On-line multi-component alkane mixture quantitative analysis using Fourier transform infrared spectrometer

Abstract

Fourier transform infrared spectrometer (FTIR) has been widely used to analyze multi-component gas mixture for more than ten years because of its potential benefits. However, it is a challenge to analyze multi-component alkane mixture on-line with FTIR because their absorption spectra overlap with each other extensively. In this paper, the methods of feature extraction and selection based on Tikhonov regularization (TR), and the modeling methods based on neural network (NN) are discussed in the practical conditions of alkane mixture analysis with FTIR. Then, the proposed methods compared with gas chromatograph (GC), normally regarded as the standard way for quantitative gas analysis, are used for gas well logging to analyze the mixture of methane, ethane, propane, iso-butane and n-butane on-line. By comparing the well logging curves obtained from FTIR with the ones from GC, it is shown that the logging curves analyzed with proposed method are good matches with the ones obtained from GC, which means that our analysis results are accurate. At the end of this paper, a calibration transfer is used to calibrate additional 18 instruments with a few sets of samples. And the work introduced in this paper demonstrates that FTIR can also be used in analyzing multi-component gas with close molecular structure accurately and the analyzer can be produced in mass.