Efficient Determination of Specific Surface Area of Shale Samples

Subscriber access provided by GAZI UNIV

Article

Efficient determination of specific surface area of shale samples by a tracer-based headspace gas chromatographic technique Liang He, Tengfei Li, Xin-Sheng Chai, Hui Tian, Xian-Ming Xiao, and Donald G. Barnes Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b04235 • Publication Date (Web): 12 Dec 2016 Downloaded from http://pubs.acs.org on December 18, 2016

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Analytical Chemistry is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 25

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 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

1

Efficient determination of specific surface area of shale samples by a

2

tracer-based headspace gas chromatographic technique

3

Liang He, a Teng-Fei Li,

4

Donald G. Barnes c

b

Xin-Sheng Chai, a,* Hui Tian,

5

a

6

South China University of Technology, Guangzhou, China

7

b

8

Chinese Academy of Sciences, Guangzhou, China

b

Xian-Ming Xiao

b

and

State Key Laboratory of Pulp and Paper Engineering, c School of Environmental and Energy,

State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry,

9 10

ABSTRACT：：This paper reports on a novel method for determining the specific

11

surface area (SSA) of shale by headspace gas chromatography (HS-GC). The method

12

is based on the water adsorption on the surface of shale sample after achieving phase

13

equilibrium at an elevated temperature; i.e., heating at 125oC for 48 h. A mathematical

14

model shows that the SSA can be determined from the signal of the vapor water

15

released during HS-GC analysis. The results obtained by this method correlated well

16

(R2 = 0.992) with data obtained by the reference BET method. Because the phase

17

equilibrium step for multiple samples can be conducted simultaneously and because

18

the phase re-equilibrium step is much faster in the HS-GC measurement, the present

19

method is more efficient for batch sample testing.

20

ACS Paragon Plus Environment


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 48 49 50 51 52 53 54 55 56 57 58 59 60

21

With the commercial success in drilling and hydraulic fracturing techniques,

22

shale gas has become an important energy resource in North America.[1, 2] It also has

23

caught the attention for other countries, such as China, India and Australia, that have

24

potential for such unconventional gas reserves.[3, 4] In order to more accurately

25

estimate the size of these reserves, many predictive mathematical models have been

26

developed, that depend upon a variety of parameters of shale samples,[3, 5, 6]

27

including total organic content (TOC), porosity, and specific surface area (SSA).[7]

28

For many years the SSA of solid samples was often measured by using the

29

mercury injection capillary pressure (MICP) technique,[8, 9] in which the mercury is

30

gradually forced through the porous shale at pressures between 0.2 and 400 MPa. By

31

measuring the decrease of mercury volume at the corresponding injection pressure,

32

the SSA can be calculated by the Young-Laplace equation.[10] However, the MICP

33

method is not suitable for measuring the SSA in very small pores, because of the

34

practical limit on the maximum injection pressure. The minimum measurable

35

diameter of pores by the MICP method is ~ 3 nm [8, 9] while pores in shale rocks

36

range from 0.7 to 100 nm [11, 12]). Moreover, the mercury toxicity and the

37

concomitant contamination of shale samples during the SSA measurement are also

38

disadvantages of this technique.

39

Recently, based on an advanced high-precision pressure sensing system, the

40

Brunauer-Emmett-Teller adsorption method (BET) can now perform the SSA test on

41

samples with very small pore sizes (down to 0.4 nm) and has been widely used in

42

shale gas reservoir assessments.[13-15] The method is based upon the physical


Page 2 of 25

Page 3 of 25

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 48 49 50 51 52 53 54 55 56 57 58 59 60


43

adsorption of gases (usually N2 or CO2, referred to BET-N2 or BET-CO2) on the

44

external- and internal-surfaces of a porous material.[15] Before the BET test, it is

45

necessary to completely remove the gaseous impurities from the sample by a

46

degassing procedure in a vacuum chamber. During the testing, N2 (or CO2)

47

adsorption–desorption isotherm measurements must be performed in ultra-cold tubes

48

using the liquid nitrogen (or drikold).

