Modelling combustion reactions for gas flaring and its resulting emissions

Ismail, O. S.; Umukoro, G. Ezaina

doi:10.1016/j.jksues.2014.02.003

Cited by 34 publications

(28 citation statements)

References 9 publications

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“…Emission from gas flares is predicted here by adopting mass balance equations for various flaring conditions as developed in Ismail and Umukoro (2014). The 6 reaction types and conditions are presented here in Eqs.…”

Section: Methodsmentioning

confidence: 99%

Modelling emissions from natural gas flaring

Umukoro

Ismail

2017

Journal of King Saud University - Engineering Sciences

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The world today recognizes the significance of environmental sustainability to the development of nations. Hence, the role oil and gas industry plays in environmental degrading activities such as gas flaring is of global concern. This study presents material balance equations and predicts results for non-hydrocarbon emissions such as CO 2 , CO, NO, NO 2 , and SO 2 etc. from flaring (combustion) of 12 natural gas samples representing composition of natural gas of global origin. Gaseous emission estimates and pattern were modelled by coding material balance equations for six reaction types and combustion conditions with a computer program. On the average, anticipated gaseous emissions from flaring natural gas with an average annual global flaring rate 126 bcm per year (between 2000 and 2011) in million metric tonnes (mmt) are 560 mmt, 48 mmt, 91 mmt, 93 mmt and 50 mmt for CO 2 , CO, NO, NO 2 and SO 2 respectively. This model predicted gaseous emissions based on the possible individual combustion types and conditions anticipated in gas flaring operation. It will assist in the effort by environmental agencies and all concerned to track and measure the extent of environmental pollution caused by gas flaring operations in the oil and gas industry. Ó 2015 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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Section: Methodsmentioning

confidence: 99%

Modelling emissions from natural gas flaring

Umukoro

Ismail

2017

Journal of King Saud University - Engineering Sciences

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“…The U.S. Environmental Protection Agency (EPA) estimates there are about 500 flares in over 100 U.S. refineries but many more in chemical plants and drilling sites. The number of permits for flaring in Texas rose from just over a hundred in 2008-2000 in 2012 [3][4][5][6]. The world bank estimates that about 140 billion cubic meters of gas was flared in 2016-2017 globally, which is about 7 billion cubic meters less than 2016 [4].…”

Section: Introduction and Literature Surveymentioning

confidence: 99%

“…Proper flare design considerations are required to safely dispose of the waste gases, some of which include the type of flare (gas/liquid), composition of fuel, temperature, flowrate, gas pressure and hydraulics [5,[16][17][18][19]. In a research by Ismail et al, percentage of stoichiometric air, natural gas type, carbon mass content, impurities and combustion efficiency of the flare system impact the quantity and pattern of chemical species in combustion zone during flaring [6]. Incomplete combustion from flares contributes to black carbon (soot) emissions.…”

Section: Introduction and Literature Surveymentioning

confidence: 99%

Flare performance modeling and set point determination using artificial neural networks

Damodara

Alphones

Chen

et al. 2019

Int J Energy Environ Eng

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Current EPA regulations mandate a minimum combustion zone heating value of 270 BTU/scf and a net heating value dilution parameter of NHV dil ≥ 22 BTU/ft 2 for all steam/air/non-assisted flares while maintaining a high combustion efficiency (CE). To achieve the target performance along with satisfying the EPA regulations, it is necessary to understand the influence of various operating parameters. Studying the effect of operating parameters through experiments is both expensive and time consuming. It is more cost effective to use validated models to guide flare operations. In this study, controlled flare test data conducted from 1983 to 2014 with a wide range of exit velocities, heating values, and fuel compositions have been modeled. The purpose of this study is to develop models that can be robustly used in the industry to achieve the desired CE without visible emissions (smoke). Steam-/air-assist rates, exit velocity, and the vent gas composition, which can be either controlled or measured in flare operations, are used as independent variables in the models. Neural network (NN) models were developed for the air-assisted, steam-assisted, and non-assisted flares using various types of fuels like propylene, propane, natural gas, methane, and ethylene. The flare performance models such as CE and opacity were developed using neural network toolbox in MATLAB. NN models for steam and air-assisted flare tests are in good agreement with experimental data and have been demonstrated by the average correlation coefficient of 0.95 and 0.97 for air-assisted and steam-assisted flare data, respectively. The very low mean absolute errors of 1.1% and 1.4% for air-assisted and steam-assisted flare data, respectively, also indicate the robustness of the NN models. 2-D and 3-D contour plots are presented to show the effect of key operating parameters. The set points (amount of steam/air/make-up fuel required) at the Incipient Smoke Point (ISP) and for Smokeless Flaring (SLF) have been developed based on the neural network models performed in this study. Desirable operating inputs can be set for the ISP and for SLF (Opacity ≤ Opacity ISP ) subject to heating value constraints (NHV dil ≥ 22 BTU/ft 2 & NHV CZ ≥ 270 BTU/scf) with a high CE (≥ 96.5%) for the 1984 EPA and 2010 TCEQ flare study test cases.

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“…There are several methods to optimize the combustion process in heat power plants [4][5][6][7]. However, the available methods do not allow reacting quickly and efficiently on fuel compositions changes or requiring a continuous analysis of fuel calorific value or exhausting gas composition.…”

Section: Introductionmentioning

confidence: 99%

The algorithm diagram of combustion optimizing of a hydrocarbon fuels variable composition in thermal power plants

Сайфуллин

Nazarychev

Malahov

et al. 2018

J. Phys.: Conf. Ser.

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Abstract. In modern power engineering, there is a problem of rational and efficient use of hydrocarbon fuels variable composition. The composition of the fuel can vary in time and from different sources. These changes lead to combustion optimum regime shift in thermal power plants. Previously, an algorithm of combustion optimizing of a hydrocarbon fuel variable composition in thermal power plants was developed. According to the algorithm, the fuel and air flows are regulated depending on the outlet temperature of the heat carrier. In this paper, a diagram of the implementation of this algorithm is presented.

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Modelling combustion reactions for gas flaring and its resulting emissions

Cited by 34 publications

References 9 publications

Modelling emissions from natural gas flaring

Modelling emissions from natural gas flaring

Flare performance modeling and set point determination using artificial neural networks

The algorithm diagram of combustion optimizing of a hydrocarbon fuels variable composition in thermal power plants

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