Leng WenXiu, Li QingYan, Bao RiMa, Zhao Kun, Miao XinYang, Li Yi Zhang
http://engine.scichina.com/publisher/scp/journal/SCPMA/62/1/10.1007/s11433-018-9229-4?slug=full%20text
In the field of geology, it is necessary to get the information about the rock geological time, which includes absolute geologic age and relative geologic age [1] . Tracing the evolutionary history of the earth is one of the research tasks of earth science. Time, space, material and motivation are the basic elements for studying geological processes and environmental evolution, and time is the basis for studying geological problems. A clear understanding of the interaction between the above elements will be able to clearly make sure the evolution of the earth and the conditions of rock formation. Nowadays, it is urgent to get the geochronological data of rocks for wide range comparison, so as to study the evolution trend and development rule of the earth’s crust [2] . At the same time, exploring the geologic age of rocks is also of great significance to exploration and development of mineral deposits. Certain minerals are usually associated with a particular geological body, while the particular geological body is formed during a particular geological period, which requires explicit rock age data. Therefore, it is of great significance to identify the geological age of rocks. At present, the research methods of rock geological dating are method of lithological stratigraphy, paleontology method, paleomagnetic method, isotope method, fission track method, geophysical method, etc. [3] . The lithostratigraphy, palaeontology and paleomagnetism determine the relative geologic age of the rock; the absolute age of the rock is measured by the isotopic method. Isotope method is the most important and most widely used dating method in geologic dating, including stable isotope method, radioisotope method (U-Pb, K-Ar, etc.), cosmic nuclide method (10Be, 36Cl, etc.).
Owing to its unique advantages, the terahertz (THz) technique has received increasing attention in many fields [4 -9 ] . Recently, the THz technique has also been applied in the geological field [10] . Here in this letter, we aim to characterize the relative geological time of rock by terahertz time-domain spectroscopy and principal component analysis. The relationship between the rock relative geological time and terahertz optical parameters is also investigated by analyzing the ingredients of the rock samples.
The clastic rock samples used here were collected from Liujiang basin, which located in Qinhuangdao, Hebei Province. Figure 1 shows the composition and structure of the clastic rock samples by transmission polarization microscope. The sample details are shown in Table 1 . As shown in Table 1 , all samples are detritus particles and there are differences in composition and content of different samples. According to Table 1 , six kinds of common ingredients were contained in the samples, and quartz, detritus and the argillaceous matrix are the main ingredients in all samples. The two samples have the same relative geologic age and are different from the other five. Before THz-TDS measurement, the rock samples were crushed into powder, then were sifted in an 200-mesh sieve to remove large particles and dried in a drying oven for 24 h to remove the effect of moisture in the sample powder. Then they were mixed with polyethylene (PE) powder with rock powder/PE mass ratio of 1.3:0.5, then pressed by a bead machine at a pressure of 20 MPa for 2 min. The mixture of polyethylene and rock powder was pressed into tablets with the thickness of approximately 1.750 mm and diameter of 30 mm .
Figure 1
(Color online) Polarized microscope pictures of clastic rocks
and the images of the samples after preparation.
and the images of the samples after preparation.
Table 1 Quantitative analysis of components of the samples
Age (Ma) |
Geological time
|
Geological era symbol
|
Quartz
|
Detritus
|
Argillaceous matrix
|
Plagioclase
|
Glimmer
|
Siliconecement
|
Others
|
800-1000
|
Qingbaikouan Period
|
Pt3
|
96%
|
1%
|
--
|
2%
|
--
|
1%
|
--
|
510-570
|
Middle Cambrian
|
Є2
|
60%
|
--
|
15%
|
13%
|
7%
|
--
|
5%
|
290-362
|
Middle Carboniferous
|
C2
|
60%
|
24%
|
16%
|
--
|
--
|
--
|
--
|
290-362
|
Late Carboniferous
|
C3
|
48%
|
30%
|
20%
|
--
|
2%
|
--
|
--
|
250-290
|
Early Permian
|
P1
|
58%
|
32%
|
10%
|
--
|
--
|
--
|
--
|
250-290
|
Early Permian
|
P1
|
70%
|
20%
|
10%
|
--
|
--
|
--
|
--
|
250-290
|
Late Permian
|
P2
|
69%
|
21%
|
10%
|
--
|
--
|
--
|
--
|
Initially, the reference THz pulse was obtained after transmitting through the Nitrogen, and then the signals of the seven rock samples were collected. Terahertz time-domain spectra for reference and seven samples are shown in
Figure 2
(Color online) (a) Time dependent THz spectra of reference and the samples; (b) variations of THz refractive index with frequency from 0.2 to 1.2 THz .