49

adsorbed at the equilibrium pressure, the SSA of the samples can be calculated from

50

the BET equation.[16] Unlike the MICP method, the BET method doses not pollute or

51

destroy the shale sample during the testing. However, in addition to the sample

52

degassing procedure, the BET method suffers from being very time-consuming in

53

order to obtain the adsorption isotherm. For example, it typically takes about 8 ~12 h

54

to test only one shale sample by the BET method.

55

that can efficiently determine the SSA in the solid sample is highly desired in many

56

surface adsorption-related research studies and practical applications.

By measuring the volume of N2 (or CO2)

Therefore, an alternative method

57

Headspace gas chromatography (HS-GC) is an effective technique for analyzing

58

the volatile species in complicated matrices and has been successfully applied in

59

many situations.[17-19] Recently, we have developed a volatile-tracer based HS-GC

60

technique to explore several new applications; e.g., the determination of the viscosity

61

of a thick liquid and the solubility of inorganic or organic compounds in water.[20-23]

62

These techniques are based on the interaction behaviors (e.g., solubility, absorption or

63

adsorption) between the spiked volatile-tracer substance and the analyte, which results

64

in the tracer content being released into the headspace.



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 48 49 50 51 52 53 54 55 56 57 58 59 60

65

In this study, we demonstrate the use of HS-GC to determine the SSA in shale

66

samples, in which water is used as a tracer species. The main focus of the work was to

67

establish the proof-of-concept for the methodology and to optimize conditions (i.e.,

68

equilibrium time in oven, headspace equilibrium time, and the sample size during

69

analysis) for its use. The results of this method correlated well with the results of the

70

conventional BET method. Since multiple samples can be equilibrated in the oven in a

71

single batch, the HS-GC method results in increased time-efficiency.

72 73 74

EXPERIMENTAL SECTION Samples.

Fourteen shale samples were collected from three shale gas reserves

75

located in southwestern of China. The mineral and total organic content (TOC) were

76

determined by X-ray diffraction analyzer (Bruker D8 Advance, Germany) and

77

Carbon/Sulfur analyzer (LECO CS-200, USA) respectively [24], and the data are

78

listed in Table 1. The samples were ground, screened to 40 - 60 meshes, placed in

79

vials, dried at room temperature, and sealed for storage prior to analysis.

80

Apparatus and operations.

All HS-GC measurements were performed with

81

an automatic headspace sampler (DANI HS 86.50, Italy) and a GC system (Agilent

82

7890A, USA) equipped with a capillary column (GS-Q, 30 m × 0.53 mm, J&W

83

Scientific, US) operated at a temperature of 105°C with nitrogen carrier gas at the

84

flow rate of 3.1 mL/min and using a thermal conductivity detector (TCD) operated at

85

220 °C.

86

sample equilibration at a temperature of 105°C for 12 min, vial pressurization for 0.2

The headspace operating conditions were as follows: gentle shaking for the


Page 4 of 25

Page 5 of 25

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 48 49 50 51 52 53 54 55 56 57 58 59 60


87

min, and sample loop (3 mL) filling time of 0.2 min.

88

A Micromeritics ASAP 2020M apparatus was used for the SSA measurement as the

89

reference method. The Brunauer–Emmett–Teller (BET) equation was applied to N2

90

adsorption isotherms to derive the total specific surface area [24].

91

Preparations and procedures.

SSA Measurement Using HS-GC.

92

0.20±0.01 gram of shale (oven-dried at 150oC for 24 h) with the particle size in the

93

range of 40 − 60 mesh and 25 µL of water were placed in a small tube (1 mL) which

94

was subsequently placed into a headspace sample vial (20 mL). The vial was

95

immediately sealed with a PTFE/silicone septum and an aluminum cap.

96

heating in an oven for 48 h at 125oC, the vial was transferred to the headspace

97

auto-sampler for automated HS-GC analysis.

98

SSA Measurement Using BET-N2 method.

