Sediment or Sand Observation and Description
In today’s lab exercise we are going to be studying sediment. We will be looking at the make-up of sediment in terms of the types of particles or grains that are present, the size and size distribution of those grains, and then make some interpretations from our observations and descriptions. As an added plus you will be learning some fundamentals of statistics and further hone your skills in using EXCEL.
Sediment is made up of terrigenous detritus for the most part, plus dead bugs, plants, worms, sea shells if marine, and do not forget the pore spaces. Sometimes there may also be a small amount of orthochemical deposits such as a little calcite cement. Terrigenous detritus is the debris of weathered rocks. The type of terrigeneous detritus (lets call it TD to keep it simple) found in sediment is dependent upon the types of rocks in the source area of the sediment. If the sediment is down stream from weathering granite then certainly expect to see detrital quartz grains in the sediment. If on the other hand your sediment is sunning itself on the beaches of Hawaii do not expect to see any quartz, (why not?). Most geology students when they think of sand or sediment they immediately think quartz grains. This is a good guess but not a sure bet. Quartz grains in most cases are the dominant grain type in a sediment but there will also be rock fragments. These are chunks of rock and yes technically a detrital quartz grain is a chunk of rock but for descriptive purposes we keep it separate. Sometimes we can recognize what type of rock those rock fragments are from. We can expect to encounter sedimentary rock fragments (SRF), metamorphic rock fragments (MRF), and igneous rock fragments (IRF). Sometimes we can even recognize that the SRF is a chert rock fragment, or a shale rock fragment, or a limestone rock fragment. The MRF could be a slate rock fragment, or a schist rock fragment, or if it is particularly nice it may be a gneiss rock fragment. Igneous rock fragments present a problem in that the intrusive igneous rocks generally have crystal sizes that are bigger than the usual size of most grains in sediment therefore we rarely have granite rock fragments or gabbro rock fragments. What we get are feldspar grains and quartz. Generally if we have an IRF it will be a chunk of an extrusive igneous rock also know as a volcanic rock fragment (VRF). Mineral grains of mica show up frequently. A special group of mineral grains are called the heavy minerals. These are all minerals with densities greater than quartz and feldspar hence the name heavy. They include magnetite, zircon, rutile, and do not forget gold. All the grains together provide us with excellent material from which to make an interpretation of the source area, provenance, of the sediment.
But before we make any interpretations we must gather the data or in this case observe and describe the sample. Hand lenses are great for this. Look at the sample with a hand lens or if you have one at hand a dissecting microscope. Make a list of what you see grain wise. Be honest, if you think it is a rock fragment but you haven’t a clue as to what flavor then call it a rock fragment. If you recognize it as a sedimentary rock fragment but can not say of what type it is then call it a SRF. If you think it is a chert rock fragment call it that in your notes. Take its identification to the furthest point you can and no further. In your life time you will encounter a whole lot of rock fragments and you will see along the way a few limestone rock fragments, and if you work on the Lilesville Gravels you may come across a Tillery Argillite rock fragment.
It is useful not only just to list what type of grains that you see put also to put a relative value on their abundance in the sample. A simple way of doing this is just to make your list run from the most abundant to the least abundant. You also could have estimated the percentage of the total population that that grain type represents. This takes some practice but is not to tuff. There are a number of published pictures of " percentage estimation charts." out there. The best that I know of is a set of charts published by the American Association of Petroleum Geologists. The trick to doing this is first get the sample so everything is spread out in even fashion. Then when you are looking at the sample with either your hand lens in the field or a binocular microscope you must play a mental game and pretend you see only two types of material (1) the thing who’s percentage of the total sample your are trying to estimate and (2) everything else. Think black and white with no grays. Stare at the sample then stare at the chart, stare at the sample then stare at the chart, until you are comfortable with your estimate. Then go on to the next grain type and repeat. When you are finished your estimates of percentages should add up to 100% ±25%. Note you have a whole lot of room for slop here [+/-25%]. When you get real good at this you will end up at ±5%.
Something that all geologists must learn to do is estimate the grain or crystal size of a particular sample. This is a skill you must develop. The best way I know to develop such a skill is by comparing know samples to unknown. Eventually you will get to the point that you will no longer need the comparison aid, what ever it is. These gizmos can be purchased from various geology supply houses or you can make one your self. [The plastic cards with ink dots on them do not do well for this.] To make your own simple comparator you could sieve out the proper size ranges and then put the splits into small vials, or glue them on a card.
A sediment sample represents a population of sediment grains. If one is interested the various sizes of these grains one could measure individually the three principle axes of each and every grain (enjoy, see ya in a few years) or one could take a representative sample of the sediment ( a subset of the grains) and run them through a set of sieves to break the sample subset in to size classes and using statistics reconstruct what the population’s size characteristic are (much easier and quicker). Statistics are a way we use to describe populations of things, like test scores and sizes of grains.
