Module II - Stereonet Fundamentals With Dips
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Transcript of Module II - Stereonet Fundamentals With Dips
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Module IIOrientation Data Analysis with Dips
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2 Orientation Data Analysis with Dips1. Stereonet fundamentals2. Introduction to Dips3. Processing data4. Clustering weighted poles5. Identifying characteristics of sets6. Querying data7. Tutorial
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Dilemma: How to plot a 3D vector (line) on a 2D plane
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Equal area (Schmidt) projection
Equal areas on the surface of the sphere map to equal areas on the plane of the projection.[BUT the shapes of the areas will be different]
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Equal angle (Wulff) projection (Yuri ViktorovichWulff 1863)
The image of a circle on the sphere is a circle in the plane.
[BUT the areas of the circles will be different]
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Equal‐angle
Equal‐area
Equal Area (Schmidt) Net Equal Angle (Wulff) Net
Constant areas anywhere on the sphere reproduce as a constant areas on the projection
Constant areas anywhere on the sphere reproduce differently on the projection
Distorts geometrical shapes and clusters of points unless they are centered at the origin.
Preserve geometrical shapes and clusters of points.
Preserves the density of clusters of points.
Does not preserve well the density of clusters of points.
Cone angle = 15°for all cones
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Equal‐angle
Equal‐area
Equal Area (Schmidt) Net
Equal Angle (Wulff) Net
Preserves the density of clusters of points.
Does not preserve well the density of clusters of points.
Does not preserve the shape of clusters of points unless they are centered at the origin.
Preserve well the shape of clusters of points.
Lack of areal distortion makes it ideal for interpreting and analysing plots of normals
Circular arcs of equal‐angle enables more precise geometrical constructions than those constructed on an equal area plot
Your choiceMy
choice
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By convention, a [one dimensional] line (e.g. borehole or scanline), defined by its orientation (trend/plunge), is plotted as a point.
300/26090/30
N
E
S
W
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By convention, a [two dimensional] surface (e.g. discontinuity), defined by the orientation (dip direction/dip angle) of the line of maximum dip, is plotted as a “Great Circle”.
300/26
090/30
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Problem: Plotting many great circles on a projection can create a “mess”
3270 discontinuities
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Plot the line equivalent to the downward directed “normal” or “pole” to the discontinuity.
Solution:Recall that lines are plotted as points.
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Lines in a plane.
on
oown 3600180
wo
n 90
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300/26
090/30
w(1)/w(1) w(2)/w(2)
n(2)/n(2)
n(1)/n(1)
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Poles
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1. Stereonet fundamentals2. Introduction to Dips3. Processing data4. Clustering weighted poles5. Identifying characteristics of sets6. Querying data7. Tutorial
2 Orientation Data Analysis with Dips
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Overview of DipsWhat can you do with Dips?
•Data storage
•Process oriented core (borehole) data
•Stereonet plots (pole, contour, scatter, rosette)
•Determine sets and set statistics
•Query any subset of data
•Feature attribute analysis
•Kinematic analysis (Module 3)
•Export to Swedge / Unwedge for detailed analysis
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Data StorageData spreadsheet allows you to record Orientation, Quantity, Traverse, and any number of additional columns with user‐defined information. The number of rows is unlimited.
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Pole PlotA Pole Plot is the most basic representation of the orientation data
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Contour PlotThe Contour Plot is the primary tool for identifying concentrations of poles required to identify sets of discontinuities.
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Scatter PlotA Scatter Plot gives a quick visual estimate of pole density using symbols to indicate the number of poles at grid locations
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Rosette PlotA Rosette Plot is a radial histogram of dip direction frequency
Dip angle is not accounted for on a rosette plot
(Geologists like these plots)
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Symbolic Pole PlotsA Symbolic Pole Plot allows you to plot qualitative or quantitative data.
For example, identifying types of discontinuities (e.gjoints, faults, bedding).