After

In this study, the nitrogen

99

adsorption isotherms were obtained at 77K (-195.8℃) on an accelerated surface area

100

and porosimetry system (ASAP 2020M, Micromeritics Instrument). The oven-dried

101

samples (40-60 mesh) were degassed under high vacuum ( 100 oC), the pressure created by the water

148

vapor in the headspace vial can hasten its adsorption on the solid surface of the

149

nano-scale pores in the shale sample.

150

As noted above, the VSE equilibration of water tracer was conducted at 125oC in



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 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 8 of 25

151

order to create a high pressure. Based on the ideal gas law, a pressure of 0.05 MPa can

152

be achieved from 5 µL of water or a pressure of 0.23 MPa from 25 of µL of water in

153

the 20-mL sealed headspace vial at 125 oC. Fig. 1 shows the effect of equilibration

154

time on the vapor water mass transfer into the surface of shale pores. The vapor

155

content of the water (spiked) in the vial decreases during the process until reaches at a

156

plateau (i.e., the VSE) at ~ 30 h, indicating that the adsorption for the water vapor on

157

the surface of the nano-scale pores is a very slow process.

158

similar to what is observed in the BET test.

159

phase equilibrium, we chose 48 h as the equilibration time for the sample preparation.

160

This phenomenon is

Therefore, in order to ensure a complete

Effect of the amounts of shale and water.

Fig. 2 shows the changes in the

161

GC signal associated with different amounts of water and shale.

162

of water, the GC signal for the water vapor decreases linearly with the size of the

163

shale sample.

164

has a greater surface area, which means that more water can be adsorbed onto the

165

sample surface. The figure also indicates that more water spiking is needed for larger

166

sample weights.

167

desired in the testing.

168

the following testing.

169

For a given amount

This observation reflects that fact that the greater shale sample size

In order to have good sample representative, a larger sample size is Therefore, we use 0.20 g shale spiked with 25 µL of water in

Conditions for HS-GC measurement. Water vapor measurement.

The

170

major interference to the measurement of the water vapor in the HS is the air

171

(nitrogen and oxygen) enclosed in the headspace sample vial. Therefore, it is

172

important to separate the water vapor signal from that of these two gases.


Fig. 3

Page 9 of 25

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 48 49 50 51 52 53 54 55 56 57 58 59 60


173

shows the chromatogram in the sample measurement. Since nitrogen was used as the

174

GC carrier gas, it is no signal in the GC measurement. The Figure shows that the

175

water is well-separated from O2 and CO2 under the GC column operating conditions.

176

Therefore, we can accurately determine the water vapor content under the GC

177

conditions.

178

Headspace equilibration.

To improve the method efficiency, the phase

179

equilibrium for the batch sample vials was conducted in an oven. After equilibration,

180

the sample vials were transferred to headspace auto-sampler where a re-equilibration

181

was required before the HS-GC measurement. As shown in Fig. 4, the re-equilibration

182

is much quicker in that the GC signal of water leveled off after 10 min. Therefore, we

183

selected 12 min as the re-equilibrium time in the following study.

184

Method calibration and evaluation. calibrated

186

measurement[13-15]. As shown in Fig. 5, there is the linear relationship between the

187

reciprocal of GC signal [26] and the SSA determined by the reference method; i.e., it

188

agrees to with the description of Eq. [26]. By linearly fitting the data in Fig. 5, the

189

slope (a) and intercept (b) of Eq. (7) can be obtained. Evaluation.

the

SSA

data

determined

by

The present method was

185

190

using

Calibration.

the

reference

BET-N2

A set of shale samples (the calibration set was not included) were

191

collected and their SSA were determined by the BET method [27] and the present

192

method, in which the factors in Eq. (6) were obtained by the above calibration. The

193

major components of the samples are listed in Table 1. Fig. 6 shows the strong

194

correlation (R2 = 0.992) between the data measured by these two different methods,



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 48 49 50 51 52 53 54 55 56 57 58 59 60

195

indicating that the present HS-GC method can become an alternative method for batch

196

measurement of the SSA of shale samples.