Useful definitions from the AGI Glossary, 6th ed., 1980
mean: an arithmetic average of a series of values.
median: the value of the middle item in a set of data arranged in rank order. If the set of data has an even number of items, the median is the arithmetic mean of the middle two ranked items.
mode: the value or group of values that occurs with the greatest frequency in a set of data; the most typical observations.
standard deviation: the square root of the average of the squares of deviations about the mean of a set of data.
skewness: the quality, state, or condition of being distorted or lacking symmetry.
kurtosis: the quality, state, of condition of peakedness or flatness of the graphic representation of a statistical distribution.
The following is a procedure that you could use to evaluate grain sizes of a sediment using sieves, we call it sieve analysis:
(1) Take approximately a 100 gram split of a sample. Examine it briefly with your hand lens or the microscope and make appropriate notes about its character. This would includes what you perceive the size of the average grain to be (remember the sand box when you were a little boy or girl, that stuff was medium grained, if sized grains dominate then coarse grained and if smaller then fine grained). How well sorted is the sample (all or most grains are the same size then well sorted, some range in grain size then sorted, and if there is quite a bit of variation in grain size then poorly sorted). Are the grains for the most part angular, sub-angular to sub-rounded, rounded, or well rounded? What is the sphericity of the grains; compact or spherical, bladed, elongate? What types of grains are present; quartz, feldspar, rock fragments, mica? Next pick through the sample and remove all large chunks of vegetation and bugs.
(2) Weigh the sample on the balance and record the mass of the sample.
(3) Take a set of sieves and make sure that they are stacked such that the screen with the smallest opening is at the base and the largest is at the top. Note that the screens have different numbers on them. These are referring to different types of size scales. The most common are the US Standard Sieve Mesh #, opening in millimeters (micrometers), opening in inches, and Phi Scale; see table below. Place the pan at the very base of the stack. Dump your sample onto the top screen and put the cover on the top screen.
(4) With a circular motion shake the screen and occasionally rap gently it on the bench top. Do this for a 5 minutes, no more and no less.
(5) Gently pry off the top cover of the screen set. You may need to use a dime to aid in this. In the same manor remove the first screen from the stack; being very careful not to launch any grains off across the lab (don’t force it be gentle). Lay a clean sheet of paper that is larger than the area of the screen on the bench top. Turn the screen over and dump its contents on the paper. Transfer the sand on the paper to the weighing paper or pan. Then take the screen and turn it over and rap its rim once on the surface of the paper. Transfer the grains to the weighing pan. Rap it again but a little harder this time and then dump the grains. Then slam the sieve down on the paper such that the entire rim contacts the paper at once; dump the grains onto the weighing pan and set the screen aside. DO NOT ATTEMPT TO POKE LOOSE THE GRAINS THAT REMAIN ON THE SIEVE; NEVER TOUCH THE WIRES OF THE SIEVE WITH ANYTHING. You will probably leave behind some grains, big deal, you also will probably gain a few grains from the previous user of the screen. This contributes to measurement error and everyone understands that.
(6) Weigh out what you have dumped from the sieve and record the results on a sieve analysis form. Set aside the sample split (what you just weighed) for future observations. See the end of this for an example of how one might set up a data sheet for doing this.
(7) Repeat (5) and (6) for each screen and the pan.
(8) Add up all the weights from each screen and the pan. Does it compare to you initial sample weight? Take the difference between the two and divide by the total weight of the size fractions. This is you measurement error. What are the sources of this error?
(9) Construct a histogram of your results. I know that you all know how to make a histogram, but I want you to think about what you are doing before you construct this. The columns of the histogram will have a width proportional to the size range of grains (expressed using the phi scale) for each sample split. For example if you used a -1,-2, and -3 phi screens then the sample which was on the -2 screen represents all the grains which were greater in diameter than -2 but less in diameter than -3. Your histogram must reflect this and if you were using odd steps in sieve size then the widths of the various columns will vary. The height of the column will be proportional to the percent retained on the respective screen and therefore it will be in units of percent, not units of mass or weight.
The tallest column indicates the mode of the grain size distribution. What is the mode of this sample? The correct answer is not the size of the corresponding sieve but the range from that sieve to the phi of the next larger sieve (the one above it in the stack).
