Category: Media

The EU Methane Regulation is reshaping emissions reporting and methane management worldwide. Learn what it means for operators and how SeekOps can help support compliance and emissions reduction efforts for your company.

Read time: 5 minutes

Methane has increased in priority within regulation to no longer being just an environmental concern. With the European Union’s Methane Regulation (EU 2024/1787) now coming to center stage, operators across the oil and gas value chain are facing a new period of measurement, reporting, verification, and emissions reduction requirements.

While much of the discussion has focused on European operators, the regulation’s impact extends well beyond the EU’s borders. Because Europe imports a significant portion of its oil and gas, the regulation also introduces new expectations for producers and exporters supplying energy into European markets. Yes, this means any asset along the value chain even if it’s located anywhere from Malaysia to Nigeria to Texas.

For operators, the message is clear that methane emissions must increasingly be measured, understood, documented, and reduced using transparent and defensible methodologies.

This update creates some obstacles, but it also creates an opportunity to improve emissions visibility and strengthen confidence in reported data.

What Is the EU Methane Regulation?

The European Union Methane Regulation (EU 2024/1787) establishes requirements for the measurement, monitoring, reporting, verification, and reduction of methane emissions across the oil, gas, and coal sectors. The regulation covers several key areas:

• Monitoring, Reporting, and Verification (MRV)

• Leak Detection and Repair (LDAR)

• Restrictions on routine venting and flaring

• Transparency requirements for imported fossil fuels

• Methane intensity reporting for imported energy products

The regulation entered into force in August 2024 and will be implemented through a number of phases extending through 2030. Over time, the requirements will become increasingly focused on direct measurement and transparent reporting rather than reliance on generalized emission factors.

Why This Regulation Is Different

Previous methane regulations have often focused primarily on operators with specific qualifications. The EU regulation is different because it doesn’t differentiate between assets.

The regulation applies not only to EU-based operators but also introduces reporting and transparency requirements for any fossil fuels (oil, gas, and coal) imported into the European market. As implementation continues, importers will increasingly need to demonstrate the quality of methane emissions data associated with their supply chains and provide information on methane management practices used by upstream producers.

Why This Matters for U.S. Exporters

Although the EU Methane Regulation is a European policy, its implications extend far beyond Europe’s borders. For U.S. oil and gas producers exporting LNG, crude oil, or other energy products into European markets, methane performance is now part of commercial discussions.

In the near term, U.S. Exporters will find the most practical pathway for demonstrating compliance with the regulation’s import transparency requirements is alignment with OGMP 2.0 Level 5 reporting, which emphasizes site-level measurements supported by robust methodologies and independent verification. While the regulation allows for the possibility of country-level equivalence determinations in the future, those frameworks are not expected to be available for several years. As a result, operators seeking to demonstrate alignment with the EU’s “highest monitoring standards” will likely need to rely on site- and source-level measurement programs.

The shift is already underway. European buyers are increasingly requesting methane emissions data from suppliers to support their own reporting obligations under the regulation. What was once a voluntary sustainability metric is becoming an operational and commercial consideration across global supply chains.

For operators with mature measurement programs, this creates an opportunity. High-quality emissions data can help demonstrate methane performance, support low-emissions energy claims, and provide transparency to customers and stakeholders. Conversely, operators with limited measurement data may find their methane performance subject to increasing scrutiny as reporting requirements expand and emissions information becomes more publicly available through mechanisms such as the EU’s planned Methane Transparency Database.

One challenge facing the industry is that independent verification capacity remains limited. While the regulation establishes requirements for third-party verification and references existing European accreditation frameworks, the infrastructure needed to support verification at scale is still developing. This makes early preparation particularly valuable for operators seeking to stay ahead of evolving requirements.

The Shift Toward Measurement-Based Reporting

One of the most significant aspects of the regulation is its emphasis on measurement-based emissions management.

Historically, many methane inventories relied heavily on bottom-up calculations using equipment counts and emission factors. While these approaches remain important, the regulation is pushing the industry toward more direct measurement and verification of emissions.

This evolution reflects a broader industry trend. Operators increasingly need to answer questions such as:

• Where are emissions occurring?

• How much methane is being emitted?

• How confident are we in the measurement?

• How do measured emissions compare to inventory estimates?

• Are emissions changing over time?

Answering these questions requires measurement technologies capable of producing defensible, repeatable data under real operating conditions.

The Growing Importance of LDAR Programs

The regulation also places significant emphasis on Leak Detection and Repair (LDAR) programs.

Operators are required to implement regular monitoring programs, identify methane emissions sources, and take timely corrective action when leaks are detected. Repair timelines and documentation requirements are intended to ensure that emissions are not only identified but also repaired when applicable.

For many operators, this means moving beyond periodic inspections and toward a more comprehensive understanding of site-level emissions behavior.

How SeekOps Supports Compliance and Emissions Management

While regulations define the requirements, operators still need practical tools to meet them.

SeekOps supports methane management programs through direct measurement and quantification of emissions using UAV-based sensing technology. Unlike many screening approaches that identify the presence of methane, SeekOps is designed to quantify emissions and provide the data needed to support measurement-informed decision making.

Our methodology combines methane concentration measurements with in-situ environmental measurements collected during flight. Wind speed, wind direction, temperature, and atmospheric conditions are measured directly and incorporated into the quantification process.

This approach provides several benefits that align closely with the objectives of the EU regulation.

Measurement-Based Quantification

As reporting frameworks increasingly move toward measured emissions rather than generalized assumptions, operators need reliable methods for quantifying methane.

SeekOps’ top-down quantification approach measures emissions as they exist in the atmosphere, providing an independent assessment of site-level emissions that can complement traditional inventory methods.

Support for LDAR Programs

SeekOps measurements can help operators identify and prioritize significant emission sources for investigation and repair. By quantifying emissions, operators can focus mitigation efforts where they will have the greatest impact.

Inventory Reconciliation

One of the challenges many operators face is understanding differences between measured emissions and inventory estimates.

SeekOps measurements provide an independent dataset that can help operators validate inventories, investigate discrepancies, and improve emissions reporting accuracy.

Transparent Uncertainty

Increasing regulatory scrutiny means confidence in measurement results matters as much as the measurements themselves.

SeekOps is unique in its ability to measure key environmental variables in-situ during each survey and propagate those uncertainties through the quantification process. The result is a measurement accompanied by a transparent uncertainty estimate tied directly to the conditions experienced during the survey. This additional layer of transparency helps operators understand not only what was measured, but how confident they can be in the result.

Looking Beyond Compliance

Although the EU Methane Regulation is often discussed in terms of compliance, its broader significance is that it accelerates the industry’s transition toward measurement-informed emissions management.

Operators that develop robust methane measurement programs today will be better positioned to respond to future reporting requirements, investor expectations, customer requests, and regulatory changes.

Measurement-based approaches can also provide operational benefits beyond compliance by helping operators:

• Identify emissions reduction opportunities

• Verify mitigation effectiveness

• Improve inventory accuracy

• Demonstrate environmental performance

• Strengthen stakeholder confidence

Preparing for the Future

The EU Methane Regulation represents one of the most comprehensive methane frameworks implemented to date. Its influence is expected to extend well beyond Europe as operators, importers, and regulators adopt more transparent approaches to methane management.

For operators, success will depend on the ability to move beyond estimates and toward defensible measurement.

SeekOps is helping support that transition by providing direct methane quantification, in-situ environmental characterization, and transparent uncertainty estimation that align with the industry’s growing demand for high-quality methane data.

As methane management continues to evolve, accurate measurement will increasingly become the foundation where effective reporting, mitigation, and operational decision-making are built.

References

European Union. (2024). Regulation (EU) 2024/1787 on the reduction of methane emissions in the energy sector. EUR-Lex. https://eur-lex.europa.eu/eli/reg/2024/1787/oj/eng

International Energy Agency (IEA). EU regulation on the reduction of methane emissions in the energy sector. https://www.iea.org/policies/18209-eu-regulation-on-the-reduction-of-methane-emissions-in-the-energy-sector

Oxford Institute for Energy Studies. Analysing the EU Methane Regulation: what is changing, for whom and by when? https://www.oxfordenergy.org/publications/analysing-the-eu-methane-regulation-what-is-changing-for-whom-and-by-when/

Carbon sensors are critical tools for emissions monitoring and climate reporting. Explore how NDIR, TDLAS, and CRDS technologies work, their strengths, and where they still face limitations.

Read time: 5 minutes

As global attention turns toward decarbonization and emissions transparency, the ability to measure carbon dioxide (CO₂) accurately and reliably has never been more important. From climate research to industrial monitoring and methane mitigation programs, carbon sensors have become foundational tools for understanding how carbon moves through our atmosphere and infrastructure.

But like any measurement technology, carbon dioxide sensing comes with both strengths and limitations. While the technology has advanced significantly in recent years, understanding what these sensors can, and cannot, do is critical for interpreting the data they produce.

In this post, we explore where carbon dioxide sensing technology stands today, what types of sensors are commonly used, and how they fit into the evolving landscape of emissions monitoring.

