NEW TECHNIQUE FOR STRATfiGRAPch ANALYSlS AND CGRRELATQOE -- FOURfiER GRAIN SHAPE MALYSB LOUISMNA OFFSHORE PUOCENE Sissertatian for the Degree of Ph. D. MICHEGAN STATE UNiVERSWY §0Hfi ‘v’ENSEflT MRAKOVECH 1974 LIBRARY Michigan State University This is to certify that the thesis entitled New Technique For Stratigraphic Analysis And Correlation--Fourier Grain Shape Analysis Louisiana Offshore Pliocene presented by John Vincent Mrakovich has been accepted towards fulfillment of the requirements for Doctoral degree in Geology fwv‘ ' Major professor Date February; 1974 0-7639 :u LII V A -1. «Q 5 NC :1 .fih C\ ‘5 Riv ¥s Q5 \ N ”U; ABSTRACT NEW TECHNIQUE FOR STRATIGRAPHIC ANALYSIS AND CORRELATION--FOURIER GRAIN SHAPE ANALYSIS LOUISIANA OFFSHORE PLIOCENE BY John Vincent Mrakovich Because quartz grain shape is sensitive to provenance and environmental processes, stratigraphic shape analysis may be a complementary technique to conventional correlation methods. To test the validity and practicality of such a technique, sidewall cores from an 11,000 foot Pliocene interval in West Delta Block 117 offshore Louisiana were sampled and analyzed by Fourier shape analysis. Approxi- mately one hundred grains from each of nineteen samples were sufficient to subdivide the interval into distinct "shape zones." Zones consist either of contiguous samples of statistically different shapes or of contiguous samples of statistically uniform shape. Shape frequency distributions of all samples were poly- modal. In most cases, sample differences are caused by the presence or absence of a subpopulation of twenty per cent or fewer characteristically shaped grains. Correlation based on quartz grain shape was successfully tested by sampling in detail two stratigraphically separated sands in one well and a correlation of one with a sand in a second well over a mile away. John Vincent Mrakovich Fourier shape analysis is amenable to a high degree of automation and could become an additional tool for sub- surface stratigraphic correlation and analysis. NEW TECHNIQUE FOR STRATIGRAPHIC ANALYSIS AND CORRELATION--FOURIER GRAIN SHAPE ANALYSIS LOUISIANA OFFSHORE PLIOCENE BY John Vincent Mrakovich A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Geology 1974 ACKNOWLEDGMENTS Special acknowledgment is extended to my advisor, Dr. Robert Ehrlich, without whose cooperation and mastery of sedimentology this research could not have succeeded. Also, special thanks go to my committee members, Drs. Robert Anstey, Sam Upchurch, and Thomas Vogel, for always giving willingly of their time for discussion and advisement. Finally, I wish to thank Gulf Oil Co. - U. S. for making available sidewall cores and electrical-induction logs used in this study. ii d: O rn ’A\“ u Vat; TABLE OF CONTENTS Page LIST OF TABLES . . . . . . . . . . . . . . . . . . . . iv LIST OF FIGURES . . . . . . . . . . . . . . . . . . . v INTRODUCTION . . . . . . . . . . . . . . . . . . . . . l MethOd O O O O O O O O O O O O C O C O O O O O O O 3 Sampling Design and Analytical Techniques . . . . . 9 ZONATION OF THE 11,000 FOOT INTERVAL . . . . . . . . . lO Harmonic Amplitude Spectra . . . . . . . . . . . . 20 STRATIGRAPHIC ZONATION AND VARIATION OF SHAPE- FREQUENCY DISTRIBUTIONS . . . . . . . . . . . . . . 24 Analysis of Shape-Frequency Distributions in Heterogeneous Shape Zone A . . . . . . . . . 25 Analysis of Shape-Frequency Distributions in the 11,000 Foot Interval . . . . . . . . . . 30 Variation of Harmonic Six . . . . . . . . . . . . . 37 SMALL-SCALE SHAPE CORRELATION OF A SANDY DEPOSITIONAL UNIT BETWEEN WELLS B-2 AND D-l BY I'IARMONIC AMPLITUDE SPECTRA . o o o o o o o o 41 CONCLU SIONS . C C C O O O O O O O O O O O O O O O O O 4 4 LIST OF REFERENCES 0 O O O O O O I O O O O O O O O O O 4 9 APPENDICES A C O O O O O O O O O O O O O O O O O O O O O O O O 51 B O O O O O O O O O O O O O O O O O O C O O O O O O 71 iii Table LIST OF TABLES Page Source of significant harmonic variability of the successively quartered interval for each harmonic. Dots indicate significant differences at the .05 level . . . . . . . . . l4 Harmonic amplitudes for harmonics one through twenty for nineteen samples arranged and labeled according to depth. Each sample con- tains approximately a hundred quartz grains . 71 iv 7a -I (1‘ Figure 7a 7b LIST OF FIGURES Location map of wells B-2 and D-l offshore Louisiana West Delta Block 117 . . . . . . . . Characteristic Spontaneous Potential (S. P.) curve, locations of nineteen samples collected from the sampling intervals in the 11,000 foot Pliocene interval of well B-2 . . . . . . . . Pattern of successive quartering of the nineteen samples in the 11,000 foot Pliocene interval (characterized S. P.) for chi-square analysis . . . . . . . . . . . . . . . . . . . Zones of grain shape heterogeneity for the 11,000 foot interval of well B-2. Shaded groups of contiguous samples indicate hetero- geneous zones for the harmonic indicated. The remainder of the interval in each case comprises zones of grain shape homogeneity . . Mean harmonic amplitude Spectra of pooled samples from the upper half of the 11,000 foot Pliocene interval and pooled samples from the lower half of the interval. Amplitudes nor- malized as described in text . . . . . . . . . Positions and membership of modes in hetero- geneous shape zone "A" as determined by ISODATA. Likely intersample mode relation- ships are denoted for harmonic six . . . . . . Mode positions for harmonic six as determined by ISODATA from shape-frequency distributions in the 11,000 foot Pliocene interval . . . . . Mode shifts in harmonic six for lower half of 11,000 foot Pliocene interval as revealed by ISODATA analysis. Interpretation of mode shifts as illustrated in Figure 6a shown for samples one through four . . . . . . . . . . . Page 12 17 22 27 32 34 Figure 7c 10 ll 13 Figure 7c 10 11 12 13 14 15 16 17 Final interpretation of mode shifting among all nineteen shape-frequency distributions in the 11,000 foot Pliocene interval for harmonic Six 0 C O O C O I O O O O O O O O O O O O O 0 Mode positions in left and right tails of the nineteen shape-frequency distributions of harmonic six in the 11,000 foot Pliocene interval . . . . . . . . . . . . . . . . . . . Characteristic Spontaneous Potential curve of sandy depositional units "Y" and "Z" in wells B-2 and 0-1 and sample locations . . . . . . . Mean harmonic amplitude Spectra for sand unit "Y"--we11 B-2, sand unit "Y"--well D-1, and sand unit "Zn-'I'well B-2 0 o o o o o o o o o 0 Positions and membership of modes of