Mathematics optimization models for downstream and midstream petroleum sectors. Literature review and future research directions
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Published:
Jul 30, 2020
Keywords:
Integer linear program, Supply Chain, downstream, midstream, hydrocarbons
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Abstract
This article resumes a literature review about Integer Linear and No-linear programming models (MILP and MINLP) applied to petroleum supply chain, especially for Downstream and Midstream sectors. These sectors work in the hydrocarbons’ production, tailored and distribution for final uses, such as intermediate distillates and LPG. The aim of this research is contrast different research articles of operations research, especially which considered multiproduct pipeline transport. The main aim of this article has focused on a future approach of research for petroleum supply chain in the Downstream and Midstream sectors. Of the articles analyzed, the 32 articles tailored a MILP, about of 26 tailored a fuel`s distribution structure in Downstream sector. There is not evidence of MILP and MINLP researched in Ecuador. Finally, discuses about futures lines of research in this topic, such as applied a MILP for operative programing in multi-products pipelines network of Ecuador’s petroleum supply chain. Tools that in the future will lead take effectives decisions a tactic and operative level, considered whole variables in the distributions multi-products pipelines network for satisfied the demand.
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Morales, J., Quitiaquez, W., & Simbaña, I. (2020). Mathematics optimization models for downstream and midstream petroleum sectors. Literature review and future research directions. Revista Técnica "energía", 17(1), PP. 103–111. https://doi.org/10.37116/revistaenergia.v17.n1.2020.398
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PRODUCCIÓN Y USO DE LA ENERGÍA
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La Revista Técnica "energía" está bajo licencia internacional Creative Commons Reconocimiento-NoComercial 4.0.
References
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[10] Sciences direct, «40,021 Search Results – Keywords (supply chain petroleum) - ScienceDirect». [En línea]. Disponible en: https://bibliotecas.ups.edu.ec:2230/search/advanced?qs=supply%20chain%20petroleum&show=50&sortBy=relevance. [Accedido: 10-nov-2019].
[11] «Oilfield Glossary en español - Schlumberger Oilfield Glossary». [En línea]. Disponible en: https://www.glossary.oilfield.slb.com/es.aspx. [Accedido: 11-nov-2019].
[12] J.-P. Favennec, «Petroleum Refining. Vol. 5 Refinery Operation and Management», en Petroleum Refining, 2001.
[13] G. Towler y R. K. Sinnott, «12.11 Mixed Integer Programming», en Chemical Engineering Design - Principles, Practice and Economics of Plant and Process Design, 2da edition., Elsevier, 2013.
[14] A. Fragkogios y G. K. D. Saharidis, «Modeling and Solution Approaches for Crude Oil Scheduling in a Refinery», en Energy Management—Collective and Computational Intelligence with Theory and Applications, C. Kahraman y G. Kayakutlu, Eds. Cham: Springer International Publishing, 2018, pp. 251-275.
[15] P. Popescu, «Software Implementation for Optimization of Production Planning within Refineries», Econ. Insights – Trends Chall, vol. VII(LXX), no 1, pp. 1-10, 2018.
[16] B. Hong et al., «An integrated MILP method for gathering pipeline networks considering hydraulic characteristics», Chemical Engineering Research and Design, vol. 152, pp. 320-335, 2019.
[17] C. Bian, H. Li, F. Wallin, A. Avelin, L. Lin, y Z. Yu, «Finding the optimal location for public charging stations – a GIS-based MILP approach», Energy Procedia, vol. 158, pp. 6582-6588, 2019.
[18] B. Wang, Y. Liang, J. Zheng, R. Qiu, M. Yuan, y H. Zhang, «An MILP model for the reformation of natural gas pipeline networks with hydrogen injection», International Journal of Hydrogen Energy, vol. 43, n.o 33, pp. 16141-16153, 2018.
[19] Q. Liao, Y. Liang, N. Xu, H. Zhang, J. Wang, y X. Zhou, «An MILP approach for detailed scheduling of multi-product pipeline in pressure control mode», Chemical Engineering Research and Design, vol. 136, pp. 620-637, 2018.
[20] H. Chen et al., «Optimizing detailed schedules of a multiproduct pipeline by a monolithic MILP formulation», Journal of Petroleum Science and Engineering, vol. 159, pp. 148-163, 2017.
[21] Q. Liao, H. Zhang, N. Xu, Y. Liang, y J. Wang, «A MILP model based on flowrate database for detailed scheduling of a multi-product pipeline with multiple pump stations», Computers & Chemical Engineering, vol. 117, pp. 63-81, 2018.
