نشریه علوم زمین خوارزمی

نشریه علوم زمین خوارزمی

تخمین ضرایب هیدرودینامیک در آبخوان‌های آلوده به نفت

نویسندگان
1 دانشگاه خوارزمی
2 دانشگاه شهید بهشتی
چکیده
یکی از مهمترین نگرانی ها در آبخوان های مجاور به تاسیسات نفتی، آلودگی ناشی از نشت LNAPL ها می باشد. این ترکیبات با توجه به وزن کمترشان نسبت به آب، به صورت لایه در روی سطح آب شناور می­مانند و همراه با جریان آب گسترش پیدا می­کنند. بازیافت LNAPL ها همواره مشکل و پر­هزینه است. این مطالعه قصد دارد با تعیین ضرایب هیدرودینامیکی LNAPL هزینه­های بازیافت را مدیریت نماید. ضرایب هیدرودینامیکی شامل قابلیت انتقال و آبدهی ویژه می باشد. در این مطالعه برای اولین بار بجای عبارت آبدهی ویژه از عبارت نفت دهی ویژه با توجه به نوع سیال موجود در آبخوان، استفاده شده است. برای محاسبه نفت دهی ویژه و حجم کل LNAPL از مدلسازی حجم LNAPL شناور روی سطح ایستابی توسط نرم افزار Rockwork و برای محاسبه ضریب قابلیت انتقال LNAPL از مدل LDRM (LNAPL Distribution and Recovery Model) استفاده شد. بدین صورت که پارامترهای خاک و LNAPL شامل تخلخل، هدایت هیدرولیکی اشباع آب، پارامترهای ونگنوختن، چگالی­های جرمی آب و LNAPL، کشش­های سطحی آب- LNAPL ، LNAPL-هوا و آب- هوا، ویسکوزیتی­های آب وLNAPL به عنوان پارامترهای ورودی به مدل LDRM معرفی شد و ضریب قابلیت انتقال و حجم ویژه قابل استحصال به عنوان نتایج خروجی از آن استخراج گردید. در پایان با کمک نتایج بدست آمده نقشه­های ضریب قابلیت انتقال، ضخامت و حجم قابل استحصال LNAPL تهیه و جهت یافتن بهترین محل­های بازیافت معرفی شدند.
کلیدواژه‌ها

عنوان مقاله English

Estimation of Hydrodynamic Coefficients in Oil-Contaminated Aquifers

نویسندگان English

Fatemeh Ebrahimi 1
Mohammad Nakhaei 1
Hamid Reza Nassery 2
Kamal Khodaei 2
چکیده English

One of the most important concerns in aquifers adjacent to oil facilities is pollution caused by LNAPL leaks. Because these compounds have less weight than water, they float on the surface of the water as a layer and move along with the water flow. Recovery of LNAPLs is always difficult and expensive. This study aims to manage the recovering costs by determining the hydrodynamic coefficients of LNAPL. The hydrodynamic coefficients include transmissivity and specific yield. In this study, for the first time, instead of the term specific yield, the term oil specific yield has been used according to the type of fluid in the aquifer. The Rockwork model was used to calculate the oil specific yield and LDRM (LNAPL Distribution and Recovery Model) model was used to calculate LNAPL transmissivity coefficient. The inputs of the LDRM model include soil and LNAPL parameters, porosity, hydraulic conductivity of water saturation, van Genuchten parameters, mass densities of water and LNAPL, surface tensions of water-LNAPL, LNAPL-air and water-air, viscosities of water and LNAPL. From the inputs, LNAPL transmissivities and recoverable and total LNAPL specific volumes were extracted as output results. With the help of the obtained results, maps of LNAPL transmissivities, thickness and recoverable volume of LNAPL were prepared and the best recovery locations were introduced.