Why Carbon Measurement Matters

Carbon dioxide is the most widely tracked greenhouse gas and plays a central role in climate reporting frameworks, emissions inventories, and atmospheric research. Measuring CO₂ helps operators and researchers:

• Track emissions from industrial processes and energy production

• Validate reported emissions inventories

• Understand combustion efficiency and fuel use

• Improve atmospheric transport models

• Support regulatory and voluntary reporting frameworks

Because CO₂ is produced alongside methane in many industrial processes, measuring both gases together can provide important context when interpreting emissions data.

Common Types of Carbon Dioxide Sensors

Several sensor technologies are used to measure carbon dioxide, each with its own advantages depending on the application.

Non-Dispersive Infrared (NDIR) Sensors

NDIR sensors are among the most widely used CO₂ detection technologies. They work by measuring how infrared light is absorbed by CO₂ molecules within a sample cell. Their popularity comes from a combination of reliability, relatively low cost, and ease of deployment. NDIR sensors are commonly used in building ventilation systems, indoor air monitoring, and portable environmental sensors. However, while NDIR sensors are robust and versatile, they generally offer lower precision than more advanced spectroscopic methods and may require periodic calibration to maintain accuracy. Additionally, NDIR sensor can have reduced selectivity where some other species or instrumental signals can sometimes mimic the signal of CO₂.

Tunable Diode Laser Absorption Spectroscopy (TDLAS)

TDLAS technology uses a narrow-band laser tuned to a specific gas absorption line. This enables extremely precise detection of gas concentrations and is widely used in industrial and research environments. Because TDLAS sensors measure gas absorption directly at specific wavelengths, they offer excellent disambiguation from other gases and fast response times. Additionally, these sensors are characteristically lightweight and require low power, so they are well suited for mobile applications like on drones. The tradeoff is complexity and cost. Laser-based systems are typically more expensive than NDIR and may require careful optical alignment and calibration.

Cavity Ring-Down Spectroscopy (CRDS)

CRDS is one of the most precise techniques available for atmospheric gas measurement. It works by measuring how quickly a laser pulse decays inside a highly reflective optical cavity. Because the light travels thousands of times through the gas sample, CRDS systems can achieve extremely high sensitivity and accuracy. These systems are widely used in atmospheric research and high-end emissions monitoring. However, they also require longer sampling time which makes surveying large areas more time consuming and increases uncertainty due to atmospheric variability. An additional downside is that CRDS instruments are generally larger, more expensive, and highly sensitive to vibration, making them less suitable for lightweight mobile deployments compared to other sensor technologies.

The Strengths of Modern Carbon Dioxide Sensors

Over the past decade, carbon dioxide sensing technology has improved dramatically in several key ways. Sensors have become smaller and more ruggedized, enabling deployment on mobile platforms such as drones, aircraft, and autonomous monitoring systems. Advances in optics and electronics have also improved detection limits and stability, allowing for higher confidence measurements in dynamic environments. Another important development is the integration of environmental sensing. Many modern systems measure temperature, pressure, and wind conditions alongside gas concentrations, allowing measurements to be interpreted in a more physically meaningful way. SeekOps has a long heritage in leading such advancements in ruggedization, precision engineering, and scientific validation. Together, these improvements have expanded the range of applications for carbon sensors, from laboratory instruments to field-ready monitoring tools.

Where Carbon Sensors Still Struggle

Despite these advances, carbon sensing is not without challenges. One limitation is that CO₂ concentrations are naturally high in the atmosphere relative to methane. This means that detecting small incremental changes in CO₂ can be more difficult, particularly in open environments where background concentrations fluctuate. Environmental factors can also affect measurements. Temperature variations, humidity, and pressure changes can introduce measurement drift if not properly accounted for.

Another challenge lies in the fact that many carbon sensing technologies were originally developed for applications such as indoor air quality monitoring, industrial process control, or carbon capture, utilization, and storage (CCUS). These use cases often prioritize stable, high-concentration environments or point measurements, rather than detecting subtle concentration enhancements from combustion sources at a distance. As a result, applying these sensors to open-air emissions monitoring, especially in dynamic environments, can introduce additional limitations.

A further challenge lies in translating concentration measurements into actual emissions rates. Measuring gas concentration alone does not directly reveal how much gas is being emitted. To estimate emission rates, measurements must be combined with wind data and atmospheric transport models or data-driven measurement strategies designed to avoid such models. This is why many modern monitoring systems integrate gas sensors with meteorological instruments and modeling frameworks.

Carbon Dioxide Sensors in Emissions Monitoring

As methane monitoring programs evolve, CO₂ measurement is increasingly being used as a complementary tool. For example, CO₂ measurements can help evaluate combustion processes such as flaring, where carbon dioxide and methane ratios can indicate flare efficiency. They can also help validate bottom-up emissions inventories by providing an independent top-down perspective. Because methane and carbon dioxide often originate from related processes, measuring both gases together can improve source attribution and reduce uncertainty in emissions estimates.

The Road Ahead for Carbon Sensing

The next generation of carbon sensing technology is likely to focus on three areas: increased sensitivity, better environmental integration, and broader deployment. Miniaturization will continue to enable smaller, lighter sensors suitable for drones and autonomous platforms. Improved calibration techniques and sensor fusion will reduce measurement drift and improve reliability in field environments. At the same time, integration with atmospheric modeling tools will make it easier to translate concentration measurements into actionable emissions data. As emissions monitoring frameworks such as OGMP 2.0 and other measurement-based reporting programs mature, the demand for reliable, field-ready carbon sensing technologies will continue to grow.

SeekOps’ Carbon Dioxide Measurement Capabilities

While SeekOps is best known for its methane detection and quantification systems, our sensing platform is expanding to include the ability to measure carbon dioxide alongside methane. This evolution reflects a broader industry shift toward multi-gas measurement as a way to better understand emissions behavior in complex environments.

We are deploying this capability in the field, with our flagship application in combining methane (CH₄) and carbon dioxide (CO₂) measurements. These campaigns provide valuable insight into how simultaneous measurements can improve interpretation of combustion processes, emissions attribution, and overall site performance.

We expect to learn more about the practical benefits and limitations of measuring both gases together in real-world conditions. We’ll be sharing those insights in more detail in a future post focused specifically on simultaneous multi-gas measurement.

As carbon measurement technologies continue to evolve, integrating multiple gas measurements with in situ environmental data will play an increasingly important role in improving transparency and confidence in emissions data.

References

Hodgkinson, J., & Tatam, R. P. (2013). Optical gas sensing: A review. Measurement Science and Technology, 24(1), 012004. https://doi.org/10.1088/0957-0233/24/1/012004

Werle, P., Mücke, R., & Slemr, F. (2002). The limits of signal averaging in atmospheric trace-gas monitoring by tunable diode-laser absorption spectroscopy. Applied Physics B, 57, 131–139. https://doi.org/10.1007/BF00425997

Berden, G., Peeters, R., & Meijer, G. (2000). Cavity ring-down spectroscopy: Experimental schemes and applications. International Reviews in Physical Chemistry, 19(4), 565–607. https://doi.org/10.1080/014423500750040627

Zimmerle, D., Vaughn, T., Bell, C., Bennett, K., Deshmukh, P., & Thoma, E. (2020). Detection limits of optical gas imaging for natural gas leak detection in realistic controlled conditions. Environmental Science & Technology, 54(18), 11506–11514. https://doi.org/10.1021/acs.est.0c01285

U.S. Environmental Protection Agency (EPA). (2023). Greenhouse Gas Reporting Program: Subpart W – Petroleum and Natural Gas Systems. https://www.epa.gov/ghgreporting

National Institute of Standards and Technology (NIST). (2022). Carbon Dioxide Measurement Techniques and Calibration Standards. https://www.nist.gov

Offshore research shows hidden methane emissions during loading operations and the value of UAV-based measurement and real-time field data.

Read time: 4 minutes

Offshore methane emissions remain one of the least understood components of the global emissions landscape. While production platforms, flaring, and venting are relatively well studied, other parts of the offshore value chain have received far less attention.

A recent study published in Environmental Science: Processes & Impacts highlights one of these gaps: methane emissions during oil loading operations to shuttle tankers. The work was conducted at a Floating Production Storage and Offloading (FPSO) asset for a major operator on the UK Continental Shelf and combines aircraft and UAV measurements across a full loading cycle to better understand how emissions occur and how much may currently be missing from inventories.

A Previously Under-Characterized Source of Emissions

The study focuses on emissions associated with transferring oil from an FPSO to a shuttle tanker. While these operations are routine offshore, their methane emissions have historically been difficult to quantify.

Using both SeekOps UAV and the Facility for Airborne Atmospheric Measurements (FAAM) aircraft measurements, the study observed that methane emissions increase during loading events, with estimated rates spanning a wide range depending on measurement approach and sampling conditions. Importantly, the two independent measurement methods were correlated across event type, with higher emissions during tanker loading activity.

What makes this finding particularly important is that these emissions are not tied to static infrastructure, but are driven by operational activity at the FPSO during loading. When scaled over time, the study found that loading-related emissions can contribute a meaningful fraction of total site emissions, suggesting that inventories focused only on steady-state processes may miss a significant portion of the picture.