[22] H. Zhang, Y. Liang, J. Ma, C. Qian, y X. Yan, «An MILP method for optimal offshore oilfield gathering system», Ocean Engineering, vol. 141, pp. 25-34, 2017.
[23] X. Zhou et al., «A MILP model for the detailed scheduling of multiproduct pipelines with the hydraulic constraints rigorously considered», Computers & Chemical Engineering, vol. 130, p. 106543, 2019.
[24] B. Wang, Y. Liang, T. Zheng, M. Yuan, y H. Zhang, «Optimisation of a downstream oil supply chain with new pipeline route planning», Chemical Engineering Research and Design, vol. 145, pp. 300-313, 2019.
[25] A. Siddiqui, M. Verma, y V. Verter, «An integrated framework for inventory management and transportation of refined petroleum products: Pipeline or marine? », Applied Mathematical Modelling, vol. 55, pp. 224-247, 2018.
[26] T. A. Albahri, C. S. Khor, M. Elsholkami, y A. Elkamel, «A mixed integer nonlinear programming approach for petroleum refinery topology optimisation», Chemical Engineering Research and Design, vol. 143, pp. 24-35, 2019.
[27] Y. Wang, S. F. Estefen, M. I. Lourenço, y C. Hong, «Optimal design and scheduling for offshore oil-field development», Computers & Chemical Engineering, vol. 123, pp. 300-316, 2019.
[28] L. S. Assis, E. Camponogara, B. C. Menezes, y I. E. Grossmann, «An MINLP formulation for integrating the operational management of crude oil supply», Computers & Chemical Engineering, vol. 123, pp. 110-125, 2019.
[29] M. K. Almedallah y S. D. C. Walsh, «A numerical method to optimize use of existing assets in offshore natural gas and oil field developments», Journal of Natural Gas Science and Engineering, vol. 67, pp. 43-55, 2019.
[30] A. M. Attia, A. M. Ghaithan, y S. O. Duffuaa, «A multi-objective optimization model for tactical planning of upstream oil & gas supply chains», Computers & Chemical Engineering, vol. 128, pp. 216-227, 2019.
[31] R. E. Franzoi, B. C. Menezes, J. D. Kelly, y J. A. W. Gut, «Design for Online Process and Blend Scheduling Optimization», en Proceedings of the 9th International Conference on Foundations of Computer-Aided Process Design, vol. 47, S. G. Muñoz, C. D. Laird, y M. J. Realff, Eds. Elsevier, 2019, pp. 187-192.
[32] M. Quinteros, M. Guignard, A. Weintraub, M. Llambias, y C. Tapia, «Optimizing the pipeline planning system at the national oil company», European Journal of Operational Research, vol. 277, n.o 2, pp. 727-739, 2019.
[33] S. Xin et al., «A two-stage strategy for the pump optimal scheduling of refined products pipelines», Chemical Engineering Research and Design, vol. 152, pp. 1-19, 2019.
[34] F. Bayu, D. Panda, M. A. Shaik, y M. Ramteke, «Scheduling of Gasoline Blending and Distribution using Graphical Genetic Algorithm», Computers & Chemical Engineering, p. 106636, 2019.
[35] R. Qiu et al., «A multi-scenario and multi-objective scheduling optimization model for liquefied light hydrocarbon pipeline system», Chemical Engineering Research and Design, vol. 141, pp. 566-579, 2019.
[36] H. Zhang, Y. Liang, Q. Liao, J. Gao, X. Yan, y W. Zhang, «Mixed-time mixed-integer linear programming for optimal detailed scheduling of a crude oil port depot», Chemical Engineering Research and Design, vol. 137, pp. 434-451, 2018.
[37] A. Zaghian y H. Mostafaei, «An MILP model for scheduling the operation of a refined petroleum products distribution system», Operational Research, vol. 16, n.o 3, pp. 513-542, oct. 2016.
[38] W. Abdellaoui, A. Berrichi, D. Bennacer, F. Maliki, y L. Ghomri, «Optimal Scheduling of Multiproduct Pipeline System Using MILP Continuous Approach», en Computational Intelligence and Its Applications, Cham, 2018, pp. 411-420.
[39] H. Qu, J. Xu, S. Wang, y Q. Xu, «A novel MINLP model of front-end crude scheduling for refinery with consideration of inherent upset minimization», Computers & Chemical Engineering, vol. 117, pp. 42-62, 2018.
