Development of a novel image analysis procedure to quantify biological porosity and illuvial clay in large soil thin sections

Geoderma ◽  
2017 ◽  
Vol 292 ◽  
pp. 135-148 ◽  
Author(s):  
Ophélie Sauzet ◽  
Cécilia Cammas ◽  
Jean Marc Gilliot ◽  
Manon Bajard ◽  
David Montagne
Keyword(s):  
Image Analysis ◽  
Analysis Procedure ◽  
Thin Sections ◽  
Large Soil

Correlation of Pore Structure and Permeability by SEM-Image Analysis

1990 ◽  
Vol 48 (1) ◽  
pp. 428-429
Author(s):  
C. A. Callender ◽  
Wm. C. Dawson ◽  
J. J. Funk
Keyword(s):  
Image Analysis ◽  
Pore Structure ◽  
Imaging System ◽  
Pore Space ◽  
Simulation Models ◽  
Image Analyzer ◽  
Imaging Data ◽  
Sem Images ◽  
Thin Sections ◽  
Rock Types

The geometric structure of pore space in some carbonate rocks can be correlated with petrophysical measurements by quantitatively analyzing binaries generated from SEM images. Reservoirs with similar porosities can have markedly different permeabilities. Image analysis identifies which characteristics of a rock are responsible for the permeability differences. Imaging data can explain unusual fluid flow patterns which, in turn, can improve production simulation models.Analytical SchemeOur sample suite consists of 30 Middle East carbonates having porosities ranging from 21 to 28% and permeabilities from 92 to 2153 md. Engineering tests reveal the lack of a consistent (predictable) relationship between porosity and permeability (Fig. 1). Finely polished thin sections were studied petrographically to determine rock texture. The studied thin sections represent four petrographically distinct carbonate rock types ranging from compacted, poorly-sorted, dolomitized, intraclastic grainstones to well-sorted, foraminiferal,ooid, peloidal grainstones. The samples were analyzed for pore structure by a Tracor Northern 5500 IPP 5B/80 image analyzer and a 80386 microprocessor-based imaging system. Between 30 and 50 SEM-generated backscattered electron images (frames) were collected per thin section. Binaries were created from the gray level that represents the pore space. Calculated values were averaged and the data analyzed to determine which geological pore structure characteristics actually affect permeability.

Validation of a new image analysis procedure for quantifying filamentous bacteria in activated sludge

2014 ◽  
Vol 70 (6) ◽  
pp. 955-963 ◽  
Author(s):  
Ewa Liwarska-Bizukojc ◽  
Marcin Bizukojc ◽  
Olga Andrzejczak
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Activated Sludge ◽  
Analysis Procedure ◽  
Automated Image Analysis ◽  
Filamentous Bacteria ◽  
Image Processing And Analysis ◽  
Manual Counting ◽  
Analysis Application ◽  
Activated Sludge Systems

Quantification of filamentous bacteria in activated sludge systems can be made by manual counting under a microscope or by the application of various automated image analysis procedures. The latter has been significantly developed in the last two decades. In this work a new method based upon automated image analysis techniques was elaborated and presented. It consisted of three stages: (a) Neisser staining, (b) grabbing of microscopic images, and (c) digital image processing and analysis. This automated image analysis procedure possessed the features of novelty. It simultaneously delivered data about aggregates and filaments in an individual calculation routine, which is seldom met in the procedures described in the literature so far. What is more important, the macroprogram performing image processing and calculation of morphological parameters was written in the same software which was used for grabbing of images. Previously published procedures required using two different types of software, one for image grabbing and another one for image processing and analysis. Application of this new procedure for the quantification of filamentous bacteria in the full-scale as well as laboratory activated sludge systems proved that it was simple, fast and delivered reliable results.

QUANTIFICATION OF POROSITY IN SUBSTRATES USING THIN SECTIONS AND IMAGE ANALYSIS

2012 ◽  
pp. 105-110
Author(s):  
L. Pineda-Marín ◽  
M.C. Gutiérrez-Castorena ◽  
R. Anicua-Sánchez ◽  
L. Cajuste-Bontemps ◽  
E.V. Gutiérrez-Castorena
Keyword(s):  
Image Analysis ◽  
Thin Sections

Use of image analysis for sludge characterisation: studying the relation between floc shape and sludge settleability

2006 ◽  
Vol 54 (1) ◽  
pp. 167-174 ◽  
Author(s):  
R. Jenné ◽  
E.N. Banadda ◽  
G. Gins ◽  
J. Deurinck ◽  
I.Y. Smets ◽  
...  
Keyword(s):  
Image Analysis ◽  
Principal Component ◽  
Analysis Procedure ◽  
Volume Index ◽  
Data Sets ◽  
Shape Descriptors ◽  
Automatic Image Analysis ◽  
Sludge Volume Index ◽  
Fully Automatic ◽  
Sludge Settleability

This paper starts by presenting a fully automatic image analysis procedure for characterisation of flocs and filaments in activated sludge images. Thereafter the attention is directed towards the results of four lab-scale experiments, in which image information is related to sludge settleability in terms of sludge volume index. This relation is statistically confirmed by applying a principal component analysis to the data. In addition, the redundancy in the data sets is studied with regard to floc shape descriptors and the monitoring potential of image analysis is demonstrated by means of a multiple linear regression exercise.

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