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Comparison of single, binary and temperature dependent adsorption models based on error function analysis

Comparison of single, binary and temperature dependent adsorption models based on error function analysis
Comparison of single, binary and temperature dependent adsorption models based on error function analysis
The choice of adsorption model to use when accounting for gas adsorption in shale gas reservoirs is critical especially for Gas in Place (OGIP) calculations since inaccurate predictions can affect reporting of overall gas reserves. To that end, different adsorption models would have to be compared and evaluated in order to select the model that fits experimental data accurately. In examining the effect of using different error criteria for determining parameters for shale gas adsorption models, a statistically robust error analysis has been performed based on the sum of normalised error (SNE). Most shale gas adsorption modelling are conducted without finding out the most appropriate error function to use which introduces adsorption prediction errors in calculations. Five different error analysis were used including Sum of squared error (SSE), average relative error (ARE), the sum of absolute error (SAE), Marquardt’s Percent standard Deviation (MPSD), and Hybrid fractional error (HYBRID). To account for the influence of temperature in adsorption capacities, the study also compares the use of temperature dependent models, such as Exponential and Bi-Langmuir models for gas adsorption. These models can be conducted at multiple temperatures and ensure adsorption data can be obtained at any temperature beyond laboratory conditions. This is particularly useful when conducting thermal stimulation as an enhanced gas recovery in both coal/shale gas reservoirs.
2630-8541
77-91
Fianu, John Senam
18396909-6a3d-4b3c-807d-9388d15bbb54
Gholinezhad, Jebraeel
79d96efe-2057-4b95-8be1-4d83162c937a
Hassan Sayed, Mohamed
ce323212-f178-4d72-85cf-23cd30605cd8
Fianu, John Senam
18396909-6a3d-4b3c-807d-9388d15bbb54
Gholinezhad, Jebraeel
79d96efe-2057-4b95-8be1-4d83162c937a
Hassan Sayed, Mohamed
ce323212-f178-4d72-85cf-23cd30605cd8

Fianu, John Senam, Gholinezhad, Jebraeel and Hassan Sayed, Mohamed (2019) Comparison of single, binary and temperature dependent adsorption models based on error function analysis. Journal of Oil, Gas and Petrochemical Sciences, 2 (2), 77-91. (doi:10.30881/jogps.00027).

Record type: Article

Abstract

The choice of adsorption model to use when accounting for gas adsorption in shale gas reservoirs is critical especially for Gas in Place (OGIP) calculations since inaccurate predictions can affect reporting of overall gas reserves. To that end, different adsorption models would have to be compared and evaluated in order to select the model that fits experimental data accurately. In examining the effect of using different error criteria for determining parameters for shale gas adsorption models, a statistically robust error analysis has been performed based on the sum of normalised error (SNE). Most shale gas adsorption modelling are conducted without finding out the most appropriate error function to use which introduces adsorption prediction errors in calculations. Five different error analysis were used including Sum of squared error (SSE), average relative error (ARE), the sum of absolute error (SAE), Marquardt’s Percent standard Deviation (MPSD), and Hybrid fractional error (HYBRID). To account for the influence of temperature in adsorption capacities, the study also compares the use of temperature dependent models, such as Exponential and Bi-Langmuir models for gas adsorption. These models can be conducted at multiple temperatures and ensure adsorption data can be obtained at any temperature beyond laboratory conditions. This is particularly useful when conducting thermal stimulation as an enhanced gas recovery in both coal/shale gas reservoirs.

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Published date: 23 April 2019

Identifiers

Local EPrints ID: 438279
URI: http://eprints.soton.ac.uk/id/eprint/438279
ISSN: 2630-8541
PURE UUID: a71ee9e7-fcb0-4f56-b4c3-fa6f086cf939
ORCID for Mohamed Hassan Sayed: ORCID iD orcid.org/0000-0003-3729-4543

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Date deposited: 04 Mar 2020 17:32
Last modified: 11 Jul 2020 00:48

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Author: John Senam Fianu
Author: Jebraeel Gholinezhad
Author: Mohamed Hassan Sayed ORCID iD

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