Oil Yield Characterization by Anisotropy in Optical Parameters of the

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Oil yield characterization by anisotropy in optical parameters of the oil shale Xinyang Miao, Honglei Zhan, Kun Zhao, Yizhang Li, Qi Sun, and Rima Bao Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.6b02443 • Publication Date (Web): 31 Oct 2016 Downloaded from http://pubs.acs.org on November 6, 2016

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Energy & Fuels

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Oil yield characterization by anisotropy in optical

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parameters of the oil shale

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Xin Y. Miao, Hong L. Zhan*, Kun Zhao*, Yi Z. Li, Qi Sun and Ri M. Bao

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Beijing Key Laboratory of Optical Detection Technology for Oil and Gas, China University of

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Petroleum, Beijing 102249, China

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KEYWORDS

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Oil yield, Oil shale, Anisotropy, Refractive index

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ABSTRACT

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Oil yield is an important indicator for oil shale to optimize the comprehensive utilization.

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Generally, oil shale is highly anisotropic owing to the combined effects similar to shale. In this

11

paper, THz-TDS was employed to investigate the anisotropic response of oil shale samples from

12

Longkou, Yaojie and Barkol with different oil yield. All the samples had significant anisotropy

13

of the refractive index (n) and absorption coefficient (α) with symmetries at the location of 180°,

14

which were corresponded with the bedding plane and the partial alignment of particles. Besides,

15

the D-values of experiment n in the vertical and parallel direction of the bedding plane were

16

calculated as ∆n’= n⊥-n‖, and samples from Beipiao and Huadian were also tested in the

17

horizontal and vertical directions for a sufficient number of THz parameters. Linear regression

18

was built between the ∆n’ of the samples from five regions and the oil yield, described as

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y=60.86x+3.72 for oil yield (y) and ∆n’ (x), with the correlation coefficient R equaled 0.9866

ACS Paragon Plus Environment

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and the residual sum of squares was 1.182, indicating THz technology could be an effective

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selection for evaluating the oil yield of oil shale.

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22 23

INTRODUCTION

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Shale formations have been found in most of the global sedimentary basins, acting as the cap

25

rock of conventional reservoirs. Moreover, energy demands have motivated the development of

26

shale formations as significant unconventional reservoirs. Oil shale, a finely grained sedimentary

27

rock with kerogen contained, has been gradually developed in China since the 1920s 1.

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Numerous oil and gas products as fuels and raw materials in petrochemical industries can be

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yielded by pyrogenation of kerogen 2-3. In order to optimize the comprehensive utilization of oil

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shale, a series of methods have been carried out for oil content and oil yield evaluation, including

31

pyrolysis 4, thermogravimetry analysis (TGA) 5, well logging 6, X-ray diffraction as well as

32

diffuse reflectance infrared fourier transforms spectroscopy (DRIFTS) 7.

33

Generally, shales as well as oil shales are often highly anisotropic owing to the combined

34

effect of partial alignment of platy clay particles, layering, microcracks, low-aspect-ratio pores

35

and kerogen inclusions 8-10. Ultrasonic measurements have demonstrated that the elastic

36

properties are isotropic in the directions parallel to the bedding, while anisotropic in other

37

directions 11-13. Besides, solid organic matters are usually more compliant than other minerals in

38

shales. Organics’ shapes and distribution exhibit some elongation parallel with bedding direction

39

14

40

content has impact on the anisotropy degree in shales; thus, anisotropy can be employed to assess

, which makes organic materials a strong source of anisotropy in shales. The organic matter


2

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the oil content theoretically; actually, precisely quantitative relations between oil content and

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anisotropy were seldom built in relative reports 15-18.

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In the past decades, optics has been proved to be the ultimate means of sending information

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to and from the interior structure of materials 19. Birefringence, defined as the division of a light

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ray into two rays when it passes through an optically anisotropic material, is dependent on the

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polarization of the light. It derives from the electrical anisotropy of a material, and is applied for

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characterizing the internal material properties 20. Terahertz (THz) radiation, which is located

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between far-IR (infra-red) and millimeter-wave bands of the spectrum and spans the transition

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range from radio-electronics to photonics 21. At present, analysis with THz radiation has attracted

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much attention owing to the unique advantages 22-27. Various crystals (e.g. quartz 28, sapphire 29,

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LiNbO3 30 and ZnO 31) have been studied to exhibit THz birefringence. Alternating structures

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with two different dielectric materials in sub-millimeter scale were also investigated to show

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form birefringence, such as multilayered polymers 32 and stacks of silicon wafers with air gaps 33.

