This article is part of our ongoing series looking at why adding quantitative OGI (QOGI) to a leak detection and repair (LDAR) regimine is critical to improving efficiency and safety, strengthening compliance, and optimizing methane monitoring programs.

Leak detection and repair (LDAR) programs have long been the foundation of emissions management in oil & gas, petrochemical, and industrial operations. For decades, these programs have focused on identifying leaks, repairing them, and demonstrating compliance with environmental regulations.

But the industry continues to evolve. Today’s regulatory landscape, ESG expectations, and operational priorities are driving a shift beyond simple detection. Operators are being asked not only to find leaks, but to understand them — to quantify emissions, track trends over time, and demonstrate measurable progress toward reduction goals.

This evolution reflects a broader shift from detection-only LDAR programs toward approaches that integrate both detection and quantification of emissions. 

At the center of this shift is Quantitative Optical Gas Imaging (QOGI) — a technology that builds on traditional optical gas imaging (OGI) by adding the ability to estimate emission rates directly at the point of inspection.

For many operators, QOGI represents not just an incremental improvement, but a practical step toward future-proofing their emissions monitoring programs.

The Shift from Detection to Decision-Making

Traditional LDAR workflows are designed to answer a simple question:

Is there a leak, and where is it?

Optical gas imaging (OGI) transformed this process by enabling operators to visualize gas emissions in real time. Using infrared cameras tuned to the absorption characteristics of hydrocarbons such as methane, OGI makes invisible leaks visible as moving plumes against a contrasting background.

This was a major step forward in both efficiency and safety. However, OGI is historically qualitative. While it shows where emissions are occurring, it does not measure size or emission rate. QOGI extends this capability.

By applying calibration models and plume analysis to infrared imagery, QOGI converts visual data into an estimated emission rate. 

Why LDAQ Is Becoming the New Standard

The move toward LDAQ is being driven by several converging factors:

1. Expanding regulatory expectations

Recent regulatory frameworks, including updated EPA methane rules, are placing greater emphasis on accurate reporting, transparency, and accountability. Operators are expected to not only identify emissions but also demonstrate reductions over time.

2. Increased monitoring frequency

Facilities are required to monitor more assets, more often. This increases the volume of data that must be collected, analyzed, and reported.

3. ESG and corporate reporting

Investors and stakeholders are demanding more detailed disclosures around emissions performance. Quantification enables more meaningful reporting and benchmarking.

4. Operational efficiency

Understanding which leaks matter most allows operators to prioritize resources and reduce unnecessary work.

Building on Existing LDAR Workflows

One of the challenges in adopting new technologies is the need to retrain personnel or overhaul existing processes. This is especially true in industries where safety, compliance, and operational continuity are critical.

Technicians trained on OGI systems can transition to QOGI with minimal changes. The inspection process remains largely the same:

• Use an infrared camera to scan equipment
• Identify emissions visually
• Capture documentation for reporting

As Craig O’Neil, Director of Business Development for OGI at Flir notes: 

“QOGI enables operators to move beyond simple identification by providing rapid, decision‑ready measurements that fit directly into existing LDAR, MRV, and reporting workflows.” 

From Snapshot Inspections to Data-Driven Programs

Traditional LDAR programs are often episodic. Inspections are conducted at set intervals, and results are recorded as discrete events.

QOGI supports a more continuous, data-driven approach. Because each inspection includes both detection and quantification, the resulting data can be used to:

• Track emissions trends over time
• Identify recurring issues or high-risk equipment
• Evaluate the effectiveness of repairs
• Support emissions inventories and reporting

This transforms LDAR from a compliance-driven activity into a source of operational insight.

Enabling Faster Response to High-Impact Emissions

Not all leaks are equal. Some emissions are small and intermittent, while others represent significant product loss or safety risk. Traditional workflows often require additional measurement steps to determine which leaks should be prioritized.

QOGI accelerates this process. By estimating emission rates during the initial inspection, QOGI allows operators to:

• Identify large leaks immediately
• Prioritize repairs based on impact
• Allocate resources more effectively

In a future LDAQ-oriented environment, the ability to act quickly on high-impact emissions will be an essential component of compliance and operational performance.

Integrating with Emerging Monitoring Technologies

Future emissions monitoring strategies are unlikely to rely on a single tool. Instead, they will combine multiple technologies, including:

• Handheld OGI/QOGI systems for component-level inspections
• Fixed monitoring systems for continuous observation
• Satellite or aerial detection for site-wide screening

Because it operates at the source level, QOGI provides detailed, actionable data that complements broader detection technologies. When a leak is identified remotely (for example, by a satellite or fixed sensor), QOGI can be used to verify and quantify the emission on-site.  This not only makes detection and quantification more efficient at a component level, it also helps meet some of the layered requirements for LDAQ by combining top-down and bottom-up technologies.  

Supporting the Transition Without Disruption

One of the most important aspects of future-proofing is minimizing disruption.

“Operators cannot afford to pause operations or undertake large-scale system changes to adopt new technologies. Any solution must integrate seamlessly into existing workflows while delivering immediate value,” says O’Neill.

QOGI is well-suited to this requirement because it is designed to detect and quantify in one familiar workflow. This dual capability means that operators can begin incorporating quantification into their LDAR programs without:

• Replacing existing equipment
• Redesigning inspection protocols
• Increasing inspection time significantly

Future-Proofing Through Practical Evolution

Future-proofing is not about predicting every regulatory or technological change. It is about adopting tools and processes that remain relevant as requirements evolve.

QOGI supports this goal by:

• Aligning with the growing emphasis on quantification
• Enhancing the value of existing LDAR workflows
• Providing actionable data for both compliance and operations
• Integrating with broader monitoring ecosystems

As the industry continues to move toward LDAQ, technologies that combine detection, visualization, and quantification in a single workflow will become increasingly important.

In this context, QOGI represents a practical and scalable path forward.

Looking Ahead

The transition from LDAR to LDAQ is already underway. While the pace of adoption will vary across regions and sectors, the direction is clear: emissions monitoring is becoming more data-driven, more transparent, and more integrated into operational decision-making.

QOGI plays a key role in enabling this shift—not by replacing existing practices, but by extending them.

In the final article in this series, we will explore why QOGI expertise matters, and how independent studies and real-world validation demonstrate the reliability and maturity of this technology.

Want to know more? 

Reach out to our sales team to learn how QOGI can help you. 

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