Application of automated image analysis to coal petrography

International Journal of Coal Geology, 2 (1982) 113--150

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Elsevier Scientific Publishing Company, Amsterdam -- Printed in The Netherlands

APPLICATION OF AUTOMATED IMAGE ANALYSIS TO COAL PETROGRAPHY

E.C.T. CHAO, J.A. MINKIN and C.L. THOMPSON

National Center, U.S. Geological Survey, Mail Stop 929, Reston, Va. 22092 (U.S.A.) (Received September 25, 1981; revised and accepted June 10, 1982)

ABSTRACT Chao, E.C.T., Minkin, J.A. and Thompson, C.L., 1982. Application of automated image analysis to coal petrography. Int. J. Coal Geol., 2:113--150. The coal petrologist seeks to determine the petrographic characteristics of organic and inorganic coal constituents and their lateral and vertical variations within a single coal bed or different coal beds of a particular coal field. Definitive descriptions of coal characteristics and coal facies provide the basis for interpretation of depositional environments, diagenetic changes, and burial history and determination of the degree of coalification or metamorphism. Numerous coal core or columnar samples must be studied in detail in order to adequately describe and define coal microlithotypes, lithotypes, and lithologic facies and their variations. The large amount of petrographic information required can be obtained rapidly and quantitatively by use of an automated image-analysis system (AIAS). An AIAS can be used to generate quantitative megascopic and microscopic modal analyses for the lithologic units of an entire columnar section of a coal bed. In our scheme for megascopic analysis, distinctive bands 2 m m or more thick are first demarcated by visual inspection. These bands consist of either nearly pure microlithotypes or lithotypes such as vitrite/vitrain or fusite/fusain, or assemblages of microlithotypes. Megascopic analysis with the aid of the AIAS is next performed to determine volume percentages of vitrite, inertite, minerals, and microlithotype mixtures in bands 0.5 to 2 m m thick. The microlithotype mixtures are analyzed microscopically by use of the AIAS to determine their modal composition in terms of maceral and optically observable mineral components. Megascopic and microscopic data are combined to describe the coal unit quantitatively in terms of (V) for vitrite, (E) for liptite, (I) for inertite or fusite, (M) for mineral components other than iron sulfide, (S) for iron sulfide, and (VEIM) for the composition of the mixed phases (Xi) i = 1,2, etc. in terms of the maceral groups vitrinite V, exinite E, inertinite I, and optically observable mineral content M. The volume percentage of each component present is indicated by a subscript. For example, a lithologic unit was determined megascopically to have the composition (V),3(I),(S)I(X,)ss(X2) 2. After microscopic analysis of the mixed phases, this composition was expressed as (V),3(I),(S)I(V,,E,gI~,M4)8~(V,TE,~IisMg)2. Finally, these data were combined in a description of the bulk composition as V,TE,,II3M3S ~. An AIAS can also analyze textural characteristics and can be used for quick and reliable determination of rank (reflectance). Our AIAS is completely software based and incorporates a television (TV) camera that has o p t i m u m response characteristics in the range of reflectance less than 5%, making it particularly suitable for coal studies. Analysis of the digitized signal from the TV

0166-5162/82/0000--0000/$02.75 © 1982 Elsevier Scientific Publishing Company

114 camera is controlled by a microprocessor having a resolution o f 64 gray levels between full illumination and dark current. The processed image is reconverted for display on a TV monitor screen, on which selection o f phases or features to be analyzed is readily controlled and edited by the operator through use of a lightpen. We expect that automated image analysis, because it can rapidly provide a large a m o u n t o f pertinent information, will play a major role in the advancement of coal petrography.

INTRODUCTION

PetrographicaUy determined detailed descriptions of the organic (maceral) and inorganic (mineral) components of coal provide some of the basic information needed to interpret coal facies with respect to depositional environments, diagenetic and burial histories, and degrees of coalification and metamorphism. Petrographic information is also necessary to delineate the lateral and vertical variations of facies and subfacies of a single coal bed or different coal beds. Furthermore, the same information, coupled with data indicative of the depositional and geochemical environment, may be useful for establishing models for predicting coal thickness and quality variation and may also be used to a limited extent for coal-bed correlation. Success in predicting coal pinchouts and thickening would benefit mining operations. Used with coal rank and chemistry, petrographic information may be helpful in solving problems involved in coal preparation and other problems of utilization such as suitability for gasification and liquefaction. This paper is concerned with quantitative petrographic characterization of coal. Coal petrologists require useful, complete, accurate and unambiguous description of coal. We are, furthermore, concerned with the ease of comprehension of data presented either in descriptive or in diagrammatic form. Ease of comprehension is critical to usefulness of coal petrographic data for coal geologists, coal chemists, and mining engineers. We are also concerned with the speed with which such data can be obtained. Waiting three months for data to be made available is impractical, and data that are not available for a year may be useless. In agreement with many other coal petrographers, we believe that the microlithotype and lithotype terms currently approved by the International Committee for Coal Petrology (ICCP, 1963, 1971, and 1975) are commonly inadequate and vague. Moreover, the most widely used current method for maceral analysis, manual point count on polished pellet mounts, is so tedious and time-consuming that it is of little use in solving the problems confronting modern coal research. The number of core and column samples of important American coal beds alone requiring study is prohibitive. Hence, any new method for coal description and petrographic analysis must be not only quantitative but also rapid. The adoption of a computer-based or automated image-analysis system (AIAS) seems to us to be the logical choice to meet these needs.

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In lieu o f the presently prevailing terminology, a quantitative m e t h o d of coal description in terms o f the modal composition of its maceral and mineral c o n t e n t is recommended. This VEIM m e t h o d (see below), coupled with the use of an AIAS, allows more rapid and precise determination of the modal megascopic and microscopic composition, resulting in greater u n i f o r m i t y of description and representation of coal petrographic data. In order to minimize possible confusion, our usages of some of the terms c o m m o n l y used in coal description are explained as follows: Megascopic (macroscopic) observation or description. We follow the general definition of the term "megascopic" as defined in the Glossary of Geology (1980): "Said of an object or phenomenon, or of its characteristics that can be observed with the unaided eye or with a hand lens." In our usage, megascopic observation is made with the naked eye, hand lens or with a low magnification binocular microscope (generally about 10X, and in no case in excess of 32X ). Microscopic observation or description. The term "microscopic" is defined in Glossary of Geology (1980) as: "Said of an object or p h e n o m e n o n or of its characteristics that can n o t be observed without the aid of a microscope." In our usage the microscope is a research petrographic microscope with a m i n i m u m magnification of 56X. Microlithotype. We follow the definition by ICCP (1971) which is "a typical association of macerals in coals, occurring in bands at least 50 microns wide. Microlithotype names bear the suffix 'ite'." Assemblages of microlithotypes. The m a x i m u m width of a microlithotype is n o t clearly defined. However, the m i n i m u m band thickness of a lithotype varies from 3 mm to 1 cm in different countries (Cameron, 1978). We use assemblages of microlithotypes to mean an association of two or more microlithotypes in alternating lamellae or overlapping lenses in thicknesses up to 2 mm or more, where other terms become more appropriate. Lithotype. We follow in general the definition by ICCP (1963) which is "a macroscopically visible band in humic coals, analyzed by physical characteristics rather than by botanical origin. The four lithotypes of banded bituminous coal are vitrain, clarian, durain and fusain. These were originally described by Stopes in 1919." ASTM (1980b) includes in this definition attrital coal and any specific mixture of two or more of the five principal lithotypes, e.g. clarodurain. Most petrographers are aware that lithotypes in fact contain microlithotypes or assemblages of microlithotypes. Mixed lithologies (X1), (X2), (X3), etc. For quantitative description of megascopically discernible units other than the pure lithotypes vitrain and fusain, instead of clarain, clarodurain and durain, we have adopted use of the term mixed lithologies. Mixed lithologies are mixtures or assemblages of microlithotypes. Each is represented by certain mass properties such as light-scattering characteristics, bulk specific gravity and modal composition. The modal composition of mixed lithologies generally can not be determined or described w i t h o u t the use of a petrographic microscope.