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In addition, THz birefringence was observed for fibrous materials (e.g. textiles 34, leaf and wood

55

35

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), which exhibits an orientation arrangement of the fiber during the production process. Recently, THz time-domain spectroscopy (TDS) has been utilized for the investigation of

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dielectric properties of reservoir rocks. Optical parameters in THz range were sensitive to the

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mineral and structures in rocks, e.g. marble, limestone, sandstone, clay as well as mudstone 36-38.

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Spectral features of organics were also studied, and THz-TDS was proved efficiently in probing

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the evolution of kerogen with different maturity and disaggregation of crude oil under magnetic

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fields 23, 25. Besides, combination of THz technology and stoichiometry had provided a practical

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means to analyze crude oils 26 as well as fuel oils blended with various additives 44. In our

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previous study, oil yields of oil shales were studied with laser-induced voltage (LIV), showing


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correlations between oil yields and the LIV parameters 39. In this paper, the anisotropic responses

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of oil shales were initially studied by THz-TDS. The anisotropy of experimental n were then

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calculated in order to investigate organic matters content based on the anisotropy in THz

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parameters.

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EXPERIMENTAL METHODS

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The oil shales used in the experiments were obtained from three districts in China, including

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Longkou, Yaojie and Barkol. The oil yields of the samples from these regions were measured as

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∼14.16, ∼9.05, and ∼5.66%, respectively 39. From each shale block, we cut slices at different

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angles (θ0) relative to the bedding plane (shown in Table 1). The size of each slice equaled ~8×8

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mm2 and the thickness were measured by micrometer caliper one by one. Therefore, totals of 17

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slices were prepared. In order to avoid the influence of water, all the slices were dried in vacuum

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at 90 °C for 10 h before testing.

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Table 1 Cutting and testing angles of the slices from three kinds of blocks Region

Longkou

Yaojie

Barkol

Cutting angles of

0°, 15°, 30°, 45°,

0°, 30°, 45°, 60°,

0°, 30°, 45°, 60°,

the slices (θ0)

Testing angles of the slices (θ)

60°, 75°, 90°

90°

90°

0°, 15°, 30°, 45°,

0°, 30°, 45°, 60°,

0°, 30°, 45°, 60°,

60°, 75°, 90°,

90°, 120°, 135°,

90°, 120°, 135°,

105°, 120°, 135°,

150, 180°, 210°,

150, 180°, 210°,

150°, 165°, 180°,

225°, 240°, 270°,

225°, 240°, 270°,


4

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195°, 210°, 225°,

300°, 315°, 330°,

300°, 315°, 330°,

240°, 255°, 270°,

360°

360°

285°, 300°, 315°, 330°, 345°, 360°

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The experiments were performed by a transmission THz-TDS system (shown in Figure 1(a))

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under air atmosphere with the temperature 294.1 K and the humidity 30%. The signal-to-noise

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ratio (SNR) of the setup was ~1500. A detailed description and schematic drawing of the THz

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system based on photo conductive antenna and electro-optical sampling has been explained in

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our previous study 26. All the slices were tested and then the refractive index (n) and absorption

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coefficient (α) anisotropy were calculated. As shown in Figure 1 (b), the measurement process

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was divided into four steps: (i) each slice was placed in the THz-TDS equipment at the focus

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position, with the angles between the input orientation of terahertz waves and the normal

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direction of the bedding plane (θ); (ii) revolved 180° of the slice around the THz-propagation

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direction (define as X-axis) with θ’=180°-θ; then the slice was turned 180° around (iii) Z-axis

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and (iv) X-axis, with θ’’=360°-θ and θ’’’=180°+θ, respectively.

88 89 90

Figure 1. Top view of (a) experimental setup for the detection of slices with transmission THz-TDS. (b) Schematic diagram of the four steps during the test.


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RESULTS AND DISCUSSION

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THz-TDS of the reference and the slices were initially measured. Fast Fourier transform (FFT)

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was used for deriving the THz frequency domain spectra (THz-FDS), and the n as well as α

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spectra were then calculated 25. Owing to the intense absorption of the slices, the spectra were

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not only composed of the samples’ characteristic features, but also many kinds of noises.

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Therefore, weaker signals at some frequencies were covered by the noises, and the effective

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frequency range was reduced to 0.4-1.0 THz for acceptable signal-to-noise ratio. Frequency

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dependent α and n spectra of slices with the testing angle 0° and 90° were exhibited in Figure 2.

100 101

Figure 2. Frequency dependent spectra of the absorption coefficient (α) and refractive index (n)

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measured with the propagate direction parallel (dotted line, θ=90°) and vertical (solid line, θ=0°)

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to the bedding plane at 0.4-1.0 THz.

