Socio-economic Nexus Investigation on the Future of the Iranian Gas industry

  • Nima Norouzi Energy department, Amirkabir university of technology, Tehran, Iran
Keywords: energy portfolio, energy market, energy trade, energy policy, MAN model, gas industry, scenario planning, natural gas, uncertainty

Abstract

Iran is holding 33.5 billion cubic meters of gas, with an 18% share of oil and gas reservoirs worldwide. Productive hydrocarbon reservoirs are among the most important competitive advantages of Iran and a specific geographic location. In this study, the likely and credible future of Iran’s fossil energy (gas) on the horizon of 2035 is presented in the four-part state. Using the Maleki-Abbaszadeh-Norouzi (MAN) model, among the 300 scenarios, ten scenarios with the maximum adaptability were obtained, which is presented in two scenarios: The eternal blossoming and the Marshland. Moreover, projections show that Iranian gas production reaches 7.8 million barrels of oil equivalent per day in the eternal blossoming and 120 thousand barrels of oil equivalent per day in the Marshland scenario by 2035. This paper shows that the geopolitical status of the Middle East is highly effective in the gas industry.

References

[1] Bao-Jun Tang, Hui-Ling Zhou, Hong Cao, Selection of overseas oil and gas projects under low oil price, Journal of Petroleum Science and Engineering, Volume 156, 2017, Pages 160-166, ISSN 0920-4105, https://doi.org/10.1016/j.petrol.2017.05.022.
[2] Bidabadi, B. &Peykarjou, K. (2010). Simulation and forecasting for universal oil price, Journal of economical: 83-117.
[3] Corrigendum to “Falling oil prices: Causes, consequences and policy implications” [J. Petrol. Sci. Eng. 149 409–427], Journal of Petroleum Science and Engineering, Volume 164, 2018, Page 11, ISSN 0920-4105, https://doi.org/10.1016/j.petrol.2018.01.034.
[4] Deng, J.L. (1989). Introduction to grey system theory. Journal of Grey system, 1(1): 1-24.
[5] Donghui Liu, Lingjie Meng, Yudong Wang, Oil price shocks and Chinese economy revisited: New evidence from SVAR model with sign restrictions, International Review of Economics & Finance, 2020, ISSN 1059-0560, https://doi.org/10.1016/j.iref.2020.04.011.
[6] Faisal Alqahtani, Nahla Samargandi, Ali M. Kutan, The influence of oil prices on the banking sector in oil-exporting economies: Is there a psychological barrier?, International Review of Financial Analysis, Volume 69, 2020, 101470, ISSN 1057-5219, https://doi.org/10.1016/j.irfa.2020.101470.
[7] Frode Kjærland, Fredrik Kosberg, Mathias Misje, Accrual earnings management in response to an oil price shock, Journal of Commodity Markets, 2020, 100138, ISSN 2405-8513, https://doi.org/10.1016/j.jcomm.2020.100138.
[8] Govinda R. Timilsina, Oil prices and the global economy: A general equilibrium analysis, Energy Economics, Volume 49, 2015, Pages 669-675, ISSN 0140-9883, https://doi.org/10.1016/j.eneco.2015.03.005.
[9] Hsu, C ,Wangch. Forecasting the output of integrated circuit industry using a grey model improved by the Bayesian analysis. (2007). Technol forecast socchange . 6, (74): 843-53.
[10] Hui-Wentt, V. Tang. & Mu-Shang, Y., Forecasting performance of grey prediction for education expenditure and school enrollment,(2012). Economic of Education Review, 31: 452-462.
[11] Hsu., Li-Chang,.Using improved grey forecasting models to forecast the output to opto-electronics industry, (2011).Expert systems with applications, 38: 13879-13885.
[12] Hsu, C., Chen, C. Applications of improved grey prediction model for power demand forecasting. (2003). Energy convers manage, 14, ( 44): 2241-9.
