PRODUCTION • PROCESSING • HANDLING L
iquid carryover in natural gas pipelines is a pervasive yet often overlooked issue that has far-reaching consequences for
both operational safety and eff iciency. Despite existing industry guidelines and standards, such as those stipulated by the American Petroleum Institute (API) and the International Organization for Standardization (ISO), traditional monitoring techniques fall short. These systems are simply not equipped to handle the complexities of two-phase fl ows, where liquid and gas coexist in the pipeline, leading to considerable shortcomings in detection and risk mitigation. Remarkably, around 60% of failures
in gas processing plants can be directly attributed to liquid carryover. This is most acute at the critical inlet stages where gas treatment processes like de- sulphurisation and de-humidifi cation occur. In these phases, liquid carryover signifi cantly undermines operational eff iciency, leading to complications like foaming. When foaming occurs, it often necessitates a substantial reduction in gas fl ow rates and incurs additional costs for de-foaming chemicals. As a precaution, operators commonly reduce gas fl ow rates intentionally, trading off optimal production levels for a semblance of safety. But the problem extends beyond
immediate operational challenges. Long-term eff ects such as fouling result from accumulated solids, which compromise the performance of heat exchangers, disrupt valve and pump operations, and can even jeopardise the fi nal stages of NGL (Natural Gas Liquids) removal. These cumulative issues have a ripple eff ect, negatively impacting both safety protocols and profi t margins. Traditional computational fl uid
dynamics (CFD) models, despite their sophistication, often fall short of predicting the actual dynamics of liquid carryover in real-world operations. This exposes a glaring need for real-time monitoring solutions that can off er immediate, actionable insights. Process cameras have emerged as a game- changing technology in this context. They provide a real-time glimpse into pipelines, revealing frequently occurring mist or stratifi ed fl ows even when the system is reported to be handling ‘dry gas’.
30
www.engineerlive.com REVOLUTION REAL-TIME
Liquid carryover detection in natural gas pipelines: the importance of real-time monitoring. By Paul Stockwell
There is a notable discrepancy
between traditional gas analysis systems and real-world conditions. Surprisingly, fi eld data has shown that existing gas analyser systems do not detect or even register the presence of wet gas, despite the fact that wet gas is not an uncommon occurrence in pipelines. These traditional systems, therefore, off er a false sense of security, given that they fail to trigger alarms even when wet gas is present. This limitation becomes particularly
problematic for gas chromatographs, which rely on gas samples that are often not representative of the actual fl uid in the pipelines. When wet gas is present, the liquid components are either removed or avoided, leading to skewed BTU calculations and inaccurate representations.
WHAT’S THE SOLUTION? Process cameras off er a solution to this conundrum. They detect wet gas in real time. These cameras can inform gas processors when they are losing valuable NGLs and can indicate
60% of failures DUE TO LIQUID CARRYOVER
the ideal times for changing out fi lter cartridges. Beyond that, they provide an avenue for performance balancing across diff erent gas processing trains, allowing for data-driven, evidence-based actions to improve phase separation and mitigate risks like foaming. The integration of process cameras,
such as Process Vision’s LineVu, has the potential to revolutionise the way gas processors manage the risks and ineff iciencies associated with liquid carryover. By off ering a real-time, comprehensive
monitoring solution, they support existing systems and pave the way for safer and more profi table natural gas operations.
Paul Stockwell is managing director of Process Vision.
www.processvision.com
Process cameras deliver
comprehensive, real-time monitoring
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52
