Using Prototypical Sites to Model Methane Emissions in Colorado’s Denver-Julesburg Basin Using the  Mechanistic Air Emissions Simulator (MAES)

Summary:

The bottom-up (BU) methods estimate emissions by considering activity factors and emission factors averages for an extended period for a large area. Some top-down (TD) methods use ethane-methane ratio to attribute methane emissions from oil and gas facilities. The BU inventory estimates are often used to drive the attribution of emissions indicated by TD data to different emission source categories. Despite widespread use, recent studies indicate that traditional BU inventory methods do not adequately capture how variations throughput and failure conditions impact gas composition and rate of emissions. Traditional BU methods typically do not model gas composition, although it differs among different facility configurations and impacts emissions from different equipment within one facility. Since most BU inventories utilize fixed emissions factors, emissions also do not scale due to throughput, which is particularly important for large emitters associated with failure conditions. Mechanistic emissions modeling can be used to address these shortcomings and make BU modeling more effective. This study illustrates how mechanistic modeling highlight changes in emissions due to variable throughput and equipment pressures and temperatures for the same production routed through same or different production facility designs. The study uses the same mechanistic models to illustrate how frequency of failure modes impacts both gas composition and total emissions. Results indicate mechanistic modeling could explain observed gas composition shift in emitted emissions from production and midstream facilities over time, a key modeling input to improve voluntary and regulatory methane mitigation efforts.

Objectives:

  • To address the three deficiencies from traditional inventories:
    1. gas composition changes,
    2. failure conditions, and
    3. variability in facility throughput.
  • To efficiently model the production complexity in a basin, i.e., how to map more than 4,000 individual facilities into a set of models that can be simulated within reasonable computational and modeling labor constraints.

Project Plan:

Validation of MAES prototypical site emissions estimates to the reported emissions to the CDPHE.

A continuous process of developing prototypical sites according to operators’ facility design changes.

Schedule:

Ongoing.

 

Results:

Developed 26 prototypical sites.

 

Opportunities to Participate:

Funding Provided by:

CDPHE 

Collaborators:

Partner operators

Project Overview:

EEMDL MAES Overview.pdf