(401d) Multiobjective Optimization for BTEX Emission Mitigation from TEG Dehydration Process

Rajib Mukherjee^1,2,3*, Urmila M Diwekar², Mahmoud M El-Halwagi^3,4

¹Department of Chemical Engineering, University of Texas Permian Basin, Odessa, TX

²Vishwamitra Research Institute, Crystal Lake, Illinois, 60012

³Gas & Fuels Research Center, Texas A&M Engineering Experiment Station, College Station, TX

⁴Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX

Abstract

Natural gas processing involves removal of acidic gases that includes CO2 and H2S (also known as sweetening process) followed by dehydration [1]. The dehydration is primarily carried out through absorption in triethyl glycol (TEG) in an absorption column. During the dehydration process, aromatics including benzene, toluene, ethyl benzene and xylene isomers (BTEX) and other volatile organic compounds (VOCs) present in natural gas are absorbed by the glycol solvent. The process regenerates TEG in a stripping column and circulated. In this thermal regeneration process as well as flash tank, substantial amount of the BTEX and VOCs are emitted to the atmosphere along with the acidic gases. Emission of BTEX and VOC has adverse environmental as well as health impact, leading to strict regulations [2]. Effective mitigation of the emission process is essential for natural gas industry. There are several process parameters associated with major equipment that may impact BTEX emission including TEG circulation rate, absorber pressure, inlet glycol temperature, flash gas pressure, reboiler temperature, glycol reflux ratio [3]. Some of these parameters are found to have an adverse impact on dehydration process, leading to an increased emission in order to achieve low dry gas water content. In this work, a multiobjective optimization is performed to find the optimal operating condition related to the process parameters to mitigates BTEX emission. The optimization is performed using data driven modeling and a novel metaheuristic algorithm; efficient ant colony optimization (EACO) for optimization [4, 5]. The surrogate model is generated from data obtained from process simulation for the selected technologies carried out in ProMax [6]. The result shows that BTEX release can be mitigated through optimal TEG circulation rate, reboiler temperature and glycol reflux ratio and inlet glycol temperature while fulfilling the constraint for the dry gas water content required for subsequent cryogenic NGL recovery process.

Keywords: Shale gas processing, TEG dehydration, BTEX mitigation, surrogate model, efficient ant colony optimization

[1] Reddy Asani, R., Mukherjee, R., El-Halwagi, M. M., (2019), “Optimal Selection of Shale Gas Processing and NGL Recovery Plant from Multiperiod Simulation”, In preparation

[2] Rueter, C. O., Reif, D. L., Menzies, W. R., & Evans, J. M. (1996). Measurement and enhanced monitoring of BTEX and VOC emissions from glycol dehydrators. SPE Advanced Technology Series, 4(02), 13-22.

[3] Braek, A. M., Almehaideb, R. A., Darwish, N., & Hughes, R. (2001). Optimization of process parameters for glycol unit to mitigate the emission of BTEX/VOCs. Process Safety and Environmental Protection, 79(4), 218-232.

[4] Ibrahim, M., Al-Sobhi, S., Mukherjee, R., & AlNouss, A. (2019). Impact of Sampling Technique on the Performance of Surrogate Models Generated with Artificial Neural Network (ANN): A Case Study for a Natural Gas Stabilization Unit. Energies, 12(10), 1906.

[5] Gebreslassie, B. H., & Diwekar, U. M. (2015). Efficient ant colony optimization for computer aided molecular design: Case study solvent selection problem. Computers & Chemical Engineering, 78, 1-9.

[6] Mukherjee, R., Reddy Asani, R., El-Halwagi, M. M., (2019), “Optimal Design of Shale Gas Processing and NGL Recovery Plant under Feed Stream Composition Uncertainty”, In preparation