Automatic fracture–vug identification and extraction from electric imaging logging data based on path morphology

Automatic fracture–vug identification and extraction from electric imaging logging data based on path morphology

Abstract We present a path morphology method to separate total rock pore space into matrix, fractures and vugs and derive their pore structure spectrum. Thus, we can achieve fine pore evaluation in fracture–vug reservoirs based on electric imaging logging data. We automatically identify and extract...

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Autores principales: Xi-Ning Li, Jin-Song Shen, Wu-Yang Yang, Zhen-Ling Li
Formato: article
Lenguaje:EN
Publicado: KeAi Communications Co., Ltd. 2018
Materias:
Path morphology
Image automatic identification
Electric imaging logging
Fracture–vug reservoir
Science
Q
Petrology
QE420-499
Acceso en línea:https://doaj.org/article/a8c5948ec10b47b8b0f3a056c1cf7e71
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spelling oai:doaj.org-article:a8c5948ec10b47b8b0f3a056c1cf7e712021-12-02T06:39:06ZAutomatic fracture–vug identification and extraction from electric imaging logging data based on path morphology10.1007/s12182-018-0282-61672-51071995-8226https://doaj.org/article/a8c5948ec10b47b8b0f3a056c1cf7e712018-12-01T00:00:00Zhttp://link.springer.com/article/10.1007/s12182-018-0282-6https://doaj.org/toc/1672-5107https://doaj.org/toc/1995-8226Abstract We present a path morphology method to separate total rock pore space into matrix, fractures and vugs and derive their pore structure spectrum. Thus, we can achieve fine pore evaluation in fracture–vug reservoirs based on electric imaging logging data. We automatically identify and extract fracture–vug information from the electric imaging images by adopting a path morphological operator that remains flexible enough to fit rectilinear and slightly curved structures because they are independent of the structuring element shape. The Otsu method was used to extract fracture–vug information from the background noise caused by the matrix. To accommodate the differences in scale and form of the different target regions, including fracture and vug path, operators with different lengths were selected for their recognition and extraction at the corresponding scale. Polynomial and elliptic functions are used to fit the extracted fractures and vugs, respectively, and the fracture–vug parameters are deduced from the fitted edge. Finally, test examples of numerical simulation data and several measured well data have been provided for the verification of the effectiveness and adaptability of the path morphology method in the application of electric imaging logging data processing. This also provides algorithm support for the fine evaluation of fracture–vug reservoirs.Xi-Ning LiJin-Song ShenWu-Yang YangZhen-Ling LiKeAi Communications Co., Ltd.articlePath morphologyImage automatic identificationElectric imaging loggingFracture–vug reservoirScienceQPetrologyQE420-499ENPetroleum Science, Vol 16, Iss 1, Pp 58-76 (2018)
institution DOAJ
collection DOAJ
language EN
topic Path morphology
Image automatic identification
Electric imaging logging
Fracture–vug reservoir
Science
Q
Petrology
QE420-499
spellingShingle Path morphology
Image automatic identification
Electric imaging logging
Fracture–vug reservoir
Science
Q
Petrology
QE420-499
Xi-Ning Li
Jin-Song Shen
Wu-Yang Yang
Zhen-Ling Li
Automatic fracture–vug identification and extraction from electric imaging logging data based on path morphology
description Abstract We present a path morphology method to separate total rock pore space into matrix, fractures and vugs and derive their pore structure spectrum. Thus, we can achieve fine pore evaluation in fracture–vug reservoirs based on electric imaging logging data. We automatically identify and extract fracture–vug information from the electric imaging images by adopting a path morphological operator that remains flexible enough to fit rectilinear and slightly curved structures because they are independent of the structuring element shape. The Otsu method was used to extract fracture–vug information from the background noise caused by the matrix. To accommodate the differences in scale and form of the different target regions, including fracture and vug path, operators with different lengths were selected for their recognition and extraction at the corresponding scale. Polynomial and elliptic functions are used to fit the extracted fractures and vugs, respectively, and the fracture–vug parameters are deduced from the fitted edge. Finally, test examples of numerical simulation data and several measured well data have been provided for the verification of the effectiveness and adaptability of the path morphology method in the application of electric imaging logging data processing. This also provides algorithm support for the fine evaluation of fracture–vug reservoirs.
format article
author Xi-Ning Li
Jin-Song Shen
Wu-Yang Yang
Zhen-Ling Li
author_facet Xi-Ning Li
Jin-Song Shen
Wu-Yang Yang
Zhen-Ling Li
author_sort Xi-Ning Li
title Automatic fracture–vug identification and extraction from electric imaging logging data based on path morphology
title_short Automatic fracture–vug identification and extraction from electric imaging logging data based on path morphology
title_full Automatic fracture–vug identification and extraction from electric imaging logging data based on path morphology
title_fullStr Automatic fracture–vug identification and extraction from electric imaging logging data based on path morphology
title_full_unstemmed Automatic fracture–vug identification and extraction from electric imaging logging data based on path morphology
title_sort automatic fracture–vug identification and extraction from electric imaging logging data based on path morphology
publisher KeAi Communications Co., Ltd.
publishDate 2018
url https://doaj.org/article/a8c5948ec10b47b8b0f3a056c1cf7e71
work_keys_str_mv AT xiningli automaticfracturevugidentificationandextractionfromelectricimagingloggingdatabasedonpathmorphology
AT jinsongshen automaticfracturevugidentificationandextractionfromelectricimagingloggingdatabasedonpathmorphology
AT wuyangyang automaticfracturevugidentificationandextractionfromelectricimagingloggingdatabasedonpathmorphology
AT zhenlingli automaticfracturevugidentificationandextractionfromelectricimagingloggingdatabasedonpathmorphology
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