116 To achieve maximum information content from the study of coal samples in accord with the above defined categories, megascopic as well as microscopic observations should be carried o u t in the laboratory, as emphasized in our companion paper in this issue (Chao et al., 1982). Laboratory conditions provide for better lighting and better sample conditions than can ever be attained in megascopic study in the field. The features of irregular surfaces o f unprepared block or drill core samples are obscure and difficult to distinguish. However, if the sample is brought into the laboratory, cut b y a band saw, and the flat surface ground and partially polished to 800 grit, many details are made readily visible when viewed b y the unaided eye or with a hand lens or binocular microscope. Any 0.1 to 3 mm thick band of microlithotype or microlithotype assemblage can be distinguished and differentiated in this way, although its maceral composition is not generally identifiable without microscopic study. If an area of the sample surface is then polished in situ using 1 p m followed b y 1/4 ~m diamond abrasives, it is possible to observe microspores and pyrite framboids 5 to 10 pm in size using a 32X binocular microscope. This in-situ polishing technique (E.C.T. Chao, unpubl, data) requires at most only a few minutes, and can produce an essentially scratch-free polished surface suitable for microscopic examination using a 50X oil-immersion objective lens. For combined quantitative megascopic and microscopic analysis of a columnar section or drill core sample of any coal bed, as a standard procedure in our laboratory a fiat surface of each sample (cut perpendicular to the bedding), is ground and partially polished as described above, in preparation for photography, binocular examination and AIAS macro analysis. Figure 1 shows a drill core sample so prepared, and Figs. 2a and 2b show microlithotype features observable at 6.3X and 32X magnification, respectively. In the megascopic phase of the analysis, distinctive medium to thick bands (2 mm* or more) are first identified and demarcated into a columnar profile (Fig. 3) b y visual inspection. These bands are either nearly pure microlithotypes or lithotypes or mixtures of microlithotypes. Pure bands are labelled (V)100 or (I)100, after microscopic verification. At the level of resolution less than 2 mm and greater than 0.5 mm, samples are then analyzed quantitatively in the megascopic m o d e by the AIAS under uniform scattered-light conditions. The c o m p o n e n t phases are designated in parentheses, for example: (V) for vitrite, (E) for liptite, (I) for inertite or fusite, (M) for mineral components, and (S) for sulfide. Mixed lithologies or assemblages of microlithotypes cannot be entirely resolved megascopically and are labelled (X1), (X2), etc. Representative subsamples or in-situ polished * T h e t h i c k n e s s o f 2 m m is arbitrarily chosen. It agrees w i t h the t h i c k n e s s o f the l o w e r limit o f " m e d i u m " band o f S c h o p f ( 1 9 6 0 ) and is a c o n v e n i e n t d i m e n s i o n that can be easily seen b y t h e unaided e y e and p l o t t e d in a c o l u m n a r s e c t i o n .

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Fig. 1. Photograph o f a split drill core sample from the Hazard Coal Bed, E. Kentucky, U.S.A., prepared for megascopic examination. The fiat surface was ground and partially polished using 800 grit size abrasives. Alternating bands of thin, dark microlithotypes (vitrite) and gray mixed lithologies X~, X 2 etc. (based on the difference o f gray tones exhibited b y these bands under the AIAS macro set-up), can be readily distinguished. Such an association is referred to as an assemblage o f microlithotypes. The thicker, more fragmental-looking band near the t o p which is distinctly lighter in tone than the rest is a lithotype (greater than 3 m m in thickness) consisting o f fragments o f vitrite (dark) in a matrix rich in inertinite group macerals. This description is based on megascopic observation only and to be verified must be examined under higher magnification. The outlined rectangular area is shown enlarged in Fig. 2a. The material seen around the coal sample is from the supporting bed o f coarse granular material used to maintain o p t i m u m orientation during photography or image analysis. Bar scale is one centimeter. areas of the mixed types are selected for microscopic analysis so that the m i x e d l i t h o l o g i e s c a n b e c h a r a c t e r i z e d in t e r m s o f t h e i r a v e r a g e ( V E I M ) modal composition, in which V represents vitrinite, E exinite, I inertinite,

118 and M optically observable mineral content. For a particular stratigraphic interval o f t h e coal, t h e v o l u m e p e r c e n t a g e s d e t e r m i n e d q u a n t i t a t i v e l y are i n d i c a t e d b y subscripts. F o r i n s t a n c e : (V)ss(I)2(M)2(V72EI~IIoM~)40 indicates t h a t t h e coal s a m p l e f r o m this s t r a t i g r a p h i c interval c o n t a i n s 56 vol. % vitrite (in layers less t h a n 2 m m b u t g r e a t e r t h a n 0.5 m m t h i c k ) , 2% e a c h o f i n e r t i t e and m i n e r a l b a n d s o r lenses, a n d 40% o f a m i x e d l i t h o l o g y having an average c o m p o s i t i o n o f V72El:I~0M6. F o r easier c o m p r e h e n s i o n , this

Fig. 2a. Photomicrograph of the central area of Fig. 1, as observed at 6.3)< magnification under the binocular microscope. (Note that this magnification is less than that using a 10)< hand lens.) The area shown was quickly polished in situ using 1 ~m followed by 1/4 ~m diamond abrasives. Although individual macerals are generally not resolved at this magnification, bands of light mixed lithologies and dark (vitrite) microlithotypes can be easily distinguished and grouped in terms of similar or different gray tones. The outlined rectangular area is shown further enlarged in Fig. 2b.

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Fig. 2b. Photomicrograph of the outlined area of Fig. 2a, as seen at 32)< magnification under the binocular microscope. Dark vitrite lenses and bands and light gray mixed lithologies (mostly trimacerites) are clearly visible. Most of the light gray to white elongated specks were verified microscopically to be microspores. The mixed lithology "X2" represented by the gray band in the lower half of the photomicrograph has an average modal composition of V66EI~II~M2, as determined by microscopic AIAS analysis. Bar scale 1 mm. long e x p r e s s i o n can be r e c a l c u l a t e d into t h e t o t a l p e r c e n t V, p e r c e n t E, p e r c e n t I, a n d p e r c e n t M, VasEsI6M4 ( C h a o et al., 1 9 8 2 ) . Within t h e last f e w years, m u c h progress has b e e n m a d e in t h e design o f m o d e r a t e l y priced ( $ 5 0 , 0 0 0 t o $ 2 0 0 , 0 0 0 ) image-analysis s y s t e m s . Several c o m m e r c i a l l y available s y s t e m s are s u i t a b l e f o r a u t o m a t e d coal p e t r o g r a p h i c research. For our work, we chose a completely software-based AIAS, the

120 Ueptrl (m, 39.6~ (V) (i) (S) ( X l ) (X2) (X3) 21 2 1 62 11 3

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Fig. 3. Columnar profile for a portion of a split drill-core sample of the I coal bed of Cretaceous age from the Ferron Sandstone Member of the Mancos Shale, Emery County, Utah. Transitional contacts between different lithologies are shown by dashed lines, sharp contacts by solid lines. The "depth" values shown to the left of the columnar profile represent the depths along the drill core from the ground surface. Brief megascopic descriptions appear to the right of the column. AIAS-determined macroscopic modal compositions are shown to the left on the columnar profile, in terms of vitrite (V), inertite (I), iron sulfide (S), and mixed lithologie8 (XI), (X2), etc. Macro G.V. (gray value) ranges, bulk S.G. (specific gravity) values, and average AIAS microscopic modal compositions for the mixed lithologies are as foUows: (XI) = macro G.V. range 11--16, S.G. 1.26, (V6~EIgI14Ms). One chip sample analyzed. (X~) = macro G.V. range 15--20, S.G. 1.41, (VsTEiIII~Ms). Three chips analyzed. (X~) = macro G.V. range 18--24, S.G. 1.43, (V62EgI23Ms). Two chips analyzed. (X4+I) = macro G.V. range 24--32, S.G. 1.40, (V~sE~ 9IlzMl 5): Two chips analyzed. J o y c e - L o e b l M A G I S C A N * , because o f its versatility, flexibility, and adaptability t o n e w research requirements. We find t h e ability to reprogram software routines or s u b r o u t i n e s an e x t r e m e l y desirable feature, if n o t a necessity, to m e e t the evolving and changing d e m a n d s in t h e application o f a u t o m a t e d image analysis to coal research.

*The use of trade or brand names in this report is for descriptive purposes only and does not constitute endorsements of products by the U.S. Geological Survey.

121 I. DESCRIPTION OF INSTRUMENTATION AND OPERATING METHODOLOGY

For coal petrographic research, an AIAS must provide capability for: (1) maceral and/or mineral modal analysis on the basis of differences in reflectance and/or transmittance, hence gray-level resolution; (2) textural analysis, such as analysis of size distribution or shape analysis of a category o f maceral or maceral group; and (3) a combination of (1) and (2) as required. In order to perform these functions as quickly and precisely as possible, the system should be easy to operate, resolve as many shades or levels of gray as possible, be able to monitor and optimize uniformity of illumination, allow the operator to set or change gray-level thresholds (see below) readily and quickly, and provide the capability to edit or amend the image to correct errors due either to flaws in the sample or to improper segmentation. These functions and capabilities in our AIAS are described below. 1. General setup and optical and television-tube characteristics The MAGISCAN is capable o f resolving or differentiating 64 gray levels o f the image under o p t i m u m illumination. The system consists of a television camera that can readily be m o u n t e d for either microscopic (Fig. 4a) or macroscopic (Fig. 4b) analysis, an analog-to
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a high-quality TV image for analysis. Polished coal samples, either block or pellet mounts or polished thin sections, are used in the micro mode. Uniformity of illumination is essential for the proper segmentation

123 I

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Fig. 6. Correlation of reflectance with gray-level values for calibrated glass standards (from commercial source) of low reflectance (wavelength of the incident light = 546 nm). Fig. 4. Photographs of the MAGISCAN AIAS. a. Overall configuration in our laboratory at the U.S. Geological Survey, Reston, Va., showing, clockwise from the left: 1 = computer terminal; 2 = console containing minicomputer (left); TV monitor screen, keypad and lightpen; microprocessor and analog-to-digital and digital-to-analog converters (inside cabinet); 3 = macro set-up for analysis of hand samples and photographs; and 4 = the TV camera, positioned on the Leitz Orthoplan microscope, b. Close-up showing setup for macro analysis of hand samples. From the top: TV camera with zoom lens, fluorescent ring light, and partly polished split-core coal sample. Flood lights are used when photographs are to be analyzed.