197

Applications: predicting TOC content in shale rock by HS-GC coupled

198

with XRD technique.

199

related to the gas content and gas-generating potentiality of shale rocks.[28] It is

200

because the adsorbed-state gas is dominant and mainly stored on the surface of

201

organic matter particles in shale rocks.[29] Traditionally, the TOC content in shale is

202

determined by the carbon analyzer, in which the sample must be pretreated with 2.4

203

mol/L hydrochloric acid for more than 10 h (to completely remove carbonates)

204

followed by washing with deionized distilled water and dried in an oven.[30]

205

Obviously, such a test procedure is complicated and time-consuming, especially for

206

the batch sample analysis. According to the literatures,[31, 32] the SSA (or porosity)

207

of shale samples has a positive correlation to the TOC content in shale rocks.

208

However, it was found that such as correlation is very poor (as shown in Fig. 7) and

209

thus cannot be used for quantitatively predicting the TOC content in shale sample. We

210

believe that the sample nature, e.g., the inorganic compositions, is also important

211

factor that affects the TOC content prediction. Therefore, it is necessary to introduce

212

the inorganic composition variables in the predict model establishment.

The content of TOC is an important parameter that directly

213

Since there are multiple inorganic minerals in the shale rock sample, we applied a

214

chemometrical software (i.e., SIMCA-P 11.5, Umetrics AB, Sweden) to the

215

multivariate calibration. This can reduce the interference of noise and other irrelevant

216

information from the variables through appropriate data-processing techniques and


Page 10 of 25

Page 11 of 25

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 48 49 50 51 52 53 54 55 56 57 58 59 60


217

then establish the TOC prediction model by implicating the relationship between the

218

variables and TOC content by partial least square regression (PLSR). [33] In Fig. 8, it

219

shows a correlation between the reference measured TOC content and the TOC

220

content predicted by the model based on PSLR analysis.[34] The square of the

221

regression coefficient for the model is 0.939, indicating that the model can provide a

222

good prediction for TOC content in shale sample. Because the proposed SSA test and

223

XRD method is relative simple and efficient, the present model can be used for

224

providing a quick estimation of the TOC content in shale samples.

225 226

CONCLUSIONS

227

We have demonstrated the utility of a new HS-GC technique for determination of

228

the SSA of shale samples which compares favorably with results obtained by the

229

BET-N2 method. Because samples can be more easily batched processed for analysis

230

with the new method, it has significant time efficiency advantages over the traditional

231

approach which are particularly important during the development of these resources.

232

A PLS model for predicting the TOC content based on the inorganic compositions and

233

SSA data of shale samples was also proposed.

234 235

AUTHOR INFORMATION

236

Corresponding author

237

*E-mail: [email protected]; Tel.: +86 20 87113713.

238

Notes

239

The authors declare no competing financial interest.



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 48 49 50 51 52 53 54 55 56 57 58 59 60

240

Page 12 of 25

ACKNOWLEDGEMENTS

241

This study was jointly supported by the National Key Basic Research Program of

242

China (973 Program: 2012CB214705) and the Natural Science Foundation of China

243

(Project Nos. 21576105 and 51409287) for sponsoring the research.

244 245

REFERENCES

246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277

[1] King GE. Hydraulic fracturing 101: what every representative, environmentalist, regulator, reporter, investor, university researcher, neighbor and engineer should know about estimating frac risk and improving frac performance in unconventional gas and oil wells.