nineteen shape-frequency distributions stratigraph- ically arranged in the 11,000 foot interval for harmonic six as determined by ISODATA . . Positions and membership of modes of nineteen shape-frequency distributions stratigraph- ically arranged in the 11,000 foot interval for harmonic seven as determined by ISODATA . Positions and membership of modes of nineteen shape-frequency distributions stratigraph- ically arranged in the 11,000 foot interval for harmonic eight as determined by ISODATA . Positions and membership of modes of nineteen shape-frequency distributions stratigraph- ically arranged in the 11,000 foot interval for harmonic nine as determined by ISODATA . . Positions and membership of modes of nineteen shape-frequency distributions stratigraph- ically arranged in the 11,000 foot interval for harmonic thirteen as determined by ISODATA Positions and membership of modes of nineteen shape-frequency distributions stratigraph- ically arranged in the 11,000 foot interval for harmonic fourteen as determined by ISODATA Positions and membership of modes of nineteen shape-frequency distributions stratigraph- ically arranged in the 11,000 foot interval for harmonic fifteen as determined by ISODATA vi Page 36 4O 43 46 52 54 56 58 60 62 64 Figure 18 19 20 Page Positions and membership of modes of nineteen shape-frequency distributions stratigraph- ically arranged in the 11,000 foot interval for harmonic sixteen as determined by ISODATA 66 Positions and membership of modes of nineteen shape-frequency distributions stratigraph- ically arranged in the 11,000 foot interval for harmonic seventeen as determined by ISODATA . . . . . . . . . . . . . . . . . . . 68 Positions and membership of modes of nineteen shape-frequency distributions stratigraph- ically arranged in the 11,000 foot interval for harmonic twenty as determined by ISODATA . 70 vii INTRODUCTION In the petroliferous Neogene deposits of the Gulf of Mexico, traditional methods of correlation have not been entirely adequate. Analysis of hydrocarbon trends and field development have been based on paleontologic and lithologic correlations. However, correlation using conventional methods is exceedingly difficult because of the complex relationship of facies evolving from rapid lateral and vertical displacement of deltaic depocenters and the pro- fusion of long ranging Tertiary fauna. This paper presents the results of a new correlation technique based on Fourier defined quartz grain shape (Ehrlich and Weinberg, 1970) that is independent of the various logging tool characters and faunal occurrences. Using this technique, an 11,000 foot Pliocene interval was successfully subdivided into distinct "shape zones.“ Based on such subdivisions, Fourier shape analysis promises to be a new complementary tool to the standard methods of correlation in areas of complex facies changes. Shape is a fundamental prOperty of particles, and its importance in geology has always been conceptually recog- nized, however, it has not been widely used as a tool for geological analysis. The limited use of shape data results 1 I65 2» L. a eve: 'v J '64 e; . Q Q . .EQ‘ ‘0 r . C N! ~.. Has 1.5 5‘0 n ‘ 2 from lack of an unambiguous and unbiased Operational technique for accurately quantifying grain shape. Recently, Ehrlich and Weinberg (1970) developed a quantitative tech- nique that precisely describes, by Fourier analysis, two- dimensional grain shape. This method allows changes in both intricate and simple forms to be easily monitored. Since morphological character is an environmental response, a grain's shape at any instant can be regarded as the sum total of a series of genetic events, where each event altered to some degree the shape imposed by previous events. Shape must reflect process of mineral formation, weathering processes, and modification by abrasion, fracture and corrosion encountered during sediment transport and deposition. Recent shape studies using Fourier analysis have estab- lished the utility of the technique. Waltz (1972) has monitored significant shape differences of quartz silt in the heterogeneous glacial drift of a Michigan drainage basin; Ehrlich and Orzeck (1973) have effectively discriminated quartz sand shape between modern river, beach, and ancient beach cliff sands in southern California; and Kennedy (1972) has demonstrated the influence of provenance and deposi- tional environment on quartz sand and silt from Holocene sediments in the Chukchi Sea. Anstey (1972), Kaesler (1972), Younker (1971), and Ehrlich 35 El“ (1972) have demonstrated the usefulness of Fourier shape analysis in paleontology and metamorphic petrology. 133m " J. Stluw 11.. w611: b.0Cfi 3 Method Fourier grain shape analysis was performed on sands from two offshore Louisiana oil wells. Sidewall cores and induction-electrical logs were made available for this study by Gulf Oil Company - U. S., New Orleans. The two wells, B-2 and D-l, are straight holes in Gulf's West Delta Block 117 field located approximately twenty-four miles southwest of the present Mississippi birdfoot delta (Figure 1). The wells are separated by a distance of 6,000 feet and penetrate Pleistocene, Pliocene, and probably upper Miocene sediments. Well B-2 was used to test for significant large-scale shape zonation, in the Pliocene interval, because of its abundance of sidewall core samples and their favorable, spacial distribution (Figure 2). Samples in well D-l were too clustered to be useful in such a large-scale study, but were suitable for testing sand correlations between the two wells. All shape measurements were made on quartz grains because of their size, ubiquity, and presumable lack of cleavage-controlled shape. Grain size ranged from fine sand to silt with most samples being very fine-grained sand. Two-dimensional shapes were obtained with a petrographic, binocular microscope and attached camera lucida. A hundred grains per sample were randomly selected. Via the camera lucida, quartz grain shapes were Optically projected and traced onto a radiating pattern of forty-eight equally spaced lines. The forty-eight points of intersection Figure 1. Location map of wells B-2 and D-l offshore Louisiana West Delta Block 117. 