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ChartsVarious charts can also be generated including histogram, line and pie
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2 Orientation Data Analysis with Dips1. Stereonet fundamentals2. Introduction to Dips3. Processing data4. Clustering weighted poles5. Identifying characteristics of sets6. Querying data7. Tutorial
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Project Settings
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Project Settings
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Scanline survey and borehole televiewer data
w/w
sl/sl
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Project Settings
Plunge/Trend of scanlinesl/sl
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Borehole orientated core logging data
Dips will convert these core b/b orientations to actual w/worientations.
b/b
hole/hole
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Orientation of borehole
Not required, leave at 0o
Project Settings
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Orientation 1 Angle from top of core to “ori” line.•0o for “top mark”•180o for “bottom mark” (usually applicable)
Orientation 2 Inclination of borehole from vertically up (0o)= Plunge (hole) + 90
o
Orientation 3 Trend of borehole (hole)
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Poles to discontinuities after processing scanlineor borehole data
“Spirals” often indicate low precision data e.g. goniometer 5o
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2 Orientation Data Analysis with Dips1. Stereonet fundamentals2. Introduction to Dips3. Processing data4. Clustering Weighted Poles5. Identifying characteristics of sets6. Querying data7. Tutorial
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Identifying sets (clusters) of discontinuities
Identifying “by eye” sets within tightly clustered polesis generally easy
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The brain has a high capacity to recognisepatterns where there are complex and overlapping clusters but..........
N=3200
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Identifying “by eye” sets within poorly clustered polesis less easy
N=2200
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Identifying clusters by eye is:
•entirely subjective and therefore susceptible to personal bias and inconsistency;
•prone to distraction by the perimeter of the projection which represents an arbitrary boundary to the pattern;
•inclined to make interpretations more detailed than the nature of the data warrants;
•more prone to call a cluster than to dismiss the data as being random;
•unable to account for orientation bias.
Identifying clusters by eye
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Use contouring and clustering algorithmsObjective and therefore not susceptible to personal bias and inconsistency;
Not distracted by the perimeter of the projection;
Able to account for orientation bias [→Terzaghi].
poles contoured & clustered poles
(schoolyard analogy)
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Terzaghi Correction
weighting = 1/sin Angle Weighting
0o ∞→15 (maximum)
45o 1.4
90o 1.0
A scanline or a borehole preferentially samples those discontinuities that are aligned most perpendicular to it
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Terzaghi Weighting
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Use contouring and clustering algorithms
polescontoured poles, no Terzaghi correction
contoured poles with Terzaghicorrection
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2 Orientation Data Analysis with Dips1. Stereonet fundamentals2. Introduction to dips3. Processing data4. Clustering weighted poles5. Identifying characteristics of sets6. Querying data7. Tutorial
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Identifying characteristics of sets•Number of sets
•Mean orientation of discontinuities assigned to each set
•Deviation of discontinuities about each mean orientation
•Proportion of random discontinuities
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mean orientation of discontinuity normalsassigned to Set 1
great circle representing a plane having the mean orientation of the discontinuities assigned to Set 1
“raw” pole data contoured poles
clustered poles
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note the different degree of clustering of the poles assigned to
each set
highly deviated data
less deviated data
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Fishers constant K•K provides a measure of the degree of clustering of data about the mean orientation.
•The Fisher distribution is symmetric and therefore only provides an approximation of asymmetric data. There are other distribution models that may provide better fits to asymmetric data.
•However, the Fisher distribution is simple and flexible and suitable for most purposes.
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Fishers constant K•As K → 0, the orienta on data get more dispersed about the mean orientation.
•As K → ∞, the orienta on data cluster more ghtly about the mean orientation. k ≈ 100 indicates data are nearly parallel.
•30 ≤ K ≤ 50 is typical for sites that have not been subjected to significant tectonic deformation (e.g. folding and faulting)
• K < 20 indicates that a site may have undergone significant deformation.
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Random Discontinuities (Isotropic component)Comprise discontinuities that are not assigned to any set.
A high proportion(Pr > 40%) of random discontinuities may be evidence that a site has undergone significant deformation.
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Fishers constant K
091 / 74
355 / 82
100 / 44
20.03270
63094910191Pr
31 ≤ F ≤ 43
Site may not have been significantly deformed
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2 Orientation Data Analysis with Dips1. Stereonet fundamentals2. Introduction to dips3. Processing data4. Clustering Weighted Poles5. Identifying sets6. Querying data7. Tutorial
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Query DataThe Query option allows data subsets to be created by querying one or more columns in the spreadsheet.
Useful for collecting data to enable for each set the mean spacings and persistences of the discontinuities to be estimated.
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Word of CautionA well interpreted projection is a necessary aid in slope stability analysis. HOWEVER it must be used in conjunction with:
• intelligent field observation, analysis and mapping of the geology at the site;
• a balanced assessment of all the available facts including:
• groundwater;
• discontinuity shear strength;
• variabilities in the characteristics of the rock mass.
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2 Orientation Data Analysis with Dips1. Stereonet fundamentals2. Introduction to dips3. Processing data4. Clustering Weighted Poles5. Identifying sets6. Querying data7. Tutorial
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Tutorial
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End Module