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As shown in Figure 2, the values of n were almost unchanged in the range of 0.4-1THz,

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while those of α augment with the increasing of the frequency. Owing to the divergence in


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mineral compositions and oil yields, the values of n and α in the three regions differed from each

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other. Generally, oil shales collected from Barkol have the maximum n, followed by Yaojie and

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Longkou. On the contrary, the α spectra of oil shales from Barkol were the minimum and those

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samples from Longkou led across most of the frequency range. Divergence was also found in the

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spectra of n and α for the samples from the same place with 0° and 90° , respectively.

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Then we investigated the θ dependences of n and α at various angles range from 0° to 360°.

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Expressions of n and α variation with the angle were obtained firstly. Oil shale was assumed as a

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uniaxial birefringent media with transverse isotropy, in which the optical axis was perpendicular

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to the bedding plane. The dielectric constant of the oil shale was denoted by ε0 in direction of the

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optical axis, as well as ε90 along the layer. The dielectric tensor was expressed as a tensor in the

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principal axes. i.e.

ε 90 0 0  ε =  0 ε 90 0   0 0 ε 0  .

117 118

(1)

Then, we defined the propagation velocities of electromagnetic wave in x, y and z directions,

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with 0 and 90 represent the transmission direction parallel and vertical to the optical axis,

120

respectively.

121 122 123

vx = vy = v90 vz = v0 ,

.

(2)

According to the theory of light propagation in an anisotropy media 40, the relationship between the propagation velocity (v) and the angle (θ) in a uniaxial crystal was given by:


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vθ =

124 125 126

2 v 02 cos 2 θ + v 90 sin 2 θ

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(3)

the refractive index (n) could be calculated by:

127

129

.

Where θ represented the angle between the propagation direction and the optical axis. Thus,

nθ =

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1 cos2 θ sin2 θ + 2 n02 n90

.

(4)

As n0 and n90 were constants associated with the properties of samples, nθ varied periodically as a function of θ with the cycle 180° in the case of n0 ≠ n90. Besides, the angle dependent attenuation of THz field were also calculated. The output field

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was expressed as a function of θ, and then α was obtained based on that. Considering the

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diagram shown in Figure 3, the output fields of the shale parallel and perpendicular to the layer

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were expressed as:

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E⊥out = Ein cos(θ )exp(iΓ⊥ )exp(−α⊥d )

,

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Eout = Ein sin(θ )exp(iΓ )exp(−α d )

.

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In which Ein was the incident electric field amplitude, Γ⊥and Γ‖were the phase retardances

(5)

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parallel and vertical to the layer, respectively. d was the thickness of the oil shales. α⊥ and α‖

138

were defined as the absorption coefficients along the two directions.


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Figure 3. Schematic diagram of the shale sample for the input THz fields. Directions α⊥ and α‖ were parallel and perpendicular to the layer, respectively.

In Figure 3, the output fields in directions perpendicular and parallel to the layer recombined and the output THz field was given by:

Eout = E⊥out cos(θ ) + Eout sin(θ )

144 145

146 147 148

150

(6)

Then, angular dependent Eout was obtained as:

E out = Ein exp(−α d ) cos 2 (θ ) exp(−∆α d ) exp(i∆Γ) + sin 2 (θ )

.

(7)

Where ∆α was the difference value of α‖and α⊥, and ∆Γ represented the phase retardance which could be expressed by:

∆Γ =

149

.

2π d

λ

∆n

.

(8)

With the birefringence (∆n) and the wavelength (λ) 27.


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152 153

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Then, the relation of α could be expressed as –ln (Eout /Ein) /d.

αθ = α −

1 ln cos 2 (θ ) exp( −∆ α d ) exp(i ∆Γ ) + sin 2 (θ ) d

(9)

Using Eq. (8) in Eq. (9), we obtained the variation of α with θ, d as well as λ:

αθ = α −

1 2π l ln(cos 4 θ e −2 ∆α d + 2 cos 2 θ e − ∆α d cos ∆ n + sin 4 θ ) 2d λ

(10)

155 156

Figure 4. (a) θ dependent measured n values of the samples (dots) and calculated n (dotted

157

curve) from Longkou, Yaojie, and Barkol, respectively. (b) Experimental value of α at 0.8 THz

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(dots) as a function of angle along with the expected angular dependence of α (dotted curve)

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calculated by Eq. (10). Error bars represent 0.5-fluctuation of standard deviation of n and α.