Why This Matters for Methane Inventories

Traditional methane inventories rely heavily on bottom-up methods, where emissions are estimated based on equipment counts, emission factors, and assumed operating conditions.

This study reinforces a growing industry realization: not all emissions fit neatly into those assumptions.

Offshore operations, especially on FPSOs like the one in this study, are inherently dynamic. Activities such as loading cycles, maintenance, and process fluctuations introduce variability that is difficult to capture with static emission factors alone. As a result, inventories may underestimate emissions if these transient events are not explicitly measured.

The Role of Measurement-Based Approaches

One of the most important aspects of this study is its reliance on real-time measurements. By directly observing methane concentrations during real operations, the researchers were able to capture emissions that would likely otherwise go unaccounted for.

This represents a broader shift in methane monitoring, from estimating emissions based on assumptions to measuring what is actually happening in the field.

It also highlights the importance of capturing emissions across complete operational cycles, particularly for offshore assets like FPSOs, where emissions can vary significantly depending on operational state.

Implications for Offshore Measurement Strategies

The findings suggest that offshore methane monitoring must extend beyond traditional sources and account for how operations evolve over time. Capturing emissions from loading events, for example, requires both spatial coverage and temporal awareness, understanding not just where emissions occur, but when.

Technologies deployed offshore must therefore be capable of responding to dynamic conditions, capturing transient plumes, and operating safely within complex logistical environments such as FPSO loading operations.

What This Means for SeekOps

For SeekOps, this study reinforces several core principles that have shaped our offshore measurement approach.

First, it highlights the importance of mobility and adaptability. Offshore emissions, particularly those associated with operations like FPSO loading, do not always occur in predictable locations or at steady rates. UAV-based systems provide the flexibility to respond to operational events as they happen.

Second, it strengthens the case for top-down quantification. By measuring methane concentrations downwind and reconstructing plume behavior through a flux plane, SeekOps captures emissions as they manifest in the atmosphere rather than relying on assumptions about source behavior. In addition, the study showed that UAV-based measurements were broadly consistent with airborne observations collected during the same operations, providing an additional layer of validation across independent measurement approaches.

Third, the study underscores the importance of in situ environmental measurement. Offshore plume behavior is heavily influenced by wind, stability, and marine boundary-layer effects. Measuring these variables directly during flight improves the reliability of emission estimates in dynamic conditions. It also increases the granularity of emissions attribution as we consider the variables.

Finally, the study reinforces a broader industry shift: measurement is uncovering emissions that inventories alone cannot fully describe. SeekOps’ approach is designed to complement existing inventory methods by helping operators reconcile measured data with reported values and identify gaps, particularly for operational emissions that are not easily captured in traditional frameworks.

Looking Ahead

Offshore methane monitoring is entering a new phase. As regulatory frameworks evolve and expectations for transparency increase, operators will need measurement strategies that reflect real-world conditions that capture both steady-state emissions and transient operational events.

Studies like this one — and recent work such as Deshpande et al. (2025) — provide a roadmap for how to get there.

For SeekOps, they reinforce the role of UAV-based measurement as a critical tool for understanding offshore emissions in full context, not just what is emitted, but when, where, and why.

References

Deshpande, S., Collins, E., Joynes, I., & O’Keeffe, R. (2025). Methane emissions measurement insights from an Offshore Measurement, Monitoring, Reporting and Verification study. Australian Energy Producers Journal, 65(2), EP24038. https://doi.org/10.1071/EP24038

Methane emission from shuttle tankers during standard oil loading operations. (2026). Environmental Science: Processes & Impacts. Royal Society of Chemistry. https://pubs.rsc.org/en/content/articlehtml/2026/em/d5em00768b

Ravikumar, A. P., et al. (2019). Single-blind inter-comparison of methane detection technologies – results from the Stanford/EDF Mobile Monitoring Challenge. Elementa: Science of the Anthropocene, 7, 37. https://doi.org/10.1525/elementa.373

SeekOps brings precision methane monitoring to the Gulf using UAV-based quantification to deliver accurate, quantified emissions data.

Read time: 5 minutes

From offshore platforms to coastal terminals, the Gulf region presents some of the most challenging conditions for methane detection and quantification anywhere in the world. At SeekOps, we’ve brought our drone-based, in situ measurement approach to this environment, pushing the limits of precision, transparency, and field resilience. This blog highlights the work we’ve done across the Gulf, the insights gained, and how these projects demonstrate the strengths that set SeekOps apart.

Why the Gulf Matters for Methane Monitoring

The Gulf of America is one of the world’s busiest offshore energy corridors. The region’s atmospheric conditions like wind shear over open water, shifting pressure systems, and complex plume behavior make methane monitoring exceptionally difficult. Satellite, fixed wing aircraft, and fixed-sensor approaches struggle in these conditions because they cannot account for the dynamic nature of offshore airflow or atmospheric and sea conditions.

Drone-based methane monitoring in this domain requires a technology that is flexible enough to fly in shifting winds, sensitive enough to detect subtle concentration enhancements, and scientifically rigorous enough to quantify emissions in the presence of marine boundary-layer effects. SeekOps meets these requirements by capturing in situ environmental data alongside gas concentrations, enabling true top-down quantification paired with dynamic uncertainty estimation.

Key Projects & Achievements in the Gulf Region

Offshore Drone Surveys & Top-Down Quantification

SeekOps deploys UAV-based methane quantification offshore, due to its operational flexibility. From vessels and helidecks, our teams fly drones equipped with the SeekIR methane sensor and an integrated suite of environmental sensors. These flights produce a flux plane, an atmospheric slice that captures methane enhancements downwind of a platform. Because we measure wind, temperature, pressure, and stability in real time, each emission rate is associated with a transparent, physics-based uncertainty bound.

For major operators in the Gulf, SeekOps has carried out repeat surveys across more than a dozen offshore assets, providing baseline and repeat measurements with follow up survey campaigns. This follow-up approach allows operators to see how emissions change over time, and how maintenance and process optimization activities influence emission behavior. These surveys have revealed previously unmeasured emissions, clarified flare venting behavior, and validated emissions inventories under the real conditions of offshore production.

Collaboration with Major Operators

SeekOps’ work in the Gulf is part of a broader industry effort to bring consistency and scientific rigor to methane quantification. Through collaborations with major operators, Gulf platforms have become part of a wider set of routine measurement sites spanning multiple continents. This integration has helped transform early R&D-style field tests into a reliable, repeatable surveying framework.

Enhancing Sensitivity in Harsh Conditions

Operating offshore means navigating constantly shifting wind fields, marine boundary-layer turbulence, and the aerodynamic wake effects created by platform structures. These conditions can reshape a methane plume from one minute to the next. SeekOps adapts to this fluid environment by measuring all relevant variables directly at altitude, rather than relying on modeled or assumed conditions. Because the quantification model incorporates the real environmental inputs captured during the flight, emissions are neither underestimated nor overstated due to simplified meteorological assumptions. Each Gulf deployment helps strengthen SeekOps’ understanding of plume transport over water and refine its algorithms and flight paths for future missions.

Client Success Story: Building an Offshore Emissions Profile Across the Gulf

A major Gulf operator sought a measurement program that could deliver credible emissions baselines, track meaningful changes over time, and provide transparent, defensible uncertainty values for internal and external reporting. SeekOps partnered with the operator to design and execute a multi-phase offshore measurement strategy.

The baseline campaign involved UAV flights across multiple assets to establish initial emission rates. The surveys revealed persistent sources, intermittent releases, and flare behavior patterns that were not evident in bottom-up inventories. Because every measurement included a condition-specific uncertainty estimate, the operator could understand not just the magnitude of each emission but also the confidence associated with that value.

SeekOps later returned for follow up, repeat surveys. These revisit measurements proved essential in distinguishing genuine changes in emissions from weather-driven variability. On several platforms, emissions decreased after maintenance activities, and the non-overlapping uncertainty bounds between the baseline and follow-up surveys confirmed that these reductions were real. On other platforms, new intermittent sources emerged, reflecting operational adjustments that had occurred between campaigns.

With two robust datasets in hand, the operator gained a nuanced view of emissions across its Gulf assets. They could see which platforms exhibited stable behavior and which showed evolving emissions profiles. They also gained insight into how plume structure interacts with atmospheric conditions, clarifying when the data were tightly constrained and when natural variability influenced the measurement.

This depth of understanding enabled the operator to prioritize maintenance efforts, refine operational procedures, and build a transparent inventory that could withstand regulatory and ESG scrutiny. The combination of repeatable UAV flight paths, in situ environmental sensing, and dynamic uncertainty modeling transformed their emissions program from reactive to proactively data-driven.

What the Gulf Work Reveals About SeekOps’ Strengths

SeekOps’ Gulf deployments highlight the company’s ability to deliver reliable, scientifically credible methane quantification in some of the most dynamic and challenging environments. Because every measurement is grounded in what the atmosphere was actually doing at the time, operators receive data they can trust, data that reflect reality rather than assumptions. The uncertainty framework travels with the measurement, ensuring that each emission rate is as transparent as it is accurate.

These Gulf campaigns also reinforce that SeekOps’ methods fit seamlessly into regulatory and ESG frameworks. As reporting expectations shift toward defensible, quantified, measurement-based inventories, the ability to pair emission estimates with quantified uncertainty will play an increasingly central role in methane management programs around the world.

Each offshore survey also contributes to SeekOps’ continuous improvement, refining flight planning, plume modeling, and environmental interpretation. The Gulf’s complex meteorology accelerates the evolution of these tools, shaping future enhancements across all operating regions.

Charting the Future of Offshore Methane Monitoring

SeekOps’ work in the Gulf illustrates what happens when engineering excellence meets atmospheric science. By measuring where others estimate, and by quantifying uncertainty where others assume it, we are helping operators build a transparent, data-driven path to methane reduction. The Gulf is where innovation meets accountability, and SeekOps continues to set the benchmark for precision in offshore methane measurement.

References

Rodgers, C. D. (2000). Inverse Methods for Atmospheric Sounding: Theory and Practice. World Scientific Publishing.

Burton, S. P., Hair, J. W., Kahnert, M., Ferrare, R. A., Hostetler, C. A., Cook, A. L., Harper, D. B., Berkoff, T. A., Seaman, S. T., Collins, J. E., Fenn, M. A., & Rogers, R. R. (2016). Observations of the spectral dependence of linear particle depolarization ratio of aerosols using NASA Langley airborne High Spectral Resolution Lidar. Atmospheric Measurement Techniques, 9, 5555–5572. https://doi.org/10.5194/amt-9-5555-2016

Corbett, A., & Smith, B. (2022). FluxPlane Methodology for Methane Quantification. SeekOps Internal Report.

SeekOps Inc. (2024). Offshore Methane Quantification Capabilities.

SeekOps & bp Case Study. (2024). Standardizing Methane Emissions Measurement Through Drone-Based Quantification. Climate Investment.

BOEM. (2023). Offshore Oil and Gas Infrastructure in the Gulf of Mexico.

EPA. (2023). Methane Emissions and Mitigation in Offshore Oil and Gas Production.

SeekOps’ dynamic uncertainty method sets a new standard for methane measurement accuracy by analyzing in situ variables like wind, temperature, and pressure, and dynamically propagating uncertainty to deliver transparent, defensible emissions data.

Read time: 5 minutes

When it comes to measuring methane emissions, knowing how much is only part of the story. Equally important is understanding how confident we can be in that number.

At SeekOps, our technology doesn’t just detect and quantify methane, it also quantifies the uncertainty in every measurement, based on the actual real time survey conditions. This framework, which we call dynamic uncertainty, brings transparency, traceability, and scientific rigor to methane emissions data.

Why Uncertainty Estimation Matters

In environmental monitoring, uncertainty is not a weakness; it’s an acknowledgment of reality. Every emission quantification is influenced by multiple variables: sensor precision, wind speed and direction, temperature gradients, atmospheric turbulence, and model assumptions.

Many methane measurement systems handle this complexity by assigning a fixed uncertainty across all measurements. But the real atmosphere doesn’t behave that way. Each survey has its own meteorology, each plume its own structure, and each flight its own sampling geometry.

At SeekOps, we believe every emission requires its own uncertainty assessment, one that reflects what actually happened in the field. That’s the foundation of dynamic uncertainty.

From Components to Confidence: The Physics of the Flux Plane

Our quantification framework begins with the flux plane, the core output of SeekOps’ methane quantification system. The flux plane represents a vertical, gridded slice of the atmosphere that captures methane concentration enhancements along the drone’s flight path.

Each grid cell corresponds to an integrated measurement of methane mixing ratio, air density (measured by temperature and pressure), and wind speed. When combined, these data reconstruct a 2D flux field which is essentially a picture of how methane moves through the air at a given moment.

Mathematically, the total mass flux through the plane is computed as:

$$
\dot{m}_i = \frac{M_i}{M_{\text{air}}}
\sum_{y,z} \rho_{\text{air}}(y,z) \,
\chi_i(y,z) \,
u_{\perp}(y,z) \,
\Delta y \, \Delta z
\tag{1}
$$

Where:
•   ρ_air: dry air density (from in situ pressure & temperature)
•   χ_i: measured methane enhancement mole fraction
•   u_⊥: wind velocity component normal to the plane
•   M_i/M_air: molar mass ratio of methane to dry air
•   Δy, Δz : grid spacing in the horizontal and vertical directions, respectively

The integration of all these cells yields the total methane emission rate for the surveyed source (ṁ_i). Note that wind direction factors in here as u_⊥ = u cos(Φ) where Φ is the angle between the incident wind direction and the flux plane normal vector.

Step 1: Decomposing the Sources of Error

The first step in quantifying dynamic uncertainty is identifying where uncertainty comes from. Some of these sources were described by Mohammadloo et al. (2025) and include:
•   Instrument errors — from the SeekIR methane sensor and onboard environmental sensors (relatively small contributor).
•   Environmental variability — fluctuating winds, turbulence, and thermal stratification (moderate contributor).
•   Sampling geometry — how well the drone’s flight pattern intersects the plume (largest contributor).
•   Model assumptions — simplifications made in the mass balance and atmospheric transport equations.

At SeekOps, our emission solution explicitly measures the variables that influence some of these error sources. So, we can put it all together to see how each contributes to the overall uncertainty in our delivered emission rate.

Step 2: Defining the Error Propagation Framework

The flux plane’s uncertainty is computed using optimal estimation theory, a framework originally developed for satellite and lidar retrievals (e.g., Rodgers, 2000; Burton et al., 2016).

We define the measurement state vector as:

$$
\textbf{x} \in
\begin{cases}
\Delta \textrm{y} &: \text{distance along the flux plane},\\
\Delta \textrm{z} &: \text{vertical step of drone intervals},\\
u &: \text{wind speed},\\
\theta &: \text{wind direction},\\
T &: \text{temperature},\\
P &: \text{pressure},\\
\chi &: \text{gas enhancement concentration}
\end{cases}
$$

and the forward model F(x) that outputs the retrieved mass flux is given by Eq. (1).

Uncertainty is then propagated by differentiating the mass balance equation per each state parameter using central finite differencing which applies first-order Taylor expansion to ignore high order terms. This process builds the Jacobian matrix (K).

Covariance matrices that describe the empirical variability from controlled release studies (presented in Corbett and Smith, 2022), instrument accuracy, and measurement variability are constructed and propagated with K per the optimal estimation framework.

The terms in our error propagation framework are:

Step 3: Building the Covariance Matrices

The total prior covariance matrix combines random, measurement, and empirical components:

$$
S_\textrm{a}=S_\textrm{r}+S_\textrm{m}+S_\textrm{e}
$$

Each term plays a specific role:
•   S_r: random measurement noise
•   S_m: atmospheric state variable correlations
•   S_e: empirical uncertainty (~30% derived from validation campaigns)

The posterior covariance matrix incorporates correlation across the flux plane grid and state variable sensitivity through the Jacobian:

$$
S_\textrm{p}=\left( K^TS_\textrm{g}^{-1}K+S_\textrm{a}^{-1}\right)^{-1}
$$

Here, K represents the forward model sensitivity matrix (Jacobian) and S_g is the measurement covariance across the flux plane grid.

These matrices allow SeekOps to translate the field measurements into gridded uncertainty estimates and state variable uncertainty components, showing not only how much methane was detected but also how reliable each part of the plane is, and which state variables contribute most to the overall error.

Step 4: Visualizing the Uncertainty Grid

Once the covariance and Jacobian are computed, the uncertainty is reshaped into a 2D spatial grid corresponding to the flux plane geometry.

Each grid cell now contains a local estimate of uncertainty (σ) in the same units as the mass flux (e.g., kg/hr). The uncertainty grid looks similar to our plume concentration enhancements as the highest uncertainty typically occurs in the same spatial region where the signal is strongest, because that is where the model is doing the most “work.” In contrast, areas far outside the plume contribute almost nothing to the mass flux calculation, so even if there is noise there, its impact on the final emission estimate is negligible. As a result, the uncertainty naturally concentrates where the plume energy is, reflecting where errors actually matter.

• The top image shows the spatial distribution of uncertainty. Brighter areas indicate regions of greater variability — for instance, where the plume edges were only partially captured or where wind shear increased error propagation.
• The bottom chart visualizes a state parameter sensitivity analysis, showing how much each variable (wind, concentration, temperature, etc.) contributes to the total uncertainty.
• Together, these visualizations demonstrate how dynamic uncertainty converts complex retrieval theory into an intuitive map of measurement confidence.

Finally, the total uncertainty is computed as the quadrature sum of the gridded variances:

$$
\sigma_{\textrm{total}}=\sqrt{\sum_{\textrm{i}}\sigma_{\textrm{i}}^2}
$$

and reported as a one-standard-deviation range on the emission estimate:

$$
M_{\textrm{i}}\pm\sigma_{\textrm{total}}
$$

Step 5: Interpreting Dynamic Uncertainty in the Field

Dynamic uncertainty means that every SeekOps emission rate reflects its true field context.
•   In steady, well-defined plume conditions, uncertainty tightens.
•   In variable atmospheres and ill-defined plume geometries, it widens.

