Profiling and trending of coriolis meter secondary process value drift due to ambient temperature fluctuations

Lindsay, Gordon; Hay, John E.; Glen, Norman; Shariatipour, Seyed M.

doi:10.1016/j.flowmeasinst.2017.12.007

Cited by 13 publications

(8 citation statements)

References 9 publications

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“…Flowmeters are normally subjected to high pressure and temperature, friction with fluids, and deposition of asphaltene, wax, and scale. These factors and other similar environmental impacts change the operational conditions of a flowmeter (Lindsay et al 2017;Liu et al 2017). Therefore, they need to be calibrated and maintained regularly to be able to work within the desired error specifications and it takes a part of annual operational costs of oil and gas companies.…”

Section: Introductionmentioning

confidence: 99%

Effect of systematic and random flow measurement errors on history matching: a case study on oil and wet gas reservoirs

Sadri

Shariatipour

Hunt³

et al. 2019

J Petrol Explor Prod Technol

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History matching is the process of modifying a numerical model (representing a reservoir) in the light of observed production data. In the oil and gas industry, production data are employed during a history matching exercise in order to reduce the uncertainty in associated reservoir models. However, production data, normally measured using commercial flowmeters that may or may not be accurate depending on factors such as maintenance schedules, or estimated using mathematical equations, inevitably has inherent errors. In other words, the data which are used to reduce the uncertainty of the model may have considerable uncertainty in itself. This problem is exacerbated for gas condensate and wet gas reservoirs as there are even greater errors associated with measuring small fractions of liquid. The influence of this uncertainty in the production data on history matching has not been addressed in the literature so far. In this paper, the effect of systematic and random flow measurement errors on history matching is investigated. Initially, 14 production data sets with different ranges of systematic and random errors, from 0 to 10%, have been employed in a history matching exercise for an oil reservoir and the results have later been evaluated based on a reference model. Subsequently, 23 data sets with errors ranging from 0 to 20% have been employed in the same process for a wet gas reservoir. The results show that for both cases systematic errors considerably affect history matching, while the effect of random errors on the considered scenarios is seen to be insignificant. Although reservoir model parameters in the wet gas reservoir were not as sensitive to the flow measurement errors as in the oil reservoir, for both cases, the future production forecast was significantly affected by the errors. Permeability was seen to be the most sensitive history matching parameter to the flow measurement errors in the oil reservoir, while for the wet gas reservoir, the most sensitive parameter was the forecast of future oil and gas production. Finally, considering the noticeable effect of systematic errors on both cases, it is suggested that flowmeter calibration and regular maintenance is prioritised, although the subsequent economic cost needs to be considered.

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Section: Introductionmentioning

confidence: 99%

Effect of systematic and random flow measurement errors on history matching: a case study on oil and wet gas reservoirs

Sadri

Shariatipour

Hunt³

et al. 2019

J Petrol Explor Prod Technol

View full text Add to dashboard Cite

show abstract

“…While the fluid flow rate was shown to influence the density error in our previous work [9], here initial trials indicated that the reported density is not sensitive to flow rate change at elevated ambient temperatures. Therefore, mass flow rates were kept constant throughout the tests, specifically at a rate which minimised fluid residency time in the temperature enclosure.…”

Section: Test Proceduresmentioning

confidence: 45%

“…Specifically, as the differential between the flowing fluid and test meter ambient air temperature increased, the error in both the uncompensated and compensated fluid density was shown to increase. These results combined with our preceeding research [9] indicate that limitations exist within the temperature compensation models tested. The errors observed are therefore likely to be incurred in the field under comparable conditions.…”

Section: Discussionmentioning

confidence: 58%

“…An initial investigation into the effects of air temperature on the density measurement from a Coriolis flow meter is reported in [9]. The results in [9] were presented to a Coriolis manufacturer and a partnership was formed, the research objective being to develop a new temperature correction model that would significantly reduce errors and which could readily be implemented in a conventional commercial transmitter [10], [11].…”

Section: = ( ) ( )mentioning

confidence: 99%

“…The VLFF was run in recirculation mode. The experimental configuration is identical to that used in the initial research phase described in [9].…”

Section: Fig 2 -Vlff Setup and Instrumentation Overview Where: -Tt Ismentioning

confidence: 99%

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Coriolis meter density errors induced by ambient air and fluid temperature differentials

Lindsay

Glen

Hay

et al. 2020

Flow Measurement and Instrumentation

Self Cite

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Coriolis metering technology is widely applied throughout industry. In addition to the mass flow rate, a Coriolis meter can measure fluid density based on the resonant frequency of the flow tube vibration. There is currently increasing interest in utilising this density measurement capability as the primary process value in applications such as precision control for fluid property conditioning, and fluid contamination monitoring.However, within these applications, ambient temperature variation can be significant.This paper details research data obtained using NEL's 'Very Low Flow' single-phase facility. The rig was modified to include a programmable temperature enclosure in which a Coriolis meter was installed. Two commercial meter models from the same manufacturer were tested. Both meters showed fluid density errors when subjected to fluctuations in the surrounding ambient air temperature. The fluid properties of the test medium were confirmed to be stable using NEL's UKAS standard reference instrumentation.Previous temperature effects research for Coriolis meters have focussed on the process fluid temperature and there is little published data on the effects of ambient temperature.1.

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An experimental study of zero-shift in a straight-tube Coriolis meter

Ford¹

2020

Flow Measurement and Instrumentation

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Profiling and trending of coriolis meter secondary process value drift due to ambient temperature fluctuations

Cited by 13 publications

References 9 publications

Effect of systematic and random flow measurement errors on history matching: a case study on oil and wet gas reservoirs

Effect of systematic and random flow measurement errors on history matching: a case study on oil and wet gas reservoirs

Coriolis meter density errors induced by ambient air and fluid temperature differentials

An experimental study of zero-shift in a straight-tube Coriolis meter

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