Research on Test and Logging Data Quality Classification for Gas–Water Identification

Tight sandstone oil and gas reservoirs are widely distributed, rich in resources, with a bright prospect for exploration and development in China. Due to multiple evolutions of the structure and sedimentary system, the gas–water distribution laws are complicated in tight sandstone gas reservoirs in...

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Autores principales:	Zehou Xiang, Kesai Li, Hucheng Deng, Yan Liu, Jianhua He, Xiaoju Zhang, Xianhong He
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	tight oil and gas reservoirs gas–water identification test quality classification gas test well-logging Technology T
Acceso en línea:	https://doaj.org/article/2010ccd2373443b7b87beed4c17ad812
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id	oai:doaj.org-article:2010ccd2373443b7b87beed4c17ad812
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spelling	oai:doaj.org-article:2010ccd2373443b7b87beed4c17ad8122021-11-11T15:48:30ZResearch on Test and Logging Data Quality Classification for Gas–Water Identification10.3390/en142169911996-1073https://doaj.org/article/2010ccd2373443b7b87beed4c17ad8122021-10-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/21/6991https://doaj.org/toc/1996-1073Tight sandstone oil and gas reservoirs are widely distributed, rich in resources, with a bright prospect for exploration and development in China. Due to multiple evolutions of the structure and sedimentary system, the gas–water distribution laws are complicated in tight sandstone gas reservoirs in the northern Ordos area. It is difficult to identify gas and water layers in the study area. In addition, in the development and production, various factors, such as the failure of the instrument, the difference in construction parameters (injected sand volume, flowback rate), poor test results, and multi-layer joint testing lead to unreliable gas test results. Then, the inaccurate logging responses will be screened by unreliable gas test results for different types of fluids. It is hard to make high-precision fluid logging identification charts or models. Therefore, this article combines gas logging, well logging, testing and other data to research the test and logging data quality classification. Firstly, we select reliable standard samples through the initial gas test results. Secondly, we analyze the four main factors which affect the inaccuracy of gas test results. Thirdly, according to these factors, the flowback rate and the sand volume are determined as the main parameters. Then, we establish a recognition chart of injected sand volume/gas–water ratio. Finally, we proposed an evaluation method for testing quality classification. It provides a test basis for the subsequent identification of gas and water through the second logging interpretation. It also provides a theoretical basis for the exploration and evaluation of tight oil and gas reservoirs.Zehou XiangKesai LiHucheng DengYan LiuJianhua HeXiaoju ZhangXianhong HeMDPI AGarticletight oil and gas reservoirsgas–water identificationtest quality classificationgas testwell-loggingTechnologyTENEnergies, Vol 14, Iss 6991, p 6991 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	tight oil and gas reservoirs gas–water identification test quality classification gas test well-logging Technology T
spellingShingle	tight oil and gas reservoirs gas–water identification test quality classification gas test well-logging Technology T Zehou Xiang Kesai Li Hucheng Deng Yan Liu Jianhua He Xiaoju Zhang Xianhong He Research on Test and Logging Data Quality Classification for Gas–Water Identification
description	Tight sandstone oil and gas reservoirs are widely distributed, rich in resources, with a bright prospect for exploration and development in China. Due to multiple evolutions of the structure and sedimentary system, the gas–water distribution laws are complicated in tight sandstone gas reservoirs in the northern Ordos area. It is difficult to identify gas and water layers in the study area. In addition, in the development and production, various factors, such as the failure of the instrument, the difference in construction parameters (injected sand volume, flowback rate), poor test results, and multi-layer joint testing lead to unreliable gas test results. Then, the inaccurate logging responses will be screened by unreliable gas test results for different types of fluids. It is hard to make high-precision fluid logging identification charts or models. Therefore, this article combines gas logging, well logging, testing and other data to research the test and logging data quality classification. Firstly, we select reliable standard samples through the initial gas test results. Secondly, we analyze the four main factors which affect the inaccuracy of gas test results. Thirdly, according to these factors, the flowback rate and the sand volume are determined as the main parameters. Then, we establish a recognition chart of injected sand volume/gas–water ratio. Finally, we proposed an evaluation method for testing quality classification. It provides a test basis for the subsequent identification of gas and water through the second logging interpretation. It also provides a theoretical basis for the exploration and evaluation of tight oil and gas reservoirs.
format	article
author	Zehou Xiang Kesai Li Hucheng Deng Yan Liu Jianhua He Xiaoju Zhang Xianhong He
author_facet	Zehou Xiang Kesai Li Hucheng Deng Yan Liu Jianhua He Xiaoju Zhang Xianhong He
author_sort	Zehou Xiang
title	Research on Test and Logging Data Quality Classification for Gas–Water Identification
title_short	Research on Test and Logging Data Quality Classification for Gas–Water Identification
title_full	Research on Test and Logging Data Quality Classification for Gas–Water Identification
title_fullStr	Research on Test and Logging Data Quality Classification for Gas–Water Identification
title_full_unstemmed	Research on Test and Logging Data Quality Classification for Gas–Water Identification
title_sort	research on test and logging data quality classification for gas–water identification
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/2010ccd2373443b7b87beed4c17ad812
work_keys_str_mv	AT zehouxiang researchontestandloggingdataqualityclassificationforgaswateridentification AT kesaili researchontestandloggingdataqualityclassificationforgaswateridentification AT huchengdeng researchontestandloggingdataqualityclassificationforgaswateridentification AT yanliu researchontestandloggingdataqualityclassificationforgaswateridentification AT jianhuahe researchontestandloggingdataqualityclassificationforgaswateridentification AT xiaojuzhang researchontestandloggingdataqualityclassificationforgaswateridentification AT xianhonghe researchontestandloggingdataqualityclassificationforgaswateridentification
_version_	1718433813175992320

Research on Test and Logging Data Quality Classification for Gas–Water Identification

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