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Fig. 7. TV screen display of grid pattern of gray-level values for an area 200 x 200 ~m on the polished glass standard for the purpose of monitoring the optimum uniformity of illumination for microscopic analysis. The uniformity o f illumination in terms of total gray-level spread o f three is excellent.

(discrimination of c o m p o n e n t phases). This uniformity can be monitored by projecting a uniform gray field from a glass* or mineral standard on the TV screen in the micro mode or by placing a uniformly colored matte surface card in the field of view in the macro mode. A grid of digital gray values (Fig. 7) is generated at equally spaced intervals approximately 1 cm apart on the screen for the entire field by calling a computer subroutine. Oj~timum u n i f o r m i t y and the desired intensity of illumination can be achieved by adjustment of the light source and the use of proper microscope filters. Also, the microscope light may be made monochromatic by use of appropriate filters. The final grid of gray values is stored in the microprocessor m e m o r y to be used in a shade correction routine to correct for the remaining areas of uneven illumination.

*Sets o f six calibrated glass standards ranging in reflectance from 0.3 to 1.6% are commercially available.

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2. Operational mode and software options As shown in the flow diagram (Fig. 5), the image analyzer can be addressed in two modes: (1) via the c o m p u t e r terminal; and (2) via a lightpen and keypad on the console. The o u t p u t data can be either displayed on the TV m o n i t o r screen or printed out on the terminal. Three c o m p u t e r languages are available for MAGISCAN operations: (a) SPEL (Simple Picture Evaluation Language) generates a "video keyb o a r d " on the TV m o n i t o r screen (Fig. 8). Through the use of the lightpen to point to the desired " k e y s , " the operator can enter the necessary commands for setting up the required image-analysis procedures, the measurements to be made, and the form in which the results are to be presented. No prior knowledge of computer programming is required to be able to use SPEL. (b) MAGIC (iMAGe basiC) incorporates the commands of Dartmouth College BASIC and adds special image-analysis commands. It is a conversational programming language that uses English words and algebraic formulation of statements, so that it can be learned quickly. MAGIC allows for more flexibility and complexity in operations and o u t p u t than SPEL. (c) F O R T R A N is the most powerful of the available software languages. It allows the full range of scientific programming plus modification of in-'X--,'ASIMPLE PICTUREEVALUATIONLANGUAGE(REV7.O)-'X--XROUTINE:0 SAMPLE: 0 • FRAME: 500.00 x 500.C~0 PP FIELDS: I x i

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Fig. 8. Diagram of SPEL video keyboard (from the manufacturer's instruction manuel). Operations and measurements are selected by using the lightpen to point to the desired "keys".

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structions to the microprocessor. It is therefore required for the larger and more complex image-analysis tasks. For example, COAL is a F O R T R A N program, supplied by the manufacturer, that was written to suit our specific needs in coal petrographic studies.

3. Phase classification and modal analysis by gray-level segmentation Organic (maceral) and inorganic (mineral) phases in coal can be classified either in terms of reflectance (gray levels in the AIAS, see Fig. 9), texture, or a combination of both. With the AIAS, segmentation of component phases in bituminous coals can generally be accomplished using only graylevel thresholding. The term "thresholding" means the bracketing of graylevel intervals that correspond to the range of gray values exhibited by a particular phase. Both the variation of reflectance values of macerals within a maceral group and the bireflectance of a single maceral contribute to the range of gray levels associated with that maceral group. (The optical proper-

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ties of macerals, for example vitrinite, are analogous to those of an uniaxial negative mineral of low birefringence. The higher the rank of the coal, the greater the birefringence, and hence the bireflectance, of a maceral.) If the gray-level intervals of major maceral groups overlap, then computer routines for curve-stripping may be necessary to resolve the overlapped region in the gray-level histograms of different phases. In our experience with bituminous coals to date, for most samples complete segmentation of major maceral groups identified before analysis is accomplished without resorting to curve-stripping techniques (Fig. 9). In our system, the establishment of gray-level thresholds can be accomplished either by using the lightpen on the TV monitor screen (Fig. 10) or by entering the digital values via the keypad. The segmenting of a particular maceral or mineral phase is shown on the TV screen by an image (in white) of the areas assigned to that phase superposed on the original image

Fig. 10. View on the T V monitor screen of an area in a polished block of a columnar sample of Kentucky #6 coal from Webster County, Kentucky. Sample K 806, depth 75 crn. Gray-level values are displayed for exinite (6--11), vitrinite (22--27), and inertinite (37--41). Area outlined is approximately 200 × 200 urn.

128

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of the total field (Figs. 11a--11c). The range of gray levels associated with this segmentation is indicated numerically at the upper right-hand corner of the TV screen and displayed pictorially as a "thermometer" along the right-hand margin of the image (Figs. l l a - - l l c ) . If adjustment of the segmentation is desired, the lightpen is used to adjust the gray-level interval on the "thermometer" display. Judgment by the operating petrographer of how accurately each phase is segmented for each sample area is critical to proper identification, classification, and analysis of the areal representation of these phases. Once the phases are properly identified and classified by gray-level ranges, then the areal extent covered by each phase or group of phases in terms of number of picture points (pixels) is quickly analyzed by the minicomputer. For maceral modal analyses carried out using a 50× oil immersion lens, a single pixel represents an area approximately 0.4 × 0.4 ~ m 2. The results of the analysis and the statisticsof the measurements can be printed out on the terminal or displayed on the T V screen as desired. Because the modal analysis is expressed as area (and hence volume --see Chayes, 1956, pp. 12--13) percent based on the n u m b e r of pixels segmented, the major sources of error lie in the degree of overfilling or underfilling of the areas occupied by the particular phase being segmented and the edge or halo effects along the contact of two adjoining phases. The latter effect is minimized by a software routine that sharpens the boundary between the two phases. Other errors, due, for example, to flaws in the sample (holes and scratches) or to overlapping of gray levels, are generally minor. Where such flaws or overlaps are numerous and seriously affect the accuracy of the analysis, corrections can be m a d e by available image-editing routines using the lightpen. Another m e t h o d of petrographic analysis, c o m m o n l y used for characterizing the bulk properties of a coal sample or coal blended for coking, is to obtain a reflectogram (a histogram of reflectance values of all components of the sample analyzed by optical photometry). Analogously, a gray-level histogram generated by our system can be correlated with reflectance data, because the information contents of reflectance and gray-level histograms

Fig. 11. Photographs of the T V monitor screen showing the segmentationof the various maceral groups in the sample area shown in Fig. 10. The modal composition for this area as determined by the AIAS is VT~E2,I2. Sclae for all photographs is the same as scalein Fig. 10. a. Segmentation of exinite. Areas occupied by exinite (black in figure 10) are filled (white overlays).At the right of the screen note the gray level"thermometer" display in which the filledregion denotes the proportionof the 64 gray levelsassignedto exinite. The digitaldisplay at the upper right indicatesthat this range of gray levelsis from 3 to 15 (gray-levelrange 0 to 3 isassignedto holesand mineralgrains in the sample,which for the field displayedamounted to only 0.3% of the sample area.)b. Segmentation of vitrinite(gray-levelrange 15 to 35). c. Segmentation of inertinite(gray-levelrange 35 to

64).

130 are identical. The equipment used differs, and the procedures for sampling also differ. Most reflectograms are based on point counts along traverses. Gray-level spectra are based on analyses of total scenes or fields. The latter have a much greater number of sampling points than the former (with the AIAS, each field analyzed contains as many as 2.5 X l 0 s pixels). Reflectograms can be fully automated and run without an operator, whereas graylevel spectra are operator dependent. However, reflectograms are not easily and accurately interpreted in terms of the quantitative maceral groups represented, whereas interpretations of gray-level spectra are less ambiguous and are more reliable and precise because the analyses are visually monitored.