کلیدواژه‌ها English

Hydrodynamic Coefficients
Oil Specific Yield
LNAPL Transmissivity
LDRM Model
Abedi Koupai, J., Gholabchian, M., 2015. Estimation of Hydrodynamic Parameters of Groundwater Resources in Kouhpayeh- Segzi Watershed Using Modflow. Water and Soil Science (Journal of Science and Technology of Agriculture and Natural Resources). 19 (72) 281-292. In Persian.
Maleki, R., Karmi, G., Davali Ardjani, F., Hosseini, H. and Asadian, F., 2010. Optimization of hydrodynamic coefficients of Shahroud Plain using GMS model, 4th Iran Water Resources Management Conference, Amirkabir University of Technology, Tehran.
Abriola, L.M., Pinder, G.F., 1985. A multiphase approach to the modeling of porous media contamination by organic compounds, 2, Numerical simulation. Water Resources Research, 21: 19-26.
API (American Petroleum Institute)., 2007. LNAPL Distribution and Recovery Model (LDRM). Volume 1: Distribution and Recovery of Petroleum Hydrocarbon Liquids in Porous Media. API Publ. No. 4760. Washington, DC: American Petroleum Institute.
Asghari Moghaddam, A., Allaf Najib, M., 2006. Hydrogeologic characteristics of the alluvial tuff aquifer of northern Sahand Mountain slopes, Tabriz, Iran. Hydrogeology Journal 14(7): 1319–1329.
Baehr, A.L., Corapcioglu, M.Y., 1987. A compositional multiphase model for groundwater contamination by petroleum products, 2, Numerical solution. Water Resources Research, 23: 201-214.
Bateni, S. M., Mortazavi-Naeini, M., Ataie-Ashtiani, B., Jeng, D, S., Khanbilvardi, R., 2015. Evaluation of methods for estimating aquifer hydraulic parameters. Applied Soft Computing 28, 541–549.
Chesnaux, R., Rafini, S., Elliott, A-P., 2012. A numerical investigation to illustrate the consequences of hydraulic connections between granular and fractured-rock aquifers”, Hydrogeology Journal 20(8): 1669–1680.
Dokou, Z., Karatzas, G.P., 2013. Multi-objective optimization for free-phase LNAPL recovery using evolutionary computation algorithms. Hydrological Sciences Journal, 58: 671-685.
Don, N.C., Araki, H., Yamanishi, H. and Koga, K., 2005. Simulation of groundwater flow and environmental effects resulting from pumping. Environmental Geology. 47:361-374.
Ebrahimi, F., Lenhard, R.J., Nakhaei, M., Nassery, H.R., 2019. An approach to optimize the location of LNAPL recovery wells using the concept of a LNAPL specific yield. Environ Sci Pollut Res. pp 1-11. https://doi.org/10.1007/s11356-019-06052-7.
Ebrahimi, F., Nakhaei, M., Nassery, H.R., Khodaei, K., Kisi, O., 2019. Light non-aqueous phase liquids simulation using artificial intelligence models: Esmaeilabad aquifer case study. Groundwater for Sustainable Development, 8: 245-254.
El Harrouni, K. D., Ouazar, G.A., Walters, A.H.D., Cheng., 1996. Groundwater opti-mization and parameter estimation by genetic algorithm and dual reciprocity boundary element method”, Eng. Anal. Bound. Elem. 18: 287–296.
Elsheikh, A.E.M., Elsayed Zeielabdein, K.A., Babikir, I.A.A., 2009. Groundwater balance in the Khor Arbaat basin, Red Sea State, eastern Sudan. Hydrogeology Journal 17(8): 2075–2082.
Ghafoori Kharanagh, S., 2012 .Selection of suitable method to estimate the aquifer hydrodynamic coefficients”, M.Sc. thesis, University of Tehran.
Jalludin, M., Razack, M., 2004. Assessment of hydraulic properties of sedimentary and volcanic aquifer systems under arid conditions in the Republic of Djibouti (Horn of Africa). Hydrogeology Journal 12(2): 159–170.
Jha, M. k., Kumar, A., Nanda, G., Bhatt, G., 2006. Evaluation of traditional and non-traditional optimization techniques for determining well parameters from step-drawdown test data”, J. Hydrol. Eng, 11: 617–630.
