of 20–40 years working in different CNG station in Surat city for >6 months and 8 h/day. The control group comprised of 30 healthy non-smokers males between the age group of 20–30 years working or studying in the SMIMER. Conclusion: In this study, we have not found statistically significant deterioration in pulmonary functions of CNG pump workers when compared to controls.

Viability of waste heat capture, storage, and transportation for decentralized flowback and produced water treatment

The use of waste heat has been proposed to reduce the energy footprint of membrane distillation for flowback and produced water (FPW) treatment. However, its feasibility has not been fully understood for FPW treatment. Accordingly, this study performs systematic assessments through thermodynamic modelling of waste heat capture, storage, and transportation for decentralized FPW treatment at well pads located in the Denver-Julesburg Basin. A wide range of sensible, phase-change, and thermo-chemical storage materials were assessed for their effectiveness at the utilization of waste heat from on-site hydraulic fracturing engines and natural gas compressor stations, in order to overcome the temporal or spatial mismatch between waste heat availability and FPW generation. Our results show that the type of storage material being used can have a high impact on the efficiency of waste heat utilization and the treatment capacity of membrane distillation. Sensible storage materials only utilize sensible heat capacities, while phase-change materials have improved performance because they are able to additionally store latent heat. However, sensible and phase-change storage materials lose 11–83% of heat due to conversion inefficiencies caused by their changing temperatures. Thermo-chemical materials, on the other hand, have the highest potential for use because they collect and release heat at constant temperatures. We identified three thermo-chemical storage materials (magnesium sulfate, magnesium chloride, and calcium sulfate) with the best efficiencies due to their elevated discharge temperatures which reduce the energy consumption of membrane distillation. In addition, these materials have high volumetric energy storage density, which enables capture and transportation of waste heat from remote locations such as natural gas compressor stations to the well sites, yielding up to 70% reduction in transportation costs relative to moving FPW to centralized treatment facilities at natural gas compressor stations. Our study, for the first time, demonstrates the importance of selecting appropriate energy storage material for leveraging low-grade thermal energy such as waste heat to power membrane distillation for decentralized wastewater treatment.

Risk Prioritization in a Natural Gas Compressor Station Construction Project Using the Analytical Hierarchy Process

Recently, the seamless construction and operation of natural gas pipelines has become even more critical, while the oil and gas industry’s capability to operate effectively with acceptable risks and hazardous situations is mainly dependent on safety. As a result, it is very important to have a wide knowledge of effective management tactics for enhancing implementation of safety regulations and procedures. The problem of assuring workers’ health and safety in the workplace is a crucial component in the endeavor to raise the productivity of labor and the level of competitiveness of building projects. To promote the health, safety, and well-being of workers, issues that are embedded within the concept of sustainability, we propose in this study a safety risk-assessment process that uses the analytical hierarchy process for assigning priorities to risks on construction worksites. This process uses a popular multicriteria method. The success of this strategy was shown by its application to the building of a natural gas compressor plant in Greece. The main contribution of this study is the application of a well-known multicriteria method for assessing risks in a natural gas compressor station construction project and prioritizing hazards to allocate budget for risk-mitigation measures.

Operation monitoring method of pipeline equipment in natural gas compressor station based on spiral microphone array

The abnormal operating conditions of pipeline equipment in natural gas compressor station, such as gas pipeline leakage or equipment failure, lead to negative social impacts. To solve the current problem of untimely and inaccurate manual maintenance, this study proposes a 24/7 real-time method for monitoring the operation of pipeline equipment in natural gas compressor station based on a spiral microphone array. First, the Linearly Constrained Minimum Variance (LCMV) beamformer is used to enhance the signal in the target angle direction and suppress the interference in other directions. Then we train the support vector machine (SVM) model based on the station’s Mel-Frequency Cepstral Coefficients (MFCC) feature dataset for diagnosis. The results show that the method is of great feasibility and reliability.