4. Texture analysis The MAGISCAN can be programmed to perform, in addition to sequential analysis of phases, textural analysis of individual features or particles. For example, the video keyboard of SPEL (Fig. 8) offers many subroutines for analyses such as size distribution, particle shape, orientation, etc. The " k e y s " of the b o t t o m two rows on the video keyboard can call subroutines for (AREA); perimeter (PERI); length (LENG); height (HGHT); orientation (ORNT); intercept (ICPT); convex perimeter (CPER); breadth (BRED); width (WDTH); integrated density, i.e. the total integrated optical density within a feature (IDEN); and nearest neighbor distance (NEIG). Derived measurements can also be formulated from combinations of existing measurements and arithmetic operations. For example, the mean radius of particles is represented b y twice the area divided b y the perimeter. Particle-size distribution analysis is particularly suited for description of the exinite and inertinite maceral groups in coal. The description of textures o f coal -- one aspect of coal characterization -- is difficult to perform witho u t the help of an image-analysis system. A c o m m o n problem in texture analysis is the discrimination of closely adjoining particles as discrete features in a sample. If such particles are not completely separated, then they will be mistakenly analyzed as a single particle. On the other hand, if a large irregular particle is not segmented or filled properly, it will be analyzed as separate particles instead of a single particle. These problems can be easily overcome by the use of lightpen editing. C o m p u t e r routines are also now available for the automatic separation o f overlapping circular features.

5. Advantages o f a software-based system A software-based AIAS provides almost unlimited flexibility for the solution o f image-analysis problems. Use of such an AIAS means that modifications can readily be made to attack any new directions a research program m a y take, as well as to include any new image acquisition algorithms that are developed, so that such an instrument should not become obsolete as the state of the art of image analysis progresses.

131 II. APPLICATION TO COAL PETROGRAPHY The application of an AIAS to coal petrography has until now been limited (Harris et al., 1977; Harris and DeRoos, 1979; Zeiss, 1979; England et al., 1979). Several automated systems have been devised to obtain reflectograms by automated point-count analysis on polished pellet mounts (Gray et al., 1979; Kojima et al., 1979; Hoover and Davis, 1979; Ting and Klinkachorn, 1979; Hampson, 1980); however, as described above, such systems clearly are not capable of utilizing the advantages of image analysis. We are convinced that for understanding coal genesis, it is preferable to visually monitor the analysis of a coal sample, as is done in phase segmentation b y image analysis. As automated image analysis is applied to systematic coal research with emphasis on geologic processes, the following major objectives must be addressed: (1) determination of the rank of coal; (2) methods and procedures for the improvement of megascopic description of coal core and block samples in the laboratory; and (3) methods and procedures for microscopic description of coal. To accomplish the latter two objectives, we must deal with the nomenclature of coal, for example, the names of microlithotypes approved b y ICCP, as pointed out in the introduction.

1. Correlation between reflectance and gray levels for coal-rank investigations Estimation of the rank of coal based on the reflectance of vitrinite or a specific type of vitrinite is a m e t h o d generally accepted and sometimes preferred to the chemical or calorific methods of coal-rank determination (Davis, 1978). The AIAS m e t h o d is based directly on the fact that the graylevel values can be correlated with standards of reflectance and can be carefully calibrated and controlled. The advantage, we think, of using AIAS over the normal reflectance m e t h o d is speed and ease. In generally accepted petrographic practice, the rank of coal is determined on the basis of the reflectance of 100 or more points measured microscopically using a p h o t o m e t e r on vitrinite (ASTM, 1980a) after calibration of the p h o t o m e t e r using calibrated glasses of known reflectance values. Carrying o u t this procedure manually takes about 1 hour (Gray et al., 1979). With the image analysis, a correlation curve of gray levels with reflectance is established using a set of calibrated minerals or glasses as standards. An example of a correlation curve used for the determination of reflectance, and hence rank, of bituminous coals is shown in Fig. 6. For rank determination b y use of the AIAS, if a polished block normal to the banding is used, the maximum gray levels correlated to maximum reflectance should lie parallel to the banding (analogous to omega for an uniaxial negative crystal}. The vibration direction having the maximum reflectance or gray level can be easily checked b y rotating the block in cross-polarized light. The maximum gray level of each vitrinite band then can be quickly determined b y the use

132 of the lightpen. If pellet mounts are used, the coal particles are in random orientation. Analogous to an uniaxial crystal, the omega or the ordinary ray o f any randomly oriented vitrinite lies in the plane of the microscope, parallel to the one o f the two extinction positions that has the larger gray level. This extinction position m a y be determined quickly, and the larger gray level can be read quickly by use of the lightpen. Alternatively, if the incident light is not polarized, one may determine the average reflectance_ (R~ on the basis of several gray-level determinations in vitrinite, where R = {R0 max)/1.066 for bituminous coals (Ting, 1978). Neavel et al. (1981) also derived the relationship R = (R0 max + 0.0237)/ 1.056. The correlation curve of gray levels with reflectance can be established in 15--20 minutes. Based on observations and measurements of numerous vitrinite particles in a sample, we have found that 15 gray-level points per vitrinite particle and 2 to 3 particles per sample are adequate to determine the rank accurately. A large number of samples can then be quickly measured (about 5 minutes is required per sample) to estimate their ranks of coalification. The good agreement between rank determination by AIAS using gray levels and determinations based on photometric reflectance measurements for several coal samples is shown in Table I. If an AIAS is available, the use of elaborate photometric measuring equipment may no longer be necessary.

2. Modal and textural analyses using the A I A S As mentioned in the introduction, any coal sample can be described quantitatively in terms of its megascopic and microscopic modal composition, using the VEIM nomenclature. The analytical characteristics of the AIAS have enabled us to evolve a method for rapid generation of this type of quantitative description of coal samples.

A. Macro-system for megascopic description o f coal core and columnar samples The overall objective of megascopic description of coal is to provide the m a x i m u m amount of useful data characterizing the variation of coal depositional units. Any m e t h o d or procedure proposed should ideally be rapid, consistent, and objective. Most megascopic descriptions in the United States follow the guidelines set forth b y Schopf (1960, 1978). Procedures devised by several authors are presented in a volume edited by Dutcher (1978). Megascopic characterizations of coal core or block samples in the laboratory, based on examination by unaided eye augmented by hand lens or binocular microscope, generally identify the lithologic layers or bands as vitrain, fusain, attrital coal, etc.; nonbanded coals as cannel or boghead coals; and impure coal as mineralized or bone coal (ASTM, 1980b). The use o f the AIAS introduces the capability for more quantitative and objective descriptions, as outlined in Table II.

Pittsburgh Pittsburgh Upper Freeport Upper Freeport Vermillion Creek unknown Lower Horsepen

OH-M L-7 H2-1/4L-2.0 L-2-3/1.5N-1.0 VC 7 116 NNG-35-20 JHM-56

Belmont Cty, Ohio unknown Indiana Cry, Pa. Indiana Cty, Pa. Wyoming Winkler Cty, Tx. Tazewell Cty, Va.

Location

0.58 0.79 1.22 1.20 0.36 2.50 1.33

0.63 0.78 1.11 1.23 0.47 2.47 1.37

~I by A I A S N 0 max I by non-polarized light, photometry 2 ~, = 546 nm polarized light ~, = 546 nm

high-vol, bituminous B high-vol, bituminous A med.-vol, bit med.-vol, bit subbituminous semi-anthracite med.-vol, bit

Rank 3

i R, average unpolarized reflectance in 1.518 oil, is related to N 0 max, average m ax i m u m reflectance in polarized light in 1.518 oil, by the expression R = R 0 max/1.066 (Ting, 1978). 2 Ronald W. Stanton, analyst. s Davis (1978).

Coal bed

Sample

Determination o f approximate rank based on measurement of gray levels in vitrinite by use of the AIAS

TABLE I

O~

134 TABLE II Procedure for columnar description 1. Visual and binocular inspection and photographic documentation of prepared samples. 2. Preparation of skeletal columnar section showing megascopic demarcation (bands 2 m m or greater in thickness). 3. Megascopic mode of lithotypes consisting of (V), (I), (M), plus mixed lithologies (X1, X2, etc.) by AIAS (bands or lenses between 0.5 m m and 2 m m in thickness). 4. Identification of representative mixed lithologies on the basis of AIAS gray-value ranges and selected S.G. determinations. 5. Preparation of in-situ polished areas, polished blocks, or polished thin sections representing distinctive mixed lithologies for microscopic examination. 6. Microscopic mode of mixed lithologies by AIAS. 7. Completion of columnar section description.

