Digital Core Imaging Case Study

Applications of High Resolution Scanned Core Images for
Investigations in Facies and 3-D Structural Analyses
Rafat, G.; Peters, St.; Schlueter, R.
Digital core imaging is a new method of acquiring data from drill cores in addition to conventional (geological
and geotechnical) core logging and geophysical borehole logging. However, this method has also some
important advantages. High resolution scans may be seen as an ideal coupling and completion not only
documenting visible features in digital formats as they would have been described by the geologist but also
connecting and comparing these data with various geophysical data. Global online accessibility is also
provided. Using a comprehensive suite of software, additional evaluations can be carried out with regard e.g.
to lithofacies characterisation, paleotransport analysis and acquisition of geotechnical parameters. Core
images on different scales in the range of mm and smaller allow to describe the lithological and physical
properties of the rock. The use of core images has proven to be accurate, quick,
and, hence economical.
New methods of evaluating digital images (360° and slabbed images) allow to
produce calibration images for lithofacies recognition, 3-D structural analysis and
determination of geotechnical parameters. In many cases, the images analysed by
the software provided make it possible to determine qualitative and quantitative
data that otherwise cannot be achieved or only with less accuracy and certainty.
Various applications of the new method will be illustrated with the help of
respective case studies.
Figure 1: Digital Imaging
System: CoreScan® Colour
1. Varve chronology of the Messel maar (Hessen, Germany)
Varves are distinctly marked annual deposits of a sediment regardless of its origin. One of the world’s most
famous occurrences of varved sediments are the oil shales of the Messel pit. The shales contain vertebrate
fossils of Eocene age in abundance. In order to protect this unique site it has been declared a world’s natural
heritage by UNESCO.
Figure 3: Section through the Messel maar prior to and during
sedimentation of the shales and today will drilling location
Figure 2: German stamp
commemorating the Messel pit as
UNESCO‘s World Natural Heritage
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Figure 4: Listing of varve
structures in the Baruth maar
(Lausitz, Germany)
Figure 5: Profile with varve structures
and graphs with corresponding
parameters
M e s s e l: P r o b e
Figure 6: Example of grain size distribution
analysis
2 1 _ 7
1 6
1 4
Peakabstand
1 2
1 0
8
6
4
2
0
0
2 0
4 0
6 0
8 0
P e a k la g e
M e s s e l: P r o b e
2 1 _ 7
1 6
1 4
Peakabstand
1 2
1 0
8
6
4
2
0
1
2 1
4 1
6 1
P e a k -N r .
The shales of Messel are sediments deposited in sweet
water lakes filling volcanic craters, in Germany called ”Maar”.
Images of slabbed drillhole sections of the Messel formation have been recently scanned by DMT. These
images allow a comprehensive documentation and set up of a data base for the complete sequence of varved
structures. Based on a grey scale (8 Bit/Pixel) or colour picture (24 Bit/Pixel) image, a special filter tool allows
to evaluate thinly laminated structures like varves. This so-called Evaluate Filter function creates a listing of the
detected maxima. Each data set of a respective maximum contains the profile number, the position in x/y coordinates, the distance between two corresponding layers, and the thickness of the individual layer.
Another tool, the Show Dialog checkbox, displays an interactive preview of the detected maxima or minima.
The maxima can be viewed and edited in the dialog before they are added to the list of measurements. To add
or delete a maximum / minimum, simply click on the red dots in the maxima / minima listing. If the Show Dialog
is not activated the detected maxima / minima will be added to the listing directly.
2. Grain distribution analysis for the oil and mineral mining industry
Core images on different scales allow to describe lithological and physical properties. For the aim of
understanding depositional environments, the images are used for lithofacies characterisation and
paleotransport analysis by grain size distribution, grain shape, and particle statistics. Based on these data an
optimised reservoir analysis can be achieved.
A new program for Core Image Analysis (C.I.A) allows to analyse images of cores, slabbed cores and other
suitable samples, e.g. thin sections according to various parameters.
Figure 6 shows an example of grain size analysis. With the CoreScan®, a high resolution overview-scan
gives you an average grain size distribution in a very short time. Scanning with CoreScan® standard
resolution highlights the medium grain size. CoreScan® high resolution includes a larger number of of
measurable particles and more precise results. The program provides e.g. weighted histograms of different
grain sizes and sieve curves.
In the CIA programme, colours (green, red, or blue) can be attributed to certain ranges of the spectrum
representing certain components of the rock. Thus, the image can be analysed much easier highlighting
e.g. certain minerals that are of interest for mining.