(10) Construct a plot of grain size (x-axis) versus cumulative percent (y-axis). The Scale of the x-axis will be in phi values (not meters) and the spacing between a phi of 1 and 2 will be the same as that between 2 and 3. The y-axis will have a scale of percent (0 to 100%) using a linear scale (uniform spacing). Plot each data point from your form on the graph. Since we are working with cumulative percent we can plot as a point the corresponding sieve size phi value. Next draw a smooth line through each point using a French Curve if you have one, otherwise eyeball it. This is not a scatter plot so do not draw a line through the field of points. This plot will be know as a cumulative curve with an arithmetic ordinate.
(11) Construct a similar plot of grain size versus cumulative percent using the probability paper. Do it the same as in (9) except the cumulative percent axis is already set up for you. Note that there are two similar scales at the top and bottom of the paper, start by using the one that has the lowest value to the left. Your grain size scale expressed in phi units will run up the side of the paper with the lowest phi value (or largest grain size) plotting somewhere in the lower left of the graph. If your data has a ‘normal’ distribution (bell shaped curve) then this plot will turn out to be a straight line running from the lower left to the upper right. This plot is known as a cumulative curve with a probability ordinate.
(12) Using either of the cumulative curves determine the phi size for each of the following phi values: (phi at 5%, phi at 16% etc. where the % refers to the cumulative percent).
The phi value at 50% is the Median of the sample or grain population. Half the population of grains (mass wise) was smaller than this and half was larger).
(13) Use the above values to calculate the other various statistics listed below with their equations. Set these up in EXCEL.
Graphic Mean
Inclusive Graphic Standard Deviation
Inclusive Graphic Skewness
Kurtosis
Notes:
The phi value is the negative logarithm to the base 2 of the particle diameter
Grain Size: (from graphic mean)
Sorting: (from inclusive graphic standard deviation)
Sorting skewness: (from inclusive graphic skewness)
Sorting kurtosis: (from graphic kurtosis)
| US Standard Sieve Mesh | Opening in millimeters | Phi Scale |
| 4096 | -12 | |
| 1024 | -10 | |
| 256 | -8 | |
| 64 | -6 | |
| 16 | -4 | |
| 5 | 4 | -2 |
| 10 | 2.00 | -1.0 |
| 18 | 1.00 | 0.0 |
| 35 | 0.50 | 1.0 |
| 60 | 0.25 | 2.0 |
| 120 | 0.125 | 3.0 |
| 230 | 0.0625 | 4.0 |
| 325 | 0.044 | 4.5 |
| 0.031 | 5.0 | |
| 0.0039 | 8.0 | |
| 0.00006 | 14.0 |
Sediment maturity is a measure of distance/time from the source area to the depositional site. A lot of factors play in here, especially the climatic condition of weathering and transport and the mineralogical make up of the source area rock. As a general rule the greater the transport distance and the greater the length of time in the transport medium the more mature a resultant sediment becomes. Maturity can be gauged in terms of texture (textural maturity), mineralogy (minerologic maturity), and composition (compositional maturity). The terminology we use to describe maturity is relatively simple: immature, submature, mature, and supermature.
Textural maturity is gauged largely in terms of grain size, grain sorting, and grain roundness. At a source site the weathering process tends to generate a wide range of grain sizes but generally big chunks. And these tend to have a rough or angular exterior. The maturation process makes big things smaller up to a point that is. Grains of medium sand size tend to resist further size reduction. The maturation process also knocks of the ruff edges reducing the grain exterior to a smooth or rounded surface. Therefore:
| Immature | Submature | Mature | Supermature | |
| Sorting | Extremely poorly sorted to very poorly sorted | poorly sorted to moderately sorted | moderately well sorted to well sorted | very well sorted |
| Grains Size | very coarse or bigger | coarse | medium | Medium |
| Roundness | Angular | subangular | rounded | well rounded |
You must keep in mind source area when you are making these subjective determinations. If the source area can only provide fine-grained material than a finely grained sediment could be submature.
Mineralogic maturity depends upon the relative deterioration of the various minerals present in the transport environment. As a general rule those minerals that are further from their pressure and temperature of formation are first to go; olivine goes quickly relative to quartz. But remember from Physical Geology that grain surface area also plays into this as well as structural integrity of the crystal lattice. A stressed lattice will be subjected to faster chemical action than a near perfect lattice of the same mineral. We can gauge mineralogic maturity by rations of stable to unstable minerals like the ratio of quartz to feldspar or the ratio of quartz + chert to feldspar + rock fragments. Immature sediments will have low ratios maybe even approaching 1 or even less than 1 whereas mature sediments will have high ratios, much greater that 1. This all assumes that the source area is a granite, which most generally are unless you are on Hawaii. In the case of a Hawaiian type source area this ratio would make little sense. There you may want to think in terms of a ratio of feldspar to olivine.
