In Situ Methane Determination in Petroleum at High Temperatures and High Pressures with Multivariate Optical Computing

被引:7
|
作者
Jones, Christopher M. [1 ]
Price, James [1 ]
Dai, Bin [1 ]
Li, Jian [1 ]
Perkins, David L. [2 ]
Myrick, Michael L. [3 ]
机构
[1] Halliburton Energy Serv, 3000 North Sam Houston Pkwy East, Houston, TX 77032 USA
[2] ExxonMobil Res & Engn Co, 1545 Route 22 East, Annandale, NJ 08801 USA
[3] Univ South Carolina, Dept Chem & Biochem, Columbia, SC 29208 USA
关键词
NEAR-INFRARED SPECTROSCOPY; DOWNHOLE-FLUID-ANALYSIS; PARTIAL LEAST-SQUARES; CRUDE OILS; CALIBRATION; PREDICTION; ELEMENT; OPTIMIZATION; REGRESSION; FRACTIONS;
D O I
10.1021/acs.analchem.9b03715
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Multivariate optical computing (MOC) is a compressed sensing technique enabling the measurement of analytes in a complex interfering mixture under harsh conditions. In this work, we describe the design, modeling, fabrication, and validation of a sensor for the measurement of dissolved methane in petroleum crude oil at high and variable combinations of pressure (up to 82.727 MPa) and temperature (up to 121.1 degrees C). Both laboratory and field validation results are presented, with five separate MOC sensors yielding a RMS error of 0.0089 g/cm(3) methane in high pressure/high temperature laboratory and field samples compared to 0.0086 g/cm(3) methane for a room temperature laboratory Fourier transform infrared (FTIR) spectrometer using partial least-squares (PLS) regression models.
引用
收藏
页码:15617 / 15624
页数:8
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