In the macro mode of operation, with illumination from the fluorescent ring light, the gray values (G.V.) of the image are related to the bulk lightscattering properties of the different bands in the coal (these do not correspond to the reflectance values of coal components in incident light}. Figure I shows a typical hand-size sample (split core) suitable for megascopic description with the use of the AIAS. The procedure used to produce the columnar profile of part of a coal bed shown in Fig. 3 is outlined in Table II and described in the introduction above. The mixed lithologies labeled (X1), (X2), etc. are characterized by their bulk specific gravities (S.G.'s) and by different G.V. ranges as determined with the AIAS in the illumination of the macro mode. Another aid to megascopic description of core or block samples is the use of an optical "logging" technique analogous to electric logging of cores. The AIAS can produce a profile or cross section of the gray values across the layered or banded structure of the coal. Such a profile is shown in Fig. 12. It m a y serve as a cross check of the demarcation lines determined as described above. The ideal, complete petrographic description of a particular coal bed would of course require microscopic analysis of in-situ polished strips, polished mounts or polished thin sections representing the entirety of the bed from t o p to b o t t o m . The tremendous workload this would entail may be justified for a standard section of an important mineable coal bed. However, in the study of additional column or core samples to monitor the lateral variations of this coal bed, we suggest that an adequate description will result from the microscopic analysis (VEIM) o f a limited number of subsamples selected as representative of the principal mixed lithologic types (X1, X2, etc.) on the basis of S.G. and megascopic G.V. ranges. This is particularly true for coals for which the major maceral groups and minerals are fairly limited in variety and number. Clearly this procedure will greatly reduce the number of subsamples required for microscopic study.

135

Fig. 12. View on the TV monitor screen of a portion of the sample profiled in Fig. 3. Stratigraphic interval shown here (right to left) is 39.65--39.71 m. Superposed on the image of the sample is a G.V. profffle (lower part of photograph) corresponding to the traverse indicated along the horizontal white fine (center of photo). Note the transition in G.V.'s between dark vitrite- and vitrain-rich areas and larnellae (G.V. range 3--9), and the medium-gray dull matrix X 1 (G.V. range 11--16). The fighter gray band of X 2 at the left of the photograph shows a higher G.V. prof'de (range 15--18). Inertite lenses and areas rich in iron sulfide are also clearly indicated as "spikes" in the profile. The notched area at the top of the sample shows where a small chip of a mixed lithology was removed for S.G. determination and microscopic modal analysis.

(1) Reproducibility and uniformity of megascopic quantitative descriptions. In t h e p a s t , t h e r e has b e e n little basis f o r e v a l u a t i n g t h e reliability or rep r o d u c i b i l i t y o f m e g a s c o p i c d e s c r i p t i o n s w i t h o u t relying fully o n m i c r o scopic d a t a b e c a u s e c o m p a r i s o n s o f d e s c r i p t i o n s using vague l i t h o t y p e t e r m s are difficult. T h e result was t h a t m e g a s c o p i c d e s c r i p t i o n s o f coal b e d s s o u n d e d basically alike. With t h e use o f t h e A I A S , we c a n e v a l u a t e t h e rep r o d u c i b i l i t y and c o m p a r a b i l i t y o f m e g a s c o p i c d e s c r i p t i o n s o f t h e coal b e d s in t e r m s o f t h e V E I M q u a n t i t a t i v e s c h e m e . We have devised s t a n d a r d i z a t i o n p r o c e d u r e s f o r assuring t h a t t h e d a t a o b t a i n e d at o n e specific t i m e are c o m p a r a b l e w i t h t h o s e o b t a i n e d at a n y o t h e r t i m e ( C h a o et al., 1 9 8 2 ) . In general, t h e e s t i m a t e d a m o u n t s o f p u r e m i c r o l i t h o t y p e s a n d m i x e d t y p e s agree w i t h i n a f e w p e r c e n t , if an i d e n t i c a l area is c h o s e n f o r t e s t i n g r e p r o d u c -

136 ibility of the quantitative data. In practice, the results are highly dependent u p o n the petrographer who makes the decisions on the classification of lithologies. Our limited experience has shown that it is possible to reach a certain level o f agreement o f megascopic description based on gray-value intervals for the segmentation of various categories of lithologies present. Such agreement would n o t have been possible without the AIAS and the standardization procedures. We are encouraged that n o w some hope exists of obtaining quantified megascopic descriptions that are both objective and uniform among different petrographer-observers.

B. Microscopic characterization o f coal polished mounts and polished thin sections For microscopic description and characterization, in-situ polished areas, polished blocks, pellet mounts, and polished thin sections of coal are used. Each t y p e of sample has its specific objective and advantage. As mentioned above, the t w o major categories of information that can be derived from microscopic studies of coal are: (1) the modal composition o f the macerals or maceral groups and minerals represented; and (2) the textures of the maceral particles or habits of the minerals. (1) Modal analysis. We have experimented with 10X, 20X, and 50X oilimmersion objectives for producing the most suitable image on the TV m o n i t o r screen for microscopic modal analysis by the AIAS. F o r quick description, the use of a 20X objective may be adequate. However, for detailed modal analysis, a 50X oil-immersion objective is preferable. In examining some coal samples, even higher magnification m a y be needed. The use o f a 50X objective limits the size of the field analyzed to about 200 X 200 /~m. Hence, meaningful results should be based on the analysis o f multiple fields. The number of such fields required for a statistically significant determination of course varies with the nature of the coal sample. Our experience in tests using a 50X objective on polished blocks and polished thin sections of Upper Freeport coal from Pennsylvania and coal from the Ferron Sandstone Member of the Mancos Shale, Utah, indicates that for a given lithologic unit or stratigraphic interval, determinations made on a maximum of six fields will yield a representative modal analysis. Similar results are obtained whether these fields are selected systematically or at random within the given lithologic unit. Table IIIa shows the results of a test on a portion o f a Utah coal core sample. Of a total of 19 fields analyzed, one area (Vl00) was included in a vitrite band demarcated separately by visual inspection, and three others (V > 95 vol. %) were included in the (V) percentage determined macroscopically for this stratigraphic interval. The data shown in Table IIIb were compiled for the remaining 15 areas analyzed. These data show that analysis of three fields would have sufficed to characterize this 40-mm stratigraphic interval o f the sample. After calibration and setting o f the gray-level thresholds, AIAS analysis of each field containing five phases takes a b o u t 3 minutes.

137 TABLE III a. AIAS determination of VEIM variation within a 40-mm stratigraphic interval of a drillcore sample of coal. Each area analyzed is approximately 200 × 200 ~m. Sampled areas are at 2-mm intervals normal to the bedding. Sample TR 3, Cretaceous coal bed, central Utah Stratigraphic interval (m)

V (vol.%)

E (vol.%)

I (vol.%) M (vol.%)

73.640 73.642 73.644 73.646 73.648 73.650 73.654 73.656 73.658 73.660 73.662 73.664 73.666 73.668 73.670 73.672 73.674 73.676 73.678

84 71 98a 89 95 100 b 80 99 a 95 76 91 98 a 79 85 90 82 95 91 92

11 1 1 7 3

3 20 0 3 1

1 7 0 1 0

8 0 2 2 2 0 13 4 3 13 3 5 3

5 1 1 17 2 0 1 5 3 1 1 2 2

6 0 2 4 4 1 7 5 4 1 1 2 3

a Included in (V) percentage determined macroscopically. bpart of a separate vitrite band.

b. Comparison of mean modal compositions determined on the basis o f different portions of the data from (a) (data for V > 95 vol. % excluded) Number o f measurements

V (vol.%)

E (vol.%)

I (vol.%) M (vol.%)

Sampling procedure

15 7

86 87

5 4

5 5

3 3

5

87

8

2

3

3

86

5

4

5

all data every second measurement every third measurement every fifth measurement

Total composition range for all 15 measurements: Vgso71E1s.~I20.1MT.0.