Compositional maturity is basically a reflection of mineralogical maturity only expressed in ratios of oxides not minerals. Think in terms of high SiO2 values relative to most other oxides. The term "high" here is a relative term, likewise the implied term "low". Think of the SiO2 to other oxide ratios as found in granite as being low ratios and therefore indicative of immature sediments whereas sediment with a ration approaching infinity as being supermature.
Useful terms: (from the AGI Glossary)
Maturity: The extent to which a clastic sediment texturally and compositionally approaches the ultimate end product to which it is driven by the formative processes that operate upon it.
Textural Maturity: It is defined in terms of uniformity of particle size and perfection of rounding and depends upon the stability of the depositional site and the input of modifying wave and current energy; it is independent of mineral content.
Mineralogic Maturity: A type of sedimentary maturity in which a sand approaches the textural end product to which is driven by the formative processes that operate upon it.
The ultimate sand is a concentration of pure quartz, and the mineralogic maturity of sandstone is commonly expressed by the quartz/feldspar ratio; this ratio is not so appropriate for sand derived from feldspar poor rocks and the ratio of quartz + chert/feldspar + rock fragments may be substituted as more generally applicable.
Compositional Maturity: A type of sedimentary maturity in which a sand approaches the textural end product to which it is driven by the formative processes that operate upon it.
It may be expressed as a ratio between chemical compounds (e.g. alumina/soda) or between mineral components (e.g. quartz/feldspar)
Additional Literature
Folk, Robert 1980. Petrology of Sedimentary Rocks. Hemphill Publishing Co. Austin, Texas. (Great book, if you ever get a chance to get one grab it!!!!). (I have placed the 1974 edition of this book on reserve for you in the Randall Library) Online Web Link: http://www.lib.utexas.edu/geo/FolkReady/entirefolkpdf.pdf
Pettijohn, Potter, & Siever; 1973; Sand and Sandstone, p. 68-85.
Wentworth, Chester K. 1920. Methods of mechanical analysis of sediments. University of Iowa Studies in Natural History, Vol. XI, No. 11, 52 p. Wentworth.pdf (3.5 mb)
Wentworth, C.K., 1922; A scale of grade and class terms for clastic sediments. Journal of Geology, Vol. XXX, p. 377-392.
Viard, J.P. and Breyer, J.A., 1979; Description and hydraulic interpretation of grain size cumulative curves from the Platt River System. Sedimentology, vol. 26, p. 427-439.
Exercise #1: You have been provided with a modest collection of the various grain types that are found in sands. Using the binocular microscopes or your hand lens (or both) examine this collection so that you can later recognize these grains in other sand samples. Spend at least 30 minutes on this before you go further in this lab exercise. You may wish to take notes for future reference but I will not ask for you to turn these in.
The remainder of this laboratory exercise is centered on seven sediment samples as documented below with some sieving data which is found in EXCEL file: grainsize.xls which you should right click on and down load to a disk. You should also download a copy of the sieve analysis form and probability paper and print hard copies of them before you come to lab.
Exercise #2: For each of the seven samples make an estimate of the grains size and sorting. Use only your hand lens for this, do not use the microscopes and do not use any sort of comparison devise. Record your results in your notes and eventually in your EXCEL file.
Exercise #3: Take one of the prepared size comparison devises or one of your own inventions and determine the size of each of the seven samples. Record this data in your notes.
Exercise #4: Examine each of the seven samples. In so doing make a list of the various grain types present. For each grain type estimate its relative percentage of the sample as a whole. Then, after making estimates for all the grain types present, describe each grain type in terms of size, sphericity, roundness, etceteras [it is your call what the etceteras are but if you think it might be important make note of it.]
Exercise #5: For each of the five samples grainsize.xls with sieving data determine all the various statistics which were discussed above. Use EXCEL to do all your mathematics and tabulate your data. Then translate these statistics into a verbal description of the sample in terms of size, sorting, skewness, and kurtosis. Record this in your notes. It is possible to do the graphic plots in EXCEL however the probability plot will be beyond your abilities for now but the other two types of plots you should do. I would suggest using separate pages in EXCEL for each of the five samples. Make it look real professional. Use text labels to identify items and make sure you use scientific formatting when appropriate. (Phi scale and Percent should not be expressed in scientific format. Phi values likewise are never expressed in scientific notation under any situation.) Steps 1 through 13 above explain the entire procedure for obtaining these values. Reading through Wentworth.pdf will also shed some light on this he does a particularly nice job of explaining the set up for the histograms.
You are to email to me your EXCEL file. You must make it look professional. It will contain your results from exercises 2 through 5 above. Be creative but professional on how you make your report appear. Remember to use the proper file naming protocol. Remember to use proper engineering nomenclature where appropriate.