光谱学与光谱分析 |
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Discussion of the Application and Influence Factors of Low-Background Gamma Spectrometry in Distinguishing Sedimentary Rock Types |
ZHANG Li-jiao1, HUANG Jin-chu1*, LIN Hong-jian1, LAI Wan-chang1, LI Dan1, WANG Guang-xi1, GU Run-qiu1, LAI Yu-rou2, YAN Rong-hui3, WANG Gang3 |
1. College of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu 610059, China 2. Chengdu Shenfu Instrument Equipment Co., Ltd., Chengdu 610059, China 3. Exploration Department of PetroChina Changqing Oilfield Company,Xi’an 710018, China |
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Abstract The contents of radionuclides uranium, thorium and potassium in the sedimentary rocks mainly depend on the contents of clay in the rocks. And the content of clay is the main basis for distinguishing types of sedimentary rock. Therefore, the value of specific activity or content of uranium, thorium and potassium can be as the quantitative index to distinguish sedimentary rock type. The specific activity or content of radionuclides uranium, thorium and potassium with the method of low-background gamma spectrometry can distinguish the type of rock quickly and accurately. Because of the influence of geometry, mass and moisture content in the sample, the accuracy of distinguishing types of rocks is influenced. This paper makes a theoretical discussion and experimental verification on the influence of mass and moisture content on the results of low-background gamma spectrometry. Results show that there is a linear relationship between (cps) of characteristic peak of all radionuclides and the mass of sample while different energy ranges and lithologies have different linear coefficient and trend fitting degree; The moisture content which is no more than 10%(while collecting samples, the moisture content is no more than 10%) has a little influence on the measurement results( the change values are within the twice standard deviation), so the moisture content which has no significant influence on the accuracy of distinguishing types of sedimentary rock using the method of low-background gamma spectrometry could not be considered. The distinguishing experiment of drilling cuttings samples collected from one oil and gas exploration area in Shanxi Dingbian is done. By the mass correction of the measured data, normalized (cps) ((cps) of per unit mass) of uranium, thorium and potassium channel can only roughly divide the types of sedimentary rocks. Therefore, synthetic distinguishing mode is established with (cps) of combination peak of characteristic peak of uranium, thorium and potassium. The type of rocks is further subdivided, and the distinguishing accuracy is more than 75%.
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Received: 2015-05-12
Accepted: 2015-09-28
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Corresponding Authors:
HUANG Jin-chu
E-mail: lwchang@cdut.edu.cn
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[1] Akkurt I, Günoglu K, Keith E. Holbert. Science and Technology of Nuclear Installations, 2014, 2014: 1. [2] Kerur B R, Rajeshwari T, Anilkumar S, et al. Journal of Radioanalytical and Nuclear Chemistry, 2012, 294 (2): 191. [3] Surinder Singh, Asha Rani, Rakesh Kumar Mahajan. Radiation Measurements, 2004, 39 (4): 431. [4] Pitta Hima Bindu, Nageswara Rao A S. Arab. J. Sci. Eng., 2011, 36: 121. [5] Kaminski S, Jakobi A, Chr. Wilhelm. Applied Radiation and Isotopes, 2014, 94: 306. [6] Shweikani R, Hasan M, Tlas M, et al. Radiation Measurements, 2014, 70: 34. [7] CHENG Ye-xun, WANG Nan-ping, HOU Sheng-li(程业勋, 王南萍, 侯胜利). Nuclear Radiation and Radioactive Exploration(核辐射场与放射性勘查). Beijing: Geology Press(北京: 地质出版社), 2005. 97. [8] ZHANG Ye, HUA Rong-zhou, SHI Bai-shen(章 晔, 华荣洲, 石柏慎). Radioactive Prospecting Methods(放射性方法勘查). Beijing: Atomic Energy Press(北京: 原子能出版社), 1990. 51. [9] Abd A El. Applied Radiation and Isotopes, 2014, 94: 247. [10] Al-Masri M S, Hasan M, Al-Hamwi A, et al. Journal of Environmental Radioactivity, 2013, 116: 28. [11] Costa J C, Borges J A R, Pires L F, et al. Annals of Nuclear Energy, 2014, 64: 206. |
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