Rather than masking that variability, we make it visible. Each measurement’s confidence is quantified and mapped, providing operators and regulators with a transparent view of what’s known, and what’s less certain.

This empowers operators to:
•   Compare sites and surveys with statistical rigor.
•   Prioritize mitigation based on both emission size and confidence.
•   Defend results in ESG or regulatory reporting with traceable mathematical justification.

Looking Ahead: Beyond Dynamic Uncertainty

Dynamic uncertainty is the first half of a broader quantification philosophy. The next stage of SeekOps’ framework will address scenario uncertainty: accounting for “what if” cases like plumes drifting between flight lines or unmeasured variability in time.

Together, these two frameworks will deliver a total uncertainty envelope, encompassing both measurable and inferential confidence limits, an industry first for drone-based methane quantification.

How Uncertainty Transparency Informs the Future Standard

By making uncertainty visible, quantified, and tied directly to real field conditions, SeekOps is enabling the industry to move beyond “black box” emissions reporting and toward evidence-based methane accountability. This level of transparency is exactly what emerging regulatory frameworks, methane intensity certifications, and voluntary reporting programs are beginning to demand, not just a number, but how confident we are in that number.

As methane standards evolve, the expectation will shift from simply reporting emissions to demonstrating defensibility, being able to show why a measurement should be trusted, how it responds to weather and operational conditions, and how it compares across time and technologies. SeekOps’ dynamic uncertainty framework future-proofs operators by aligning directly with this direction of travel. It transforms methane quantification from a static output into a traceable, decision-grade dataset, the foundation required for what will become the next generation of international measurement standards.

References

Corbett, A., & Smith, B. (2022). Study of a Miniature TDLAS System Onboard Two Unmanned Aircraft to Independently Quantify Methane Emissions from Oil and Gas Production Assets and Other Industrial Emitters. Atmosphere, 13(5), 804. https://doi.org/10.3390/atmos13050804

Burton, S. P., Hair, J. W., et. al. (2016). Observations of the spectral dependence of linear particle depolarization ratio of aerosols using NASA Langley airborne High Spectral Resolution Lidar. Atmospheric Measurement Techniques, 9, 5555–5572. https://doi.org/10.5194/amt-9-5555-2016

Rodgers, C. D. (2000). Inverse Methods for Atmospheric Sounding: Theory and Practice. World Scientific.

Discover how SeekOps combines advanced engineering, scientific rigor, and operational know-how to deliver reliable, field-validated methane monitoring solutions worldwide.

Read time: 5 minutes

Why Integration Matters

In methane emissions monitoring, success doesn’t come from technology alone. It’s the integration of engineering design, scientific validation, and operational execution that sets SeekOps apart. Each survey requires not only advanced hardware but also the methodologies to use it effectively and the field expertise to adapt to real-world conditions.

SeekOps was built on this integration. From the earliest development of the SeekIR sensor at NASA’s Jet Propulsion Laboratory to today’s global deployment across six continents, the mission has always been the same: to combine the best of science and engineering with practical, real-world operations that make data both reliable and actionable.

Engineering Excellence – Technology Built for the Field

At the heart of SeekOps is the SeekIR sensor, a lightweight, high-sensitivity methane detector capable of measuring emissions down to parts per billion. Its origins in NASA’s Mars Curiosity Rover program demanded extreme durability and precision, and that legacy continues today.

But engineering doesn’t stop at the sensor. SeekOps systems are drone-agnostic, ruggedized, and efficient. This engineering foundation ensures that every mission can be executed safely, efficiently, and with high-quality data capture whether onshore, offshore, or in complex industrial environments.

Scientific Rigor – Measurement You Can Trust

Technology alone isn’t enough; it must be scientifically validated. That’s why SeekOps emphasizes continuous field validation and peer-reviewed collaboration. Our methods are grounded in spectroscopy, fluid dynamics, and controlled release testing, ensuring that every measurement is backed by science, not assumption.

SeekOps technology has been validated in:

• Blind controlled release trials such as METEC and landfill experiments.

• Independent academic research comparing technologies for detection and quantification.

• Peer-reviewed publications and global methane trials, including TADI 2024 and inter-comparison studies.

This scientific rigor translates into uncertainty reporting, confidence intervals, and reconciliation analysis, giving operators not just numbers, but numbers they can stand behind in regulatory and ESG contexts.

Operational Expertise – Delivering in the Real World

Even the best sensor and methods fall short without operational excellence. That’s why SeekOps invests heavily in training, safety, and adaptability. Our field teams are experienced in working alongside ongoing operations without disrupting production or safety protocols.

Operational expertise means launching drones from helidecks, supply vessels, or tight industrial installments, adapting flight plans in real time to shifting winds or unexpected hazards, and ensuring consistency by repeating flight paths for comparative analysis.

By uniting engineering and science with field know-how, SeekOps ensures that technology translates into reliable performance under the toughest conditions.

The Advantage in Action

SeekOps’ combined approach delivers tangible value to operators:

• Regulatory Compliance – Data that meets international standards like OGMP 2.0, EPA rules, and EU Methane Regulation.

• Operational Efficiency – Faster survey turnaround with live GCS streaming and FASTR reporting.

• Trusted Transparency – Uncertainty and reconciliation included in every report.

• Global Reach – Proven deployments across North and South America, Europe, the Middle East, Africa, Asia, and Australia.

From oil and gas fields in Texas to offshore rigs in the North Sea, from tropical biogas plants to desert well pads, SeekOps delivers consistent, high-quality results that operators can act on with confidence.

Building a More Sustainable Future

The climate challenge demands not only innovation but also collaboration. SeekOps works hand-in-hand with operators, regulators, and research institutions to ensure that emissions monitoring evolves with industry needs and global climate goals.

By uniting engineering ingenuity, scientific rigor, and operational expertise, SeekOps empowers industries to measure, manage, and ultimately reduce methane emissions. It’s not just about technology; it’s about making emissions data actionable in the pursuit of a more sustainable energy future.

Ready to see the SeekOps Advantage for yourself?
Request a Demo today and discover how SeekOps can help you achieve your emissions monitoring and sustainability goals.

References

Webster, C. R. (2005). Measuring methane and its isotopes 12CH₄, 13CH₄, and CH₃D on the surface of Mars with in situ laser spectroscopy. Applied Optics, 44(7), 1226–1235. https://doi.org/10.1364/AO.44.001226

NASA (National Aeronautics and Space Administration). (2019). Methane Detector Sniffs Out Leaks. NASA Technology Transfer Program. https://spinoff.nasa.gov/Spinoff2019/ps_7.html

Ravikumar, A. P., Sreedhara, S., Wang, J., et al. (2019). Single-blind inter-comparison of methane detection technologies – results from the Stanford/EDF Mobile Monitoring Challenge. Elementa: Science of the Anthropocene, 7(1), 37. https://doi.org/10.1525/elementa.373

Corbett, A., & Smith, B. (2022). Study of a Miniature TDLAS System Onboard Two Unmanned Aircraft to Independently Quantify Methane Emissions from Oil and Gas Production Assets and Other Industrial Emitters. Atmosphere, 13(5), 804. https://doi.org/10.3390/atmos13050804

Smith, B. J., Buckingham, S., Touzel, D., et al. (2021). Development of Methods for Top-Down Methane Emission Measurements of Oil and Gas Facilities in an Offshore Environment Using a Miniature Methane Spectrometer and Long-Endurance UAS. SPE Annual Technical Conference and Exhibition, Dubai, UAE. https://doi.org/10.2118/206181-MS

Tavner, C. A., Touzel, D. F., & Smith, B. J. (2021). Application of Long-Endurance UAS for Top-Down Methane Emission Measurements of Oil and Gas Facilities in an Offshore Environment. SPE Offshore Europe Conference and Exhibition, Virtual. https://doi.org/10.2118/205467-MS

Hossian, R. I., et al. (2024). A Controlled Release Experiment for Investigating Methane Measurement Performance at Landfills. Environmental Research and Education Foundation (EREF). https://erefdn.org/eref-funded-study-highlights-advances-in-measuring-landfill-methane-emissions

Dawson, K. W., Smith, B. J., Stocker, I., & Evans, P. (2024). Assessing the Application of Drone TDLAS Methane Emissions Monitoring Technology in the Intertropical Convergence Zone Using Machine Learning. APOGCE 2024. https://doi.org/10.2118/221317-MS

Gully-Santiago, M. A., Smith, B., Frederick, T., Dawson, K., & Elliott, D. (2025). Results and Learnings from the TADI 2024 Methane Quantification Trial. SPE Europe Energy Conference and Exhibition, Vienna, Austria. https://doi.org/10.2118/225634-MS

Learn how SeekOps helps operators compare measured and reported methane emissions using reconciliation reporting and the Celsius analytics platform.