138

(a) Precision The value of any new m e t h o d or procedure depends not only on speed and ease of operation, but also on precision. We have devoted a great deal of time and care to the detailed evaluation of the parameters that contribute to and affect precision. We have also compared the precision of the AIAS data with that of data obtained b y point count, and we have studied the agreement of data obtained b y either AIAS or point counting by different petrographer-operators. We summarize our current results as follows: The major factors affecting the precision of AIAS microscopic modal analysis are: (1) The quality of sample preparation. (2) Stability of the AIAS instrument. (3) Overfilling or underfilling of the phases segmented. (4) The total perimeter or the amount of shared boundaries between two phases. (5) Overlapping of gray levels of different maceral phases. (6) The number of fields to be analyzed and sampled in order to obtain a representative or average modal analysis. (7) J u d g m e n t or identification biases of the operating coal petrographer. The quality of microscopic analysis is strongly dependent u p o n the quality of polish of the sample. Firstly, the better the polish and the more scratch- and flaw-free the sample is, the better is the contrast, and therefore the gray-level separation, between the categories of phases classified. Secondly, the sample should have minimal relief, because relief creates broad boundaries between adjoining phases, resulting in greater errors in segmentation. F o r AIAS analysis, we recommend polishing with diamond abrasives (Chao et al., 1982), and the maintenance of rigid quality control for the cleanliness of the polishing substrates. Instrumental stability is of course of great concern. An unstable instrument will give erratic analytical results. Hence, first we determined that o p t i m u m uniform illumination was achieved, and then we evaluated the operating characteristics of the AIAS. Using coal samples, we experimentally verified that the manufacturer's specification is accurate regarding resolution of 64 gray levels below 5% or less reflectance. Then the instrumental stability was tested. We established with a standard polished glass block that the illumination remains highly uniform. Repeated AIAS analyses of the same area do not vary throughout several hours of continued operation (Table IV). This stability of performance is maintained so long as the room is air conditioned and temperature does not exceed 25°C. Further, different fields or areas of sample were analyzed using the same gray-level threshold for the classification of the various categories of maceral groups or mineral groups to be measured. This procedure established that usually analyses can proceed without resetting of gray-level thresholds for each field of the same sample to be analyzed. If the operator suspects that the instrument is o u t of adjustment, a simple procedure of restandardization is sufficient

139 TABLE IV Test of instrumental stability of the AIAS. Repeated modal analysis of the same microscopic field without adjusting gray-level thresholds

Mean Minimum Maximum Standard deviation

V (vol.%) E (vol.%)

I (vol.%)

M (vol.%)

66.3 66.1 66.1 65.9 65.8 65.8 65.7 66.1 66.0 66.5

14.2 14.5 14.4 14.6 14.6 15.0 14.8 14.2 14.6 13.8

6.8 6.6 6.7 6.6 6.5 6.5 6.5 6.6 6.6 7.0

12.0 12.0 12.0 12.1 12.1 12.0 12.1 12.0 12.0 11.9

66.0 65.7 66.5 0.2

14.5 13.8 15.0 0.3

6.6 6.5 7.0 0.2

12.0 11.9 12.1 0.05

Duration of test: 40 minutes. to restore stability. Finally, t he same field was analyzed at different times by different operators who used the same standardization and gray-level settings. T he results are in good agreement. This is n o t only a test for instrumental stability, b u t a test of all factors involved in AIAS modal analysis. I m p r o p e r segmentation causing either overfilling or underfilling o f a classified phase on the TV m o n i t o r appears to be t he major limitation of precision in AIAS m oda l analysis. Table V shows results of testing by varying the gray-level threshold by increments of one gray level. A change of one gray level in thresholding can result in a change of 4 or more volume p e r c e n t in the de t e r m i na t i on o f the a m o u n t of a given phase present. Because it is n o t possible t o judge segmentation closer than one gray level, this factor p r o b a b l y accounts for the major variation in modal analysis perf o r m e d by the AIAS m e t h o d . The edge or halo effect between the shared boundaries o f adjoining maceral phases can also be a significant c o n t r i b u t o r to t he spread of estimates o f t he amounts o f the two involved phases present. The m ore abund an t these t w o phases are and the finer the grain size, the greater will be the total perimeter o f boundaries bet w een the two phases. T he variation in d e t e r m i n a t i o n is split bet w e e n these two phases. F o r example if the coal sample contains 40 to 50% of fine-grained vitrinite, 30 to 40% of finegrained inertinite, and only a small a m o u n t of exinite, t h e n a slight shift in gray-level thresholding bet w e e n vitrinite and inertinite will result in large variation in t he a m o u n t o f vitrinite versus inertinite, but will n o t affect th e a m o u n t o f exinite.

140 TABLE V Effects of single gray-level increments on microscopic modal analysis o f coal obtained by the AIAS. Original gray-level thresholds: 23 between M (mineral matter) and E (exinite group), 27 between E and V (vitrinite group), 33 between V and I (inertinite group). All measurements on same field of view M (vol.%)

E (vol.%)

V (vol.%)

I (vol.%)

I. Analysis with original gray-level (G.L.) settings (average o f 6 determinations): 10.9 7.9 73.5 6.7 Standard deviation 0.1 0.4 0.4 0.3 II. Threshold between M and E lowered by 1 G.L. (23 to 22): 8.2 74.2 6.8 9.8 III. Threshold between M and E raised by 1 G.L. (23 to 24): 6.5 73.8 6.6 12.8 IV. Threshold between E and V lowered by 1 G.L. (27 to 26): 4.5 77.1 6.6 11.0 V. Threshold between E and V raised by 1 G.L. (27 to 28): 12.4 69.3 6.6 10.7 VI. Threshold between V and I lowered by 1 G.L. (33 to 32): 8.0 72.1 8.3 10.9 VII. Threshold between V and I raised by 1 G.L. (33 to 34): 8.4 73.9 5.7 11.0

Depending on the rank of coal, maceral phases present in any coal sample m a y have a small to a significant amount of overlap in gray-level values, making the separation o f phases difficult. In low-rank coal, dark exinite is difficult to distinguish from minerals that do not exhibit internal reflections. Differentiating among vitrinite, pseudovitrinite, low-reflecting semifusinite, and exinite in high-rank coals is more difficult than differentiating among these c o m p o n e n t s in lower-rank coals. In order to obtain a representative or average composition of a mixed lithology such as a finely interlayered vitrite alternating with trimacerite, we must measure enough fields in order to reach a representative composition. On the basis of our determinations, as few as three fields are adequate to reach the representative or average composition (Tables IIIa and b). The last major contributing factor to be considered is the difference in classification or identification of maceral or mineral phases b y different coal petrographers. We found this to be a significant problem, even when there has been prior consultation to establish the same set of standards for identification. We are inclined to believe that differences of judgment among petrographers h a v e a slightly less severe effect in modal analysis with the AIAS than with the point-count m e t h o d (see below). With all of these possible contributing factors, we conclude that the precision of modal analysis by AIAS is generally within a b o u t 5% of the a m o u n t of a given phase present for bituminous coals.

141

(b) Comparison of AIAS microscopic modal analysis with point count In general, the AIAS and the point-count m e t h o d of microscopic modal analysis are confronted b y similar conditions or difficulties. However, some aspects affect the precision of the two methods in different ways. We have already described and evaluated the precision of the AIAS method. Let us also briefly review the m e t h o d of point counting. The standard ASTM approved m e t h o d for manual point c o u n t on polished pellet mounts (ASTM, 1980a) is to count a minimum of 1000 points on each of two pellet mounts of the same sample. The results are considered acceptable if the t w o determinations of the volume percents of the components present agree within 2% mean variation. On the basis of the inherent difficulties in point counting (see below), we believe that the 2% deviation standard set by ASTM may assure internal consistency b u t b y no means guarantees the validity or accuracy of the data. The well-known pitfalls of point counting are: (1) The operator must make decisions of identification of the maceral at every point being counted. Identification error varies. It may be small or it may be significant, b u t it cannot be avoided. (2) The use of a cross-hair eye piece for point counting always introduces a parallax error. This error c o m p o u n d s the error of an arbitrary choice of classification when the point lands on the boundary of t w o phases. This error can be severe if the sample contains an appreciable amount of small micron-size particles such as micrinite or if the sample is generally fine grained. (3) Because the time required for counting averages 2 hours or more, there must be a fatigue factor for the eye and concentration span of the operator. The quality of point identification must, therefore, inevitably decrease towards the end of an analysis. If a 50X oil-immersion objective lens is used, both the AIAS and the point-count m e t h o d will lack precision on the amount of micrinite present. The reasons are evident. For AIAS, micrinite although small can be resolved on the TV monitor, b u t the lack of contrast from the enclosing vitrinite or other phases prevents proper segmentation. For point count, the cross-hair parallax reduces the reliability of the micrinite determination. The quality of modal analysis by either method is fundamentally dependent on the petrographer-observer. In b o t h situations, the petrographer must make decisions regarding identification and classification of the maceral and mineral phases present. However, a notable difference exists between the AIAS method and the point-count method. In the AIAS m e t h o d , the graylevel thresholds of various phases are set and then checked for validity and acceptability using additional fields of the same sample. Once the segmentation is accepted, due to the stability of the AIAS instrument, no further decisions or changes need to be made on that sample. Analysis b y the machine proceeds on a uniform basis using the same gray-level thresholds. In point counting, however, the petrographer has to make decisions

