بررسی ارتباط بین ویژگی‌ های بافتی و کانی‌ شناسی سنگ‌ های آذرین متبلور با کمینه‌ سازی بافتی به کمک آنالیز تصویری

مشخصات پتروگرافیکی همچون بافت، کانی‌شناسی و ریزساختار، اثری بنیادی بر ویژگی‌های فیزیکی و کیفی مصالح دارد. بسیاری از معیارهای طبقه‌بندی بنیادی یا انتخاب کیفی مصالح برای کاربردهای صنعتی بر مبنای ویژگی‌های بافتیکانی‌شناسی و شیمیایی تعیین می‌شوند. آگاهی از اهمیت و درک ارتباط متقابل انواع مولفه‌های بافتی، کانی‌شناسی و شیمی‌بلورها می‌تواند در پیشگویی رفتارهای کمی و کیفی مصالح موثر واقع‌شود. در این پژوهش، پتروگرافیکی بافتی 15 نوع سنگ آذرین متبلور با تنوع گسترده بافتیکانی‌شناسی به‌روش آنالیز تصویری مقاطع میکروسکوپی کمینه‌سازی و بانک داده‌ای مشتمل بر مشخصات بافتی‌کانی‌شناسی حدود 18000 کانی ایجاد‌شد. هم‌زمان نقشه توزیع کانی‌شناسی تهیه و در کنار پتروگرافی توصیفی برای تحلیل روابط بافتی‌کانی‌شناسی به‌کار گرفته‌شد. میانگین حسابی مولفه‌های طبقه‌بندی شده اندازه‌سنجی، شکل‌سنجی و ارتباط‌ بین‌دانه‌ای در سطوح مختلف دانه‌ای و فازی (کانی‌شناسی) تعیین و ارتباط بین مولفه‌های بافتی با کانی‌شناسی و شیمی‌بلورها و نیز ارتباط بینابینی بین انواع مولفه‌های بافتی با تحلیل‌های رگرسیونی خطی مورد ارزیابی قرار‌گرفت. نتایج پژوهش نشان‌داد اندازه (در اقسام مختلف طول، مساحت و محیط) مهم‌ترین مولفه بافتی سنگ‌های متبلور است که با ویژگی‌های بافتی و ماهیتی (کانی‌شناسی و شیمی) بلورها در ارتباط است. به‌علاوه بررسی توزیع آماری ویژگی‌های بافتی بلورها نشان‌داد به‌دلیل توزیع نامتقارن و غیرنرمال توزیع اندازه بلورها، برآورد اندازه متوسط به‌روش میانگین حسابی اغلب با خطای غیرقابل‌اجتناب تمایل به‌ریزدانه همراه است؛ در‌حالی‌که ویژگی‌های بافتی و کیفی سنگ‌ها با فراوانی محتوای حجمی دانه‌درشت و دانه‌متوسط کنترل می‌شود. برای تعدیل این خطا، قطر میانگین مساحتموزون مستخرج از منحنی‌های توزیع تجمعی برای تعیین میانگین اندازه دانه (بلورها) مصالح متبلور به‌ویژه با تنوع گسترده در اندازه دانه پیشنهاد شد.

Relationship between Textural and Mineralogical Properties of Crystalline Igneous Rocks Using Textural Quantification by Image Analysis