Read time: 5 minutes

Beyond Measurement: Why Reconciliation Matters

Accurately detecting and quantifying methane emissions is just the first step. But raw data, no matter how precise, doesn’t solve the bigger question: what does this mean for the operator?

That’s where reconciliation comes in. At SeekOps, we don’t just hand over measurement numbers, we can help operators interpret them in the context of what’s already known. Reconciliation aligns top-down measured data with bottom-up reported values from emissions inventories, equipment logs, and operational activity.

This “closing of the loop” delivers practical insights. It helps operators meet regulatory and voluntary reporting standards like OGMP 2.0, EPA requirements, and the EU Methane Regulation for one. Additionally, it can improve the accuracy of corporate emissions inventories, identify sources that may be under- or over-reported in bottom-up data, and feed continuous improvement cycles for emissions reduction strategies.

In short, reconciliation turns numbers into context, and context into action.

What Is Reconciliation Reporting?

Reconciliation reporting is the process of comparing what is measured during a SeekOps survey to what is reported by the operator. A SeekOps Reconciliation Report provides more than just totals. It includes site-level emissions estimates with uncertainty bounds clearly defined, breakdowns of emissions by equipment groups or component areas, annotations of major discrepancies that warrant further investigation, and suggestions for follow-up actions such as retesting or repairs.

This level of detail helps ensure that operators don’t just comply with requirements but actually gain operational intelligence they can use.

Introducing Celsius – An Emissions Intelligence Dashboard

Measurement and reconciliation are powerful on their own, but they become transformative when paired with Celsius, SeekOps’ cloud-based analytics platform that can be accessed anywhere in the world. Celsius turns raw measurement and reconciliation results into interactive dashboards that make emissions data easy to understand and act on. Rather than static spreadsheets or one-off reports, Celsius provides a central hub for emissions intelligence, a single source of truth accessible across teams, sites, and geographies.

How It Works in Practice

Here’s how SeekOps’ reconciliation and Celsius workflow comes together in real-world operations:

1. Survey Conducted – SeekOps drones scan the site, capturing methane concentrations and wind vectors.

2. Celsius Visualization – Survey results are uploaded into Celsius for easy review, filtering, and export.

3. Emission Quantification – Mass flow rates are calculated using validated top-down scientific models.

4. Data Analysis – Our analysts use Celsius, thoroughly reviewing each survey, to generate reports that inform operators of where their leaks are and how much is leaking

5. Reconciliation – Operators take the finalized report and can compare against their inventories and logs, highlighting gaps or discrepancies.

This workflow ensures not just the data, but the entire data pipeline, is auditable and traceable.

Real-World Value for Operators

For oil & gas producers, landfill operators, or renewable natural gas facilities, the challenge isn’t just detecting methane, it’s proving reductions over time. Regulators and stakeholders alike demand measured, verified, and contextualized data.

SeekOps helps close this gap. By reconciling measurements with reported values, we enable operators to demonstrate compliance with confidence, benchmark emissions performance against industry standards, and support transparent ESG disclosures backed by field-validated science.

From Numbers to Action

Methane reduction isn’t about single measurements, but about building a trusted, repeatable workflow. SeekOps reconciliation and Celsius create that workflow by connecting measurement, interpretation, and reporting.

With this combination, operators move from asking “what are our emissions?” to confidently answering “how are we performing, where can we improve, and how fast can we act?”

Stay tuned for the next post in our series: “The SeekOps Advantage – Uniting Engineering, Science & Operational Expertise”

Want to see how SeekOps reconciliation and the Celsius platform can enhance your emissions management strategy?
Request a Celsius Demo or Ask to Speak to an Expert

References

Corbett, A., & Smith, B. (2022). Study of a Miniature TDLAS System Onboard Two Unmanned Aircraft to Independently Quantify Methane Emissions from Oil and Gas Production Assets and Other Industrial Emitters. Atmosphere, 13(5), 804. https://doi.org/10.3390/atmos13050804

Ravikumar, A. P., Sreedhara, S., Wang, J., et al. (2019). Single-blind inter-comparison of methane detection technologies – results from the Stanford/EDF Mobile Monitoring Challenge. Elementa: Science of the Anthropocene, 7(1), 37. https://doi.org/10.1525/elementa.373

Smith, B. J., Buckingham, S., Touzel, D., et al. (2021). Development of Methods for Top-Down Methane Emission Measurements of Oil and Gas Facilities in an Offshore Environment Using a Miniature Methane Spectrometer and Long-Endurance UAS. SPE Annual Technical Conference and Exhibition, Dubai, UAE. https://doi.org/10.2118/206181-MS

Tavner, C. A., Touzel, D. F., & Smith, B. J. (2021). Application of Long-Endurance UAS for Top-Down Methane Emission Measurements of Oil and Gas Facilities in an Offshore Environment. SPE Offshore Europe Conference and Exhibition, Virtual. https://doi.org/10.2118/205467-MS

Hossian, R. I., et al. (2024). A Controlled Release Experiment for Investigating Methane Measurement Performance at Landfills. Environmental Research and Education Foundation (EREF). https://erefdn.org/eref-funded-study-highlights-advances-in-measuring-landfill-methane-emissions

Dawson, K. W., Smith, B. J., Stocker, I., & Evans, P. (2024). Assessing the Application of Drone TDLAS Methane Emissions Monitoring Technology in the Intertropical Convergence Zone Using Machine Learning. APOGCE 2024. https://doi.org/10.2118/221317-MS

Gully-Santiago, M. A., Smith, B., Frederick, T., Dawson, K., & Elliott, D. (2025). Results and Learnings from the TADI 2024 Methane Quantification Trial. SPE Europe Energy Conference and Exhibition, Vienna, Austria. https://doi.org/10.2118/225634-MS

Discover how SeekOps combines its Ground Control Station with the FASTR system to stream real-time methane data, accelerate reporting, and give operators actionable insights during flight.

Read time: 5 minutes

Real-Time Awareness with GCS

When we fly a site, our UAV operators don’t have to wait hours, or days, to understand what they’re seeing. Our Ground Control Station (GCS) streams live data straight from the drone to the operator’s screen, giving immediate insight into emissions behavior.

This live dashboard includes:

• Methane concentration levels visualized as the drone flies.

• Drone position and altitude for precise context.

• Wind direction and speed from our on-site 3D ultrasonic anemometer.

• Active maps and flight paths overlaid on satellite imagery.

• Telemetry data like battery life and drone status for safe operations.

By combining environmental data, navigation details, and live methane concentration maps, the GCS empowers operators to make smarter decisions on the spot.

If a methane plume appears unexpectedly, the drone operators don’t just see it, they can adapt instantly, rerouting the drone to capture more detail, focusing on emission hotspots, or adjusting altitude to map the plume structure more completely.

FASTR: Accelerating Results Beyond the Field

While GCS is all about awareness during the flight, the FASTR system, released mid-2025, addresses what happens after the flight. Traditionally, emissions monitoring relied on lengthy post-processing workflows, sometimes taking weeks before results were ready. FASTR shortens that cycle dramatically.

By automating the ingestion, processing, and reporting pipeline, FASTR delivers results in minutes, not days, without requiring any cellular connection. The platform organizes data from multiple flights, integrates environmental parameters, and produces clear emissions quantification reports that are easy to interpret and act upon.

For operators and asset managers, this speed translates into immediate value through rapid response to unexpected or large leaks, integration with mitigation workflows so that identified leaks can be prioritized, and quick validation of repairs, allowing teams to verify success before leaving the site.

Why GCS + FASTR Matters

The real strength of SeekOps comes from combining the real-time situational awareness of GCS with the accelerated reporting power of FASTR. Together, they provide a seamless workflow from detection to action:

• In the field: Drone operators see emissions data live, with the ability to investigate plumes before the drone even lands.

• Post-flight: FASTR processes the mission data quickly, generating quick view quantification reports.

This dual system transforms emissions monitoring from a reactive process into a proactive management tool, enabling real-time awareness, rapid response, and quality assurance.

The Value of Speed and Certainty

In methane monitoring, speed is about more than convenience. Methane is over 80 times more potent than carbon dioxide in the short term, which means rapid detection and mitigation have a direct climate impact.

With GCS streaming and FASTR reporting, SeekOps helps clients move from data collection to climate action faster than ever before. Whether it’s an oilfield in Texas, a biogas plant in Europe, or an offshore platform in the Middle East, operators can trust that the data they’re seeing is accurate, timely, and actionable.

For industries under increasing regulatory pressure, from OGMP 2.0 requirements to the EU Methane Regulation, this combination provides both compliance support and operational efficiency.

Designed for Flexibility and Reliability

Both SeekOps apps are designed with field realities in mind:

• Drone-agnostic integration means SeekOps sensors and software work with multiple airframes, from small quadcopters to long-endurance fixed-wing drones.

• Lightweight payloads ensure minimal impact on flight performance.

• Independent power systems maximize flight time without draining the drone’s batteries.

• Built-in redundancy and QC checks reduce error margins and enhance reliability.

Whether operating in desert heat, offshore winds, or tropical humidity, SeekOps systems are tested to deliver dependable performance.