SPE Hydraulic Fracturing Technology

Conference: Society of Petroleum Engineers; 2012. [2] Charlez PA. Rock mechanics: petroleum applications: Editions Technip; 1997. [3] Sun L, Tuo J, Zhang M, Wu C, Wang Z, Zheng Y. Formation and development of the pore structure in Chang 7 member oil-shale from Ordos Basin during organic matter evolution induced by hydrous pyrolysis. Fuel. 2015;158:549-57. [4] Deutch J. Good News about Gas-The Natural Gas Revolution and Its Consequences, The. Foreign Aff. 2011;90:82. [5] Zhu X, Cai J, Wang X, Zhang J, Xu J. Effects of organic components on the relationships between specific surface areas and organic matter in mudrocks. International Journal of Coal Geology. 2014;133:24-34. [6] Yang F, Ning Z, Zhang R, Zhao H, Krooss BM. Investigations on the methane sorption capacity of marine shales from Sichuan Basin, China. International Journal of Coal Geology. 2015;146:104-17. [7] Gregg SJ, Sing KSW, Salzberg H. Adsorption surface area and porosity. Journal of The Electrochemical Society. 1967;114:279C-C. [8] Ritter H, Drake L. Pressure porosimeter and determination of complete macropore-size distributions. Pressure porosimeter and determination of complete macropore-size distributions. Industrial & Engineering Chemistry Analytical Edition. 1945;17:782-6. [9] Drake L, Ritter H. Pore-size distribution in porous materials. 2. Macropore-size distributions in some typical porous substances. Industrial and Engineering Chemistry-Analytical Edition. 1945;17:787-91. [10] Rootare HM, Prenzlow CF. Surface areas from mercury porosimeter measurements. Journal of Physical Chemistry. 2002;71:2733-6. [11] Cao T, Song Z, Wang S, Cao X, Li Y, Xia J. Characterizing the pore structure in the Silurian and Permian shales of the Sichuan Basin, China. Marine and Petroleum Geology. 2015;61:140-50. [12] Mastalerz M, He L, Melnichenko YB, Rupp JA. Porosity of coal and shale: insights from gas adsorption and SANS/USANS techniques. Energy & Fuels. 2012;26:5109-20. [13] Zhu X, Cai J, Xu X, Xie Z. Discussion on the method for determining BET specific surface area in argillaceous source rocks. Marine and Petroleum Geology. 2013;48:124-9. [14] Liang L, Xiong J, Liu X. An investigation of the fractal characteristics of the Upper Ordovician


Page 13 of 25

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 48 49 50 51 52 53 54 55 56 57 58 59 60


278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321

Wufeng Formation shale using nitrogen adsorption analysis. Journal of Natural Gas Science and Engineering. 2015;27:402-9. [15] Gregg SJ. Absorption, surface area and porosity. 1982. [16] Brunauer, Stephen, Emmett PHE, Teller, Edward. Brunauer, S., Emmett, P. H. & Teller, E. Adsorption of gases in multimolecular layers. J. Am. Chem. Soc. 60, 309-319. Journal of the American Chemical Society. 1938;60:309-19. [17] Zhong JF, Chai XS, Fu SY, Qin XL. An improved sample preparation method for monomer conversion measurement using headspace gas chromatography in emulsion polymerization research. Journal of Applied Polymer Science. 2012;124:3525-8. [18] Tao Z-Y, Chai X-S, Wu S-B. Determination of epichlorohydrin and 1, 3-dichloro-2-propanol in synthesis of cationic etherifying reagent by headspace gas chromatography. Journal of Chromatography A. 2011;1218:6518-21. [19] Chai X, Dhasmana B, Zhu J. Determination of volatile organic compound contents in kraft mill streams using headspace gas chromatography. Journal of pulp and paper science. 1998;24:50-4. [20] Hu H-C, Chai X-S. A novel method for the determination of black liquor viscosity by multiple headspace extraction gas chromatography. Journal of Chromatography A. 2013;1320:125-9. [21] Chai X-S, Samp J, Yang Q, Song H, Zhang D, Zhu J. Determination of microstickies in recycled whitewater by headspace gas chromatography. Journal of Chromatography A. 2006;1108:14-9. [22] Chai X-S, Verrill CL. Determination of Inorganic Salt Solubility at a Temperature above the Boiling Point of Water by Multiple Headspace Extraction Gas Chromatography. Industrial & Engineering Chemistry Research. 2011;50:6413-7. [23] Chai XS, Hou Q, Schork F. Determination of the solubility of a monomer in water by multiple headspace extraction gas chromatography. Journal of applied polymer science. 2006;99:1296-301. [24] Tian H, Li T, Zhang T, Xiao X. Characterization of methane adsorption on overmature Lower Silurian–Upper Ordovician shales in Sichuan Basin, southwest China: Experimental results and geological implications. International Journal of Coal Geology. 2016;156:36-49. [25] Sing KSW, Everett DH, Haul RAW, Moscou L, Pierotti RA, Rouquerol J, et al. Reporting Physisorption Data for Gas/Solid Systems1985. [26] He L, Chai X-S. A rapid method for determining the reactivity of dissolving pulps by visible spectroscopy. Cellulose. 2015:1-7. [27] Brunauer S, Emmett PH, Teller E. Adsorption of gases in multimolecular layers. Journal of the American chemical society. 1938;60:309-19. [28] Zhang T, Ellis GS, Ruppel SC, Milliken K, Yang R. Effect of organic-matter type and thermal maturity on methane adsorption in shale-gas systems. Organic Geochemistry. 2012;47:120-31. [29] Curtis JB. Fractured shale-gas systems. AAPG bulletin. 2002;86:1921-38. [30] Prell W, Wang P, Blum P, Rea D, Clemens S. 16. DATA REPORT: CARBONATE AND ORGANIC CARBON CONTENTS OF SEDIMENTS FROM SITES 1143 AND 1146 IN THE SOUTH CHINA SEA. [31] Passey QR, Bohacs K, Esch WL, Klimentidis R, Sinha S. From Oil-Prone Source Rock to Gas-Producing Shale Reservoir - Geologic and Petrophysical Characterization of Unconventional Shale Gas Reservoirs. Beijing. 2010;131350. [32] Milliken KL, Esch WL, Reed RM, Zhang T. Grain assemblages and strong diagenetic overprinting in siliceous mudrocks, Barnett Shale (Mississippian), Fort Worth Basin, Texas. Aapg Bulletin. 2012;96:1553-78. [33] Xin L-P, Chai X-S, Barnes D, Chenb C-X, Chenb R-Q. Rapid identification of tissue paper made from