Deep learning-based scheduling of virtual energy hubs with plug-in hybrid compressed natural gas-electric vehicles

The virtual energy hub (VEH), a combination of virtual power plant and energy hub concepts, faces many uncertainties due to its constituent distributed energy resources. This paper presents the deep learning-based scheduling of VEH for participation in electrical and thermal markets using bidirectional long short-term memory (BLSTM) network, which offers excellent accuracy in forecasting uncertain parameters by concurrent using past and future dependencies. In addition to applying learning methods, energy storage systems can also influence the optimal management of uncertainties. To provide the required electrical storage equipment, the VEH employs plug-in hybrid CNG-electric vehicles (PHGEVs) that can use both electrical energy and compressed natural gas (CNG) to fulfill their energy needs. The alternative fuel can tackle the limitations of prolonged charging of electric vehicles and excess load caused by these vehicles at peak hours. To supply the secondary fuel of PHGEVs, the modeled VEH includes a CNG station, which compresses the natural gas imported from the natural gas grid before delivering it to the vehicles. Furthermore, phase change material-based thermal energy storage (PCMTES) is considered in the VEH configuration, which unlike other common thermal energy storage systems, operates at a constant temperature during the charging and discharging period. Lastly, the simulation of the developed system illustrates that PHGEVs can reduce the imposed cost in unforeseen situations by up to 26 percent and increase the system’s flexibility.

Scenario-based robust energy management of CCHP-based virtual energy hub for participating in multiple energy and reserve markets

The multi-energy systems can operate and schedule the distributed energy resources (DERs) locally to supply the multi-type loads and participate in the energy markets by aggregating the output power of DERs. Recently, the virtual energy hub (VEH) concept, derived from the energy hub and virtual power plant concepts, has been proposed for participating in the electrical and thermal markets. In this paper, robust self-scheduling of a VEH for participating in the energy and reserve markets is presented. The thermal reserve market is proposed to maintain the real-time thermal power balance and compensate for the effects of thermal demand uncertainty. Various types of DERs for supplying loads of each energy carrier are considered. Compressed natural gas (CNG) station is discussed and modeled linearly in the developed VEH to provide the fuel needed by Hybrid CNG and plug-in electric vehicles, which used the CNG as their secondary energy resource. A scenario-based robust approach is developed and presented to maximize the VEH profit and control the downside risk without adding surplus constraints. Finally, the proposed model is simulated in three case studies to evaluate its performance and effectiveness. • Self-scheduling of virtual energy hub for participating in the bilateral markets. • Thermal and electrical reserve markets. • Hybrid CNG and Plug-in electric vehicles. • CNG station for supplying needed CNG fuel. • Downside risk control via developed scenario-based robust method.

Analysis of Cylindrical Damper Effects on Turbine Meters Accuracy in a Pulsating CNG Suction Line: An Optimal Design through CFD Simulations

Turbine meters are used in compressed natural gas (CNG) stations in abundance to measure the volumetric flow rate of the inlet gas. These types of meters are very sensitive to oscillating and pulsating flows. When the station’s reciprocating compressor starts to work, due to the piston and valve performance, pulsating flow will create in the suction line and downstream of turbine meter. This pulsation makes false pulses in the meter and finally makes difference between the measured gas flow from the metering of the gas company and the amount of gas that has been sold at the station. In this study, numerical simulation of dampeners has been investigated after turbine meter and before entering gas to compressor. The goal is eliminating or reducing the effects of operating compressor in CNG station on turbine meter and reducing measurement errors. Numerical simulation of dampener was investigated by Ansys-Fluent CFD software for a CNG station with the gas inlet pressure 250 psi, inlet and outlet pipe diameter of 2 inches. In this study, several parameters such as (1) height-to-diameter ratio in the cylinder, (2) distance between dampener and compressor, and (3) volume-to-minimum volume ratio according to API 618, have been checked. The numerical results show that by increasing height-to-diameter ratio up to 3, the pulsating amplitude on Plane 1 will be reduced, and this is the best ratio according to the present results. Also, by increasing the outlet pipe length, the pressure pulsation amplitude decreases from 3.4% of pressure line in 2 m length to 0.7% in 5 m length. Moreover, the results showed 2.4% increase and 1.9% decrease in the maximum and minimum pressure for CV = 1 and CV = 16.7, respectively. Comparing fluent numerical method with previous studies shows less than 2% difference that demonstrates the validity and reliability of present investigation.

