Developing a Strategy for Site-Level Methane Emissions Monitoring to Meet OGMP2.0 Level 5: A Case Study

Abstract

The voluntary Oil and Gas Methane Partnership (OGMP) 2.0 framework requires companies to improve their methane measurements and reconcile between source-level (bottom-up) monitoring and site-level (top-down) measurement campaigns. This study presents an analysis to develop a multi-site strategy for meeting level 5 OGMP2.0 standards. The framework involves a series of site assessments based on the available bottom-up emissions estimates, local weather data that impact measurement conditions, and emissions dispersion modelling. To demonstrate the developed framework, two site-level methane monitoring techniques (drone A and B) were selected for analysis of suitability on 6 gas assets, both offshore and onshore. Firstly, bottom-up emissions estimates are collected for each site and assessed for data quality. The distribution of emissions for each source is used to develop a Monte Carlo simulation that analyses the benefit of conducting increased numbers of site-level measurements for reconciliation. Weather has a critical bearing upon the capacity to conduct many top-down measurements. High-resolution weather data was synthesized for each region to determine the likelihood of a successful site-level drone measurement on each day during the year-long study period. A dispersion model derived using computational fluid dynamics was used to integrate bottom-up and weather data to shed light on potential estimation uncertainties from conducting site-level measurements across different days in the year. The results show that weather plays a very important part in predicting the success of a measurement campaign and the technique selection, with some sites having particularly restrictive rain and wind patterns. Sites with lower emission rates and high winds will not suit a site-level technique that monitors at distances of >250m. The quality of the bottom-up emissions estimations is also a vital parameter in decision making and data analysis: where the time resolution of source data is poor, it is not recommended to conduct several site-level studies as there is little potential for reconciliation.