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作 者:宋宁[1,2] 徐晓轩[1,2] 王斌[1,2] 张存洲[1,2]
机构地区:[1]南开大学泰达应用物理学院,天津300457 [2]天津市南开大学弱光非线性光子学材料先进技术及制备教育部重点实验室,天津300457
出 处:《光谱学与光谱分析》2009年第2期378-381,共4页Spectroscopy and Spectral Analysis
基 金:教育部"振兴计划"项目(A01504)资助
摘 要:红外漫反射光谱技术越来越普遍地被应用到粉末样品的快速测量分析中,在应用红外漫反射光谱技术对粉末状的烃源岩样品的生烃潜量进行定量分析时,由于样品的颗粒度、密度、表面粗糙程度等几何参数的变化对散射光的影响非常大,使得漫反射光谱数据的信噪比很低、背景干扰很大,这样很难对样品进行定量分析。因此需要一种有效的方法对漫反射数据进行预处理来消除散射的影响,提高信噪比。文章利用正交信号校正算法(OSC)作为一种光谱过滤手段,并与间隔偏最小二乘(iPLS)相结合,有效地消除了粉末状样品散射光的影响,可以显著提高烃源岩红外光谱预测模型的准确性,使得红外漫反射光谱技术在石油录井中有了广阔的应用前景。In many cases, the scattering can be an overpowering contributor to the spectrum, sometimes accounting for most of the variance in the data. Although the degree of scattering is dependent on the wavelength of the light that is used and the particle size and refractive index of the sample, the scattering is not uniform throughout the spectrum. In order to remove the effects of scattering and noise on multivariate calibration of IR spectral signals, orthogonal signal correction (OSC) was used as a method to preprocess the infrared spectra of the hydrocarbon source rocks to be quantitatively determined, thus to establish the cali- bration model of hydrocarbon source rocks before and after pretreatment by inetval partial least square (iPLS). Pretreatment was smoother and more orderly array. This indicated that the major information in hydrocarbon source rocks spectra could be reserved while part of noise was removed by OSC method. In this study, pretreatment calibration model was obtained, the model's correlation coefficient is 0. 994 04 and RMSE is 0. 635 2, but with no pretreatment the calibration model's correlation coefficient is 0. 770 9 and RMSE is 3. 925 7.
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