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Figure 4 showed the angular dependent n and α (at 0.8 THz) of the samples from Longkou,

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Yaojie, and Barkol, respectively. It was clear from Figure 4 (a) that all the oil shale samples from

162

three regions had significant anisotropy of n, and there was data symmetry at the location of 180°.


10

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Moreover, the data also showed a significant attenuation of n in the THz propagation direction

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parallel to the layering compared with that perpendicular to the layering. Then, calculated n were

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obtained and plotted (the dotted lines in Figure 4(a) by Eq. (4) with the experimental n0 and n90.

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Slightly larger differences existed between the calculated and observed n for Longkou and

167

Barkol samples compared to that of Yaojie, but followed the same overall trend. Likewise, the

168

measured (solid curves) and calculated (dotted curves) αθ as a function of the angle were shown

169

in Figure 4(b). For all the three samples, the peak values of measured α were obtained at ~45° in

170

the range from 0° to 90°, which remained coincide with the calculated values. The experimental

171

data met the expectations in Eq. (10), and the results clearly demonstrated the anisotropy

172

behavior of the measured oil shale samples. Various studies have shown that the observed THz

173

anisotropy of materials with natural fibers are contributed by their intrinsic structure 34, 35.

174

Similarly, for the oil shale samples, the anisotropy in THz parameters are caused by the

175

preferential orientation of basic structural units. The data symmetries at the location of 180° in

176

the experimental data as well as the calculated lines are corresponded with the bedding plane and

177

the partial alignment of particles in oil shales.

178

In addition, the presence of alternating layers with varying organic matter content has

179

influence on the degree of anisotropy of elastic wave velocity and attenuation 14. The organic

180

matter appears to have little intrinsic birefringence, nevertheless, the effect of organic matter on

181

the anisotropy was speculated to be strongly related to the texture of shales 15-19. Organic matter

182

such as kerogen has always exhibited some elongation parallel with the bedding, which is caused

183

by lithostatic overburden and deformation, and by the original orientation when kerogen first

184

deposits 42. The organic matter content resulted in the variation of ∆n with the oil yields in this

185

research. Herein, we calculated the D-value of n⊥ and n‖as ∆n’, in which n⊥ and n‖represented


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the average value of experiment n in the vertical and parallel direction of the bedding plane.

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Organic matter has a very low refractive index in THz range, 36,43 in addition, owing to the effect

188

of oriented organic matters, n‖decreased more than n⊥ with the increasing in organic matter

189

content. The possibility of using ∆n’ to infer oil yield promoted us to test two more samples with

190

different oil yields. Oil shale samples from Beipiao and Huadian were tested in the horizontal

191

and vertical directions, with the oil yields ~5.00 and ~9.96, respectively. ∆n’ of the samples from

192

five places were calculated and plotted with oil yield in Figure 5. Significant positive correlation

193

was shown between the anisotropy parameters and the oil yield, indicating that the increase in

194

organic matter has promoted the anisotropy in THz range. Therefore, THz technology was

195

expected to be valid in evaluating the oil yields of oil shales.

196 197

Figure 5. Linear fit of oil yield as a function of ∆n’, with the correlation coefficient R equal to

198

0.9866 and the residual sum of squares equal to 1.182. The inset is the n spectra of Beipiao and

199

Huadian samples with the propagate direction parallel and vertical to the bedding plane. Error

200

bars represent 0.5-fluctuation of standard deviation of the oil yields.


12

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Anisotropic degree of n in horizontal and vertical directions have provided alternative

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parameters for oil yield characterization, with small amount of samples required. According to

203

previous researches, a variety of methods can be implemented to evaluate the organic matter

204

content in oil shales, mostly assessed by heating and combusting 41. Fisher assay has been

205

extensively applied in oil yield characterization, which is time consuming, destructive and

206

expensive with large amount of samples required 7. TGA measurements have been utilized to

207

determine the temperature affected pyrolyzation and kinetic parameters of oil shales with the

208

heating rates 5-40 °C/min and final temperature 950 °C 5,7. Other methods such as well-logging

209

provides the total organic carbon content (TOC) by relations between the TOC and ∆logR,

210

however, the log curve is always influenced by the well environment and cannot reflect the

211

information on undisturbed formation accurately 6. According to our previous studies, positively

212

related relationships were observed between the photo induced voltage (∆v) and the oil yield, in

213

which ∆v directly affected by organic matter content 39. In this paper, we determined the content

214

of organic matter by its promotion of the anisotropic degree. In terms of the anisotropy in THz

215

parameter, by measuring n of oil shale slices with two bedding plane direction, n0 and n90 could

216

be obtained based on relations formulated in Eq. 4, and ∆n’ can be quantitatively related to the

217

oil yield. Linear correlation has been shown with the results of the samples from three places,

218

described as y=60.86x+3.72 for oil yield (y) and ∆n’ (x), with the correlation coefficient R

219

equaled 0.9866 and the residual sum of squares (RSS) was 1.182. Therefore, THz technology has

220

provided a promising means in non-destructive detection of oil yields in oil shales from different

221

places.