142 at every point -- decisions such as assigning phases if the cross hair lands on a b o u n d a r y between two phases, and decisions of a phase with reflectance that could be either one of two maceral phases based on what the petrographer can see for comparison in the microscope field of view. This decision process continues until the point counting is culminated. The question to be raised concerns the consistency of such decisions. We believe that this builtin requirement for making repeated consistent decisions is an inherent weakness in the point-count method. The first revelation or impression we gained in reviewing and comparing the precision of modal analysis data obtained b y AIAS with the precision of data obtained by point counting (Tables VI and VII) is that the agreement of data obtained by a single method or b y both methods with different petrographers is related to the rank, grain size, and the modal composition of the coal sample. The data in Table VI indicate that the agreement between observers and methods is better for the medium-volatile bituminous Upper Freeport coal than for the I coal bed (high-volatile bituminous C) o f the Emery coal field. The I coal is finer grained and is also compositionally more complex than the Upper Freeport coal. The dependence of precision upon sample nature appears to be reasonable. However, to be certain, it needs to be tested further. The preliminary results comparing the precisions of the AIAS and pointcount methods, although far from conclusive, seem to indicate that the AIAS method is not any less reliable and may be more reliable than the point-count method for determining VEIM percentages. (c) Variation o f modal analysis results among different petrographers We are aware of the role of the petrographer in modal-analysis precision. The coal petrographer as a variable is most difficult if n o t impossible to evaluate. Evidently a good modal analysis is dependent upon the petrographer's competence as well as conscientious effort and concentration. The AIAS method, we believe, will help any petrographer to first explore and make his or her decision based upon various comparisons of gray-level values of different phases in a numerical quantitative manner on the TV monitor. Such comparisons with 64 gray-level resolution provide a distinct advantage over the point-count method. This opportunity for exploring the differences among maceral phases to be analyzed should allow the petrographer to make decisions with greater confidence than could be achieved by relying on the microscope alone. There will be differences in modalanalysis data among different coal petrographers but with the AIAS, a basis exists for comparison and judging which classification is more reasonable and therefore better.

(2) Use o f polished thin sections. Polished thin sections prepared perpendicular (or nearly so) to the coal-bed layering provide certain advantages in the study of complex coal microlithotypes and lithotypes with the AIAS because the AIAS can be used with either reflected or transmitted lighting

Stratigraphic interval

Point count (vol. %)1

Number of points

AIAS (vol. %)~

40.433 m

40.965 m

39.678 m

41.103 m

41.242 m

1.24

1.30

1.32

1.32

1.32

V,gE~2ITM~ Vs,ETI,M 7 V, sE~gIsM4 VsoEgI,M 5 Vs3EgI3,M , VsgE,I2sM 7 V3,E24I~0Ms Vs,E,I20M23 V,TE~2137M, V~E4I:~M ~ V,,E~I,0M , Vs~EsI3,M9

(S=0.2) (S=0.1) (S=0.4) (S=0) (S=0) (S=0) (S=0.4) (S=0) (S=0) (S=0) (S=0) (S=0)

1200 1260 807 828 984 992 637 798 905 908 510 529

V, sE,213M20 Vs,E~212Ms V92E413M, V83EgI~M, VT~EsI22M2 V,0E~xI2,M2 V55EsI2,M2o Vs,(E+M)2,I22 V~oE~I,, V,,(E+M):~II~ Vs~EsI~M s V,~E~oI,oM~

58 --59.5 cm

1.39

V~4E21,3M~ V~3E~II~M, V87E~I4M9 VsoI2M,~

(S=0.4) (S=0.2) (S=0) (S=0)

956 996 894 1061

V93E3I,M 1 V89E~I,M~ VgoI~M9 VsoI,M~9

1 Interval between measurements 0.05 m m along each row, 0.166 m m between rows. 2 Area of each field measured approximately 0.04 m m 2, interval between fields 1 ram. 3 CLT = Carolyn L. Thompson, BWH = Bruce W. Hall.

3.5--5.0 cm

1.26

Column sample H2-42P-1, Upper Freeport coal (medium-volatile bituminous), Indiana County, Pa.:

40.410 m

1.24

Core sample TRM-1, I coal bed (high-volatile bituminous C), Emery coal field, central Utah:

Specific gravity

8 8 10 10

4

(S--0)

(S=0.03) (S=0) (S=0) (S=0)

7 7 5 5 5 6 5 6 4 6 4

(S=0.02) (S=0) (S=0) (S=0) (S=0) (S=0) (S=0.02) (S=0) (S=0) (S=0) (S=0)

Number of fields

CLT BWH CLT BWH

CLT BWH CLT BWH CLT BWH CLT BWH CLT BWH CLT BWH

Analyst ~

Microscopic modal analyses; Comparison of point-count and AIAS data determined by two different analysts (Polished blocks, 50× oil-immersion objective; V = vitrinite, E = exinite, I = inertinite, M = optically observable mineral components other than iron sulfide (S))

TABLE VI

¢o

144 TABLE VII Modal analyses of pellet mounts: comparison between point-count and AIAS data (50)< oil-immersion objective) Sample

Point count*

AIAS

L2WM5.1 (2 mounts)

V83.,E,.0I~0.,MMfree

VB,ETIsM~(10 fields)

V~9.4Es.~II0.~M4.8 Parr formula WVG-P-1.0 (2 mounts)

V73Es.sI~8.~MMfree

VssE,I10 (10 fields)

*Analyst, R.W. Stanton, 500 points per mount.

conditions. F o r example, a polished thin section of a sporinite- and alginitebearing commercial cannel coal from eastern Kentucky is shown in reflected light in Fig. 13a and in transmitted light in Fig. 13b. In reflected light, only the maceral groups exinite, vitrinite, and inertinite can be distinguished. The reflectance or corresponding gray-level values of the sporinite and alginite are essentially the same and hence cannot be distinguished or segmented on the basis of gray-level difference. However, the sporinites and alginites can be readily separated and segmented in transmitted light because alginites are colorless and sporinites are yellow (light gray and medium gray, respectively, in the TV image). The relative abundance of alginite versus sporinite can aid significantly in interpreting the depositional environment of the coal bed. In transmitted light, cutinite can also be distinguished from resinire and sporinite for a specific rank of bituminous coal. In addition, cell walls and cell fillings of vitrinite can be distinguished much more readily in transmitted light than in reflected light for image analysis. These are just a few examples where polished thin sections can be used to greater advantages than polished mounts.

(3) Texture analysis o f maceral particles in coal. Figure 14a shows a representative portion of a trimacerite microlithotype in a polished block sample of coal from Takou, Shanxi Province, North China. The modal composition is V42E14143M1 as determined by gray-level segmentation using AIAS. As seen in the photomicrograph, elongated particles of exinites and inertinites are e m b e d d e d in a matrix of vitrinite in this microlithotype. For more complete characterization, the size (area} distribution of both the Fig. 13. a. Photomicrograph o f a polished thin section o f commercial cannel coal from eastern Kentucky taken in reflected light. Bar scale is 100 ~m. b. Photomicrograph o f area shown in (a) but taken in transmitted light. Note that alginites (a) appear light gray and the sporinites (s) are medium gray in this photomicrograph.

h~ 01

146

60

40

20

~

(b)

1

Exinite 250 particles

o 60

"6

40 Inertinite 422..par ticles

20

10

20

30

40

50

60

70

Size(area) of Particles (IJm2)

80

90

100

147

exinites and inertinites can be precisely determined using the AIAS. Figure 14b shows these size distributions. Out of 250 exinite particles, 68% (171), mostly microspores, are less than 10 sq. microns in area; 50% (125) are 5 sq. microns or less; 6% (15) are between 50 and 100 sq. microns. The largest particle among the 250 represented is between 90 and 95 sq. microns. Although these sizes were determined in terms of area, they could just as easily have been measured in terms of length or any other similar parameter. The histogram of size distribution of the inertinite particles (Fig. 14b) shows that of 422 particles measured, 78% (331) are 5 sq. microns or less in area. The finer particle size of the inertinite group may possibly represent the degree of degradation of probably oxidized organic material in the coal. It is quite possible that information on size distribution of maceral particles may constitute significant data needed either for distinguishing microlithotypes of different coal beds or as an indication of the effects of transport and the nature of sites of deposition. The total amount of time required for textural analysis of a field is a b o u t 5 minutes. (4) The use o f A I A S as an extension o f the optical microscope. The human eye is more sensitive in distinguishing shades of colors than shades of gray. The ability to distinguish 64 gray levels b y the AIAS certainly exceeds the capability of the unaided human eye viewing a sample in reflected light through the optical microscope. Our experience has shown that there is a wide range of reflectance differences within a single maceral group and even within a single maceral fragment. With the help of the AIAS, the detail of gray-level variations (corresponding to reflectance variations) o f various vitrinite particles in the same coal sample can be further examined. Differences in textural details between various exinites or semifusinites, as well as gradations between semifusinites and fusinite, can be studied. Furthermore, any significant differences for classification can be measured quantitatively. We have just begun to take advantage of this potential, which may give us new observations and better understanding of coal macerals. III DISCUSSION

Since the installation of the MAGISCAN in our laboratory, a great deal of time has been spent learning about the capabilities of the instrument and the merits and the problems associated with its application to coal research. Although we have been most impressed with the performance of the AIAS in our petrographic procedures, several capabilities are still needed. These include the abilities: (1) To better distinguish different macerals having similar or overlapping gray-level intervals. Fig. 14. a. Photomicrograph o f a trimacerite microlithotype V4~E14143M~ from Takou o f Shanxi Province, North China. Bar scale is 100 pm. b. Histograms o f size (area) distribution of exinite and inertinite particles in this microlithotype.

