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 °C).
Both laboratory and field validation results are presented, with five
separate MOC sensors yielding a RMS error of 0.0089 g/cm3 methane in high pressure/high temperature laboratory and field samples
compared to 0.0086 g/cm3 methane for a room temperature
laboratory Fourier transform infrared (FTIR) spectrometer using partial
least-squares (PLS) regression models.