Due to the complexity of rock composition, principal component analysis (PCA) was carried to establish the predictive models among the parameters obtained in this study. Principal component analysis, which has been successfully employed in THz-TDS to classify the different kinds of materials, is a common statistical method to decrease the dimensions and uses a dimension and uses an orthogonal transformation to convert the input data into a set of linearly uncorrelated principal components (PCs). The number of PCs is less than or equal to the number of the input data and the PC1which has the highest variance and contribution rate reflects most information of input data [11 -14 ] . In this study, PCA was done with the refractive index spectra of all samples ranging from 0.2 to 1.2 THz as input data. We put the selected data in an excel table. The first column of the table is the terahertz frequency, the second column is the first sample data, and the third column is second sample data, and so on. Then we put the excel table and the already compiled MATLAB program into the same file, and run the program to get the principal component analysis results [15] . Figure 3 is obtained by further optimizing the results. There are seven samples in Figure 3 , and we use geological era symbol to represent each sample. For example, Pt3 represents a sample of Qingbaikouan period in the relative geological age, and 800-1000 Ma (million years) means that the sample started from 1 billion to 800 million years ago. The geological age information of other samples is given in Table 1 . There are two samples with the same geological age, both of which were early Permian (P1). As shown in Figure 3 , PC1 accounts for 99.64% and PC2 accounts for a further 0.16% of the variance between the samples, with the total contribution rate equaling 99.80% in all deviations. Due to its large contribution, PC1 has vital significance for analyzing the relative geological era of rocks. Although the contribution rate of PC2 is not large, it is also very important for the analysis of geological age. We can find the distance between each sample based on the difference between the scores of PC1 and PC2 of each sample. The distances between the samples with large differences in geological age are far away, and the distances between the samples with smaller differences in geological age are close to each other. Then based on the values of PC1 and PC2, rocks of different geological ages are distinguished, and the same geologic age samples are grouped together (such as two Early Permian rock samples). As can be seen from the Table 1 , the differences in the composition and content of the samples with large geologic age gaps are obvious, and there is little difference in the composition and content of the samples with little geological age gaps. In addition, it can be seen from the three Permian samples that the physical property of rock can also be an influential factor in addition to the composition. The result shows that the combination of terahertz time-domain spectroscopy and PCA can characterize the rocks relative geochronology.
Figure 3
(Color online) Two dimensional system of PC1 versus PC2 calculated from Figure 2 (b).
We aim to assess the relative geological time of rocks by measuring terahertz optical parameters, so the relationship between the relative geological time and the absorption coefficient is investigated. As shown in Figure 4 (a), with the geological time increasing, the absorption coefficient of the samples at 0.7 and 1.0 THz tends to increase first and then decrease. The illustration in Figure 4 (a) shows that the absorption coefficient increases from 240 to 310 Ma . In order to analyze the tendency mentioned above, further study of the THz response to the percentage of each ingredient is essential. Figure 4 (b)-(d) shows the variations between each ingredient contents and the absorption coefficient. It is obvious that the variation tendency of the absorption coefficient is positively correlated with the detritus content and the argillaceous matrix content but negatively correlated with the quartz content. It could be speculated that detritus and the argillaceous matrix have a stronger absorption of the THz pulse than quartz. The outliers in Figure 4 (b)-(d) are marked in different colors. In Figure 4 (b) and (c), the outliers are the same sample, and the geologic age of the sample is P1. P1 and P2 have the same composition and content, except for the geological age. It can be seen that there is a direct relationship between geological age and absorption coefficient. Due to the different tectonic movements experienced in different geological periods, the composition and content of rock formed in different geologic periods are different. That is why the absorption coefficient changes
Figure 4
(Color online) (a) Absorption coefficient of the samples at selected frequencies together with geologic age; (b) absorption coefficient versus quartz content; (c) absorption coefficient versus detritus content; (d) absorption coefficient versus the argillaceous content.
In summary, clastic rocks of different geologic age in the same area were studied by using THz time domain spectroscopy. The research focused on reporting that the relative geological age of rock can be characterized by the combination of terahertz time domain spectroscopy and PCA. Moreover, the terahertz absorption coefficient shows a trend of increasing first and then decreasing with the relative geological age of rocks. The effect of sample composition on the absorption coefficient was investigated with the identification of thin slices. The results prove that THz technology is a promising means for determining the relative geologic age of rocks, and it will be a significant supplementary method in geological survey fields.
Acknowledgment
This work was supported by the National Nature Science Foundation of China (Grant No. 61405259).
Contributions Statement
These authors contributed equally to this work.
References
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