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 48 49 50 51 52 53 54 55 56 57 58 59 60

322 323 324 325

blended recycled fibre by Fourier transform near infrared spectroscopy. J Near Infrared Spec. 2014;22:347-55. [34] He L, Xin L-P, Chai X-S, Li J. A novel method for rapid determination of alpha-cellulose content in dissolving pulps by visible spectroscopy. Cellulose. 2015;22:2149-56.

326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345


Page 14 of 25

Page 15 of 25

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 48 49 50 51 52 53 54 55 56 57 58 59 60


346 347

Tables and Figures Captions

348

Table 1 Compositions of shale samples

349 350

Fig. 1 Effect of time on water equilibration

351

Fig. 2 Effect of shale sample size on the GC signal of vapor water at equilibrium.

352

Fig. 3 Chromatogram for water detection

353

Fig. 4 Effect of time on the water re-equilibrium

354

Fig. 5 Relationship between the reciprocal of GC signals and the surface area of shale

355

samples measured by BET-N2 method.

356

Fig. 6 Correlation between the SSA data measured by the HS-GC and BET methods

357

Fig. 7 Relationship between the SSA and TOC content in the shale samples

358

Fig. 8 TOC model prediction based on the inorganic compositions and SSA in the

359

shale samples

360 361

Table of Contents

362 363 364 365 366 367



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 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 16 of 25

368 369

Table 1

370

371

Sample

Mineral composition, %

no.