148 {2) To distinguish exinite from some of the minerals or holes in low-rank coals. (3) To improve sensitivity of image analysis to allow analysis in fluorescence. (4) To improve the efficiency of the lightpen editing capability. (5) To improve software routines for correction of the edge or halo effects. At present, if t w o maceral phases have substantially overlapping gray-level intervals, one approach is to use an algorithm for curve stripping in order to separate the two phases. An alternative is to use polished thin sections and transmitted light to see if the gray values o f the t w o phases can be better distinguished in transmitted rather than reflected light. Another possible solution, which we have not yet explored, is the combined or sequential use of gray-level gradient and textural characteristics. This approach would work if the gray-level intervals overlap b u t the t w o phases are distinguishable on the basis of size, shape, or texture, for example, if one phase has an elongated or platy habit and the other is ovoid. If the reflectance or gray-level values of exinite and some minerals or holes in a low-rank coal appear to be the same in reflected light (E+M in Table VI), we can also use texture as the criterion for segmentation because exinites normally have very distinctive shapes, which car be distinguished among themselves. Another alternative is to use fluorescence excitation as exinites in low-rank coals have characteristic fluorescence. Normally the prepared specimen contains some scratches, holes, or other flaws due to imperfect polishing. As mentioned above, the better the polish, the better the gray-level contrast between phases for cleaner segmentation. If an area is poorly polished or separate particles coalesce and hence are improperly segmented, the petrographer can use the lightpen editing capability to eliminate erroneously segmented areas prior to analysis. It is well worth the extra few minutes this may require to improve the accuracy of analysis in such instances. Our experience indicates that minor scratches rarely affect the analytical results, so that the requirement for lightpen editing must be left to the judgment of the petrographer. One further problem which arises with our present operating system is associated with fine-grained samples. If the sample contains great numbers o f interfaces between grains of different macerals, the present "edge" software routine, aimed at sharpening the boundary between adjoining phases, results in t o o large a total correction, and AIAS analyses of such fields consequently tend to give totals as low as 93--95, rather than 100, area (and hence volume) percent. This situation should be correctable by modification o f the computer algorithm. IV. SUMMARY This paper introduces a new technique and procedure for the estimation

149

of the rank of coal and the description of drill core or block samples of coal. We have given a fairly detailed description and evaluation of the capabilities o f a completely software-controlled AIAS and its application to the study of coal. The AIAS instrument, in our opinion, is invaluable to quantitative coal petrography. Because of the large numbers of samples involved, it is an important tool and m a y become an indispensable tool for obtaining rarge amounts o f quantitative data for the petrologic study of the geological processes affecting coal genesis, and for the prediction of coal quantity and quality changes horizontally and vertically. In order to use the AIAS for coal description and analysis, we have derived a procedure for describing the coal both megascopically and microscopically and introduced a quantitative VEIM nomenclature for easy representation and comprehension of the coal petrographic data obtained. We have described in detail, h o w modal analysis can be performed using the AIAS and h o w textural analysis of coal components can be made. We have evaluated factors affecting the precision of the AIAS microscopic modal analysis and have also included data comparing the precision of the AIAS with the precision of the current point-counting method. Effective use of the AIAS requires a c o m p e t e n t petrographer. The instrument, which can resolve 64 gray levels, enables the coal petrographer to distinguish slight differences in reflectance b e t w e e n macerals that he could not distinguish by using only the optical microscope. The AIAS method not only provides a maximum of pertinent and quantitative data b u t is relatively rapid so that a large number o f coal samples can be studied within a reasonable number of days or weeks. We believe that the remaining AIAS problems to be resolved are mostly minor. We are still exploring the potential capabilities of the AIAS for coal research. On the basis of data and experience already gained and presented in this paper, we are convinced of the merits and would recommend the AIAS for a major role in the advancement of coal petrography. V. ACKNOWLEDGMENT

We are grateful to Ronald W. Stanton for providing us with samples and data for comparative measurements with the AIAS, and to Bruce W. Hall for valuable assistance with sample preparation and data collection.

REFERENCES ASTM, 1980a. Standard method for microscopical determination of the reflectance of the organic components in a polished specimen of coal. In: 1980 Annual Book of ASTM Standards, Part 26. Am. Soc. Test. Mater., Philadelphia, Pa., pp. 372--375. ASTM, 1980b. Standard definitions of terms relating to megascopic description of coal and coal beds and microscopical description and analysis of coal. In: 1980 Annual Book of ASTM Standards, Part 26. Am. Soc. Test. Mater., Philadelphia, Pa., pp. 363-366.

150 Cameron, A.R., 1978. Megascopic description of coal with particular reference to seams in southern Illinois. In: R.R. Dutcher (Editor), Field Description of Coal. Am. Soc. Test. Mater., Spec. Tech. Publ., 661: pp. 9--32. Chao, E.C.T., Minkin, J.A. and Thompson, C.L., 1982. Recommended procedures and techniques for the petrographic description of bituminous coal. Int. J. Coal Geol., 2: 151--179. Chayes, F., 1956. Petrographic Modal Analysis. Wiley, New York, N.Y., 113 pp. Davis, A., 1978. The reflectance of coal. In: C. KarL Jr. (Editor), Analytical Methods for Coal and Coal Products vol. 1. Academic Press, New York, N.Y., pp. 27--81. Dutcher, R.R. (Editor), 1978. Field Description of Coal. Am. Soc. Test. Mater., Spec. Tech. Publ. 661, 71 pp. England, B_M., Mikka, R.A. and Bagnall, E.J., 1979. Petrographic characterization of coal using automatic image analysis. J. Microscopy, 116 (3): 329--336. Gray, R.J., Todd, S.J. and Drexler, T.D., 1979. Status of automated coal petrography at U,S. Steel (abstr.). Ninth Int. Congr. Carb. Strat. and Geol., Urbana, Ill., Abstr. p. 75. Hampson, A.J., 1980. Coke quality control by on-line coal quality monitoring at DOFASCO. Ironmaking Proc., Metall. Soc. AIME, March 23, 1980, pp. 162--168. Harris, L.A., Rose, T., DeRoos, L. and Greene, J., 1977. Quantitative analyses of pyrite in coal by optical image techniques. Econ. Geol., 72: 695--697. Harris, L.A. and DeRoos, L.F., 1979. Automated objective coal petrography by image analyses systems (abstr.). Ninth Int. Congr. Carb. Strat. and Geol., Urbana, Ill., Abstr., p. 86. Hoover, D.S. and Davis, A., 1979. The development and evaluation of an automated reflectance microscope system for the petrographic characterization of bituminous coals. U.S. Dept. Energy Tech. Report FE-2030-TR 23, 261 pp. ICCP, International Handbook of Coal Petrography, 1963 (second edition), 1971 (Supplement 1) and 1975 (Supplement 2). Centre National de la Recherche Scientifique, Paris. Kojima, K., Sugai, T. and Hara, Y., 1979. Automatic system for evaluating coking coals and its application in Nippon Steel Corporation (abstr.). Ninth Int. Congr. Carb. Strat. and Geol., Urbana, Ill., Abstr., p. 109. Neavel, R.C., Smith, S.E., Hippo, E.J. and Miller, R.N., 1981. Optimum classification of coals. Proc. Int. Conf. on Coal Sci., Dusseldorf, Germany, September 7--9, 1981, pp. 1--9. Schopf, J.M., 1960. Field description and sampling of coal beds. U.S. Geol. Surv. Bull., l l l l - B : 25--70. Schopf, J.M., 1978. Further suggestions about coal description in the field. In: R.R. Dutcher (Editor), Field Description of Coal. Am. Soc. Test. Mater., Spec. Tech. Publ., 661 : 3--8. Ting, F.T.C., 1978. Petrographic techniques in coal analysis. In: C. Karr, Jr. (Editor), Analytical Methods for Coal and Coal Products, Vol. 1. Academic Press, New York, N.Y., pp. 3--26. Ting, F.T.C. and Klinkachorn, P., 1979. Automated petrographic analysis of coal: electronically enhanced maceral and reflectance analyses (abstr.). Ninth Int. Congr. Carb. Strat. and Geol., Urbana, Ill., Abstr., p. 216. Zeiss, H.S., 1979. Automated coal petrography at Bethlehem Steel (abstr.). Ninth Int. Congr. Carb. Strat. and Geol., Urbana, Ill., Abstr., p. 242.