Investigating different types of fluids in pulsating heat pipes for improving heat transfer in an air-cooled heat exchanger

Air-cooled heat exchangers are utilized in various industries to cool process fluids. To have a better heat transfer, fins are used in the structure of exchangers. In this study, a set of experiments were performed to investigate the improvement in the amount of heat transfer in an air-cooled heat exchanger. For this purpose, a real case study was conducted on air-coolers in a natural gas compressor station; afterward, the finned tubes were replaced by pulsating heat pipes (PHPs), and a different type of fluid was applied to the pulsating heat pipes. The laboratory system was set up to measure the overall heat transfer coefficient under two conditions involving either finned tubes or a PHP with R134, R22, and filled acetone fluids. Finally, the results were verified by the theory method. The results showed that all the three fluid agents (R134, R22, and Acetone) with natural convection of 9.94 m/s, an inlet fluid velocity of 5.54 m/s, and an average feed velocity were able to enhance the heat transfer coefficient by 10, 13, and 11%, respectively. In addition, compared with finned tubes, R134, R22, and Acetone improved the natural convection heat transfer coefficient by 22.2, 18.6, and 21.7%, respectively.

Two-stage robust power cost minimization in a natural gas compressor station

Optimal operation of a compressor station is important since it accounts for 25 % to 50 % of a company's total operating budget. In short-term management of a compressor station, handling demand uncertainty is important yet challenging. Previous studies either require precise information about the distribution of uncertain parameters or greatly simplify the compressor model. We build a two-stage robust optimization framework of power cost minimization in a natural gas compressor station with non-identical compressors. In the first stage, decision variables are the ON/OFF state of each compressor and discharge pressure. The worst-case cost of the second stage is incorporated in the first stage. First-stage decision variables feasibility is discussed and proper feasibility cuts are also proposed for the first stage. We employ a piece-wise approximation and propose accelerate methods. Our numerical results highlight two advantages of robust approach when managing uncertainty in practical settings: (1) the feasibility of first-stage decision can be increased by up to 45 % , and (2) the worst-case cost can be reduced by up to 25 % compared with stochastic programming models. Furthermore, our numerical experiments show that the designed accelerate algorithm has time improvements of 1518.9% on average (3785.9% at maximum).

Research on Abnormal Vibration and Vibration Reduction Measures of a Natural Gas Compressor Station: A Case Study of the JYG Compressor Station

As an important medium transmission element, the pipeline has a very important application in the chemical industry, electric power industry, and petroleum industry. However, the pipeline vibration problem has seriously restricted the large-scale development of equipment, reduced the reliability of equipment operation, and even caused serious accidents. Therefore, it is very important to analyze the dynamic characteristics of these vibrations and to reduce the impact of vibrations within pipelines. We focus on the problem of abnormal vibrations within the JYG compressor station pipeline and use a 3D calculation model of the launcher pipeline of west–east gas pipeline III to perform simulation analysis using Fluent to find the cause of the abnormal vibrations. Our results show that the fluid pressure fluctuation in the pipeline is the main factor for the abnormal vibration of the launcher pipeline in the JYG compressor station. The main causes of the vibrations are excessive fluid flow and high flow velocity. Also, by comparing and analyzing the natural frequency of the pipeline system and the pressure fluctuation frequency of the vortex core in the pipeline, we found that the pressure fluctuation frequency is close to the low-order natural frequency of the pipeline system, which is prone to resonance. In this paper, three vibration reduction schemes of the JYG compressor station are suggested and verified. The efficiency of vibration reduction is 68–94%, which can be effectively applied to the outgoing pipeline of the west–east gas pipeline III to solve the abnormal vibration problem of the pipeline.

