Air Monitoring 37
constant airspeed of 30 metres per second. Once at the lowest safe altitude, the aircraft ascended at the same altitude step heights fl ying between the previous laps, creating an vertically interlaced pattern. Further details of the fl ight management are documented elsewhere [5]. Three repeat fl ights were conducted over a period of two days, each taking 2 hours to complete, with the on-station measurements taking approximately 40 minutes. Details of the fl ight protocol have been previously published [7]
For site 2 onshore measurements, the SeekIR sensor was mounted on a DJI M300 quadcopter drone operated by a pilot with visible line of sight. Following an initial site survey, the site was divided into a series of zones, each comprising one or more major equipment groups such as a fl are or bank of turbines. Such site division is an adaptation of the concept of functional elements [8] and provides a practical way to manage a site that is too large to be completed within a single fl ight. Moreover, it allows the sequence of measurements and position of the drone to adapt to changeable weather conditions. The boundaries of each zone were typically defi ned by access roads. Drones were fl own in a raster formation downwind of each equipment group. At no stage was the drone fl own directly over equipment. Distance from the equipment to the drone path was typically 50m or less.
Figure 2: Reported and measured emissions from site 2.
Results Figure 1 show offshore results at Site 1. The average of three top-down measurements is 17.1 ±4.7 kg/h which is indistinguishable from the reported value of 20.5 ± 1.0 kg/h using a k=2 expanded uncertainty. The uncertainty of the individual top- down measurements do not overlap with one another, with the measurement performed on day 1 higher than on day 2.
Figure 2 contrasts pie charts for the reported and measured emissions from Site 2. The reported value (229 kg/h ±10 kg/h k=2) is indistinguishable from the measured value (267 ± 80 kg/h k=2). However, the composite value includes source-level values that contrast signifi cantly. The emissions associated with fl aring are larger in the reported value than in the measured (191 kg/h vs. 75 kg/h) which is the opposite to the fi red equipment in which measured values were lower in the reported value than encountered in the fi eld (15 kg/h compared to 163 kg/h).
Discussion For Site 1 the averaged top-down measured results from an offshore location are indistinguishable from those that would be reported for that time. The reported value would therefore be deemed to be reconciled under OGMP2.0 and fulfi l the expectations of Level-5. This value cannot be extrapolated to derive an annual emission rate, nor should it be assumed that all emissions from the site are fully understood from one measurement. Further measurements would be required over an extended period to make more defi nitive statements about long-term accuracy of reporting. The difference in the top-down values over the two-day measurement period is not accounted for by the measurement uncertainty. Either the uncertainty of the top-down method has not been fully derived or there are unknown changes taking place at the site. A review of the minute-by-minute data from the process data, Figure 3, revealed no measurable differences in fl ow. However, it is possible that there are shifts in the combustion effi ciency taking place in the fl are or turbines, highlighting the importance of continuous tracking of emissions where feasible. Whatever the cause, it is of note that the total emissions, around 20 kg/h, are small when compared to values reported in other producing environments.
For Site 2, the reported emissions can also be considered to be reconciled as the aggregate values are indistinguishable. However, in examining the source of the emissions it is evident that the reporting is not fully constrained, representing opportunities for reduction. A review of the data at Site 2 identifi ed higher than expected emissions from both a turbine and from a hot oil heater. Further work is required to investigate performance of the fi red equipment and either operational changes be made to bring them in line with expected values and/or improvements made to how emissions are measured. Site specifi c measurement of the fl are effi ciency would allow values other than an assumed destruction effi ciency to be applied to fl are gas data. This highlights a key aspect of the OGMP2.0 Levels in that the data should be applied to a process of continuous improvement.
As for Site 1, values cannot be extrapolated to annual emission rates and further measurements are required, but on the currently available data there is no evidence that there is a gross error in the reported emissions and the methane intensity of the site is low. The method of dividing a large site into functional areas and building an aggregate emission value for the purposes of reconciliation is shown to be effective.
Figure 3: Detailed analysis of process related emissions shows stable conditions over the two days of measurements at Site 1 – shown here in 1-hour increments over 48 hours. Differences in Top-Down values recorded during this period cannot be assigned to changes in the process.
Conclusion Bottom-up and Top-down data from two contrasting large oil and gas sites has been successfully compared, fulfi lling the expectations of OGMP2.0 Level 5. The use of the SeekIR sensor mounted on quad and fi xed-wing drones has been shown to be effective. The division of the onshore site into multiple zones has been demonstrated to be a practical way of reconciling data from large footprint sites. Level 5 data has been used to identify ways that reported emissions can be improved and opportunities for emissions reductions identifi ed.
The results highlight the advantages and disadvantages of different methods. The fi xed-wing aircraft reduces the need to send personnel offshore, increases independence in the measurements and provides a true moment-in-time assessment of all emissions at a site. Conversely, the rotary drone offers greater special resolution – allowing the source of anomalies to be more readily identifi ed. Together this highlights the need to select the method best suited to the specifi c site.
References 1
http://oleladesarrollo.es/webun2020/themes/ogmp_theme/ fi les/OGMP_20_Reporting_Framework.pdf
2
https://www.ogmpartnership.com/sites/default/fi les/fi les/ OGMP%202.0%20U%26R%20Guidance%20document%20-%20 SG%20approved.pdf
Author Contact Details Peter Evans, Senior Engineer, BP • Sunbury on Thames, Middlesex TW167LN, UK • Tel: 01932 760000 • Email:
PETER.EVANS@uk.bp.com • Web:
www.bp.com
WWW.ENVIROTECH-ONLINE.COM
3 EEMS-Atmospheric Emissions Calculations (Issue 1.810a) 2008 Oil and Gas UK
4 JCGM-100. Evaluation of measurement data - Guide to the expression of uncertainty in measurement. Committee for Guides in Metrology (JCGM/WG 1), 2008.
5 Smith, B., Buckingham, S., Touzel, D., Corbett, A., & Tavner, C. (2021, September). 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. In SPE Annual Technical Conference and Exhibition.
6 Corbett, A., & Smith, B. (2022). A 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
7 Tavner, C. A., Touzel, D. F., & Smith, B. J. (2021, September). Application of Long Endurance UAS for Top-Down Methane Emission Measurements of Oil and Gas Facilities in an Offshore Environment. In SPE Offshore Europe Conference & Exhibition.
8 Innocenti, F., Robinson, R., Gardiner, T., Howes, N., & Yarrow, N. (2021, April). Update on a global study measuring methane emissions from Liquid Natural Gas facilities. In EGU General Assembly Conference Abstracts (pp. EGU21-5730).
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