An agent-based model for estimating emissions reduction equivalence among leak detection and repair programs

Fox, T. A.; Gao, Mozhou; Barchyn, Thomas E.; Jamin, Yorwearth L.; Hugenholtz, Chris H.

doi:10.1016/j.jclepro.2020.125237

Cited by 17 publications

(31 citation statements)

References 12 publications

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“…In practice, emissions may increase or decrease over time as faults in new equipment are addressed (decreasing emissions), old equipment becomes more leak prone (increasing emissions) or other phenomena affect trends in emissions. 30 UDIM repair rates that result in increasing or decreasing emissions over time are explored in the SI, Section S4. LDAR models simulate regulatory LDAR surveys that occur in addition to UDIM activities.…”

Section: Methodsmentioning

confidence: 99%

“…32 Similar models have been used to approve alternative fugitive emission management programs in Alberta. 30,31 Previous work has compared the performance of OGI-based detection methods to alternative detection methods and shown that their performance depends on the properties of the oil and gas basin where they are applied. 30,32 In this work, we critically explore the trade-offs across several technology and LDAR program parameters that help achive equivalent emissions reduction compared to existing methane mitigation policies.…”

Section: Introductionmentioning

confidence: 99%

“…30,31 Previous work has compared the performance of OGI-based detection methods to alternative detection methods and shown that their performance depends on the properties of the oil and gas basin where they are applied. 30,32 In this work, we critically explore the trade-offs across several technology and LDAR program parameters that help achive equivalent emissions reduction compared to existing methane mitigation policies. The modeling approach presented here accommodates any component-level or site-level survey-based LDAR program and provides recommendations for the design of cost-effective emission mitigation policies.…”

Section: Introductionmentioning

confidence: 99%

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New Technologies Can Cost Effectively Reduce Oil and Gas Methane Emissions, but Policies Will Require Careful Design to Establish Mitigation Equivalence

Kemp

Ravikumar

2021

Environ. Sci. Technol.

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Reducing methane emissions from oil and gas systems is a central component of US and international climate policy. Leak detection and repair (LDAR) programs using optical gas imaging (OGI)-based surveys are routinely used to mitigate fugitive emissions or leaks. Recently, new technologies and platforms such as planes, drones, and satellites promise more cost-effective mitigation than existing approaches. To be approved for use in LDAR programs, new technologies must demonstrate emissions mitigation equivalent to existing approaches. In this work, we use the FEAST modeling tool to (a) identify cost vs mitigation trade-offs that arise from using new technologies and (b) provide a framework for effective design of alternative LDAR programs. We identify several critical insights. First, LDAR programs can trade sensitivity for speed without sacrificing mitigation outcomes. Second, low sensitivity or high detection threshold technologies have an effective upper bound on achievable mitigation that is independent of the survey frequency. Third, the cost effectiveness of tiered LDAR programs using site-level detection technologies depends on their ability to distinguish leaks from routine venting. Finally, "technology equivalence" based on mitigation outcomes differs across basins and should be evaluated independently. The FEAST model will enable operators and regulators to systematically evaluate new technologies in nextgeneration LDAR programs.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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New Technologies Can Cost Effectively Reduce Oil and Gas Methane Emissions, but Policies Will Require Careful Design to Establish Mitigation Equivalence

Kemp

Ravikumar

2021

Environ. Sci. Technol.

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“…Stakeholders should carefully consider the tradeoffs identified here such as survey speed, quantification accuracy, and spatial resolution before choosing a specific solution. Models such as FEAST and LDAR-Sim can help operators and regulators evaluate new technologies in a systematic manner and achieve cost-effective methane emissions mitigation [49]- [51]. The AMFC provides critical insights to researchers, operators, and regulators on the challenges of conducting a field trial for new technologies at producing O&G facilities.…”

Section: Discussionmentioning

confidence: 99%

Field Performance of New Methane Detection Technologies: Results from the Alberta Methane Field Challenge

Singh¹,

Barlow²,

Hugenholtz³

et al. 2021

Preprint

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Emerging methane technologies promise rapid and cost-effective methods to measure and monitor methane emissions. Here, we present results from the Alberta Methane Field Challengethe first large-scale, concurrent field trial of eleven alternative methane emissions detection and quantification technologies at operating oil and gas sites. We evaluate new technologies by comparing their performance with conventional optical gas imaging survey. Overall, technologies are effective at detecting methane emissions, with 8 out of 11 technologies achieving an effectiveness of approximately 80%. Importantly, results highlight the key differences in technology performance between those observed at controlled release tests versus those in field conditions. Intermittent emissions from tanks substantially affects detection and site-level quantification estimates and should be independently monitored while assessing technology performance. In this study, all technologies improved their effectiveness in detecting tank emissions when intermittency was considered. Truck-and plane-based systems have clear advantages in survey speed over other technologies, but their use as effective screening technologies to identify high-emitting sites rests on their quantification effectiveness. Drone-based technologies demonstrated higher effectiveness than other technologies in identifying quantification rank compared to baseline OGI-based survey. Overall, quantification under in-field conditions is affected by several exogenous factors such as temporal variation in emissions and changing environmental conditions. We recommend that assessment studies of new methane detection technologies at oil and gas facilities include comprehensive, continuous, and redundant emissions measurement.Recently, several new methane emissions detection technologies that promise faster and more cost-effective leak detection than existing approaches have been developed [19]. These technologies include continuous monitoring systems, mobile sensors mounted on drones, trucks, and planes, handheld sensors, and satellite systems [20]. Most of these technologies are not currently approved for use in regulatory LDAR programs. To enable widespread deployment, the efficacy of new technologies must be validated through rigorous testing, modeling, and field trials. Recent studies in the US have evaluated a variety of mobile methane detection technologies under controlled conditions [21]-[23]. The Stanford/EDF Mobile Monitoring Challenge, for example, evaluated ten truck-, drone-, and plane-based systems for their effectiveness in detecting and quantifying methane emissions at controlled release test facilities [21]. The US Department of Energy's MONITOR program funded the development of several new methane sensors that were tested under controlled conditions [24]. While these studies provided data on technology parameters such as probability of detection and false positive rates, they are not representative of typical O&G operations. Thus, systematic field trials at producing O&G...

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“…The flexibility that BMI offers has led to its adoption in a variety of different applications, including US Geological Survey rainfall-runoff models (Markstrom et al, 2015;Regan et al, 2018Regan et al, , 2019, hydrodynamic modeling (including flagship models developed by Deltares and the Netherlands eScience Center, Hoch and Trigg, 2019;, delta and coastline evolution modeling (Ratliff et al, 2018), and modeling of methane emissions (Fox et al, 2020), to name a few. One disadvantage of a standard interface like BMI is the extra up-front investment in program development.…”

Section: Community Engagementmentioning

confidence: 99%

CSDMS: A community platform for numerical modeling of Earth-surface processes

Tucker

Hutton

Piper

et al. 2021

Preprint

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Abstract. Computational modelling occupies a unique niche in Earth and environmental sciences. Models serve not just as scientific technology and infrastructure, but also as digital containers of the scientific community's understanding of the natural world. As this understanding improves, so too must the associated software. This dual nature–models as both infrastructure and hypotheses–means that modelling software must be designed to evolve continually as geoscientific knowledge itself evolves. Here we describe design principles, protocols, and tools developed by the Community Surface Dynamics Modeling System (CSDMS) to promote a flexible, interoperable, and ever-improving research software ecosystem. These include a community repository for model sharing and metadata, interface and ontology standards for model interoperability, language bridging tools, a modular programming library for model construction, modular software components for data access, and a Python-based execution and model-coupling framework. Methods of community support and engagement that help create a community-centered software ecosystem are also discussed.

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An agent-based model for estimating emissions reduction equivalence among leak detection and repair programs

Cited by 17 publications

References 12 publications

New Technologies Can Cost Effectively Reduce Oil and Gas Methane Emissions, but Policies Will Require Careful Design to Establish Mitigation Equivalence

New Technologies Can Cost Effectively Reduce Oil and Gas Methane Emissions, but Policies Will Require Careful Design to Establish Mitigation Equivalence

Field Performance of New Methane Detection Technologies: Results from the Alberta Methane Field Challenge

CSDMS: A community platform for numerical modeling of Earth-surface processes

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