9’0" l "2 7q 0 \WA-\ 45’ new ("NEWS 0 P .i\ \\ / 2? \ \\ " “5—. o4 (f? y %9 / oWEll. D-l ‘ ’ ‘WEll 3-2 20 o 20_ —== miles Figure 1 6 between the pattern lines and shape curve were then auto- matically digitized and punched onto Hollerith cards as X, Y coordinates. This data was then subjected to Fourier analysis. The full theoretical discussion and application of Fourier analysis to grain shape can be found in Ehrlich and Weinberg (1970). In essence, Fourier analysis resolves a grain's two-dimensional shape into multiple shape components or harmonics, with each harmonic accounting for a specific contribution to the total shape. The sum of harmonics can describe grain shape as precisely as desired. With the origin at the center of gravity, the "zeroth" harmonic is a centered circle with an area equal to the total grain area, the first harmonic describes the contribution of an offset circle, the second harmonic the contribution of a "figure eight," and the third the contribution of a "trifoil." The "nth" harmonic describes the contribution of a geometrical shape with "n" nodes. Harmonic coefficients or amplitudes indicate the relative contribution of each harmonic to total grain shape. Lower harmonics describe gross grain shape and progressively higher harmonics describe progressively smaller surface texture. In order to compare grains or samples harmonic-by- harmonic, all amplitudes are "normalized" by division by the "zeroth" harmonic. Normalization makes shape comparisons independent of grain size and sets all "zeroth" harmonics equal to unity in value. Analysis of the first harmonic Figure 2. Characteristic Spontaneous Potential (S. P.) curve, locations of nineteen samples collected from the sampling intervals in the 11,000 foot Pliocene interval of well B-2. Sample Figure 2 Locations I 5-"-_,.4500 §-—- ~-ssoo 4:: '4‘ 5__. ..6500 6___ —»7500 7— I. 3.. A 3500 9.. ' —-9soo 11::7 E“ —~l0500 ~~Il500 12.. __ |3__ l4__. — l2500 '5_ L_. . r4l3500 '6‘- fit l7__ '8—— l4500 I9__ 1’ 93.9.1". Five Hundred Foot Sampling Intervals will the ; Thus, ’4- :71 \D D. 9 will not appear herein because it is primarily a function of the precision of location of the grain's center of gravity. Thus, only harmonics two through twenty occur in the follow- ing discussions. Sampling Design and Analytical Techniques To date, the utility of shape variation, as defined by Fourier analysis, has not been established in a strati- graphic sense. The research presented here investigates shape variation throughout the Pliocene epoch, an interval represented by approximately 11,000 feet of sediments in West Delta Block 117. Samples were collected according to a stratified random sampling plan, with "stratified" being used, here, in both a statistical and a geological sense. This design tests for a functional relationship of shape versus depth. Sampling was applied to the suite of sidewall core samples from well B-2, which was collected several years prior to this study. Starting at the well surface, 500 foot intervals of strata were delineated until the deepest sidewall core of the well was included in one such interval. Then, one core per interval was selected at random. A total of nineteen samples was collected by the above scheme. The resulting sampled interval probably includes the entire Pliocene (personal communication, Gulf Oil Company) and ranges in depth from 4,500 feet to 15,500 feet with only three intervals containing no samples (Figure 2). 10 Orthogonal hierarchical partitioning of chi-square contingency tables, as developed by Kimball (1954), was used for determining which harmonics were carrying significant shape information. Chi-square analysis was chosen because of the obvious polymodal character of the data. Upon determining which harmonics were carrying signifi- cant shape information, posterior comparisons were made according to a simultaneous test procedure (STP) developed by Gabriel (1966) as a method to locate "tops" and "bottoms" of "shape zones." The complex, polymodal nature of the data precluded use of simple statistical measures such as the mean or standard deviation as indicators for significant shape variability. A pattern recognition algorithm—-ISODATA (Ball and Hall, 1965)--was used to define location of modes and assign grains to apprOpriate modes. ZONATION OF THE 11, 000 FOOT INTERVAL In the absence of any prior information on the exis- tence or position of zones, the sampled interval was pro- gressively quartered for testing. That is, the upper half of well B-2 was compared to the lower half, the lowest quarter was compared to the next lowest quarter, etc. (Figure 3). These orthogonal comparisons were the basis for determining if significant differences in quartz grain shape existed from sand to sand. Evaluation of the interval by the chi-square test statistic, harmonic-by-harmonic, indicated significant grain 11 Figure 3. Pattern of successive quartering of the nineteen samples in the 11,000 foot Pliocene interval (characterized S. P.) for chi-square analysis. 12 450011. _| 7' .1 -l _2 / Sample Number -2 -2 -2 _3 . 3 -3 -3‘ _4 1-4 -4 -4 . ‘ -5 -5 _5 -5 -6 -5 -5 _5 -7 -7 -11 -s —; _7 1L7 -9 -9 " —8 9 -9 -s -9 .10 E4 -11 C -10 —|0 -'° -11 -|| é" -12 -13 . -14 _I2 _'2 -15 -13 -|3 -12 -'2 -14 -13 o 16 J4 -'4 "3 -17 -15 O -14 -15 - -15 -19 I7 _|6 ..|6 15,301 11. ‘13 _17 I8 _l9 I7 l8 _l8 1_ 1 W 11 1. ‘T o :1. Figure 3 1 ‘1‘ hUh 13 shape variation for all but five harmonics (Table I). Inspection of the general results (Figure 4) suggests the existence of two major zones and perhaps two minor zones of significant quartz shape variability. On the basis of the contingency table analysis, precise location of zone bound- aries might be slightly in error since this zonation was detected by analysis of successive quarterings of the inter- val. Gabriel's (1966) "post hoc" simultaneous test pro- cedure (STP) was utilized to test the validity of the positions of zone boundaries. STP results are independent of quartering and involve analysis of shape variation as sands are progressively added to a zone. STP results con- firm position of zone boundaries defined by quartering. The term "zone," as used herein, is based on the con- cept of heterogeneity or homogeneity among sands occurring within a specific subinterval of the 11,000 foot interval with respect to quartz grain shape. A set of stratigraph- ically contiguous sands showing no significant quartz grain shape differences between sands is considered to com- prise--and be defined herein as--a "homogeneous" zone. Likewise, a set of stratigraphically contiguous sands of significant quartz grain shape variablity between sands is considered to comprise--and be defined herein as--a "hetero- geneous” zone. A collection of heterogeneous and homogeneous zones can be produced in a number of different ways. For example, given two populations of quartz grains, X and Y, having 14 Table 1. Source of significant harmonic variability of the successively quartered interval for each harmonic. Dots indicate significant differences at the .05 level. TABLE 1. $00 RCE O F VAnlAslyrv (I vs! vs...vs 9) 15 HARMONICS resume 0|: (IO vs II vs...vsl9) (”2...”) vs (l0+ll...