Introduction;The mineralogical and textural characteristics of rock materials have an important influence on physicomechanical properties. The effects of some textural characteristics like grain size (Brace, 1961), grain shape (Cox and Budhu, 2008), grain surface (Diepenbroek et al., 1992), grain size distribution (Gurkan Ozgurel and Vipulanandan, 2005), and grains interlocking (Hoek, 1965) on physicomechanical behavior of rock materials has always been emphasized. On the other hand, it has been found that textural properties are originally controlled by the mineralogy and chemistry of rock materials (Locat et al., 1984). Knowing the textural, mineralogical and chemical properties of rock materials and understanding the governing relationships can help us predict the quantitative and qualitative behavior of rock materials. The aim of this study is to investigate the interrelationships among the various textural properties besides the relationship between the textural characteristics and the mineralogy and chemical composition.; ;Materials and methods;Fifteen crystalline igneous rock samples including a wide variety of rock types and grain size were collected from the granite quarries of NW Iran (Fig. 1) and the thin sections of the samples were prepared for quantification of the textural characteristic by image acquisition analysis under a polarized microscope. A total of 360 digital photomicrographs of each thin section were taken from the entire surface area of the thin section in three steps of natural light (PPL), polarizing light (XPL), and polarized light by a 45° rotation of the stage (Fig. 2). After preprocessing of distortion and skewness, the images were joined by Adobe Photoshop software to make the integrated mosaic image layers. The grain boundary tracing was carried out by drawing the grain outline through the interface of the adjacent grains via the three mosaic image layers on the background using the JMicroVision software (schematic diagram in Fig. 3). Simultaneously, identification and documentation of the mineral grains (crystals) were conducted by utilizing the optical properties of the minerals occurring in image layers. Overall, about 18,000 mineral grains were traced from the thin sections of fifteen samples. The accomplished graphic files after some of the fileformat conversions were loaded by the ArcMap program to extract the main geometric textural properties like length, width, area, perimeter, circularity, and some related geometric concepts (Fig. 4) which were used to calculate advanced textural parameters such as roughness, rugosity, etc. Simultaneously, the mineralogy composition of the samples was obtained from the covered area of minerals in thin sections and used for classification of the samples according to the IUGS system (Fig. 5). In addition, textural mineral distribution map (TMDM) of the samples (Fig 6) were prepared and used to do petrographic textural studies of the samples.; ;Discussion;The results of correlations revealed that "size " is the most important textural parameter, which shows a notable relationship with mineralogy and chemical composition of the studied rock samples. Moreover, the result exhibited that the number frequency graphs of the grains (crystals) size distribution are asymmetric and nonnormal that show negative (right) skewness. Consequently, arithmetic average cannot be an acceptable statistical mean to determine the average of the grain size due to the finegrains tendency error, whereas textural and qualitative properties of rock are mainly controlled by the coarse and moderate grains content. Thus, the areaweighted mean diameter extracted from the cumulative distribution curves, (Fig 22) was suggested instead of the common arithmetic average to determine the mean grains size of the crystallized rock material. In addition, it was found that the elongation (aspect ratio) of the grains shows a good correlation with most of the shapemetric and grainsinterrelation parameter. Thus, it should be considered as an efficient textural index to evaluate the grains interrelationships rather than the common texture coefficient (TC) index because of the simplicity and rapidity of its calculation.; ;Results and Conclusions;The statistical mean of the geometric textural parameters besides the total constituent grains were determined for the main minerals phases (quartz, plagioclase, alkalifeldspar) and mafic minerals (here all the other minerals). Therefore, correlation analyses were conducted among the various nonphasic and phasic textural variable as well as the chemical and mineralogical composition. The analysis was carried out through classification of textural parameters into three main groups of sizemetric (diameter, area and perimeter), shapemetric (elongation, circularity, rectangularity, roundness, roughness, rugosity and compactness) and graininteraction (size homogeneity, heterogeneity index, interlocking index and Texture Coefficient) parameters with respect to the nature of parameters ' demands. Considering abundance of the evaluating textural variable, at first, the matrix correlations among the various textural, mineralogical and chemical variables were calculated and the significant correlations were interpreted via linear regression analyses and graphical illustrations.; ;References;Brace, W.F., 1961. Dependence of fracture strength of rocks on grain size. 4th Symposium on Rock Mechanics, Pennsylvania State University, Pennsylvania, USA.;Cox, M.R. and Budhu, M., 2008. A practical approach to grain shape quantification. Engineering Geology, 96(1–2): 1–16.;Diepenbroek, M., Bartholomä, A., and Ibbeken, H., 1992. How round is round? A new approach to the topic “roundness” by Fourier grain shape analysis. Sedimentology, 39(3): 11–422.;Gurkan Ozgurel, H. and Vipulanandan, C., 2005. Effect of Grain Size and Distribution on Permeability and Mechanical Behavior of Acrylamide Grouted Sand. Journal of Geotechnical and Geoenvironmental Engineering, 131(12): 1457–1465.;Hoek, E., 1965. Rock Fracture under Static Stress Conditions. Ph.D. Thesis, University of Cape Town, Cape Town, South Africa, 270 pp.;Locat, J., Lefebvre, G. and Ballivy, G., 1984. Mineralogy, chemistry, and physical properties interrelationships of some sensitive clays from Eastern Canada. Canadian Geotechnical Journal, 21(3): 530–540.