HIGH-RESOLUTION 3D IMAGE ANALYSIS OF SATURATED PORE SPACE: HOW IMAGE SEGMENTATION AND MACHINE LEARNING CAN BE APPLIED TO GROUNDWATER REMEDIATION

Groundwater reservoirs are distinguished by the petrophysical characteristics that condition their capacity to store (i.e. reservoir porosity) and transmit (i.e. reservoir permeability) significant volumes of groundwater that can be exploited by society (Feitosa et al., 2008). Recent works (Archilha...

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Main Authors: PAOLA RODRIGUES RANGEL ROSA, THIAGO VALLIN SPINA, NATHALY LOPES ARCHILHA
Format: Article
Language:English
Published: Associação Brasileira de Águas Subterrâneas 2019-01-01
Series:Revista Águas Subterrâneas
Online Access:https://aguassubterraneas.abas.org/asubterraneas/article/view/29451
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spelling doaj-c1fd0142b6a04cf3a8f3bddd169a25f62020-11-25T01:20:31ZengAssociação Brasileira de Águas SubterrâneasRevista Águas Subterrâneas0101-70042179-97842019-01-010010.14295/ras.v0i0.2945117505HIGH-RESOLUTION 3D IMAGE ANALYSIS OF SATURATED PORE SPACE: HOW IMAGE SEGMENTATION AND MACHINE LEARNING CAN BE APPLIED TO GROUNDWATER REMEDIATIONPAOLA RODRIGUES RANGEL ROSATHIAGO VALLIN SPINANATHALY LOPES ARCHILHAGroundwater reservoirs are distinguished by the petrophysical characteristics that condition their capacity to store (i.e. reservoir porosity) and transmit (i.e. reservoir permeability) significant volumes of groundwater that can be exploited by society (Feitosa et al., 2008). Recent works (Archilha, N. L., 2015a; Archilla et al., 2016; Eberli et al., 2003) showed that specific properties from the pore space, such as pore geometry and pore connectivity, also control the pore space permeability. High resolution X-ray imaging can reveal complex 3D structures without destroying the samples. Through digital slicing, it is possible to determine pore surface area, volume, connectivity, and many other microproperties of individual pores. In the case of saturated pores spaces, it is also possible to reveal and distinguish the different saturating phases, such as oil, contaminants, water, gas, etc. All this characterization is only possible if the 3D image, originally in grey scale, is segmented, i.e. partitioned into multiple segments that share the same attributes. In this work we segment two saturated pore scales: (i) a real dolomite rock, saturated with a non-aqueous phase liquid (NAPLs) and water and (ii) a pack of glass beads saturated with water and a toxic halocarbon industrial solvent. The segmented image is now being used to train different machine learning models for, soon in the future, turn this time-consuming segmentation method into a quick and reliable process. This has a very important implication to a cutting-edge technique: time resolved X-ray tomography (so called 4D X-ray tomography), which allows the 3D study, in real time, of any type of fluid flow in porous media.https://aguassubterraneas.abas.org/asubterraneas/article/view/29451
collection DOAJ
language English
format Article
sources DOAJ
author PAOLA RODRIGUES RANGEL ROSA
THIAGO VALLIN SPINA
NATHALY LOPES ARCHILHA
spellingShingle PAOLA RODRIGUES RANGEL ROSA
THIAGO VALLIN SPINA
NATHALY LOPES ARCHILHA
HIGH-RESOLUTION 3D IMAGE ANALYSIS OF SATURATED PORE SPACE: HOW IMAGE SEGMENTATION AND MACHINE LEARNING CAN BE APPLIED TO GROUNDWATER REMEDIATION
Revista Águas Subterrâneas
author_facet PAOLA RODRIGUES RANGEL ROSA
THIAGO VALLIN SPINA
NATHALY LOPES ARCHILHA
author_sort PAOLA RODRIGUES RANGEL ROSA
title HIGH-RESOLUTION 3D IMAGE ANALYSIS OF SATURATED PORE SPACE: HOW IMAGE SEGMENTATION AND MACHINE LEARNING CAN BE APPLIED TO GROUNDWATER REMEDIATION
title_short HIGH-RESOLUTION 3D IMAGE ANALYSIS OF SATURATED PORE SPACE: HOW IMAGE SEGMENTATION AND MACHINE LEARNING CAN BE APPLIED TO GROUNDWATER REMEDIATION
title_full HIGH-RESOLUTION 3D IMAGE ANALYSIS OF SATURATED PORE SPACE: HOW IMAGE SEGMENTATION AND MACHINE LEARNING CAN BE APPLIED TO GROUNDWATER REMEDIATION
title_fullStr HIGH-RESOLUTION 3D IMAGE ANALYSIS OF SATURATED PORE SPACE: HOW IMAGE SEGMENTATION AND MACHINE LEARNING CAN BE APPLIED TO GROUNDWATER REMEDIATION
title_full_unstemmed HIGH-RESOLUTION 3D IMAGE ANALYSIS OF SATURATED PORE SPACE: HOW IMAGE SEGMENTATION AND MACHINE LEARNING CAN BE APPLIED TO GROUNDWATER REMEDIATION
title_sort high-resolution 3d image analysis of saturated pore space: how image segmentation and machine learning can be applied to groundwater remediation
publisher Associação Brasileira de Águas Subterrâneas
series Revista Águas Subterrâneas
issn 0101-7004
2179-9784
publishDate 2019-01-01
description Groundwater reservoirs are distinguished by the petrophysical characteristics that condition their capacity to store (i.e. reservoir porosity) and transmit (i.e. reservoir permeability) significant volumes of groundwater that can be exploited by society (Feitosa et al., 2008). Recent works (Archilha, N. L., 2015a; Archilla et al., 2016; Eberli et al., 2003) showed that specific properties from the pore space, such as pore geometry and pore connectivity, also control the pore space permeability. High resolution X-ray imaging can reveal complex 3D structures without destroying the samples. Through digital slicing, it is possible to determine pore surface area, volume, connectivity, and many other microproperties of individual pores. In the case of saturated pores spaces, it is also possible to reveal and distinguish the different saturating phases, such as oil, contaminants, water, gas, etc. All this characterization is only possible if the 3D image, originally in grey scale, is segmented, i.e. partitioned into multiple segments that share the same attributes. In this work we segment two saturated pore scales: (i) a real dolomite rock, saturated with a non-aqueous phase liquid (NAPLs) and water and (ii) a pack of glass beads saturated with water and a toxic halocarbon industrial solvent. The segmented image is now being used to train different machine learning models for, soon in the future, turn this time-consuming segmentation method into a quick and reliable process. This has a very important implication to a cutting-edge technique: time resolved X-ray tomography (so called 4D X-ray tomography), which allows the 3D study, in real time, of any type of fluid flow in porous media.
url https://aguassubterraneas.abas.org/asubterraneas/article/view/29451
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AT thiagovallinspina highresolution3dimageanalysisofsaturatedporespacehowimagesegmentationandmachinelearningcanbeappliedtogroundwaterremediation
AT nathalylopesarchilha highresolution3dimageanalysisofsaturatedporespacehowimagesegmentationandmachinelearningcanbeappliedtogroundwaterremediation
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