+l9) (lvs2vs3vs4) (5 vs 6 vs...vs 9) “+2....“ vs (SH...+9) (IO vs II vs...vs l4) (I!) vs l6 vs...vs l9) (l0+ll..§l4)vs(l5+l6..:O-l9) t ”vs 2) { (3 vs 4) ((+2) vs (3+4) (5 vs 6) (‘1sz vs 9) (5+0) vs (Ll-8+9) (l0 vs II) (l2 vs l3 vs l4) (101-11) vs (121431-14) (l5 vs l6) (I? vs l8 vs l9) “5446) vs (”4- l8+l9) (8 vs 9) (7) vs (8+9) (l3 vs I4) (l2) vs (I3+|4) (18 vs l9) (I7) vs (ISO-IO) 16 Figure 4. Zones of grain shape heterogeneity for the 11,000 foot interval of well B-2. Shaded groups of contiguous samples indicate heterogeneous zones for the harmonic indicated. The remainder of the interval in each case comprises zones of grain shape homogeneity. 17 s~ 5 ss 5 3 5 N h “x“ \x x \ \\ \\ s, \ .\ R V \ \\ s a s m. 3 2 a a n m0_202m<1 v wusmflm : 3}. 2. up up 3 m. 3 N.- $31dWVS A; Vs .s‘ ~u. .5. s 18 significantly different shapes, zone A--representing hetero- geneity--cou1d represent an interfingering of sands alter- nately containing grains of X and Y. Homogeneity of the remainder of the 11,000 foot interval could be caused by sands containing quartz grains of only X or Y; or homo- geneity of the remainder of the interval could, however, be caused by all sands containing equal prOportions of quartz grains from both pOpulations X and Y. Still a more complex model giving the same statistical result might include sands from three populations X, Y, and Z all having significantly distinct shapes. Many explanations are thus possible for the existence of heterogeneous and homogeneous zones as defined by the orthogonal chi-square and STP analysis. There is no ques- tion, however, that the zonation discussed below exists whatever the underlying cause. Documentation of this zona- tion is presented next. Following that, the causes of the zonation will be discussed. Two major heterogeneous zones (Figure 4)--"A" and "B"-- occur in the upper half of well B-Z. Zone A ranges in depth from 4,767 feet to approximately 6,375 feet and is hetero- geneous with respect to harmonics six, seven, nine, thir- teen, and sixteen. These, excepting harmonic thirteen (Figure 4), are homogeneous throughout the remainder of the 11,000 foot interval. Zone B ranges from approximately 6,375 feet to 9,520 feet and is heterogeneous with respect to harmonics 19 fourteen, fifteen, and twenty. Excepting harmonic fourteen (Figure 4), the remainder of the 11,000 foot interval is homogeneous in those harmonics. Minor zones, "C" and ”D" (Figure 4), are defined on the basis of one significant harmonic apiece, harmonics eight and fourteen, respectively. Zone C ranges from approxi- mately 10,020 feet to 12,628 feet, and zone D ranges from approximately 14,220 feet to 15,249 feet. Harmonic thirteen diSplays heterogeneity for a portion of zone C. In the sense that the lower zone of the 11,000 foot interval con- tains only minor zones, as defined, it can be generally concluded that this interval is essentially homogeneous, whereas, the upper half is significantly heterogeneous. Orthogonal quartering, in addition to revealing zones of heterogeneity and homogeneity, allows for the grouping or ”pooling” of samples and their orthogonal comparisons (Table I). The upper half of the 11,000 foot interval differed significantly from the lower half of the interval (samples one through nine versus samples ten through nine- teen) in six harmonics (nine, twelve, sixteen, seventeen, eighteen, and nineteen) suggesting that a fundamental shape change exists between the lower and upper halves of the interval. This conclusion is corroborated by the general zonation discussed above which suggests the upper half of the 11,000 foot interval is significantly heterogeneous, and the lower half is essentially homogeneous with respect to quartz grain shape. Ilt n n; 20 Harmonic Amplitude Spectra The nineteen samples under discussion can be graphi- cally displayed as mean harmonic amplitude spectra. Since each of the nineteen samples consists of a hundred quartz grains, the mean amplitude for any harmonic can be calcu- lated by averaging the hundred amplitudes of that harmonic in a sample. The collection of mean harmonic amplitudes (in this case, harmonics two through twenty) is termed the "mean harmonic amplitude spectrum." Harmonic amplitude spectra of quartz grains are loga- rithmically distributed (Ehrlich and Weinberg, 1970). Harmonic amplitude spectra in following discussions were transformed to an arithmetic scale by dividing all harmonic amplitudes by their respective grand means as calculated from approximately nineteen hundred quartz grains. This produced mean values of similar magnitude for each harmonic. Spectra of several samples may be visually inspected and compared. Grains of a sample with a relatively low mean harmonic amplitude spectra approach circularity more closely than samples with relatively high mean harmonic amplitude spectra. A comparison of the plot of the mean harmonic amplitude spectrum (Figure 5) of samples one through nine pooled (4,767 feet to 9,170 feet), with samples ten through nine- teen pooled (9,870 feet to 15,249 feet), clearly illustrates a fundamental difference in grain shape between halves of the interval. Beginning with harmonic eight, the spectra 21 Figure 5. Mean harmonic amplitude spectra of pooled samples from the upper half of the 11,000 foot Pliocene interval and pooled samples from the lower half of the interval. Ampli- tudes normalized as described in text. 22 on mmmEDz 2. or 2. NF .\Olc .