(579c) FLARE Emissions Monitoring and Reduction Using Parametric Models

Incomplete combustion in flaring is one of the major contributors globally to methane emissions from the oil and gas industry. The World Bank estimates that over 138 billion m³ of gas is flared globally each year. Unlike some other key sources of emissions, such as fugitives, the flare is frequently an integral part of the design and safe operation of many existing oil and gas facilities. While initiatives, such as the World Bank zero-routine flaring by 2030 initiative, have led to measurable reductions in routine flaring, the need for flaring during maintenance and in emergency situations to keep workers safe means they shall continue to be part of some oil and gas production for the foreseeable future. The objective of this presentation and paper is to explain how new flare monitoring technology from Panametrics is enabling operators to accurately report emissions and target opportunities for emissions reductions.

Methods

This paper presents the development of the suite of flare.IQ solutions based on ultrasonic flare gas measurement as a key in situ flare emissions management technology. We describe how this inferential technology works to estimate Net Heating Value (NHV) of the vent gas from speed of sound measured by ultrasonic flow meters. We also present a predictive parametric model for estimating flare combustion efficiency (CE) and destruction and removal efficiency (DRE) in real time with minimal additional instrumentation. Unlike some other systems for flare control, flare.IQ can be configured to work with a wide range of flare types including those using air and steam assist and is available online 24/7/365. Using an advanced and scalable analytics platform, operators can pull critical information about their flare system operation, including temperature, pressure, vent gas velocities, gas composition and crosswind speed to calculate optimum levels of assist gas and supplemental fuel to ensure >98% flare combustion efficiency. Ensuring optimal flare combustion efficiency under a wide variety of operating conditions enables operators to significantly reduce methane emissions.

Results

The flare.IQ solution is being increasingly adopted by flare operators across the globe as they recognize its ability to positively impact their decarbonization strategies. Its benefits include:

• real time quantification and reporting on methane emissions from flares
• compliance to OGMP 2.0 Level 4 reporting
• optimizing flare operation by providing steam/air assist flow and supplemental fuel flow set points to maintain a CE of >98% in assisted flares by ensuring NHV in the combustion zone (NHVcz) is always > 270 BTU/SCF
• monitoring CE, DRE, vent gas NHV, CO2eq and VOC emissions
• replacing static emissions factors with more accurate real-time CE / DRE measurement
• identifying operational issues early and intervene quickly by having access to real-time combustion efficiency data.

Three different CE models have been developed for steam-assisted, air-assisted, and unassisted (including pressure-assisted) flares. These parametric models were derived from Computational Fluid Dynamics (CFD) studies and existing empirical data on flare combustion to model the correlation of multiple factors including NHVcz, crosswind speed, exit velocity and flare tip diameter with flare CE. These CE models include the effect of flare exit velocity as higher tip velocity shortens the residence time in the combustion zone, which has a negative impact on CE for conditions with low heating value. As high crosswinds could strip away flare gas from the combustion zone, crosswind effect on flare efficiency is also included in the model. For conditions with high heating value, the effect of smoke on CE is also considered. DRE can then be derived from the calculated CE as they have shown a near linear relationship.

This flare CE prediction model based on inferential NHV measurement has recently been validated at the John Zink flare test facility in Tulsa, OK using the most widely accepted reference method of extractive sampling of the flare plume. The flare CE calculated by flare.IQ models was validated against CE derived from offline chemical analysis of extracted flare gas samples with tests conducted on three full-scale industrial flares including non-assisted, single-arm pressure-assisted, and multi-arm pressure-assisted flare designs. A total of 70 valid test points were carried out with varying flow rate and flare gas heating value, covering a CE range from 46 – 100%. The uncertainty of the method was assessed using both traditional error propagation and Monte Carlo methodology. The results from the parametric model agree with the extractive method to within 0.8% in the ≥98% DRE region where flares are expected to operate to limit the impacts of flaring. Uncertainty analysis revealed that the larger DRE discrepancy for DRE ≤ 98% correlates to the measurement uncertainties for both methods. Furthermore, we have used CFD simulations of these full-scale industrial flare tests based on extractive sampling to extend validation of the parametric models to high crosswind states up to 50 m/s that cannot be readily or safely examined empirically.

We also present data from deployed systems that illustrate the impact of continuous measurement of flares. This includes improved understanding and control of how flares behave under high cross wind conditions and the optimization of air/steam to combustible gas ratios to maintain effective combustion.

Conclusions

Methane emissions from flaring is one of the most critical focus areas to combat climate change. Panametrics’ flare.IQ presents a novel, accurate and scalable flare CE monitoring method using an adaptive parametric model that is based on empirical flare combustion data and computational fluid dynamics (CFD) calculations. This method can be deployed on both assisted and unassisted flares to achieve maintenance-free real-time CE/DRE monitoring. If deployed on every downstream flare globally, flare.IQ could save more than 80 million tons of CO2 equivalent emissions annually.

As oil and gas operators work towards eliminating routine flaring, the existing global fleet of flares will be subject to longer periods of low flow and purge only conditions in which they are more acutely exposed to the risks of over-assisting and environmental impacts such as high crosswinds. We demonstrate how real-time monitoring provides the basis for both accurate reporting and mitigation.