[40] T. Kirschstein, «Planning of multi-product pipelines by economic lot scheduling models», European Journal of Operational Research, vol. 264, n.o 1, pp. 327-339, 2018.
[41] H.-R. Zhang, Y.-T. Liang, Q. Liao, J. Ma, y X.-H. Yan, «An MILP approach for detailed scheduling of oil depots along a multi-product pipeline», Petroleum Science, vol. 14, n.o 2, pp. 434-458, may 2017.
[42] V. R. Rosa, E. Camponogara, y V. J. M. F. Filho, «Design optimization of oilfield subsea infrastructures with manifold placement and pipeline layout», Computers & Chemical Engineering, vol. 108, pp. 163-178, 2018.
[43] M. Jalanko y V. Mahalec, «Supply-demand pinch based methodology for multi-period planning under uncertainty in components qualities with application to gasoline blend planning», Computers & Chemical Engineering, vol. 119, pp. 425-438, 2018.
[44] O. Akgul, N. Shah, y L. G. Papageorgiou, «An MILP Model for the Strategic Design of the UK Bioethanol Supply Chain», en 21st European Symposium on Computer Aided Process Engineering, vol. 29, E. N. Pistikopoulos, M. C. Georgiadis, y A. C. Kokossis, Eds. Elsevier, 2011, pp. 1799-1803.
[45] A. Bittante, F. Pettersson, y H. Saxén, «Optimization of a small-scale LNG supply chain», Energy, vol. 148, pp. 79-89, 2018.
[46] P. Gutiérrez et al, «Análisis Nodal para determinar el punto óptimo de operación entre producción de petróleo y producción de GLP, maximizando el recurso energético de la Estación de producción de Petróleo, Aguarico», Revista Técnica "energía", Edición No. 16, Vol. 16 Núm. 2 (2020).
[47] S. Golla et al, «Primer Estudio para una Transición Energética Completa y Sostenible para Ecuador “El Fin del Petróleo”», Revista Técnica “energía”. No. 14, Pp. 246-255.
[48] Susana Relvas and Suelen N. et al, «Integrated scheduling and inventory management of an oil products distribution system», Revista Omega. No. 6, Pp. 955 - 968.
[2] M. Govil y J.-M. Proth, «Supply Chain Design and Management Strategic and Tactical Perspectives», en Supply Chain Design and Management, M. Govil y J.-M. Proth, Eds. San Diego: Academic Press, 2002, pp. 1-6.
[3] S. M. Saad, E. H. Elsaghier, y D. Ezaga, «Planning and optimising petroleum supply chain», Procedia Manufacturing, vol. 17, pp. 803-810, ene. 2018.
[4] N. Moradinasab, M. R. Amin-Naseri, T. J. Behbahani, y H. Jafarzadeh, «Competition and cooperation between supply chains in multi-objective petroleum green supply chain: A game theoretic approach», Journal of Cleaner Production, vol. 170, pp. 818-841, 2018.
[5] X. Zhang y H. M. A. U. Yousaf, «Green supply chain coordination considering government intervention, green investment, and customer green preferences in the petroleum industry», Journal of Cleaner Production, p. 118984, 2019.
[6] R. G. Siwi, F. Aljumah, J. Li, y X. Xao, «Optimal Strategic Planning of Integrated Petroleum and Petrochemical Supply Chain», en 28th European Symposium on Computer Aided Process Engineering, vol. 43, A. Friedl, J. J. Klemeš, S. Radl, P. S. Varbanov, y T. Wallek, Eds. Elsevier, 2018, pp. 1201-1206.
[7] M. Farahani y D. Rahmani, «Production and distribution planning in petroleum supply chains regarding the impacts of gas injection and swap», Energy, vol. 141, pp. 991-1003, 2017.
[8] K. Tong, F. You, y G. Rong, «Robust design and operations of hydrocarbon biofuel supply chain integrating with existing petroleum refineries considering unit cost objective», Computers & Chemical Engineering, vol. 68, pp. 128-139, 2014.
[9] H. An, W. E. Wilhelm, y S. W. Searcy, «Biofuel and petroleum-based fuel supply chain research: A literature review», Biomass and Bioenergy, vol. 35, n.o 9, pp. 3763-3774, 2011.
[10] Sciences direct, «40,021 Search Results – Keywords (supply chain petroleum) - ScienceDirect». [En línea]. Disponible en: https://bibliotecas.ups.edu.ec:2230/search/advanced?qs=supply%20chain%20petroleum&show=50&sortBy=relevance. [Accedido: 10-nov-2019].