\Ol: 21-: moan-mm 1’ x o. 202m<1 3 a o - - - - - a1. moan-mm m musmwm sepa: straf conte 1.). an Uilais cre war ii L 23 separate and remain so, through harmonic twenty, demon- strating that the upper half of the 11,000 foot interval contains quartz grains that, on the average, are smoother than quartz grains in the lower half interval. It is evident that higher numbered harmonics--ranging from harmonic six to at least the twentieth harmonic-- exhibit significant variability, suggesting that shape differences among quartz grains are due to surface features of intermediate scale rather than grain shape which might be associated with the concept of "sphericity." In addition to the contingency table analysis that gave rise to the "shape zones," a number of analytical operations based on the assumption of unimodal, normal distributions were performed (for example, plotting of the sample mean or variance against depth). None detected significant zones of shape variation. This, coupled with the significant con- tingency table results, indicates that the data patterns arise from polymodal variation. That is, the frequency distribution of each harmonic amplitude is polymodal and significant variation results from shifting of modes, addi- tion or subtraction of modes, or strengthening or weakening of certain modes. Analysis of results based on the ISODATA (Ball and Hall, 1965) algorithm in the succeeding section substantiates the existence of polymodality and clarifies the underlying causes of the stratigraphic quartz grain shape variability. ea: 5. E C "VJ \HH 24 STRATIGRAPHIC ZONATION AND VARIATION OF SHAPE-FREQUENCY DISTRIBUTIONS Shape variation between samples can be understood only by recognition and characterization of the polymodal shape- frequency distributions. In this study, this requires analysis of nineteen shape-frequency distributions (one for each harmonic) of nineteen samples, each composed of one hundred quartz grains--resulting in a total of three hundred sixty-one shape-frequency distributions. In each distribu- tion the location of modes and number of grains contributing to each mode must be estimated as objectively and precisely as possible. In order to accomplish these objectives, the ISODATA algorithm was used. ISODATA is an iterative clustering algorithm which locates "cluster centers" (modes) and assigns grains to the centers on the basis of stochastic distance. In essence, ISODATA clusters have minimal within- cluster variance as compared to variance between cluster centers. Although this is, to our knowledge, the first geological application of the ISODATA algorithm, ISODATA is a commonly used pattern recognition technique in other fields (Ball and Hall, 1965, 1967). Each harmonic that defined statistically significant heterogeneous shape zones within the 11,000 foot interval was analyzed separately by ISODATA. Operating parameters ‘were defined such that the algorithm attempted to locate nine or fewer modes by a process which begins with a small 25 number of modes and through iterative splitting and lumping (split/lump ratio set at .80) enlarges the set. If after fourteen iterations convergence on cluster centers was not achieved, the program was instructed to terminate its search. Minimum mode membership was set at two. For most frequency distributions, eight or nine clusters were identified. Most grains were assigned to one of four or five dominant modes that contained about twelve to thirty quartz grains each. Minor modes contained six or fewer grains. Analysis of Shape-Frequency Distributions in Heterogeneous Shape Zone A The exact cause of statistically significant hetero- geneity in a shape zone can arise from changes in mode strengths, shifts of modes, subtraction or addition of modes or various combinations of these. One of the simplest patterns of variation is illustrated by the mode behavior of harmonic six (Figure 6d). Inspection of ISODATA results of harmonic six (Figure 6d) indicates that major modes in all four samples in zone A occur at approximately the same positions and with about the same strength. However, there is a progressive loss of modes from samples one through three on the right tail of the shape-frequency distributions causing their ranges to systematically decrease with depth. The frequency distribu- tion of sample one consists of nine modes ranging from .19 to 2.47 in harmonic amplitude, sample two consists of eight 26 Figure 6. Postions and membership of modes in hetero- geneous shape zone "A" as determined by ISODATA. Likely intersample mode relationships are denoted for harmonic six. PJIJI11fscer £3£a1nw13 lee Number Sample :- w I Figure 6 1- 2- 3- 4- 1- 2- 3- ” .5 I I Harmonic N \l '-°-‘—'." --- -- ---.“-‘-- 0’s.-." -.-‘.- -s-- -s- -.- -.- (a) Harmonic Six (b) Harmonic Seven (c) Harmonic Nine (d) Harmonic Thirteen (e) Harmonic Sixteen 5 m] (E 3 Less than 0 a: ' < Seven Amplitude 1.66 in sample three 9 tion. tions. that sa‘ 'rouqh" P-PProxiJ resyect CO‘lpled which a- frECTdEn. Men I Shape P4 In Hated : fer ham 28 modes ranging from .19 to 2.16 in harmonic amplitude, and sample three consists of seven modes ranging from .14 to 1.66 in harmonic amplitude. Sample four is very similar to sample three except for an additional small mode containing three grains on the right tail of the frequency distribu- tion. The cause of heterogeneity in zone A (samples one through four), with respect to harmonic six, then, is due to loss of modes in the right tail of the frequency distribu- tions. The differences among samples is due to the fact that sample one contains approximately twenty per cent more "rough" grains than sample three and sample two contains approximately seven per cent more "rough" grains (with respect to harmonic six) than sample three. This fact, coupled with the near constancy of position of major modes which account for eighty to ninety per cent of the shape- frequency distributions, suggests that the variable com- ponent probably represents the addition of a distinctly new shape population to the area with time. In this interval another example (Figure 6d) is illus- trated by harmonic thirteen. Differences between samples for harmonic thirteen are not expressed as those for har- monic six by the addition or deletion of modes on the tails of the shape-frequency distributions. Here, all frequency distributions have nine modes, excepting sample four which has eight, and all distributions have approximately the same range. Simple addition or subtraction of modes cannot, in II '71 29 this instance, cause the observed statistically significant heterogeneity. Instead, differences are manifest by a complex pattern of mode shifting and changes in mode strength. The behavior of the shape-frequency distributions of harmonic thirteen can be easily simulated by selective changes in value of-a subpopulation of no more than twenty per cent of the frequency distributions. Differences in shape variation patterns between harmonic six and harmonic thirteen for zone A probably reflect a shape contribution of a subpopulation falling predominantly outside the main shape-frequency distribution of harmonic six, but falling within the range of the main shape-frequency distributions of harmonic thirteen. Because the subpopulation is in itself polymodal and contains so