A Stepwise-Inference-Based Optimization System for Supporting Remediation of Petroleum-Contaminated Sites

X. S. Qin
Faculty of Engineering, University of Regina, Regina, Canada
G. H. Huang
Chinese Research Academy of Environmental Science, Anwai, Beijing, P.R. China
A. Chakma
Department of Chemical Engineering, University of Waterloo,Waterloo, Ontario, Canada

In real-world applications, the subsurface conditions are mostly heterogeneous and anisotropic. The simulation-regression-optimization approach works better if the necessary parameters are known. Thus, the solutions from the optimization models are only meaningful when sufficient site characterization data are available. Moreover, it is desirable that further verifications be conducted through comparing the results from regression-based forecasting system with those from observed production data or monitored operational system-response data.


Mansfield, C. M., Shoemaker, C. A., & Liao, L. Z. (1998). Utilizing sparsity in time-varying optimal control of aquifer cleanup. Journal of Water Resources Planning and Management, ASCE, 124(1), 15–21.
Bayer, P., & Finkel, M. (2004). Evolutionary algorithms for the optimization of advective control of contaminated aquifer zones. Water Resources Research, 40(W06506, DOI 10.1029/ 2003WR002675.
Borkowski, A., & Grabska, E. (2001). Graphs in layout optimization. In C. J. Anumba, O. O. Ugwu, & Z. Ren (Eds.), Artificial Intelligence in Construction and Structural Engineering. Proceedings of the 8th International Workshop of the European Group of Structural Engineering. Applications of Artificial Intelligent (EG-SEA-AI). ISBN 1 897811 24 6 (pp. 114–121). Loughborough University.
Chang, L. C., Shoemaker, C. A., & Liu, P. L. (1992). Optimal time-varying pumping rates for groundwater remediation: Application of a constrained optimal control algorithm. Water Resources Research, 28(12), 3157–3174.
Chen, Z., Huang, G. H., & Chakma, A. (1998). Integrated environmental risk assessment for petroleum-contaminated sites: A North American case study. Water Science and Technology, 38(4/5), 131–138, 296.
Chipperfield, A. J., Fleming, P. J., Pohleim, H., & Fonseca, C. M. (1994). Genetic Algorithm Toolbox User’s Guide, ACSE Research Report No. 512, University of Sheffield.
Culver, T., & Shoemaker, C. A. (1992). Dynamic optimal control for groundwater remediation with flexible management periods. Water Resources Research, 28(3), 629–641.