Quartz

Feldspar

Illite

Chlorite

Calcite

Dolomite

1

43.7

9.6

25.7

16.1

5

ND

2

39.4

12.2

31.4

10.4

5.1

3

49.1

10.7

19.3

9.6

4

65.7

8.2

22**

5

66.6

7.9

6

57.6

7

Pyrite

TOC, %

ND

1.35

ND

1.5

4.03

7.1

2.5

1.7

3.72

ND

4.1

ND

ND

8.49

19.8

5.7

ND

ND

ND

1.90

7.2

14

21.1

ND

ND

ND

5.20

26.4

15.4

26.5

23.1

6.2

ND

2.5

1.19

8

31.3

13.2

25.8

24.6

3.2

ND

1.8

0.75

9

28.0

11.9

18.1

26.8

14.6

ND

0.7

0.25

10

34.1

17.4

21.8

16.6

8.1

ND

2.0

2.96

11

47.0

19.9

22.5

ND

ND

6.8

3.8

2.02

12

44.7

22.3

18.7

ND

ND

6.5

7.8

4.53

13

83.2

3.4

6.4

ND

ND

4.3

2.8

7.17

14

83.1

6.1

7.6

ND

ND

0

3.2

8.52

15

54.5

14.1

20.3

ND

ND

6.2

4.8

5.85

*

-- Non-detectable;

**

-- illite/smectite mixture.

372


*

Page 17 of 25

373 374 375

3500

VH2O = 5 µL mShale = 100 mg

3000

o

Equil. temp. = 125 C

2500

GC signal

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 48 49 50 51 52 53 54 55 56 57 58 59 60


2000 1500 1000 500 0 0

376 377

10

20

30

40

50

60

Time, h Fig. 1

378 379 380 381 382 383 384 385 386 387 388


70

80


389 390 391

8000 Water, µL 5 15

25

6000

GC signal

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 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 18 of 25

4000

2000 o

0

Equil. temp. = 125 C Equil. time = 48 h

0.0

392 393

0.4

0.8

1.2

Sample size, g Fig. 2

394 395 396 397 398 399 400 401 402 403 404


1.6

Page 19 of 25

405 406 407

500

10000

o

Column temp. = 105 C

y = 293.74x + 50.757 (R2 = 0.9907) 8000

300

Peak area

400

GC signal

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 48 49 50 51 52 53 54 55 56 57 58 59 60


H2O

6000

4000

2000

0

200

0

O2

5

10

15

20

25

30

The amount of water, µg

100 CO2

0 0

408 409

2

4

6

8

Retention time, min Fig. 3

410 411 412 413 414 415 416 417 418 419 420


10


421 422 423

10000

8000

GC signal

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 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 20 of 25

6000

4000

2000 o

Equil. temp. = 105 C

0 0

424 425

5

10

15

20

Equilibration time, min Fig. 4

426 427 428 429 430 431 432 433 434 435 436


25

Page 21 of 25

437 438 439

Reciprocal of GC signal

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 48 49 50 51 52 53 54 55 56 57 58 59 60


2.5x10

-4

2.0x10

-4

1.5x10

-4

1.0x10

-4

5.0x10

-5

-6

-4

2

y = 1.953*10 x +1.355*10

R = 0.973

VH2O = 25 µL mShale = 200 mg o

Equil. temp. = 125 C Equil. time = 48h

0

5

10

15

20

Surface area, m2/g 440 441

Fig. 5

442 443 444 445 446 447 448 449 450 451 452


25


453 454 455

25

HS-GC method, m2/g

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 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 22 of 25

20 y = 1.083x 2

R = 0.992

15

10

5

0 0

456 457

5

10

15

BET method,

20

m2/g

Fig. 6

458 459 460 461 462 463 464 465 466 467 468


25

Page 23 of 25

469 470 471

10 Sample sources #1 well #2 well

8

TOC, wt%

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 48 49 50 51 52 53 54 55 56 57 58 59 60


6

4

2

0 0

5

10

15

20 2

472 473

Specific surface area, m /g Fig. 7

474 475 476 477 478 479 480 481 482 483 484


25


485 486 487

10 Sample sources #1 well #2 well

8

Predicted value

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 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 24 of 25

6

4

y = 0.9998x 2 R = 0.939

2

0 0

488 489

2

4

6

8

Measured value Fig. 8

490 491 492 493 494 495 496 497 498 499 500


10

Page 25 of 25

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 48 49 50 51 52 53 54 55 56 57 58 59 60


501 502

Table of Contents artwork here


Efficient Determination of Specific Surface Area of Shale Samples

Recommend Documents