From Sky to Screen, From Data to Decisions

Methane monitoring has entered a new era. No longer do operators need to wait weeks for reports or rely on incomplete detection methods. With GCS providing live awareness and FASTR delivering accelerated results, SeekOps bridges the gap between measurement and mitigation.

Together, these tools give industries the power to act quickly, reduce emissions effectively, and meet the world’s growing demand for transparent, trustworthy climate data.

Stay tuned for the next post in our series: “Making Emissions Actionable – How SeekOps Reconciliation Reporting and Celsius Help Operators Close the Loop”

Ready to see FASTR in action?
Request a Live Demo today and discover how SeekOps helps you move from sky to screen—and from data to decisions—faster.

References

Corbett, A., & Smith, B. (2022). Study of a Miniature TDLAS System Onboard Two Unmanned Aircraft to Independently Quantify Methane Emissions from Oil and Gas Production Assets and Other Industrial Emitters. Atmosphere, 13(5), 804. https://doi.org/10.3390/atmos13050804

Dawson, K. W., Smith, B. J., Stocker, I., & Evans, P. (2024). Assessing the Application of Drone TDLAS Methane Emissions Monitoring Technology in the Intertropical Convergence Zone Using Machine Learning. APOGCE 2024. https://doi.org/10.2118/221317-MS

Smith, B. J., Buckingham, S., Touzel, D., et al. (2021). Development of Methods for Top-Down Methane Emission Measurements of Oil and Gas Facilities in an Offshore Environment Using a Miniature Methane Spectrometer and Long-Endurance UAS. SPE Annual Technical Conference and Exhibition, Dubai, UAE. https://doi.org/10.2118/206181-MS

Tavner, C. A., Touzel, D. F., & Smith, B. J. (2021). Application of Long-Endurance UAS for Top-Down Methane Emission Measurements of Oil and Gas Facilities in an Offshore Environment. SPE Offshore Europe Conference and Exhibition, Virtual. https://doi.org/10.2118/205467-MS

Ravikumar, A. P., Sreedhara, S., Wang, J., et al. (2019). Single-blind inter-comparison of methane detection technologies – results from the Stanford/EDF Mobile Monitoring Challenge. Elementa: Science of the Anthropocene, 7(1), 37. https://doi.org/10.1525/elementa.373

Gully-Santiago, M. A., Smith, B., Frederick, T., Dawson, K., & Elliott, D. (2025). Results and Learnings from the TADI 2024 Methane Quantification Trial. SPE Europe Energy Conference and Exhibition, Vienna, Austria. https://doi.org/10.2118/225634-MS

Discover how SeekOps designs intelligent drone flight paths and uses high-resolution imagery, orthomosaics, 3D models, and flux planes to assist in accurate, efficient methane emissions monitoring in any environment.

Read time: 5 minutes

Optimized Routes for Emissions Detection

Before we begin a project, we program detailed flight paths tailored to each site’s unique conditions. Every route is designed with two key priorities: maximizing methane plume coverage and ensuring operational safety.

Plans are built before our teams even arrive on site, using forecasted wind data to anticipate plume behavior and shape efficient flight patterns. If conditions shift, such as a sudden wind change, our skilled operators can generate new routes instantly, ensuring no data gaps and no wasted flight time.

This approach isn’t just about flying drones, it’s about flying the right path for the environment, infrastructure, and emissions target.

Flux Planes: Mapping Plumes in Motion

At the heart of SeekOps’ quantification strategy is the use of flux planes, or vertical slices of space where methane concentration and wind data are measured simultaneously. As the drone flies back and forth across these planes, it builds a precise, three-dimensional profile of the methane plume in real time.

Flux planes allow us to quantify the total mass flow rate of methane passing through the plane, capture plume shape, density, and movement under actual site conditions, and adapt flight patterns mid-mission if the plume shifts due to wind changes.

By integrating flux planes into our flight paths, we turn aerial surveys into dynamic, high-fidelity measurements. It’s not just about detecting a leak, it’s about understanding exactly how much methane is moving, where it’s going, and what’s driving it.

A Bird’s-Eye View

To support our detailed analysis and data presentation, we can capture high-resolution, up-to-date imagery that shows the site exactly as it is, whether that means newly installed process equipment, scaffolding, or temporary construction zones. This visual intelligence is far more reliable than outdated satellite images, ensuring that we have context that matches the reality in the field.

Orthomosaics: Detailed Maps for Analysis

While flight paths are the backbone of our approach, orthomosaic maps add a layer of precision. These are high-resolution, georeferenced images stitched together from hundreds of individual aerial photographs.

For SeekOps, orthomosaics are:

• Operationally current – showing the exact site layout on the day of the survey, including temporary installations, scaffolding, and safety barriers.

• Analysis-ready – allowing our findings to be overlaid and interpreted directly within operational workflows

• Reusable – serving as a reference for future surveys and change detection over time.

Orthomosaics are especially valuable for sites where outdated satellite imagery might show an empty lot but are actually a busy industrial environment.

3D Models: Adding Height to the Equation

In certain environments, such as offshore platforms, urban facilities, or sites with stacked infrastructure, 2D maps alone aren’t enough. That’s where 3D models come in.

Using photogrammetry from multiple angles, our drones can generate 3D representations of the site. This allows us to:

• Understand equipment height and elevation changes for better plume modeling.

• Accurately attribute emissions to the proper equipment groups.

• Depict where the methane plumes are coming from in our reports.

3D models are particularly effective in tight or congested areas where methane plumes may behave unpredictably due to airflow restrictions.

Efficiency in the Air

The drones fly these custom routes autonomously, but each one is backed by human expertise. Skilled operators know how to integrate wind data, site hazards, and plume modeling into the plan, balancing complete coverage with the shortest possible airtime.

This efficiency matters. It reduces battery use, minimizes exposure to harsh environments, and ensures that methane detection happens at the optimal time and place.

Consistency You Can Compare

Once a flight path has been proven effective, we save it for future surveys. This enables exact repeatability, allowing operators to track changes in emissions before and after maintenance, compare seasonal conditions, or analyze the same equipment over time. Consistency like this builds robust data sets and high-confidence trends, something extremely difficult to achieve with handheld tools or one-off aerial flyovers.

From Planning to Action

By pairing accurate site imagery, orthomosaics, and 3D modeling with intelligent flight path design, SeekOps ensures that every drone mission collects the most useful data in the least amount of time.

When combined with our real-time monitoring capabilities, this approach transforms aerial surveys into actionable intelligence, helping operators identify, quantify, and act on emissions faster than ever.

Stay tuned for the next post in our series: “FASTR Insights – Real-Time Awareness from Sky to Screen”

Want to see what methane emissions your site is emitting?

Schedule a survey or Talk to an expert

References

Corbett, A., & Smith, B. (2022). Study of a Miniature TDLAS System Onboard Two Unmanned Aircraft to Independently Quantify Methane Emissions from Oil and Gas Production Assets and Other Industrial Emitters. Atmosphere, 13(5), 804. https://doi.org/10.3390/atmos13050804

Smith, B. J., Buckingham, S., Touzel, D., et al. (2021). Development of Methods for Top-Down Methane Emission Measurements of Oil and Gas Facilities in an Offshore Environment Using a Miniature Methane Spectrometer and Long-Endurance UAS. SPE Annual Technical Conference and Exhibition, Dubai, UAE. https://doi.org/10.2118/206181-MS

Tavner, C. A., Touzel, D. F., & Smith, B. J. (2021). Application of Long-Endurance UAS for Top-Down Methane Emission Measurements of Oil and Gas Facilities in an Offshore Environment. SPE Offshore Europe Conference and Exhibition, Virtual. https://doi.org/10.2118/205467-MS

Hossian, R. I., et al. (2024). A Controlled Release Experiment for Investigating Methane Measurement Performance at Landfills. Environmental Research and Education Foundation (EREF). https://erefdn.org/eref-funded-study-highlights-advances-in-measuring-landfill-methane-emissions

Ravikumar, A. P., Sreedhara, S., Wang, J., et al. (2019). Single-blind inter-comparison of methane detection technologies – results from the Stanford/EDF Mobile Monitoring Challenge. Elementa: Science of the Anthropocene, 7(1), 37. https://doi.org/10.1525/elementa.373

Emissions data is only useful if you know how reliable it is. Here’s how SeekOps evaluates and improves confidence in methane measurements.

Read time: 5 minutes

Why Uncertainty Matters in Emissions Monitoring

In the world of methane detection and quantification, accuracy is only half the story. Just as important, is knowing how confident you can be in your results, and that’s where uncertainty comes in.

Uncertainty isn’t a flaw in a measurement; it’s an attribute necessary for measurement transparency. In any real-world measurement, especially in a dynamic outdoor environment, there’s always going to be a degree of uncertainty. At SeekOps, we take uncertainty seriously because it gives regulators, operators, and stakeholders a clear picture of how reliable an emissions estimate really is. It builds trust, enables better decision-making, and supports compliance with high-integrity reporting frameworks like OGMP 2.0 and other global methane standards.

