TOPBOT : In-depth Investigation of TD/BU Reconciliation: Data, Methods, and Quality Control

Summary:

A combined team from Colorado State University (prime, PI Zimmerle) and Pennsylvania State University (sub, co-PI, Davis) will conduct an intensive review of the disagreements between top-down (TD) and bottom-up (BU) methods for estimating emissions in an oil and gas production basin. Rather than construct ‘yet another’ BU model for comparison, the team proposes a deep dive into the uncertainties of both TD and BU approaches to better understand how to improve both the models and comparisons between them. The team expects to refine the understanding of what data is available, what data has the most impact on results, what is missing, and what approaches would likely be the most successful approaches to improvement.

The proposed project is designed to have key experts in BU and TD modeling consider these questions, supported by a graduate student for modeling experiments. The team is an intentional pairing of one of the leading BU modeling teams (CSU) with one of the leading TD modeling teams (PSU), to bring diverse viewpoints to the table. We disagree on some aspects … and that is exactly the point of combining these two teams. Additionally, we propose a project structure where CAMS’ technical representatives are integrated into working sessions to inject in-depth industry knowledge into the debate.

We are not proposing several aspects which have been part of similar studies performed by both teams. We will not build another ‘more complete’ model of a basin. Instead, we propose to do ‘just enough’ modeling to investigate key questions. To that end, we will hybridize data from the Permian basin with a very detailed data set from the Denver-Julesburg (DJ) basin. We will also not produce another ‘TD/BU disagree by X%’ result; that has been done N times before. Our goal is to understand why the disagreement is happening, through questioning and experiment, and then to outline what is needed to reduce the disagreement.

Deliverables from the project will include improved understanding of why & what, outlined above, and the co-learning of the team and participating technical representatives during working sessions. As requested, this will substantially develop a framework for better estimating emissions intensity, verified by TD/BU comparisons.

Objectives:

Working with a diverse set of BU and TD data (measurements, mapping data, industry data, etc.), the study team will:

1) Analyze the usefulness and value of available input data sources through crafted simulations and comparisons.

2) Evaluate assumptions in identified TD methods.

3) Document one or more methods and quality control procedures to integrate each data set into the BU or TD model.

4) Define required meta data, resolution, and coding of data needed to improve the usefulness of TD or BU estimates (both for future use). These data likely exist, but are not currently accessible. We will provide recommendations on which additional data (or data fields) are most likely to have a substantive impact on TD/BU reconciliation, considering technical, confidentiality and licensing concerns.

5) Identify key methods and metrics to make high quality TD/BU comparisons, including quality control procedures. These methods and metrics will include both what is possible with today’s data and what could be possible with expected future data.

In summary, we propose a thorough and inter-disciplinary approach to improve TD/BU comparisons, providing a roadmap to comparisons that are sufficiently robust to guide policy decisions at company, state, and federal levels.