Identification and Clean-Up of Contaminants From Vaporized NGL CGT Fuel Available to Purchase

This paper describes an analytical approach used to identify heavy natural gas liquid (NGL) fuel components and fuel conditioning solutions employed to prevent fouling of the vaporized fuel delivery systems. The discussion includes high pressure vaporized fuel sampling, isolation of C7+ and C14+ hydrocarbon fractions from NGL, and performance validation of fuel processing apparatus. Saudi Aramco operates more than 80 aeroderivative gas turbines (CGT’s), from four manufacturers, to drive crude oil pumps and generate electrical power on the East-West Pipeline that traverses the Arabian Peninsula. Since the pipeline was first commissioned in 1980, the CGT’s have been operated primarily on vaporized C2+ NGL. Although the properties of this C2+ NGL (such as density and heating value) are nearly identical to propane, its use as CGT fuel has presented challenges. Fuel system fouling resulted from the presence of heavy hydrocarbons including residual surface-active compounds derived primarily from corrosion inhibitors and intermittent crude oil carryover. This fouling consisted of hard, epoxy-like deposits coating all manifolds and fuel nozzle passages downstream of the vaporizers. The entire fleet suffered from increased operating and maintenance costs and reduced reliability from plugging of last-chance filters to blocked fuel nozzles. This led to temperature spreads in combustors and hot component damage. High temperature rated coalescing filters were applied successfully in three vaporized NGL fuel system configurations. One fuel system configuration that required even more stringent fuel conditioning was modified to reject approximately 15 percent (heavy ends fraction) of the NGL. Performance tests were conducted to measure the extent to which heavy ends were reduced in the modified fuel vaporizers. Analytical methods were developed to identify and measure heavy hydrocarbons at ppm concentrations. The actual fuel compositions determined analytically agreed with compositions predicted from process simulations.