In short, when the stakes are high, vague numbers aren’t enough. SeekOps reports how confident we are in those results. It’s data you can act on, with confidence grounded in precision.

What Is Measurement Uncertainty?

Measurement uncertainty is a calculated estimate of how much the actual value could differ from the reported result. In simple terms, it’s our way of saying:

“Here’s the number—and here’s how sure we are.”

As stated above, uncertainty is not an error or a flaw. It’s a necessary part of scientific honesty and provides context to any measured value.

What Causes Measurement Uncertainty?

There are several factors that contribute to uncertainty in all top-down emissions measurements (e.g. drone, aircraft, satellite, continuous, etc.), including:

• Sensor sensitivity and precision
  How precisely can methane concentrations be measured, especially at low levels? Sensitivity and calibration factors extend to the sensors measuring wind, temperature, pressure, and position.

• Environmental conditions
  Wind speed and direction, turbulence, temperature, and humidity can all affect how plumes behave.

• Plume geometry and flight path
  Complex terrain or poorly optimized flight paths can miss parts of the plume or cause the measured concentrations to be artificially lowered.

• Background methane levels
  Differentiating the source signal from regional background can be challenging.

• Model assumptions
  Any model-based approach requires assumptions about wind fields, dispersion, or boundary conditions which all carry their own uncertainties. However, SeekOps only utilizes a small number of assumptions due to our rigorous mass-balance approach.

SeekOps acknowledges and quantifies all of these to provide a realistic, statistically grounded picture of methane emissions.

How SeekOps Quantifies and Reduces Uncertainty

SeekOps applies a rigorous process when evaluating uncertainty in methane emissions measurements. Thanks to our ability to detect leaks as small as 0.02 kg/h, we can reliably observe virtually all measurable emission enhancements in the field. This exceptional sensitivity means that a probability of detection (PoD), a common industry metric, does not meaningfully apply, as our detection rate is effectively 100% (Ravikumar et al., 2019).

Instead of stopping at “we detected it,” we focus on how confident we are in the measured emission rate. That means identifying, quantifying, and transparently reporting the factors that influence uncertainty. Our estimation of confidence includes consideration of:

1. Controlled Release Testing

SeekOps has participated in dozens of blind controlled release trials from landfills to offshore platforms where known amounts of methane are released and measured. These trials serve as ground truth and provide hard data on the system’s accuracy and repeatability. Results consistently show SeekOps’ technology delivers low false-positive and false-negative rates and quantification within industry-accepted tolerances.

2. Environmental Profiling and Wind Modeling

Wind is one of the biggest variables in emissions monitoring. That’s why we pair our methane sensor with a 3D ultrasonic anemometer on site and apply local wind profile models, customized for each site’s surface roughness and topography.

This allows us to:

• Understand how methane plumes move across a site

• Improve the placement of control volumes

• Quantify variability in wind conditions over time

These insights are used to model uncertainty ranges for each quantification result. Recent research in Atmospheric Measurement Techniques (Mohammadloo et al., 2025) further supports this approach, showing that detailed wind profiling and adaptive plume sampling strategies are essential for reducing error margins in drone-based methane quantification.

3. Statistical Confidence Intervals

Rather than provide a single number, SeekOps delivers results with confidence bounds, typically expressed as a 95% confidence interval (2σ). This range reflects the potential variability in mass flow estimates based on real-world sampling conditions.

Incorporating uncertainty into the result isn’t just honest, it’s scientifically rigorous. It enables regulators and inventory teams to prioritize mitigation based on both emission rate and measurement reliability.

4. Cross-Site Comparisons and Continuous Improvement

With hundreds of deployments across 6 continents, SeekOps has built a robust internal benchmark of expected uncertainty under a variety of site types and conditions. We regularly update our models based on new data, seasonal trends, and learnings from large-scale campaigns like:

• The 2024 Controlled Landfill Release Trial (Hossian et al., 2024)

• Offshore OGMP Programs (Smith et al., 2021; Tavner et al., 2021)

• TADI 2024 Quantification Challenge (Gully-Santiago et al., 2025)

Field-Proven Performance

Our real-world uncertainty performance is validated by measured results, not estimates.

• In complex offshore environments, like bp’s Clair Phase 1 facility, our drone-mounted methane spectrometer measured emissions within ±20% of known release rates, with detection sensitivity down to 2.5 kg/h, even from 500 m away (Smith et al., 2021; Tavner et al., 2021).

• Independent studies at landfills and oilfields show our measurements closely match actual emissions, with agreement between platforms within 10–15% (Hossian et al., 2024; Corbett & Smith, 2022).

These results give operators the confidence that reported values reflect real conditions as opposed to modelled assumptions, enabling more reliable regulatory reporting and verification.

Transparency in Reporting

SeekOps integrates uncertainty bounds directly into reports and dashboards, whether through emission rate ranges (e.g., “12.4 ± 3.1 kg/h”), confidence classification for each source, documentation of assumptions and environmental conditions, or repeatability scoring across revisits or campaigns.

This transparency is essential for high-integrity emissions inventories and meets emerging global standards for ESG and methane reporting like OGMP 2.0 or the new EU Methane Regulation.

Reducing Uncertainty Over Time

Our measurement platform improves with every flight.

As we collect more field data, refine our models, and adjust flight strategies based on terrain and weather, we continually reduce our uncertainty margins, giving customers increasing confidence in our results.

We do it with the use of site-specific wind profiles from on-site anemometers, adaptive flight patterns to capture full plume geometry, real-time quality control during flight operations, and machine learning models to predict and minimize measurement error in complex environments.

Toward a More Confident Climate Future

As the world moves toward net-zero goals and increasingly rigorous climate disclosure frameworks, uncertainty isn’t a liability: it’s a strength.

By quantifying uncertainty, SeekOps empowers operators to prioritize mitigation based on both scale and confidence, communicate transparently with regulators and the public, and build robust emissions inventories that stand up to scrutiny.

Because in the end, reducing emissions isn’t just about knowing there’s a leak, it’s about knowing how much, how sure, and what to do next.

Stay tuned for the next post in our series: “Drone Deployment and Site Mapping – Smarter Surveys Start from the Sky.” And look out for our blog post covering dynamic uncertainty in the coming weeks!

Want to learn how SeekOps quantifies uncertainty and improves confidence in your methane data?

Ask us about our uncertainty and speak with an expert today

Image Credits

Figure 1 from Pérez-Díaz, L., Best, J., Gómez-Martín, F., Hodgson, D., Lang, A., Mather, A., McCarthy, D., & Thorpe, R. (2020). Introduction: Handling uncertainty in the geosciences: identification, mitigation and communication. Solid Earth, 11, 889–897. https://doi.org/10.5194/se-11-889-2020 — Licensed under CC BY 4.0.

References

Corbett, A., & Smith, B. (2022). Study of a Miniature TDLAS System Onboard Two Unmanned Aircraft to Independently Quantify Methane Emissions from Oil and Gas Production Assets and Other Industrial Emitters. Atmosphere, 13(5), 804. https://doi.org/10.3390/atmos13050804

Dawson, K. W., Smith, B. J., Stocker, I., & Evans, P. (2024). Assessing the Application of Drone TDLAS Methane Emissions Monitoring Technology in the Intertropical Convergence Zone Using Machine Learning. APOGCE 2024. https://doi.org/10.2118/221317-MS

Gully-Santiago, M. A., Smith, B., Frederick, T., Dawson, K., & Elliott, D. (2025). Results and Learnings from the TADI 2024 Methane Quantification Trial. SPE Europe Energy Conference and Exhibition. https://doi.org/10.2118/225634-MS

Hossian, R. I., et al. (2024). A Controlled Release Experiment for Investigating Methane Measurement Performance at Landfills. Environmental Research and Education Foundation (EREF). https://erefdn.org/eref-funded-study-highlights-advances-in-measuring-landfill-methane-emissions

Mohammadloo, T. H., Jones, M., Van De Kerkhof, B., Dawson, K., Smith, B. J., Conley, S., et al. (2025). Quantitative estimate of sources of uncertainty in drone-based methane emission measurements. Atmospheric Measurement Techniques, 18, 1301–1325. https://doi.org/10.5194/amt-18-1301-2025

Ravikumar, A. P., Sreedhara, S., Wang, J., et al. (2019). Single-blind inter-comparison of methane detection technologies – results from the Stanford/EDF Mobile Monitoring Challenge. Elementa: Science of the Anthropocene, 7(1), 37. https://doi.org/10.1525/elementa.373

Smith, B. J., Buckingham, S., Touzel, D., et al. (2021). Development of Methods for Top-Down Methane Emission Measurements of Oil and Gas Facilities in an Offshore Environment Using a Miniature Methane Spectrometer and Long-Endurance UAS. SPE Annual Technical Conference and Exhibition. https://doi.org/10.2118/206181-MS

Tavner, C. A., Touzel, D. F., & Smith, B. J. (2021). Application of Long Endurance UAS for Top-Down Methane Emission Measurements of Oil and Gas Facilities in an Offshore Environment. SPE Offshore Europe Conference and Exhibition. https://doi.org/10.2118/205467-MS