few grains, none of its modes would contain enough grains in a hundred-grain sample to be identified by ISODATA with respect to harmonic thirteen. Instead, their presence would be manifest by shifts in mode position and changes in mode intensity of the main frequency distribu- tions. Samples one and two of harmonic thirteen provide some confirmation of this explanation. As suggested in the dis- cussion of harmonic six, samples one and two should contain larger amounts of a "rougher" subpopulation. Inspection of the shape-frequency distributions of samples one and two of harmonic thirteen display dominant modes and significant H' ui fre I) 1 I 30 total grain proportions at higher harmonic amplitude values than samples three and four (Figure 6d). Analysis of Shape-Frequency Distributions in the 11,000 Foot Interval Analysis of statistically significant heterogeneous shape zones by ISODATA shows the ways in which shape- frequency distributions change to give significant chi- square and STP results. These analyses suggest that progressive addition or deletion of a distinct subpopulation of quartz grains is probably the root cause of significant variability among samples. ISODATA can also be used for inspecting frequency distributions in homogeneous shape zones for trends or changes in mode structure that are too subtle for the statistical methods used. The chi-square test statistic and STP test are not well suited for trend analysis. All samples in the 11,000 foot interval were analyzed by ISODATA for all harmonics that displayed heterogeneity. The purpose was to inspect "homogeneous" intervals for trends. In general, the results for the entire interval paralleled the pattern of differences found with respect to the heterogeneous zones. That is, at some harmonics con- tinuous trends of mode shifts could be observed, whereas in others variation was erratic and discontinuous. As with the previous analysis, the change in shape-frequency distribu- tions of harmonic six in the 11,000 foot interval was most clear (Figure 7a). 31 Figure 7a. Mode positions for harmonic six as determined by ISODATA from shape-frequency distributions in the 11,000 foot Pliocene interval. 32 -. «5 as r- a: :: E? 53 E: :3 UHBWHN 31dWVS HARMONIC AMPLITUDE Figure 7a 33 Figure 7b. Mode shifts in harmonic six for lower half of 11,000 foot Pliocene interval as revealed by ISODATA analysis. Interpretation of mode shifts as illustrated in Figure 6a shown for samples one through four. 34 s1 1: °< N C O .g. s . s s 9.0.. 7.5.; O Q 0 O C O O . C C C C O C . C -.-1\&/, . . O O IIIIIIIIIIIIIIIIIII UJSWDN 31dWVS HARMONIC AMPLITUDE Figure 7b 35 Figure 7c. Final interpretation of mode shifting among all nineteen shape—frequency distributions in the 11,000 foot Pliocene interval for harmonic six. 36 m0:......¢2< 0.2021(7- .\ 5 oh ousmwm a. 2 m. m. ”MFG STdWVS HSSWHN RC 9? "l t.‘ (f (1’ ti" (7| 37 Variation of Harmonic Six Inspection of mode positions within the nineteen shape- frequency distributions of harmonic six suggests that more or less continuous trends of mode shifts occur in samples taken from the lower half of the interval (eleven through nine- teen, Figure 7a). The strongest and most continuous trend is that of the mode near harmonic amplitude 1.0 (Figure 7b). Trends of adjacent modes roughly follow the same pattern. The upper half of the 11,000 foot interval is not as clearly defined. The uppermost 1,400 feet comprise "hetero- geneous zone A" and, as discussed above, reflect the pro- gressive addition of a "rough" pOpulation of grains. The interval between the base of zone A at 6,176 feet and the top of the lower half of the interval at 10,172 feet does not display clear progressive shifts in mode position. However, in this interval there is a consistent shift of the total shape-frequency distribution and component modes. Mode positions reflect either "random" variations (for example, the first three or four modes on the right tail of the frequency distributions) or a "zig-zag" pattern (for example, mode positions A, B, C, and D, Figure 7c). An argument that the variation is real can be based on the similarity of response from mode to mode and the consis- tently alternating mode position about a central axis-- especially for positions A, B, C, and D (Figure 7c). Inspection of ISODATA analysis of the nineteen shape- frequency distributions, with reSpect to harmonic six, in ff ('9 5.: A__‘ 38 the 11,000 foot interval suggests that a cyclic addition and deletion of a suprpulation of characteristically shaped quartz grains occurred in a more or less continuous fashion with time from samples nineteen through ten (Figure 7c). Conversely, samples five through nine exhibit rapid, alter- nating mode shifts suggesting the subpopulation of charac- teristically shaped quartz grains are alternately present or absent with time rather than continuously varying in pro- portion from sample to sample. The remaining samples, one through four, exhibit seemingly random mode shifting and a statistically significant increase of modes in the right tail as discussed in the previous section. Inspection of the mode positions of the sixth harmonic on the tails of the shape-frequency distributions in the 11,000 foot interval reveals a distinctive difference between samples of the upper half and lower half of the interval (Figure 8). Variation of mode positions in the left tail of samples ten through nineteen (excepting sample fifteen) occurs always at harmonic amplitudes greater than .21, whereas, mode positions in the left tail of samples one through nine (excepting samples five and six) occur always at harmonic amplitudes less than .21. Mode positions in the right tail of the shape-frequency distributions parallel the trend of the left tail (Figure 8). The argument for a fundamental difference between the upper and lower halves of the interval, as suggested by analysis of the tails of shape-frequency distributions in 39 Figure 8. Mode positions in left and right tails of the nineteen shape—frequency distributions of harmonic six in the 11,000 foot Pliocene interval. 40 . Left Tail Right Tail l; :2 <’ __ 5 332 -9 ? s 2 .21 2.3 NUMBER SAMPLE HARMONIC AMPLITUDE Figure 8 harmoni average of the A: iistrii nartz interv ofa“ eQuiv elgh ‘1. 