[13] Hsu, C. Applying the grey prediction model to the global integration circuit industry.( 2003). Technol forecast sochange, 6, (70): 563-74.
[14] Jinyu Chen, Xuehong Zhu, Hailing Li, The pass-through effects of oil price shocks on China’s inflation: A time-varying analysis, Energy Economics, Volume 86, 2020, 104695, ISSN 0140-9883, https://doi.org/10.1016/j.eneco.2020.104695.
[15] Jianliang Wang, Changran Lei, Meiyu Guo, Daily natural gas price forecasting by a weighted hybrid data-driven model, Journal of Petroleum Science and Engineering, Volume 192, 2020, 107240, ISSN 0920-4105, https://doi.org/10.1016/j.petrol.2020.107240.
[16] Javanmard, Habibollah, Faqidian, Seyedeh Fatemeh. OPEC crude oil price forecast using gray forecasting model. Journal of Economic Modeling, 2014; 8 (27): 91-114.
[17] Khashei,M. Bijari, M. Application hybrid ANNs and fuzzy regressive for gold price forecasting.2012,Journal of industrial engineering, 44, (1): 39-47.
[18] Kurmaş Akdoğan,Fundamentals versus speculation in oil market: The role of asymmetries in price adjustment?, Resources Policy, Volume 67, 2020, 101653, ISSN 0301-4207, https://doi.org/10.1016/j.resourpol.2020.101653.
[19] Kayacan, E,.Ulutas, B. ,.&Kaynak,O., Grey system theory-based model in time series prediction .(2010). Expert systems with applications, 37: 1784-1789.
[20] Liu ,S.F., Buffer operator its application,(1992).Theor.Pract.Grey system. 2: 45-50.
[21] Liu, S.F., Dang, Y.G., & Fang, Z.G. Fang. (2004). Grey system Theory and its application. Third ed. Science press, Beijing.
[22] Lin. ,Yong - Huang ,P. Chan, & Lee , chang,T., Adaptive and high-precision grey forecasting model,(2009). Expert systems with applications, 36: 9658-9662.
[23] Mu-Shang, Y., Hui-wen, Tang,V., On the fit and forecasting performance of grey prediction models for china labor formation,(2013). Mathematical and computer modeling, 57: 357-365.
[24] Makian, Seyed Nezam-ud-Din, Mousavi, Seyed Fatemeh Sadat (2012). Economic Modeling Quarterly, 6 (18): 121-105.
[25] Miller, R. G., & Sorrell, S. R. (2013). The future of oil supply. Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 372(2006), 20130179. https://doi.org/10.1098/rsta.2013.0179
[26] Motunrayo O. Akinsola, Nicholas M. Odhiambo,Asymmetric effect of oil price on economic growth: Panel analysis of low-income oil-importing countries, Energy Reports, Volume 6, 2020, Pages 1057-1066, ISSN 2352-4847, https://doi.org/10.1016/j.egyr.2020.04.023.
[27] Melike Bildirici, Özgür Ömer Ersin,Forecasting oil prices: Smooth transition and neural network augmented GARCH family models, Journal of Petroleum Science and Engineering, Volume 109, 2013, Pages 230-240, ISSN 0920-4105, https://doi.org/10.1016/j.petrol.2013.08.003.
[28] Meysam Naderi, Ehsan Khamehchi, Behrooz Karimi, Novel statistical forecasting models for crude oil price, gas price, and interest rate based on meta-heuristic bat algorithm, Journal of Petroleum Science and Engineering, Volume 172, 2019, Pages 13-22, ISSN 0920-4105, https://doi.org/10.1016/j.petrol.2018.09.031.
[29] Muhammad Imran Khan, Falling oil prices: Causes, consequences and policy implications, Journal of Petroleum Science and Engineering, Volume 149, 2017, Pages 409-427, ISSN 0920-4105, https://doi.org/10.1016/j.petrol.2016.10.048.