Kaluarachchi, J.J., Parker, J.C., 1989. An efficient finite element method for modeling multiphase flow in porous media. Water Resources Research, 25: 43-54.
Kresic, N., 2007. Hydrogeology and groundwater modeling, 2ed. CRC Press. 830pp.
Kuppusamy, T., Sheng, J., Parker, J.C., Lenhard, R.J., et al., 1987. Finite element analysis of multiphase immiscible flow through soils. Water Resources Research, 23: 625-631.
Lenhard, R.J., Rayner, J.L., Davis, G.B., et al., 2017. A practical tool for estimating subsurface LNAPL distributions and transmissivity using current and historical fluid levels in groundwater wells: Effects of entrapped and residual LNAPL. Journal of Contaminant Hydrology, 205: 1-11.
Li, Y., A.B.C. Hilton., 2006. An algorithm for groundwater long-term monitoring spa-tial optimization by analogy to Ant Colony Optimization for TSP, in: World Environmental and Water Resource Congress, pp. 1–6.
Lingireddy, S., 1998. Aquifer parameter estimation using genetic algorithms and neu-ral networks, Civil Eng. Environ. Syst. 15: 125–144.
Mirabbasi, R. and Rahnama, M.B., 2008. The impact of construction of Tangooye dam on the groundwater resources by simulation of Sirjan plain aquifer using Modflow software. Iranian Water Research Journal. 1(1):1-9.
Mokhtari, H., Espahbod, H., 2009. The investigation of hydrodynamic parameters potentiality of the Varamin plain regarding the variation of salinity gradient. Journal of Geoscience. 4(2) 27-47.
Nasimi. A, Mohammadi. Z., 2015. Evaluation of methods for determination of hydrodynamic coefficients of aquifer based on pumping test in Fars province, Journal of Water and Soil Science. 25 (2/4) 201-215.
Pruess, K., Battistelli, A., 2005. TMVOC, A Numerical Simulator for Three-Phase Non-isothermal Flows of Multicomponent Hydrocarbon Mixtures in Variably Saturated Heterogeneous Media. Lawrence Berkeley National Laboratory. Retrieved from https://escholarship.org/uc/item/3n95k4nm
Qin, X., Huang, G., Yu, H., et al., 2009a. Enhancing remediation of LNAPL recovery through a response-surface-based optimization approach. Journal of Environmental Engineering, 135: 999-1008.
Qin, X.S., Huang, G.H., He, L., et al., 2009b. Simulation and optimization technologies for petroleum waste management and remediation process control. Journal of Environmental Management, 90: 54-76.
Rajesh, M., Kashyap, D., Hari Prasad, K. S., 2010. Estimation of unconfined aquifer parameters by genetic algorithms”, Hydrol. Sci. J, 55: 403–413.
Rohallahi, A., 2011. Estimation of hydrodynamic coefficients of free aquifers using genetic algorithm optimization method”, M.Sc. thesis, Faculty of Agriculture, Water Engineering Department, Birjand University.
Samuel, M., Jha, M., 2003. Estimation of aquifer parameters from pumping test data by genetic algorithm optimization technique”, J. Irrigat. Drain. Eng, 129: 348–359.
Sookhak Lari, K., Johnson, C.D., Rayner, J.L., Davis, G.B., et al., 2018. Field-scale multi-phase LNAPL remediation: Validating a new computational framework against sequential field pilot trials. Journal of Hazardous Materials, 345: 87-96.
Sookhak Lari, K., Rayner, J. L., & Davis, G. B., et al., 2019. Toward optimizing LNAPL remediation. Water Resources Research, https://doi.org/10.1029/2018WR023380.
Thorley, M., Callander, P., 2005. Christchurch city groundwater model”, Environment Canterbury report, U05/53. pp: 10.
Yitbarek Baye, A., Razack, M., Ayenew, T., Zemedagegnehu E., 2013. Estimating transmissivity using empirical and geostatistical methods in the volcanic aquifers of Upper Awash Basin central Ethiopia”, Environmental Earth Sciences, 69 (6)1791–1802.