73_5_Evaluation.XLS[Short]: 82 Particles
Histogram
73_5_Evaluation.XLS[Short]: 82 Particles
[%]
Sum-Curve
Particle Statistics: File: 73_5
100
[%]
51,59
90
45,85
80
40,12
70
34,39
60
28,66
50
22,93
40
17,20
30
11,46
20
5,73
10
[Num]
0
0
0,50
6,08
11,67
[%]
17,25
22,84
28,42
34,00
39,59
73_5_Evaluation.XLS[Short]: 82 Particles
Sieve Curve
45,17
50,76
10
-0,30
10
-0,10
10
0,11
0,32
0,52
0,73
0,93
1,14
1,34
1,55
10
10
10
10
10
10
10
73_5_Evaluation.XLS[Short]: 82 Particles
[mm]
100
Particle Size Distribution (fracta l)
[mm]
Average
Minimum
Maximum
Standard
Deviation
Quartile 1
Median
(Q2)
Quartile 3
Sum
Area
3,3430
0,5009
56,3397
7,5987
Holes::
Num
2,7805
0
76
9,5297
Holes::
Area
0,2391
0
9,3132
1,1033
Holes::
Circumference
0,2391
0
9,3132
1,1033
0
0
Short
Axis::Length
1,7676
0,7151
8,1280
1,3891
Unit [mm]
Figure 8: Thin section of South African kimberlite with green colour
attributed to a defined range of the total spectrum
Short Axis::Phi
96,5122
0
179
49,5093
8,3317
12,5335
0,6648
0,9973
0
0
0
0
1,0153
1,2521
63,5000
100
22,7922
1750,8131
2,3264
274,1296
1
228
0,0391 0,0391
19,6064 19,6064
1,9004
144,9409
143
7914
Long
Axis::Length
2,9111
1,1510
12,8457
2,1117
Long
Axis::Phi
84,9024
1
179
55,9876
Convex
Area
5,5908
0,6700
72,7628
11,0305
Paris
2,4420
1,3188
5,2030
0,8025
Inertia
Moment::Max
10,4249
0,0279
447,3873
53,0160
Inertia
Moment::Min
4,7498
0,0102
177,9506
22,9318
Inertia
Moment::Phi-Min
82,7454
0,2345
178,9440
52,9672
0,1155
0,2765
10e2
Area
Area
90
80
Quartile 3: 7270 µm
10e1,50
Average
Minimum
Maximum
Standard
Deviation
Quartile 1
Median
(Q2)
Quartile 3
Sum
70
60
50
Circumference
21,3514
4,5435
146,8034
24,2822
Number of Particles: 82
Quartile 2: 5626 µm
10e1
40
30
Quartile 1: 3758 µm
10e0,50
20
10
0
10e0
6
20
63
20
0
63
2
20
00
63
25
20
00
0
63
24
6
10
-0,30
10
-0,10
10
0,11
10
0,32
10
0,52
10
0,73
[µm]
Equivalent Circle Diameter
10
0,93
10
1,14
10
1,34
10
1,6801
2,1884
34,5000
77
1,2798
2,0556
1,8352
2,3246
3,0699
238,7126
139,5000
6962
4,4111
458,4453
2,8071 1,1056
200,247 854,8385
0,0277
0,0699
31,5918
79,8444
0,4285
389,4811
128,1203
6785,1236
1,55
[mm]
Area
Figure 9: Thin section of kimberlite with edge detection
Figure 7: Grain size distribution and analysis
of tuffitic breccia
Another feature works with different edge detection algorithms. The standard edge detector of CIA takes a
colour or grey value image and returns a binary and thinned image. Depending on the material, the use of
edge enhancement or Canny edge detection may be advisable
3. CoreScan®-CoreBase – the core image data base
CoreBase is a powerful data base for core images. It allows an easy step by step one-click zooming in
from location to drillhole, core run and the actual core image including data connected with this particular
section (figure 10). Various options of synoptic presentations like scrolling the complete core of the
borehole or sequential compilations are possible. Different Types of structural features can be picked
and their strike and dip identified. These features can be displayed together with the core images (figure
11).
4. Structural and geotechnical analysis using
CoreLog Integra & Fracture Statistics
Structural analysis is based on the differentiation of various elements like bedding joints, foliation and
their orientation. The data are particularly important for structure controlled deposits (sedimentary and
non-sedimentary) as well as for geotechnical applications in mining and civil engineering.
A comprehensive interpretation of structural features for tectonic and geotechnical analyses of core
images can be carried out with CoreLog Integra. After scanning the core, the features can be picked
manually and attributed to different structural types like bedding, cleats, foliation etc.
Figure 10: Zooming-in windows in CoreBase, the database
management system
Figure 11: Synoptic representation of a selected sequence from
the database
If borehole deviation data are connected with the scanned images the structures can be re-oriented according
to their strike and dip. Virtual orientation of the core – e.g. by comparison with acoustic measurements of the
borehole wall (FMI/BHTV) – also helps to position internal features that have been described during core
logging relative to the bedding or cleats.
The program offers a variety of options not only for the presentation of structural elements of to drillhole.
Various geotechnical parameters like RQD, fracture density, and fracture distance can be calculated and
plotted along the scanned sequence. For any defined section of the borehole, the respective structural data
can be analysed automatically and represented in diagrams like pole, rose, density, or isoline diagrams as
well as in cross-sections and planar plots marking the selected elements with their true strike and dip along
the borehole axis.
Figure 12: Scanned core image with
structural elements and geotechnical
parameters
Figure 13: Various diagrams produced by CoreLog Integra from scanned
and interpreted core images