[30] Marcelo Nunes Fonseca, Edson de Oliveira Pamplona, Victor Eduardo de Mello Valerio, Giancarlo Aquila, Luiz Célio Souza Rocha, Paulo Rotela Junior, Oil price volatility: A real option valuation approach in an African oil field, Journal of Petroleum Science and Engineering, Volume 150, 2017, Pages 297-304, ISSN 0920-4105, https://doi.org/10.1016/j.petrol.2016.12.024.
[31] Nima Norouzi, Maryam Fani, Zahra Karami Ziarani, The fall of oil Age:A scenario planning approach over the last peak oil of human history by 2040, Journal of Petroleum Science and Engineering, Volume 188, 2020, 106827, ISSN 0920-4105, https://doi.org/10.1016/j.petrol.2019.106827.
[32] Nuket Kirci Cevik, Emrah I. Cevik, Sel Dibooglu, Oil Prices, Stock Market Returns and Volatility Spillovers: Evidence from Turkey, Journal of Policy Modeling, 2020, ISSN 0161-8938, https://doi.org/10.1016/j.jpolmod.2020.01.006.
[33] Pedram, Mehdi, Shirinbakhsh, Shamsullah, Rezaei Abyaneh, Bahareh (2012). Investigating the asymmetric effects of exchange rate fluctuations on the prices of exported goods. Quarterly Journal of Economic Research. (165): 9-143.
[34] Ruey,.Chyn.Tsaur,T. The development of an interval grey regression model for limited time series forecasting. (2010). Expert systems with applications, 37: 1200-1206.
[35] Sufang An, Xiangyun Gao, Haizhong An, Feng An, Qingru Sun, Siyao Liu, Windowed volatility spillover effects among crude oil prices, Energy, Volume 200, 2020, 117521, ISSN 0360-5442, https://doi.org/10.1016/j.energy.2020.117521.
[36] Saud M. Al-Fattah, Non-OPEC conventional oil: Production decline, supply outlook and key implications, Journal of Petroleum Science and Engineering, Volume 189, 2020, 107049, ISSN 0920-4105, https://doi.org/10.1016/j.petrol.2020.107049.
[37] Shang-Lingou,. Forecasting agricultural output with an improved grey forecasting model based on the genetic algorithm. (2012). Computers and Electronics in agriculture, 85: 33-39.
[38] Shahbazi, Kiomars, Asgharpour, Hossein, Moharramzadeh, Karim (2012). The impact of petroleum products on economic growth in the country’s provinces. Journal of Economic Modeling, 6 (17): 44-25.
[39] Sifeng Lin, Lin, Y., Grey Information Theory and Practical Applications, (2006). Springrer-Verlag London Limited.
[40] Shaista Arshad, Syed Aun R. Rizvi, Omair Haroon, Fahad Mehmood, Qiang Gong, Are oil prices efficient?, Economic Modelling, 2020, ISSN 0264-9993, https://doi.org/10.1016/j.econmod.2020.03.018.
[41] Salah A. Nusair, The asymmetric effects of oil price changes on unemployment: Evidence from Canada and the US, The Journal of Economic Asymmetries, Volume 21, 2020, e00153, ISSN 1703-4949, https://doi.org/10.1016/j.jeca.2019.e00153.
[42] Wang.,Chao,.& Hung, Predicting tourism demand using fuzzy time series and hybrid grey theory. (2004). Tourism Management: 367-374.
[43] Wang, Z.L., Liu, S.F., Extension of grey superiority analysis. (2005). IEE Trans. Syst ,Man Cybern.Conf.1: 616-621.
[44] Wen, . KL,et al., Grey system theory and applications .(2009).Wunan Publisher, Taipei.
[45] Wang, J .,.Zhu, S. , Zhao, W.,&Wen,J. Optimal parameters estimation and input subset for grey model based on chaotic particle swarm optimization algorithm, (2011).Expert system with Applications, 38: 8151-8158.
[46] Xiang Zhang, Zongyi Zhang, Han Zhou, Oil price uncertainty and cash holdings: Evidence from China, Energy Economics, Volume 87, 2020, 104732, ISSN 0140-9883, https://doi.org/10.1016/j.eneco.2020.104732.
[47] Xu Gong, Liqiang Chen, Boqiang Lin, Analyzing dynamic impacts of different oil shocks on oil price, Energy, Volume 198, 2020, 117306, ISSN 0360-5442, https://doi.org/10.1016/j.energy.2020.117306.
[48] Norouzi, Nima. “An introduction to the foresight planning”, Lambert academic publisher, 2020, ISBN: 978-620-0-56536-5
[49] Norouzi, Nima; Norouzi, Muhammad. Energy Analysis Framework II: An Introduction to the Energy Economics, Lambert academic publisher, 2020, ISBN: 978-620-0-78611-1
[50] Norouzi, Nima. Energy Analysis Framework: An Introduction to the Energy systems, Lambert academic publisher, 2020, ISBN: 978-620-0-65443-4
[51] Abbaszadeh, P., et al., Iran’s oil development scenarios by 2025. Energy Policy, 2013. 56: p. 612-622.
[52] Silberglitt, R. and S. Kimmel, Energy scenarios for Southeast Asia. Technological Forecasting and Social Change, 2015. 101: p. 251-262.
[53] Bentley, R. and Y. Bentley, Explaining the price of oil 1971–2014: The need to use reliable data on oil discovery and to account for ‘mid-point’ peak. Energy Policy, 2015. 86: p. 880-890.
[54] Ebrahimi, M. and NC. Ghasabani, Forecasting OPEC crude oil production using a variant Multicyclic Hubbert Model. Journal of Petroleum Science and Engineering, 2015. 133: p. 818-823.
[55] Cunado, J., S. Jo, and FP de Gracia, Macroeconomic impacts of oil price shocks in Asian economies. Energy Policy, 2015. 86: p. 867-879.
[56] Grunwald, A., Energy futures: Diversity and the need for assessment. Futures, 2011. 43(8): p. 820-830.
[57] Schoemaker, P.J.H., When and how to use scenario planning: A heuristic approach with illustration. Journal of Forecasting, 1991. 10(6): p. 549-564.
[58] Schoemaker, P.J.H., Multiple scenario development: Its conceptual and behavioral foundation. Strategic Management Journal, 1993. 14(3): p. 193-213.
[59] Jetter, A.J. Educating the guess: strategies, concepts, and tools for the fuzzy front end of product development. in Portland International Center for Management of Engineering and Technology (PICMET). 2003. Portland, OR, USA.
[60] Nawaf S. Alhajeri, Mohannad Dannoun, Abdullah Alrashed, Ahmed Z. Aly, Environmental and economic impacts of increased utilization of natural gas in the electric power generation sector: Evaluating the benefits and trade-offs of fuel switching, Journal of Natural Gas Science and Engineering, Volume 71, 2019, 102969, ISSN 1875-5100, https://doi.org/10.1016/j.jngse.2019.102969.
[61] Mauro Chávez-Rodríguez, Daniela Varela, Fabiola Rodrigues, Javier Bustos Salvagno, Alexandre C. Köberle, Eveline Vasquez-Arroyo, Ricardo Raineri, Gerardo Rabinovich, The role of L.N.G. and unconventional gas in the future natural gas markets of Argentina and Chile, Journal of Natural Gas Science and Engineering, Volume 45, 2017, Pages 584-598, ISSN 1875-5100, https://doi.org/10.1016/j.jngse.2017.06.014.
[62] Giovanni Di Lullo, Abayomi Olufemi Oni, Eskinder Gemechu, Amit Kumar, Developing a greenhouse gas life cycle assessment framework for natural gas transmission pipelines, Journal of Natural Gas Science and Engineering, Volume 75, 2020, 103136, ISSN 1875-5100, https://doi.org/10.1016/j.jngse.2019.103136.
[63] Liping Liu, ByongJae Ryu, Zhilei Sun, Nengyou Wu, Hong Cao, Wei Geng, Xianrong Zhang, Yonggang Jia, Cuiling Xu, Lei Guo, Libo Wang, Monitoring and research on environmental impacts related to marine natural gas hydrates: Review and future perspective, Journal of Natural Gas Science and Engineering, Volume 65, 2019, Pages 82-107, ISSN 1875-5100, https://doi.org/10.1016/j.jngse.2019.02.007.
[64] Mauro F. Chávez-Rodríguez, Rafael Garaffa, Gisela Andrade, Gonzalo Cárdenas, Alexandre Szklo, André F.P. Lucena, Can Bolivia keep its role as a major natural gas exporter in South America?, Journal of Natural Gas Science and Engineering, Volume 33, 2016, Pages 717-730, ISSN 1875-5100, https://doi.org/10.1016/j.jngse.2016.06.008.
[65] Reza Hafezi, AmirNaser Akhavan, Saeed Pakseresht, Projecting plausible futures for Iranian oil and gas industries: Analyzing of historical strategies, Journal of Natural Gas Science and Engineering, Volume 39, 2017, Pages 15-27, ISSN 1875-5100, https://doi.org/10.1016/j.jngse.2016.12.028.
[66] Miao Zhang, Luis F. Ayala, Variable rate and pressure integral solutions to the nonlinear gas diffusivity equation in unconventional systems, Fuel, Volume 235, 2019, Pages 1100-1113, ISSN 0016-2361, https://doi.org/10.1016/j.fuel.2018.08.065.
[67] Avishai Lerner, Michael J. Brear, Joshua S. Lacey, Robert L. Gordon, Paul A. Webley, Life cycle analysis (LCA) of low emission methanol and di-methyl ether (DME) derived from natural gas, Fuel, Volume 220, 2018, Pages 871-878, ISSN 0016-2361, https://doi.org/10.1016/j.fuel.2018.02.066.
[68] G. Maggio, G. Cacciola, When will oil, natural gas, and coal peak?, Fuel, Volume 98, 2012, Pages 111-123, ISSN 0016-2361, https://doi.org/10.1016/j.fuel.2012.03.021.
[69] Toluleke Emmanuel Akinola, Eni Oko, Meihong Wang, Study of CO2 removal in natural gas process using mixture of ionic liquid and MEA through process simulation, Fuel, Volume 236, 2019, Pages 135-146, ISSN 0016-2361, https://doi.org/10.1016/j.fuel.2018.08.152.
[70] Nima Norouzi, Maryam Fani, Zahra Karami Ziarani, The fall of oil Age:A scenario planning approach over the last peak oil of human history by 2040, Journal of Petroleum Science and Engineering, Volume 188, 2020, 106827, ISSN 0920-4105, https://doi.org/10.1016/j.petrol.2019.106827.
[71] Fani, Maryam; Norouzi, Nima, Using Social and Economic Indicators for Modeling, Sensitivity Analysis and Forecasting the Gasoline Demand in the Transportation Sector An ANN Approach in case study for Tehran metropolis, Iranian Journal of Energy, 2019
[72] Nima Norouzi, Ghazal Kalantari, The sun food-water-energy nexus governance model A case study for Iran, Water-Energy Nexus, 2020, ISSN 2588-9125, https://doi.org/10.1016/j.wen.2020.05.005.
Published
2022-06-01
How to Cite
Norouzi, N. (2022). Socio-economic Nexus Investigation on the Future of the Iranian Gas industry. Majlesi Journal of Energy Management, 11(2), 7-22. Retrieved from http://journals.iaumajlesi.ac.ir/em/index/index.php/em/article/view/427
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