Emissions and Air Quality Implications of Upstream and Midstream Oil and Gas Operations in Mexico

Mexico approved amendments to its constitution in December 2013 that initiated transformational changes to its energy sector. This study developed a 2016 bottom-up emissions inventory for volatile organic compounds (VOCs), nitrogen oxides (NOx), sulfur dioxide (SO2), carbon monoxide (CO), and fine particulate matter (PM2.5) from upstream and midstream sector sources, including onshore and offshore well sites, gas flaring, natural gas processing facilities, and natural gas compressor stations, throughout Mexican basins. Crude oil storage tanks at onshore oil well sites and venting and fugitive sources at offshore oil production sites were the primary sources of VOC emissions. Key contributions to NOx, CO, and PM2.5 emissions were from internal combustion engines at offshore oil well sites and midstream operations. SO2 emissions were associated with onshore and offshore gas flaring and boilers and process heaters at natural gas processing facilities. Application of the inventory with the Comprehensive Air Quality Model with Extensions (CAMx) indicated that oil and gas production operations could contribute to ozone and PM2.5 concentrations in Mexican and U.S. states under favorable transport patterns. This study provides a foundation for assessing the implications of Mexico’s future energy policies on emissions and domestic and cross-border air quality and public health.

Ethane measurement by Picarro CRDS G2201-i in laboratory and field conditions: potential and limitations

Abstract. Atmospheric ethane can be used as a tracer to distinguish methane sources, both at the local and global scale. Currently, ethane can be measured in the field using flasks or in situ analyzers. In our study, we characterized the CRDS Picarro G2201-i instrument, originally designed to measure isotopic CH4 and CO2, for measurements of ethane-to-methane ratio in mobile-measurement scenarios, near sources and under field conditions. We evaluated the limitations and potential of using the CRDS G2201-i to measure the ethane-to-methane ratio, thus extending the instrument application to simultaneously measure two methane source proxies in the field: carbon isotopic ratio and the ethane-to-methane ratio. First, laboratory tests were run to characterize the instrument in stationary conditions. Subsequently, the instrument performance was tested in field conditions as part of a controlled release experiment. Finally, the instrument was tested during mobile measurements focused on gas compressor stations. The results from the field were afterwards compared with the results obtained from instruments specifically designed for ethane measurements. Our study shows the potential of using the CRDS G2201-i instrument in a mobile configuration to determine the ethane-to-methane ratio in methane plumes under measurement conditions with an ethane uncertainty of 50 ppb. Assuming typical ethane-to-methane ratios ranging between 0 and 0.1 ppb ppb−1, we conclude that the instrument can accurately estimate the “true” ethane-to-methane ratio within 1σ uncertainty when CH4 enhancements are at least 1 ppm, as can be found in the vicinity of strongly emitting sites such as natural gas compressor stations and roadside gas pipeline leaks.

Fugitive methane detection using open-path stand-off chirped laser dispersion spectroscopy.

We report an open-path chirped laser dispersion spectrometer capable of detecting the atmospheric methane concentration above the background using both specular and diffusive reflective surfaces via two distinct operation modes in a stand-off detection configuration. The system is integrated with simultaneous ranging functionality, which enables average concentration measurements for varying optical pathlengths. The system was first tested for accuracy and characterized to achieve sensitivity of 2.9ppm-m/Hz1/2 and pathlength precision of 0.2m/Hz1/2 with a controlled release of methane outside the laboratory. The instrument was subsequently field-deployed in the proximity of a natural gas compressor station for fugitive methane detection. The instrument successfully detected methane plumes and narrowed down the location of the plume through multi-path measurement. The field measurements were verified by a co-located reference mobile methane sensor.