31 Jan 2023
 | 31 Jan 2023
Status: this preprint is currently under review for the journal ESSD.

Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution

Mark Omara, Ritesh Gautam, Madeleine O'Brien, Anthony Himmelberger, Alex Franco, Kelsey Meisenhelder, Grace Hauser, David Lyon, Apisada Chulakadaba, Christopher Miller, Jonathan Franklin, Steve Wofsy, and Steven Hamburg

Abstract. Reducing oil and gas methane emissions is crucially important for limiting the rate of human-induced climate warming. As the capacity of multi-scale measurements of global oil and gas methane emissions have advanced in recent years, including the emerging ecosystem of satellite and airborne remote sensing platforms, a clear need for an openly accessible and regularly updated global inventory of oil and gas infrastructure has emerged as an important tool for characterizing and tracking methane emission sources. In this study, we develop a spatially explicit database of global oil and gas infrastructure, focusing on the acquisition, curation, and integration of public-domain geospatial datasets reported by official government sources, industry, academic, and other non-government entities. We focus on the major oil and gas facility types that are key sources of measured methane emissions, including production wells, offshore production platforms, natural gas compressor stations, processing facilities, liquefied natural gas facilities, crude oil refineries, and pipelines. The first version of this global geospatial database (Oil and Gas Infrastructure Mapping database, OGIM_v1) contains a total of six million features, including 2.6 million point locations of major oil and gas facility types and over 2.6 million kilometers of pipelines globally. For each facility record, we include key attributes—such as facility type, operational status, oil and gas production and capacity information, operator names, and installation dates—which enable detailed methane source assessment and attribution analytics. Using the OGIM database, we demonstrate facility-level source attribution for multiple airborne remote sensing detected methane point sources from the Permian Basin, which is the largest oil producing basin in the U.S. In addition to source attribution, we present other major applications of this oil and gas infrastructure database in relation to methane emission assessment, including the development of an improved bottom-up methane emission inventory at high resolution (1 km x 1 km). We also discuss the tracking of changes in basin-level oil and gas activity, and the development of policy-relevant analytics and insights for targeted methane mitigation. This work and the OGIM database, which we anticipate updating on a regular cadence, helps fill a crucial oil and gas geospatial data need, in support of the assessment, attribution, and mitigation of global oil and gas methane emissions at high resolution. OGIM_v1 is publicly available at (Omara et al. 2022).

Mark Omara et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-452', Anonymous Referee #1, 09 Mar 2023
  • RC2: 'Comment on essd-2022-452', Anonymous Referee #2, 20 Mar 2023

Mark Omara et al.

Data sets

Oil and Gas Infrastructure Mapping (OGIM) database Mark Omara; Ritesh Gautam; Madeleine O'Brien; Anthony Himmelberger

High-resolution Permian bottom-up oil and gas methane emission inventory Mark Omara; Ritesh Gautam

Mark Omara et al.


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Short summary
We acquire, integrate, and analyze over six million geospatial oil and gas infrastructure data records based on information available in the public-domain, and develop an open-access global database including all the major oil and gas facility types that are important sources of methane emissions. This work helps fill a crucial geospatial data need, in support of the assessment, attribution, and mitigation of global oil and gas methane emissions at high resolution.