Satellite Methane Quantification Patents: Leaders & White Space 2026
A young, data-processing-heavy field
Satellite methane quantification sits at the intersection of remote sensing, atmospheric science and emissions accounting. The scope tracked here covers 16 published records from 2015 through the 2026 cut-off, with filing activity effectively absent until it climbed to a peak of 7 records in 2023. That timing lines up with tightening methane-reporting rules and the commercial availability of higher-resolution satellite imagery, both of which turned quantification from a research exercise into something worth claiming.
The technology composition leans toward computation rather than hardware: AI models, business/administrative data processing and image recognition each touch over a third of records, ahead of material analysis and testing. That pattern says the contested ground is increasingly the algorithm that turns a plume image into an emissions rate, not the sensor itself.
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Filing trend and technology mix
Two views of the same 16-record dataset: how filing activity has moved over time, and which IPC subclasses the claims fall into.
Filing trend
Filings were flat at zero from 2017 before rising to a peak of 7 records in 2023. Because publication typically lags filing by roughly 18 months, the most recent years in this chart understate actual filing activity and should not be read as a slowdown.
Technology composition
G06N (AI models), G06Q (business/admin data processing) and G06V (image/video recognition) each appear in 37.5% of the 16 records, with G01N (material analysis and testing) close behind at 31.3%. Because a single record can carry several IPC classes, these shares sum to more than 100% — the overlap itself shows that most inventions combine a sensing or data-analysis step with a computational one, rather than sitting in a single discipline.
Shares are the percentage of the 16 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Methane Detection & Mitigation: Satellite Methane Quantification Patent Landscape with Eureka
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Try EurekaThe most-cited records in scope
System and Method for a Remotely Deployable, Off-Grid System to Autonomously Detect, Quantify, and Automatically Report Emissions of Methane and Other Gases to the Atmosphere
The filing describes an off-grid, remotely deployable system that autonomously detects and quantifies methane emissions using commercially available CH4 sensors, with accuracy maintained by correcting for interfering gases such as carbon monoxide and water vapor and for ambient temperature drift. Leak rate quantification is calculated automatically and reported without manual intervention.Filed by Scientific Aviation, Inc.; published 2022-06-30. It is the second most-cited record in this dataset.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20230111401A1 | Automated detection and quantification of gas emissions | 14 |
| 2 | CN118278294A | 基于Sentinel-2识别甲烷点源逸散羽流及估算甲烷排放速率的方法 | 9 |
| 3 | US20220205964A1 | System and Method for a Remotely Deployable, Off-Grid System to Autonomously Detect, Quantify, and Automatica… | 9 |
| 4 | CN118858185A | 基于地基高光谱成像的甲烷排放遥感检测方法 | 5 |
| 5 | US20240281702A1 | Method and system for emissions-based asset integrity monitoring and maintenance | 4 |
| 6 | US20240119464A1 | System for managing decommissioned fossil fuel resources | 1 |
Citation counts are drawn from within this searched corpus and favour older filings; treat them as a signal of influence on later work, not as a ranking of present-day importance.
Patent titles are shown in the language they were filed in, not translated, so that each record stays verifiable against the original filing — a translated title will not match in Eureka or in any national register. Publication numbers are shown where the record carries one (6 of 6 rows); clicking a row searches Eureka by that number.
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Browse MCP servers →What the numbers mean for a filing decision
Three findings that matter more than the raw counts on their own.
A leader, then a long tail
The assignee ranking covers 10 companies. The leader holds 4 records, fifth place holds 1, and tenth place holds 1 — a steep drop-off rather than a gradual one. That shape favours a fast-follower strategy: a handful of white-space claims can still outflank the leader before the field consolidates.
The field is recent and still accelerating
No activity is recorded before the ramp that produced a 2023 peak of 7 of the 16 records in scope. Publication lag means 2025-2026 figures are understated, so the true recent trend is likely stronger than the chart shows, not weaker.
Algorithms, not just sensors, are being claimed
G06N, G06Q and G06V each cover 37.5% of the 16 records, ahead of G01N material analysis at 31.3%. Claims are increasingly written around how plume imagery is processed and interpreted rather than around the sensor hardware alone, which changes where a freedom-to-operate search needs to look.
Filing is concentrated in the US, with PCT and China as secondary routes
Of the receiving offices recorded, the United States accounts for 7, WIPO (PCT) for 3, and China for 2, with single filings in the UAE, Europe and the UK. That distribution suggests the US market is where enforcement risk is highest today, while PCT filings signal an intent to expand coverage later.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to methane detection & mitigation: satellite methane quantification patent landscape, with the prior art for and against each one.
Where to take this analysis
The dataset points to a young field with concentrated computational claims and a thin geographic footprint outside the US. The next steps depend on whether you are filing, licensing, or clearing a product.
Map freedom-to-operate against the AI-heavy classes
With G06N, G06Q and G06V each touching over a third of records, a clearance search limited to sensor-hardware classes like G01N will miss where the contested claims actually sit.
Run a claims search in EurekaWatch the leader's filing cadence, not just its count
A leader with 4 records against a field of 10 ranked assignees can move quickly; tracking new publications from that assignee gives earlier warning than waiting for the next annual snapshot.
Set up assignee tracking in EurekaTreat 2025-2026 filing counts as a floor, not a ceiling
Publication lag of roughly 18 months means recent-year figures will keep rising as more applications publish; re-check the trend before concluding the field has cooled.
Explore the live trend in EurekaCommon questions about this landscape
This landscape tracks 16 published records worldwide between 2015 and the 2026 data cut-off, drawn from a search targeting satellite-based methane quantification specifically. That is a small corpus compared to broader oil-and-gas monitoring technologies, which reflects how recent and narrowly defined the field still is. Because publication lags filing by roughly 18 months, the true number of filed-but-not-yet-published applications is likely somewhat higher than 16.
The assignee ranking in this dataset covers 10 companies, with the leader holding 4 of the ranked records and the field dropping off quickly to single-filing entrants by fifth place. This is a ranked list from the data endpoint, not a top-50 or top-100 filter, so it represents the full set of assignees the search surfaced. The steep drop from leader to long tail suggests the space has not yet consolidated around one or two dominant players.
Filing activity in this dataset was flat at zero as recently as 2017 and did not pick up meaningfully until several years later, reaching a peak of 7 records in 2023. That timing tracks with the growing availability of high-resolution satellite imagery and tightening methane-reporting requirements in the oil and gas sector. Because recent years are understated by publication lag, it is too early to say whether 2023 was the true peak or simply the most recent year with enough time to publish fully.
Three IPC subclasses tie for the largest share: G06N (AI-based computing), G06Q (business and administrative data processing) and G06V (image and video recognition), each covering 37.5% of the 16 records in scope. G01N, material analysis and testing, follows at 31.3%. Because a record can carry multiple classes, these figures overlap, but the pattern is clear: quantification claims are being written primarily around data processing and imagery analysis rather than sensor hardware alone.
US20220205964A1, assigned to Scientific Aviation, Inc. and published 2022-06-30, describes a remotely deployable, off-grid system that autonomously detects and quantifies methane and other gas emissions, correcting for interfering gases and temperature drift to improve accuracy. It is the second most-cited record in this dataset, indicating other filers have built on or referenced its approach to autonomous emissions reporting. Anyone designing an autonomous, sensor-based quantification system should review its claims closely before finalizing a similar architecture.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.