50t- fth 41 harmonic six, is supported by earlier comparisons of the average harmonic amplitude spectra for the respective halves of the interval (Figure 5). Analysis of mode positions in tails of shape-frequency distributions in harmonic six suggest that deposition of quartz sands and silts in the upper half of the 11,000 foot interval differed from sediments in the lower half by loss of a "rough" subpopulation of quartz grains and marked addi- tion of a "smooth" subpopulation. Such large scale varia- tions as those that exist between lower and upper halves of the interval may reflect major changes in provenance. Smaller scaled variations in mode positions within these intervals possibly reflect changes in quartz grain shape caused by changes in environmental processes. SMALL-SCALE SHAPE CORRELATION OF A SANDY DEPOSITIONAL UNIT BETWEEN WELLS B-2 AND D-l BY HARMONIC AMPLITUDE SPECTRA To test the feasibility of correlating lithologically equivalent sands on the basis of Fourier defined shape, an eighty-five foot sandy depositional unit, "Y," present in both wells B-2 and D-l, at depths of 10,114 feet and 9,800 feet, respectively, were sampled and analyzed (Figure 9). Five samples of one hundred quartz grains each were collected from sand unit Y in each well. All major correla- tive sand stringers between the two wells were sampled in both. The five samples in each well were then combined, rnaking two samples of five hundred grains each. The mean 42 Figure 9. Characteristic Spontaneous Potential curve of sandy depositional units "Y" and "Z" in wells B-2 and D-1 and sample locations. 43 .C can up Sites Sampm .: van...- #- an «In :03 .: o2...- Dz oz oz) c. «Q S .- I»). 44 harmonic amplitude spectrum for the first twenty harmonics of sand unit Y was calculated for each well (Figure 10). The two mean harmonic amplitude spectra were then compared to the mean harmonic amplitude spectrum of another sandy depositional unit, "Z," in well B-2 at a depth of 13,125 feet. Five samples of one hundred quartz grains each were randomly selected from a suite of ten samples available for that sand. The five samples were combined into one sample of five hundred grains, and its mean harmonic ampli- tude spectrum was compared to the two of sand unit Y (Figure 10). Inspection of the three mean harmonic amplitude Spectra (Figure 10) clearly indicates strong similarity between the two samples of interval Y and distinct differences between both Y samples and sample Z for the higher numbered har- monics, especially ten through twenty. The constant separa- tion and increasing divergence of the harmonic amplitude spectra of the two sand units throughout the higher numbered harmonics suggest that significant shape differences between sand units Y and 2 lie in the finer surface texture of the quartz grains sampled. CONCLUSIONS The 11,000 foot Pliocene interval was successfully zoned using Fourier shape analysis. Zonation could be accomplished by any one of ten harmonics, of which several expressed similar results. The zonation may have been caused by a variable suprpulation of approximately twenty 45 Figure 10. Mean harmonic amplitude spectra for sand unit "Y"-—well B—2, sand unit "Y"—-well D—1, and sand unit "Z”-— well B-2. 46 cu @— _ _ _ .I’ I OI IO! .0. 0.. .... or m m m S a 2 v— «F - . _ - _ O s\\ I \\s/ \s 6% (s I \ \0 «VI 0 4: 9 \\0 Au 9...... so 0; so . so... \9” .. e . coo... .e\ O _ 2 O E m < I a o _ _ _ _ _ s N 9- 0.11000 \ I\\G V4 ”4‘ \s I. so... 00. o- «Haven 13. V W 18.. d 1 I. n 12.- a :- lcué 47 per cent or fewer characteristically shaped quartz grains. Understanding the cause of zonation was easier with respect to harmonic six than others because it involved the addition of a subp0pulation outside the range of the main shape- frequency distribution. Differences between sands stratigraphically separated were so extreme that correlation between wells could be achieved by simple graphic inspection of their mean harmonic amplitude spectra. The results demonstrate that the shape of quartz grains in the coarse fraction varied significantly with time in the Pliocene interval in West Delta Block 117. Whether due to environmental factors (e.g., fluvial versus beach) or prove- nance (e.g., uplift of the Rockies), they probably represent a localized contribution to the regional system of sediment dispersal. In such a region where growth faulting or other factors render lithologic correlations difficult or meaning- less, the dispersal of these characteristically shaped grains allows establishment of a stratigraphic framework. To the extent that introduction of characteristic shapes is limited in time, the shape zones may actually have some chronostratigraphic significance. Although the technique used in this study for genera- tion, digitation, and Fourier analysis of grain shape involved considerable time, electronics and software exist for automating analysis of this kind. Therefore, it is feasible for such analysis to be performed automatically at 48 drilling sites. Because of the very small sample sizes needed, this technique could also be used for monitoring grain shape from mud samples during drilling. LIST OF REFERENCES '1—"—_— —_"“, ‘ 5;. LIST OF REFERENCES Anstey, R. L., and Delmet, D. A., 1972, Genetic meaning of zooecial chamber shapes in fossil bryozoans: Fourier analysis: Science, v. 177, p. 1000-1002. Ball, G. H., and Hall, D. J., 1965, ISODATA, A novel tech- nique for data analysis and pattern classification. Technical Report, Menlo Park, California: Stanford Research Institute, May 1965. , , 1967, A clustering technique for sum- mariZing multivariate data: Behavioral Science, V. 12' I10. 2' p. 153-155. Ehrlich, R., and Weinberg, B., 1970, An exact method for characterization of grain shape: Jour. Sedimentary Petrology, v. 40, no. 1, p. 205-212. , Vogel, T. A., Weinberg, B., Kamilli, D. C., Byerly, G., and Richter, H., 1972, Textural varia- tion in petrogenetic analyses: Geol. Soc. America Bull., v. 83, p. 665-676. , Orzeck, J., and Weinberg, B., 1973, Detrital quartz as a natural tracer--Fourier grain shape: Jour. Sedimentary Petrology, in press. Gabriel, K. R., 1966, Simultaneous test procedures for multiple comparisons on categorical data: Jour. American Statistical Association, v. 61, p. 1081- 1096. Kaesler, R. L., and Waters, J. A., 1972, Fourier analysis of the ostracode margin: Geol. Soc. America Bull., V. 83' p. 1169-1178. Kennedy, J. W., 1972, Shape response of Pleistocene and Recent sediment--Chukchi Sea: A Fourier analysis (M.S. thesis): East Lansing, Michigan, Michigan State University. Kimball, A. W., 1954, Short-cut formulas for the exact partition of in contingency tables: Biometrics, V. X, p. 452-458. 