Breakthrough Pressure Prediction Based on Neural Network Model

The increasing carbon dioxide content is identified as the main cause of global warming. Capturing carbon dioxide in the atmosphere and transporting it to deep salt layer for storage have been proven and practiced in many aspects, which considered to be an effective way to reduce the content of carb...

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Autores principales:	Shuren Hao, Jixiang Cao, Hua Zhang, Yulian Liu, Haian Liang, Mingdong Li
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Geology QE1-996.5
Acceso en línea:	https://doaj.org/article/b3dcf0746a4648d0a55e2a50ecaa856d
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id	oai:doaj.org-article:b3dcf0746a4648d0a55e2a50ecaa856d
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spelling	oai:doaj.org-article:b3dcf0746a4648d0a55e2a50ecaa856d2021-11-22T01:11:03ZBreakthrough Pressure Prediction Based on Neural Network Model1468-812310.1155/2021/6154468https://doaj.org/article/b3dcf0746a4648d0a55e2a50ecaa856d2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/6154468https://doaj.org/toc/1468-8123The increasing carbon dioxide content is identified as the main cause of global warming. Capturing carbon dioxide in the atmosphere and transporting it to deep salt layer for storage have been proven and practiced in many aspects, which considered to be an effective way to reduce the content of carbon dioxide in the atmosphere. The sealing property of cap rocks is one of the key factors to determine whether CO2 can be effectively stored for a long time. In view of the disadvantages of tedious and time-consuming laboratory test methods for breakthrough pressure of cap rock, this paper explores the relationship between breakthrough pressure and other parameters such as porosity, permeability, density, specific surface area, maximum throat radius, and total organic carbon. The results show that the rock breakthrough pressure is closely related to the maximum throat radius and permeability determined by the mercury injection method, followed by the porosity and specific surface area, and less related to the density, depth, and TOC content of the rock itself. Then, with the selected parameters, a neural network model is established to predict the breakthrough pressure of cap rock, which can achieve good prediction results.Shuren HaoJixiang CaoHua ZhangYulian LiuHaian LiangMingdong LiHindawi-WileyarticleGeologyQE1-996.5ENGeofluids, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Geology QE1-996.5
spellingShingle	Geology QE1-996.5 Shuren Hao Jixiang Cao Hua Zhang Yulian Liu Haian Liang Mingdong Li Breakthrough Pressure Prediction Based on Neural Network Model
description	The increasing carbon dioxide content is identified as the main cause of global warming. Capturing carbon dioxide in the atmosphere and transporting it to deep salt layer for storage have been proven and practiced in many aspects, which considered to be an effective way to reduce the content of carbon dioxide in the atmosphere. The sealing property of cap rocks is one of the key factors to determine whether CO2 can be effectively stored for a long time. In view of the disadvantages of tedious and time-consuming laboratory test methods for breakthrough pressure of cap rock, this paper explores the relationship between breakthrough pressure and other parameters such as porosity, permeability, density, specific surface area, maximum throat radius, and total organic carbon. The results show that the rock breakthrough pressure is closely related to the maximum throat radius and permeability determined by the mercury injection method, followed by the porosity and specific surface area, and less related to the density, depth, and TOC content of the rock itself. Then, with the selected parameters, a neural network model is established to predict the breakthrough pressure of cap rock, which can achieve good prediction results.
format	article
author	Shuren Hao Jixiang Cao Hua Zhang Yulian Liu Haian Liang Mingdong Li
author_facet	Shuren Hao Jixiang Cao Hua Zhang Yulian Liu Haian Liang Mingdong Li
author_sort	Shuren Hao
title	Breakthrough Pressure Prediction Based on Neural Network Model
title_short	Breakthrough Pressure Prediction Based on Neural Network Model
title_full	Breakthrough Pressure Prediction Based on Neural Network Model
title_fullStr	Breakthrough Pressure Prediction Based on Neural Network Model
title_full_unstemmed	Breakthrough Pressure Prediction Based on Neural Network Model
title_sort	breakthrough pressure prediction based on neural network model
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/b3dcf0746a4648d0a55e2a50ecaa856d
work_keys_str_mv	AT shurenhao breakthroughpressurepredictionbasedonneuralnetworkmodel AT jixiangcao breakthroughpressurepredictionbasedonneuralnetworkmodel AT huazhang breakthroughpressurepredictionbasedonneuralnetworkmodel AT yulianliu breakthroughpressurepredictionbasedonneuralnetworkmodel AT haianliang breakthroughpressurepredictionbasedonneuralnetworkmodel AT mingdongli breakthroughpressurepredictionbasedonneuralnetworkmodel
_version_	1718418362849034240

Breakthrough Pressure Prediction Based on Neural Network Model

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