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

Abstract

<p>Alternative leak detection and repair (alt-LDAR) programs are being introduced by regulators in North America to provide flexibility in how oil and gas producers manage their fugitive methane emissions. However, emissions reduction equivalence must be established between a proposed program and a regulatory standard. We present LDAR-Sim, an open-source, agent-based numerical model for estimating equivalence among LDAR programs and exploring specific LDAR scenarios. Novel advancements include the ability to: (1) set facility-specific LDAR requirements and deployment constraints, (2) simultaneously deploy multiple technologies, each with multiple intelligent agents, (3) integrate screening and close-range methods in a collaborative work practice, (4) consider unique environmental limitations of different technologies, (5) evaluate the impact of limited equipment and labour, and (6) explore the impact of legally vented emissions on screening technologies. We examine several alt-LDAR scenarios using real assets and discuss model confidence and sensitivity to inputs. We show that equivalence determinations depend on explicit definition of reference standards, including weather and labour availability. Screening method performance is vulnerable to the confounding presence of vented emissions and to criteria that trigger follow-up surveys. Relative mitigation of programs is highly sensitive to leak production and null repair rates, two elusive parameters used in previous studies.</p>

Numerical modeling of Earth's dynamic surface: a community approach

“…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.…”

Tiered Leak Detection and Repair Programs at Oil and Gas Production Facilities

“…This work uses a model based on the leak module of the Methane Emission Estimation Tool (MEET), 17,18 with the inclusion of LDAR programs. The resulting model is similar in operation to other open source LDAR models, 11,12 but has some differences that are detailed in the following sections. The simulation is stochastic and each LDAR scenario was ran in a Monte Carlo approach 50 times to get a range of reductions.…”

“…On the other hand, the centralized tank batteries include larger numbers of tanks and typically do not have wellheads on the pad, rather they process output from multiple wellhead only sites located at pads in close proximity. The types of facilities here simulated are the first difference compared to previous simulations, 11,12 making the simulation more representative of facilities in the field, particularly the Permian basin and allowing to test the effect of having certain LDAR programs present only at facilities with larger potential to emit. Details on equipment and component counts at each facility are described in the Supporting Information (SI) Section S.1.…”

“…Mean Time To Repair (MTTR) represents the time that leaks stop emitting outside LDAR inspections, and is a parameter referred to as null repair rate in FEAST and LDAR-Sim. 11,12 MTTR is included in these types of models as it keeps the number of leaks relatively steady at the value of pLeak, when averaged over a long period of time and over multiple simulations, in scenarios that do not have LDAR programs.…”

“…The way that MTBF is typically estimated is to count the number of components of a particular kind that are leaking on a given LDAR survey and then divide the total time those components were operating in between LDAR surveys by the number of leaks, to arrive at the average time to leak. 12 The MTTR and MTBF parameters for component type of leaks were taken directly from the MEET model, while MTTR and MTBF for emissions from tanks and flares were estimated using the same approach as components, based on the time between the first Bridger flyover and the second one. Because some sites had OGI inspections in between the aerial surveys, if a site had detected emissions during an OGI inspection (some tanks were found to be emitting) those findings were also counted in the number of emissions in the time frame, as they were repaired before the second Bridger flyover.…”