McKinney, D. C., & Lin, M. D. (1996). Pump-and-treat groundwater remediation system optimization. Journal of Water Resources Planning and Management, ASCE, 122 (2), 128–136.
DAEM (Draper Aden Environmental Modeling Inc.) (1997). MOVER Multiphase Organic Vacuum Enhanced Recovery Simulator: Technical Documentation & User Guide. Blacksburg, VA: Draper Aden Environmental Modeling Inc.
Davis, L. (1991). Handbook of genetic algorithms. New York: Van Norstrand Reinhold.
De Blanc, P. C. (1998). Development and demonstration of a biodegradation model for non-aqueous phase liquids in groundwater, Ph.D. dissertation, The University of Texas at Austin, USA.
Dougherty, D. E., & Marryott, R. (1991). Optimal groundwater management, 1, Simulated annealing. Water Resources Research, 19(2), 305–319.
Faust, C. R., Guswa, J. H., & Mercer, J. W. (1989). Simulation of three-dimensional flow of immiscible fluids within and below the unsaturated zone. Water Resources Research, 25 (12), 2449–2464.
Gallichand, J., Prasher, S. O., Broughton, R. S., & Marcotte, D. (1991). Kriging of hydraulic conductivity for subsurface drainage design. Journal of Irrigation and Drainage Engineering, 117(5), 667–681.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning. Reading, Mass: Addison-Wesley.
Holland, J. H. (1975). Adaptation in natural and artificial systems. Ann Arbor: University of Michigan Press.
Huang, G. H., & Chang, N. B. (2003). The perspectives of environmental informatics and systems analysis. Journal of Environmental Informatics, 1(1), 1–7.
Huang, Y. F., Huang, G. H., Chakma, A., Maqsood, I., Chen, B., Li, J. B., et al. (2007). Remediation of petroleumcontaminated sites through simulation of a DPVE-aided cleanup process: Part 1. model development. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 29(4), 347–365.
Huang, G. H., Huang, Y. F., Wang, G. Q., & Xiao, H. N. (2006). Development of a forecasting system for supporting remediation design and process control based on NAPL-biodegradation simulation and stepwise-cluster analysis. Water Resources Research, 42(6), W06413.
Huang, Y. F., Li, J. B., Huang, G. H., Chakma, A., & Qin,  X. S. (2003). An integrated simulation–optimization approach for real time dynamic modeling and process control of surfactant enhanced remediation at petroleum contaminated site. Practice Periodical of Hazardous, Toxic, and Radioactive Waste Management (ASCE), 7(2), 95–105.
Katyal, A. K. (1992). MOTRANS: A finite element model for multiphase organic chemical flow and multispecies transport, technical and user’s guide. Blacksburg, VA: Draper Aden Environmental Modeling, Inc.
Kennedy,W. J., & Gentle, J. E. (1981). Statistics: Textbooks and monographs (pp. 200–270). New York: Marcel Dekker.
Kim, B., Steele, K. F., & Fugitt, T. (2006). Comparison of dissolved and acid-extractable metal concentrations of ground water, Eastern Arkansas, USA. Journal of Environmental Informatics, 7(2), 56–65.
Li, J. B., Huang, G. H., Chakma, A., & Zeng, G. M. (2003). Numerical simulation of dual phase vacuum extraction to remove non-aqueous phase liquids in subsurface. Practice Periodical of Hazardous, Toxic, and Radioactive Waste Management (ASCE), 7(2), 106–113.
Liu, L. (2005). Modeling for surfactant-enhanced groundwater remediation processes at DNAPLs-contaminated sites. Journal of Environmental Informatics, 5(2), 42–52.
Mccray, J. E., & Falta, R. W. (1997). Numerical simulation of air sparging for remediation of NAPL contamination. Ground Water, 35(1), 99–110.
Minsker, B. S., & Shoemaker, C. A. (1998). Computational issues for optimal in situ bioremediation design. Journal of Water Resources Planning and Management, ASCE, 124, 39–46.
Morshed, J., & Kaluarachchi, J. J. (1998). Parameter estimation using artificial neural network and genetic algorithm for free-product migration and recovery. Water Resources Research, 34(5), 1101–1113.
O’melia, B. C., & Parson, D. R. (1996). Dual-phase vacuum extraction technology for soil and ground-water remediation: A case study. In W. Wang, J. Schnoor, & J. Doi (Eds.), Volatile Organic Compounds in the Environment, ASTM STP 1261. American Society for Testing and Materials, 272–286.
Parker, B. L., Gillham, R. W., & Cherry, J. A. (1994). Diffusive disappearance of immiscible-phase organic liquids in fractured geologic media. Ground Water, 32(5), 805–820.
Perry, R. H., & Green, D. (Eds.) (1984). Perry’s chemical engineers’ handbook (6th ed.). New York: McGraw-Hill.
Qin, X. S., Huang, G. H., Chakma, A., Chen, B., & Zeng, G.M. (2007). Simulation-based process optimization for surfactant-enhanced aquifer remediation at heterogeneous DNAPL-contaminated sites. Science of the Total Environment. DOI 10.1016/j.scitotenv.2007.04.011.
Rao, C. R. (1965). Linear statistical inference and its applications (pp. 239–301). New York: Wiley.
Rathfelder, K. M., Lang, J. R., & Abriola, L. M. (2000). A numerical model MISER for the simulation of coupled physical, chemical and biological processes in soil vapor extraction and bioventing systems. Journal of Contaminant Hydrology, 43, 239–270.
Tatsuoka, M. M. (1971). Multivariate analysis (pp. 38–197). New York: Wiley. USACE (United States Army Corps of Engineers) (1999). Engineering and design – multi-phase extraction. EM 1110-1-4010, Washington, DC.
USEPA (1990). State of technology review: Soil vapor extraction system technology. Cincinnati, OH: Hazardous Waste Engineering Research Laboratory. EPA/600/2-89/024.
Wilks, S. S. (1963). Statistical inference in geology. In T. W. Anderson (Ed.), Contributions to mathematical statistics (pp. 112–128). New York: Wiley.
Yen, H. K., Chang, N. B., & Lin, T. F. (2003). Bioslurping model for assessing light hydrocarbon recovery in contaminated unconfined aquifer, I: simulation analysis. Practice Periodical of Hazardous, Toxic, and Radioactive Waste Management, 7(2), 114–130.

Ahlfeld, D. P. (1990). Two-stage ground-water remediation design. Journal of Water Resources Planning and Management, ASCE, 116(4), 517–529.

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