Pore network quantification of sandstones under experimental CO2 injection using image analysis

Berrezueta, Edgar; González-Menéndez, L.; Ordóñez-Casado, Berta; Olaya, Peter

doi:10.1016/j.cageo.2015.01.005

Cited by 36 publications

(21 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…3) before and after SC CO 2 -brine exposure. The general procedure for the automated image analysis was developed, adapting the procedures and algorithms described by Berrezueta et al (2015), in order to quantify the textural and porosity changes (area, roughness of minerals/pore boundaries, fractal dimension, roundness of minerals/pores and porosity) provoked by experimental CO 2 injection. Assessment of pore-network distribution by optical transmitted light studies of thin sections requires distinction between mineral and pore networks according to their optical characteristics.…”

Section: Methodology Of Studymentioning

confidence: 99%

Qualitative and quantitative changes in detrital reservoir rocks caused by CO<sub>2</sub>–brine–rock interactions during first injection phases (Utrillas sandstones, northern Spain)

2016

View full text Add to dashboard Cite

Abstract. The aim of this article is to describe and interpret qualitative and quantitative changes at rock matrix scale of lower-upper Cretaceous sandstones exposed to supercritical (SC) CO 2 and brine. The effects of experimental injection of CO 2 -rich brine during the first injection phases were studied at rock matrix scale, in a potential deep sedimentary reservoir in northern Spain (Utrillas unit, at the base of the Cenozoic Duero Basin).Experimental CO 2 -rich brine was exposed to sandstone in a reactor chamber under realistic conditions of deep saline formations (P ≈ 7.8 MPa, T ≈ 38 • C and 24 h exposure time). After the experiment, exposed and non-exposed equivalent sample sets were compared with the aim of assessing possible changes due to the effect of the CO 2 -rich brine exposure. Optical microscopy (OpM) and scanning electron microscopy (SEM) aided by optical image analysis (OIA) were used to compare the rock samples and get qualitative and quantitative information about mineralogy, texture and pore network distribution. Complementary chemical analyses were performed to refine the mineralogical information and to obtain whole rock geochemical data. Brine composition was also analyzed before and after the experiment.The petrographic study of contiguous sandstone samples (more external area of sample blocks) before and after CO 2 -rich brine injection indicates an evolution of the pore network (porosity increase ≈ 2 %). It is probable that these measured pore changes could be due to intergranular quartz matrix detachment and partial removal from the rock sample, considering them as the early features produced by the CO 2 -rich brine. Nevertheless, the whole rock and brine chemical analyses after interaction with CO 2 -rich brine do not present important changes in the mineralogical and chemical configuration of the rock with respect to initial conditions, ruling out relevant precipitation or dissolution at these early stages to rock-block scale. These results, simulating the CO 2 injection near the injection well during the first phases (24 h) indicate that, in this environment where CO 2 enriches the brine, the mixture principally generates local mineralogical/textural readjustments on the external area of the samples studied.The application of OpM, SEM and optical image analysis have allowed an exhaustive characterization of the sandstones studied. The procedure followed, the porosity characterization and the chemical analysis allowed a preliminary approximation of the CO 2 -brine-rock interactions and could be applied to similar experimental injection tests.

show abstract

Section: Methodology Of Studymentioning

confidence: 99%

Qualitative and quantitative changes in detrital reservoir rocks caused by CO<sub>2</sub>–brine–rock interactions during first injection phases (Utrillas sandstones, northern Spain)

2016

View full text Add to dashboard Cite

show abstract

“…In more recent years, with improvements in computer power and storage capabilities, it has become possible to use SEM to acquire high-resolution images over increasingly larger areas [2][3][4][5]. Pore image analysis from SEM images for a variety of porous media have been performed by a number of authors [6][7][8], and are routinely used in the analysis of petrographic thin sections examined by optical microscopy [9,10]. Image analysis has an important role in supporting microscopic observations, being used to improve pore characterization of sedimentary rocks (pore shape, size, orientation, distribution, etc.).…”

Section: Introductionmentioning

confidence: 99%

Quantifying Porosity through Automated Image Collection and Batch Image Processing: Case Study of Three Carbonates and an Aragonite Cemented Sandstone

et al. 2017

View full text Add to dashboard Cite

Abstract:Modern scanning electron microscopes often include software that allows for the possibility of obtaining large format high-resolution image montages over areas of several square centimeters. Such montages are typically automatically acquired and stitched, comprising many thousand individual tiled images. Images, collected over a regular grid pattern, are a rich source of information on factors such as variability in porosity and distribution of mineral phases, but can be hard to visually interpret. Additional quantitative data can be accessed through the application of image analysis. We use backscattered electron (BSE) images, collected from polished thin sections of two limestone samples from the Cretaceous of Brazil, a Carboniferous limestone from Scotland, and a carbonate cemented sandstone from Northern Ireland, with up to 25,000 tiles per image, collecting numerical quantitative data on the distribution of porosity. Images were automatically collected using the FEI software Maps, batch processed by image analysis (through ImageJ), with results plotted on 2D contour plots with MATLAB. These plots numerically and visually clearly express the collected porosity data in an easily accessible form, and have application for the display of other data such as pore size, shape, grain size/shape, orientation and mineral distribution, as well as being of relevance to sandstone, mudrock and other porous media.

show abstract

“…Our goal was to produce an example of the type of information that the proposed methodology could provide when applied to real rock samples. The automated segmentation of quartz particles was carried out in previous studies [40,54] by applying a segmentation algorithm developed in Aphelion 3.2. In addition, the evaluation process proposed by [16] was applied on samples from a case study.…”

