Application of temperature-dependent adsorption models in material balance calculations for unconventional gas reservoirs
Application of temperature-dependent adsorption models in material balance calculations for unconventional gas reservoirs
Langmuir isotherm is the most common adsorption model used in the prediction of gas adsorption in most shale and coal bed methane reservoirs. However, due to the underlying assumption of single temperature, it fails to model gas adsorption where temperature differential exists in the reservoir. To address this shortcoming, temperature-dependent gas adsorption models have been incorporated into material balance calculations for accurate prediction of original gas in place as well as determining both average reservoir pressure and future performance in coal/shale gas reservoirs. The material balance equation has been expressed as a straight line with both Bi-Langmuir and Exponential models used in prediction of gas adsorption rather than the Langmuir isotherm. With this methodology, several adsorption capacities can be obtained at multiple temperatures which will allow for better estimation of original gas in place and future gas production. The results from this works show that temperature-dependent gas adsorption models can be used in place of Langmuir isotherm to account for the effect of temperature variations and more accurate representation of the adsorption of gas in coal/shale gas reservoirs.
Unconventional Reservoirs, Adsorption Models, Material Balance, Shale Gas
1-12
Fianu, John Senam
18396909-6a3d-4b3c-807d-9388d15bbb54
Gholinezhad, Jebraeel
79d96efe-2057-4b95-8be1-4d83162c937a
Hassan, Mohamed
ce323212-f178-4d72-85cf-23cd30605cd8
16 May 2019
Fianu, John Senam
18396909-6a3d-4b3c-807d-9388d15bbb54
Gholinezhad, Jebraeel
79d96efe-2057-4b95-8be1-4d83162c937a
Hassan, Mohamed
ce323212-f178-4d72-85cf-23cd30605cd8
Fianu, John Senam, Gholinezhad, Jebraeel and Hassan, Mohamed
(2019)
Application of temperature-dependent adsorption models in material balance calculations for unconventional gas reservoirs.
Heliyon, 5 (5), , [e01721].
(doi:10.1016/j.heliyon.2019.e01721).
Abstract
Langmuir isotherm is the most common adsorption model used in the prediction of gas adsorption in most shale and coal bed methane reservoirs. However, due to the underlying assumption of single temperature, it fails to model gas adsorption where temperature differential exists in the reservoir. To address this shortcoming, temperature-dependent gas adsorption models have been incorporated into material balance calculations for accurate prediction of original gas in place as well as determining both average reservoir pressure and future performance in coal/shale gas reservoirs. The material balance equation has been expressed as a straight line with both Bi-Langmuir and Exponential models used in prediction of gas adsorption rather than the Langmuir isotherm. With this methodology, several adsorption capacities can be obtained at multiple temperatures which will allow for better estimation of original gas in place and future gas production. The results from this works show that temperature-dependent gas adsorption models can be used in place of Langmuir isotherm to account for the effect of temperature variations and more accurate representation of the adsorption of gas in coal/shale gas reservoirs.
This record has no associated files available for download.
More information
Accepted/In Press date: 9 May 2019
e-pub ahead of print date: 16 May 2019
Published date: 16 May 2019
Keywords:
Unconventional Reservoirs, Adsorption Models, Material Balance, Shale Gas
Identifiers
Local EPrints ID: 438280
URI: http://eprints.soton.ac.uk/id/eprint/438280
ISSN: 2405-8440
PURE UUID: 48207b5c-5a0b-4c74-a4e6-9c2f1a5db36b
Catalogue record
Date deposited: 04 Mar 2020 17:32
Last modified: 17 Mar 2024 04:00
Export record
Altmetrics
Contributors
Author:
John Senam Fianu
Author:
Jebraeel Gholinezhad
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics