November 1998

Instrumentation/Control

Neural networks help optimize solvent extraction

Benefits from this application were worth about $7 million per year

Riddle, A. L., ExxonMobil; Bhat, N. V., Pavilion Technologies, Inc.; Hopper, J. R., Lamar Univeristy

Significant process improvements can be made even on older process units using artificial neural network models. At Mobil's Beaumont, Texas refinery, yields were improved by 8.4% on the light neutral stock and 6.2% on the medium neutral stock. This was achieved with no capital investment and as a result of optimizing a furfural solvent extraction unit in a conventional lubricant refinery. Variability in byproduct quality also decreased. Energy consumption was reduced by 7.7% on light neutral stock and by 2.3% on medium neutral stock. Air emissions were reduced by 6.4%. The benefits of these improvement in the processes are estimated at about $7 million per year. Solvent extraction p

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