Section: Application To a Case Study And Validationmentioning

confidence: 99%

“…Furthermore, computer vision-based image processing provides shape measurements of particles or granular materials [17,30,[34][35][36][37]. The quantification and analysis of particles' sizes and shapes, and their distribution, have been successfully addressed through the use of: (i) advanced programming using specialized languages (e.g., C++ and Visual basic) or software (i.e., Matlab) with a specific image processing tool box (i.e., [38,39]), (ii) commercial image processing software (e.g., Image-Pro Plus ® , Aphelion) with morphological functions and a programming module (e.g., Visual basic) to automate the procedure [40], and (iii) free and open source image processing programs (e.g., ImageJ: [35,41]). Due to precision image scales and high data density, observations and measurements are capable of combining roundness and roughness.As mentioned above, although conceptually the three descriptors of particle form (sphericity, roundness, and roughness) are independent of each other [1,2,23], some parameters that define them lose their independence due to the methods by which they are obtained.…”

mentioning

confidence: 99%

Representativity of 2D Shape Parameters for Mineral Particles in Quantitative Petrography

et al. 2019

Self Cite

View full text Add to dashboard Cite

This paper introduces an assessment of the representation of shape parameter measurements on theoretical particles. The aim of the study was to establish a numerical method for estimating sphericity, roundness, and roughness on artificially designed particles and to evaluate their interdependence. The parameters studied included a fractal dimension (FD), solidity (So), Wadell's roundness (Rw), a perimeter-area normalized ratio (¥), and sphericity (S). The methods of the work included: (a) the design of theoretical particles with different shapes, (b) the definition of optimal analysis conditions for automated measurements, (c) the quantification of particle parameters by computer vision-based image processing, and (d) the evaluation of interdependence between the parameters. The study established the minimum sizes required for analysis of the particle shape. These varied depending on the method used (150 pixels or 50 pixels). Evaluating the relationships between the parameters showed that FD and So are independent of S. Nevertheless, Rw and ¥ are clearly dependent on S and, thus, must be numerically corrected to Rwc and ¥c. FD, So, Rwc, and ¥c were used to establish, mathematically, a new regularity parameter (RBC) that reflects the degree of roundness of a particle. The process was applied to a case study and the evaluation of all parameters corroborated previous petrographic characterizations. Minerals 2019, 9, 768 2 of 21 corners of the particle. Six categories of roundness for sediment grains have been established and, for each category, one grain of low and one of high sphericity was introduced [3,6-9]. The six categories are: Very angular, angular, subangular, sub-rounded, rounded, and well-rounded. Two-dimensional particle shape measurements are particularly applicable when individual particles cannot be extracted from the rock matrix (e.g., thin sections under an optical microscope). Microscopic images are two-dimensional. Therefore, they only show part of the shape of the three-dimensional particle. The assessed image is usually of particles lying on their most stable plane on a flat support, i.e., showing the largest projection area.Traditionally, roundness indices compare the outline of a 2D projection of the particle to a circle. The first comparison defines the roundness as the ratio ri/R, which was shown in [10] (where ri is the radius of the sharpest corner, and R is the radius of the smallest circumscribing sphere). On the other hand, [11] defined the roundness parameter based on the radius of the curvature of particle corners and the radius of the largest inscribed sphere.[6] and [7] used comparison charts with a class limit table for roundness. Some authors considered angularity to be the opposite of roundness, while others considered the degree of angularity [12] to be a combination of the angular relationship between the planes bounding a corner and the distance of the corner from the center of the particle. The overall particle form heavily influences the method. In addition, [12] presente...

show abstract

Pore network quantification of sandstones under experimental CO2 injection using image analysis

Cited by 36 publications

References 32 publications

Qualitative and quantitative changes in detrital reservoir rocks caused by CO<sub>2</sub>–brine–rock interactions during first injection phases (Utrillas sandstones, northern Spain)

Qualitative and quantitative changes in detrital reservoir rocks caused by CO<sub>2</sub>–brine–rock interactions during first injection phases (Utrillas sandstones, northern Spain)

Quantifying Porosity through Automated Image Collection and Batch Image Processing: Case Study of Three Carbonates and an Aragonite Cemented Sandstone

Representativity of 2D Shape Parameters for Mineral Particles in Quantitative Petrography

Contact Info

Product

Resources

About

Pore network quantification of sandstones under experimental CO2 injection using image analysis

Cited by 36 publications

References 32 publications

Qualitative and quantitative changes in detrital reservoir rocks caused by CO&lt;sub&gt;2&lt;/sub&gt;–brine–rock interactions during first injection phases (Utrillas sandstones, northern Spain)

Qualitative and quantitative changes in detrital reservoir rocks caused by CO&lt;sub&gt;2&lt;/sub&gt;–brine–rock interactions during first injection phases (Utrillas sandstones, northern Spain)

Quantifying Porosity through Automated Image Collection and Batch Image Processing: Case Study of Three Carbonates and an Aragonite Cemented Sandstone

Representativity of 2D Shape Parameters for Mineral Particles in Quantitative Petrography

Contact Info

Product

Resources

About

Qualitative and quantitative changes in detrital reservoir rocks caused by CO<sub>2</sub>–brine–rock interactions during first injection phases (Utrillas sandstones, northern Spain)

Qualitative and quantitative changes in detrital reservoir rocks caused by CO<sub>2</sub>–brine–rock interactions during first injection phases (Utrillas sandstones, northern Spain)