222

CONLUSION


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In summary, THz-TDS was utilized to study the oil shale slices with different angles between the

224

surface and the bedding plane. The samples from three regions had significant anisotropy of n

225

and α with the variation of θ, and the data symmetries corresponded with the bedding plane and

226

the preferential alignment of particles in oil shales. In addition, n anisotropy of the oil shale

227

samples from five districts were compared with each other and plotted as a function of the oil

228

yield, showing that the increase of organic matter has promoted the anisotropy in THz range.

229

Therefore, THz technology is supposed to be a valuable tool for the oil yields evaluation of oil

230

shales.

231

AUTHOR INFORMATION

232

Corresponding Author

233

*Telephone: +86-10-89732270. E-mail: [email protected]; [email protected].

234

Author Contributions

235

The manuscript was written through contributions of all authors. All authors have given approval

236

to the final version of the manuscript.

237

Notes

238

The authors declare no competing financial interest.

239

ACKNOWLEDGMENTS

240

This work was supported by the National Nature Science Foundation of China (Grant No.

241

61405259 and 11574401), National Basic Research Program of China (Grant No.

242

2014CB744302), the Specially Founded Program on National Key Scientific Instruments and

243

Equipment Development, China (Grant No. 2012YQ140005) and the China Petroleum and


14

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Chemical Industry Association Science and Technology Guidance Program (Grant No. 2016-01-

245

07).

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(24) Zhan, H. L.; Zhao, K.; Xiao, L. Z. Spectral characterization of the key parameters and elements in coal using terahertz spectroscopy. Energy 2015, 93, 1140-1145.

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Page 20 of 29

(b) 1

(a) THz Emitter

2

X

θ 180

THz Detector

180-θ

Z Samples

180

4

180+θ


180

3 360-θ

Page 21 of 29

Barkol

2.6

2.0 1.6

n

2.4

Yaojie

2.2

Longkou

(mm )

2.0

-1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Energy & Fuels

1.2

1.8 0.4

0.5

0.6

0.7

0.8

0.9

1.0

Frequency (THz)

0.8 0.4 0.4

90

0 0.5

0.6

0.7

0.8

Frequency (THz) ACS Paragon Plus Environment

0.9

1.0

Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Page 22 of 29

αǁ Ein

Eout θ

α


Page 23 of 29

2.05

Longkou

2.00 1.95

n

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Energy & Fuels

1.90 1.85 1.80

0

40

80 120 160 200 240 280 320 360 o

Angle( )


Energy & Fuels

2.22 2.20

Yaojie

2.18 2.16

n

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Page 24 of 29

2.14 2.12 2.10 2.08 0

40

80 120 160 200 240 280 320 360 o

Angle( )


Page 25 of 29

Barkol

2.53 2.52 2.51

n

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Energy & Fuels

2.50 2.49 2.48 0

40

80 120 160 200 240 280 320 360 o

Angle ( )


Energy & Fuels

1.6 1.5 1.4

mm )

1.3 -1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Page 26 of 29

1.2 1.1 1.0 0.9 0.8

Longkou 0

40

@0.8THz

80 120 160 200 240 280 320 360 o

Angle ( )


Page 27 of 29

1.00 0.95

 mm )

0.90 -1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Energy & Fuels

0.85 0.80 0.75 0.70 0.65

Yaojie 0

40

@0.8THz 80 120 160 200 240 280 320 360 o

Angle ( )


Energy & Fuels

0.75

Barkol

mm 

0.70 0.65

-1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Page 28 of 29

0.60 0.55 0.50 0.45

@0.8THz 0

40

80 120 160 200 240 280 320 360 o

Angle ( )


Page 29 of 29

18

2.15

Longkou ~14.16

2.05

n

14

Beipiao

2.10

16

Oil yield (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Energy & Fuels

2.00

Huadian

1.95

12 10

1.90 0.4

90°

0° 0.5

0.6

0.7

0.8

0.9

1.0

Frequency (THz)

Huadian ~9.96

Yaojie ~9.05

8 Barkol ~5.66

y=60.86x+3.72

6 4

Beipiao ~5.00

0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18

n'


Oil Yield Characterization by Anisotropy in Optical Parameters of the

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