|Perfect Number of Pages to Order||5-10 Pages|
EES 2021 is a project that will take place in the year
GRANULOMTERY LABORATORY NO. 2
The most basic physical feature of sediment is grain size. Geologists and sedimentologists analyze patterns in surface processes related to the dynamic circumstances of movement and deposition using the information on sediment grain size. A grain-size analysis’s goals are to precisely measure individual particle sizes, estimate their frequency distribution, and compute a statistical description that sufficiently defines the sample.
Particle-size analysis procedures and equipment must be quick, accurate, and produce highly repeatable results. Sampling methodology, storage conditions, analysis methods, equipment, and, most importantly, the operator’s capability all restrict the accuracy of these measurements. To produce the finest potential results, extreme caution and attention to detail are required. There is no single approach or procedure that will produce the most ideal grain size data in all instances, as there is with most sorts of sedimentological analyses. Over time, several types of analyses have been developed to accommodate various types and sizes of samples as well as the motivations for conducting the study. A settling tube, sieves, and a Camsizer, a device that measures grains using two cameras, are among these ways.
You will examine data from the optoelectronic Camsizer analyzer in this lab (you can see it when you visit our lab).
Grain Size Distributions (Part 1)
Use the Excel spreadsheet that comes with this lab.
Using a correct equation (taught in class), convert micrometers to phi units such that all values are compiled in yellow-highlighted boxes in column C of your spreadsheet.
To calculate the numbers in the yellow boxes, insert equations for each size statistic (see Table 1 in this handout) (Line 7; columns E through I in your spreadsheet)
– Kurtosis, Kurtosis, Kurtosis, Kurtosis, Kurtosis, Kurtosis, Kurtosis, Kurtosis, Kurtosis, Kurto
SEDIMENT STATISTICS (TABLE 1) (Folk, 1968)
Note that 50 refers to the phi size that corresponds to 50% of the cumulative frequency, and so on for different phi sizes and cumulative frequency percentages.
While raw particle size data can tell you a lot about a sediment sample, sedimentologists have established a set of other criteria to help with sediment sample description, analysis, and comparison. Mean grain size, median, sorting, skewness, and kurtosis are some of these.
The standard formulae described in Folk’s (1968) Petrology of Sedimentary Rocks are used to calculate the grain size statistics of the sediment samples. Table 1 shows the equations for each of the sediment statistical measurements (be sure to use the phi size from column C rather than micrometers):
Mean Grain Size: A sample’s average grain size (in mm); values for the current data set typically range from:
Median Grain Size: the phi size that corresponds to 50% of the cumulative frequency; for this research, it was converted to mm.
Sorting: also known as “Graphic Standard Deviation,” this is a measure of the degree of scatter – a sediment sample’s “uniformity” or “homogeneity.”
Skewness: a measure of symmetry that evaluates the preponderance of specific sediment fractions (i.e. a symmetrical distribution of frequencies of different particle sizes, would look like a normal bell curve; skewness is a distortion of this curve to left or right).
Kurtosis: a measure of a sample’s range of particle sizes that evaluates the % frequency distribution of particle sizes in terms of a particular type of deviation from the normal distribution.
Part 2: Analyzing the Data
1. Make a graph of FREQUENCY DISTRIBUTION (see the solid line in Fig. 1B below). Column A should be used for the X-axis, and column C or D should be used for the Y-axis.
Figure 1: Typical graphic representations of grain-size data. A) Table of grain sizes. B) From the data in A, a histogram and a frequency curve were plotted. C) Arithmetic ordinate scale with a cumulative curve. D) A probability ordinate scale for a cumulative cure.
2. For each size statistic derived in Part 1 (from row 7) right below each number, provide a description (e.g., fine sand, poorly sorted, negatively skewed, leptokurtic) (in row 8). Use the following descriptions and grain-size chart from Figure 2:
Figure 2: Sorting, skewness, and kurtosis terminology. In your sample descriptions, you should utilize this terminology.
3rd Part: Interpretation
Interpret the depositional habitat of your sample (point bar, dune, floodplain, beach, reef, deep sea, etc.) based on your description in Part 2. (remember to use several statistics to give you the most accurate result). Sphericity (column E) may also be beneficial.
GRAPH AS A SINGLE EXCEL SPREADSHEET (use your last name in naming the file).