49 50 Waltz, S. R., 1972, Evaluation of shape of quartz silt grains as provenance indicators in central Michigan (M.S. thesis): East Lansing, Michigan, Michigan State University. Younker, J. K., 1971, Evaluation of the utility of two dimensional Fourier shape analysis for the study or ostracode carapaces (M.S. thesis): East Lansing, Michigan, Michigan State University. APPENDICES APPENDIX A Results of ISODATA Analysis of Nineteen Shape-Frequency Distributions for Ten Statistically Significant Harmonics fid 51 Figure 11. Positions and membership of modes of nineteen shape-frequency distributions stratigraphically arranged in the 11,000 foot interval for harmonic six as determined by ISODATA. 52 1- 00111001. < 2- -s".'|ss 3- 0 s'|'.'0 4- g 0"...ss N 5- 0"... ss s 6- "I'... s K7. 0"...ss s I“ :8- 0...... s :9. ..".'.C. 210. II III .. . "- "..ssss s “‘12- '.|'.. O Q :13- ..'.. 0 ss 214- .‘U'...ss <1 0515- ss"'.s' s 16- .‘.." sss 17- s'.|'.. ss 18- s...'s. s I9. "'.'..ss I 1 1 1 1 1 1 I I .0 .4 .8 1.2 1.6 2.0 2.4 2.8 3.2 HARMONIC AMPLITUDE (6) F igure 11 53 Figure 12. Positions and membership of modes of nineteen shape-frequency distributions stratigraphically arranged in the 11,000 foot interval for harmonic seven as determined by ISODATA. 54 A L. I IIIIss.. 3- a, IIIIIII .. 4- S IIIIII... 5- N .IsIIIII . 6- IIIIIs.. . m L. as IIII I . g8. IIIIsI.. :9. IIII I... . z 10- IIIuI .0. ll- 08."...s “.12.. IIIIIII.. :41. IIII Is... . EEIL. .II II . .1. «Ms- .11'1.1.1. m- .oIIIII.. . 17. sIIIIsss . 18- IIIII 0.. w. sIIIII I .. 1 1 1 1 1 1 1 1 1 .o .4 .s 1.2 1.5 2.0 2.4 2.8 3.2 HARMONIC AMPLITUDE (7) F igure 12 55 Figure 13. Positions and membership of modes of nineteen shape-frequency distributions stratigraphically arranged in the 11,000 foot interval for harmonic eight as determined by ISODATA. 56 . 2.. .'.'.0 s s 3.. 0"... 0 s s 4- s.'II'sss 5- .‘I'.ssss 6- '."..O m7—‘ s"l.. ss s III-I g8- 0"...sss D9. '0'...‘ ss 2 IO- 00"8's8s 11. U '8'0000 s “‘12- a, .IIII I 1.. _.1 l: I Q13- '3 .' .COOss 2I4. s...|'0ss < mIS— s..'..0 ss 16- .."...C 0 I7- .."'.. ss 18- 0"... ss s 19- sIIIsH.I . 0 14 812162024 2832 HARMONIC AMPLITUDE (8) F isure 13 57 Figure 14. Positions and membership of modes of nineteen Shape-frequency distributions stratigraphically arranged in the 11,000 foot interval for harmonic nine as determined by I SODATA . 58 1- II IIsstl. . A 2.. ""O. s s 3- O) '..I..s.s N 5- .' ' ' sss 6- I'IIIsIss 17— .|'|..... I.” ma. ."..Isss 2 II a m. s I 1.... Z "- 'I'... 0. “IL. I IIllss o... :13.- .. 'IIOIOs 2M- "".si s < 056. I III II . . 16- 0"I'ssss I7. ..'." O O 18- s....'. ss 19. s' IIIIsss I I I I I I I I I o A 312152o242333 HARMONIC AMPLITUDE (9) 1" isure 14 59 Figure 15. Positions and membership of modes of nineteen shape-frequency distributions stratigraphically arranged in the 11,000 foot interval for harmonic thirteen as determined by ISODATA. 60 A 2- sIIII s... 3- a, .IIIsIs .. 4.. E IIIIII. . 5- N sl'. 0. ..-. FL! 6- IIIIsss.. E7. sIIIIsss. ; g8- sI'IIIsss I :9. IIIIIIs.. .210-) IIIIIs... 11- sIIIIIII . “.12- sIIIIs. s :13.- sll'IIII s :14- IIIIII s .. €015- IIIIII .. lb— IIIIIss. 17. IIIIIIs .. Is- II '00. . . l9. 1|II... . I I .0 .'4 812162024 2832 HARMONIC AMPLITUDE (13) Figure 15 61 Figure 16. Positions and membership of modes of nineteen shape-frequency distributions stratigraphically arranged in the 11,000 foot interval for harmonic fourteen as determined by ISODATA. 62 I- "'0.ssss 2- IIIIII.. . 3- IIIIsos. 4- IIIII s 5- m IIIIIIss 5- IIIII.... 0:7- II'I OOss s I“ go. 2 III.11. :9- '3 IIIIII.. z..- 1111.... u- ..IIII Io . 11.1'2- sIIIII.. :13- sIIIIsss. :14- .IIIIss.. W15- sIIIIIss ‘6' .IIIIIII . l7. IIIII Is.. 18. sIIII s s s 19. IIIIIs.. s l I 1 1 1 1 1 I 1 .0 .4 .8 1.2 1.6 2.02.4 2.8 3.2 HARMONIC AMPLITUDE (14) Figure 16 63 Figure 17. Positions and membership of modes of nineteen shape-frequency distributions stratigraphically arranged in the 11,000 foot interval for harmonic fifteen as determined by ISODATA. 64 2- 100000.. 3- 000000 a. 4- 0000000. . 5- m 000000... FL 6- 0000000. 0 0:7. 000 0 o . . 5} III-0 :8- 2 0.000000. L» :9. '3 0000000.. 210. 00000.... H. 0.00000 0 o “.12- .000011.. :13- 0000000. . :14- 0000000. . “’15- 00000000 0 16- 00100.... 17- 100000.. 18. .00001 I. . 19. 000.0 0 o 30 .4 00008121620142.8302 HARMONIC AMPLITUDE (15) Figureu 65 Figure 18. Positions and membership of modes of nineteen shape-frequency distributions stratigraphically arranged in the 11,000 foot interval for harmonic sixteen as determined by ISODATA. 66 1. 00.0000 0 < 2- "0000 o o 3- Q0 ."'...' 4- g .".|. o. O . N 5- 0.0.0.... ”It 6... .0000 00 o 1 ‘1 127- ."...o o. “' I ma..- .. ... C O ,L- E :9. .00.... 0 Z 10.- 000000000 11- 100001. .. u.112- 0000111.. :13- 1100011 1. 204.. 0....I'Io < "’15- 10100101. 06- "| "O. C 07- .00000 0 o 18.. 0000011. I 19. 000000 . . 1111111 11 .0 .4 .8 1.2 1.6 2.0 2.4 2.8 3.2 HARMONIC AMPLITUDE (16) F‘igure18 67 Figure 19. Positions and membership of modes of nineteen shape-frequency distributions stratigraphically arranged in the 11,000 foot interval for harmonic seventeen as determined by ISODATA. NUMBER * ll... 12. '13.. I4. SAMPLE 15... lb... 17. 18... 19.. Figure 19 68 E00000011 : 1011001 . .2 10000.... I 10000011. .- 000001 .. . : 000001. 1 iii 00001101 1 0 0 0 0 0 0 0 0 . 0 .o .4 .8 1.2 1.6 2.02.4 2.8 3.2 HARMONIC AMPLITUDE (17) 69 Figure 20. Positions and membership of modes of nineteen shape-frequency distributions stratigraphically arranged in the 11,000 foot interval for harmonic twenty as determined by ISODATA. :lPBr 1- 2... 3- 4- 5- 6- 7.. 8- 9.. NUMBER 10.. 11... 12.. 13.. 14- SAMPLE 15.. 16.. 17. 18- 19.. Figure 20 1355.1?" '15" d1 0...... o C '3 0| 0...... 0.0.00... .0 .4 3100002162024 200832 HARMONIC AMPLITUDE (20) APPENDIX B Harmonic Amplitudes for Nineteen Samples of Approximately a Hundred Quartz Grains Each Used for Determining Zones of Heterogeneity and Homogeneity 71 Table 2. Harmonic amplitudes for harmonics one through twenty for nineteen samples arranged and labeled according to depth. Each sample contains approximately a hundred quartz grains. SAMPLE NUMBER (in feet) 82N4767 .40843'5. .056933 .002FO“. .310°551 13146440 .004575 10591”4 101504” .015461 .01025’. .000131 1013361 .009??? .015453 10394;, 101? 9'11 101-5.).-5) .811595 3124;? .00Q371 .0031’1 1005124. 10n137a 1902597 1035‘33 1004063 0003603 0005123 3005111, 00187:,59 .004614 . 81.41.": 0 O Cnbéffl'; 03101-9 0 3 3131‘ ‘1 03:90‘7 0 C 0311"" OUDIDCJGO )1 0 \1 (J 1 {A 1 '\1 331‘PQQQ UCJfl (3 4'1. I“ -J 1\. 1‘) 0’ ‘0 'ul IA 7.) _.\\0) " ‘21 .4; Cu- ‘ .. (ac-1.! Q‘L. t-QH‘W 1 \I 1‘ f). 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