[11] «Oilfield Glossary en español - Schlumberger Oilfield Glossary». [En línea]. Disponible en: https://www.glossary.oilfield.slb.com/es.aspx. [Accedido: 11-nov-2019].
[12] J.-P. Favennec, «Petroleum Refining. Vol. 5 Refinery Operation and Management», en Petroleum Refining, 2001.
[13] G. Towler y R. K. Sinnott, «12.11 Mixed Integer Programming», en Chemical Engineering Design - Principles, Practice and Economics of Plant and Process Design, 2da edition., Elsevier, 2013.
[14] A. Fragkogios y G. K. D. Saharidis, «Modeling and Solution Approaches for Crude Oil Scheduling in a Refinery», en Energy Management—Collective and Computational Intelligence with Theory and Applications, C. Kahraman y G. Kayakutlu, Eds. Cham: Springer International Publishing, 2018, pp. 251-275.
[15] P. Popescu, «Software Implementation for Optimization of Production Planning within Refineries», Econ. Insights – Trends Chall, vol. VII(LXX), no 1, pp. 1-10, 2018.
[16] B. Hong et al., «An integrated MILP method for gathering pipeline networks considering hydraulic characteristics», Chemical Engineering Research and Design, vol. 152, pp. 320-335, 2019.
[17] C. Bian, H. Li, F. Wallin, A. Avelin, L. Lin, y Z. Yu, «Finding the optimal location for public charging stations – a GIS-based MILP approach», Energy Procedia, vol. 158, pp. 6582-6588, 2019.
[18] B. Wang, Y. Liang, J. Zheng, R. Qiu, M. Yuan, y H. Zhang, «An MILP model for the reformation of natural gas pipeline networks with hydrogen injection», International Journal of Hydrogen Energy, vol. 43, n.o 33, pp. 16141-16153, 2018.
[19] Q. Liao, Y. Liang, N. Xu, H. Zhang, J. Wang, y X. Zhou, «An MILP approach for detailed scheduling of multi-product pipeline in pressure control mode», Chemical Engineering Research and Design, vol. 136, pp. 620-637, 2018.
[20] H. Chen et al., «Optimizing detailed schedules of a multiproduct pipeline by a monolithic MILP formulation», Journal of Petroleum Science and Engineering, vol. 159, pp. 148-163, 2017.
[21] Q. Liao, H. Zhang, N. Xu, Y. Liang, y J. Wang, «A MILP model based on flowrate database for detailed scheduling of a multi-product pipeline with multiple pump stations», Computers & Chemical Engineering, vol. 117, pp. 63-81, 2018.
[22] H. Zhang, Y. Liang, J. Ma, C. Qian, y X. Yan, «An MILP method for optimal offshore oilfield gathering system», Ocean Engineering, vol. 141, pp. 25-34, 2017.
[23] X. Zhou et al., «A MILP model for the detailed scheduling of multiproduct pipelines with the hydraulic constraints rigorously considered», Computers & Chemical Engineering, vol. 130, p. 106543, 2019.
[24] B. Wang, Y. Liang, T. Zheng, M. Yuan, y H. Zhang, «Optimisation of a downstream oil supply chain with new pipeline route planning», Chemical Engineering Research and Design, vol. 145, pp. 300-313, 2019.
[25] A. Siddiqui, M. Verma, y V. Verter, «An integrated framework for inventory management and transportation of refined petroleum products: Pipeline or marine? », Applied Mathematical Modelling, vol. 55, pp. 224-247, 2018.
[26] T. A. Albahri, C. S. Khor, M. Elsholkami, y A. Elkamel, «A mixed integer nonlinear programming approach for petroleum refinery topology optimisation», Chemical Engineering Research and Design, vol. 143, pp. 24-35, 2019.
[27] Y. Wang, S. F. Estefen, M. I. Lourenço, y C. Hong, «Optimal design and scheduling for offshore oil-field development», Computers & Chemical Engineering, vol. 123, pp. 300-316, 2019.
[28] L. S. Assis, E. Camponogara, B. C. Menezes, y I. E. Grossmann, «An MINLP formulation for integrating the operational management of crude oil supply», Computers & Chemical Engineering, vol. 123, pp. 110-125, 2019.
[29] M. K. Almedallah y S. D. C. Walsh, «A numerical method to optimize use of existing assets in offshore natural gas and oil field developments», Journal of Natural Gas Science and Engineering, vol. 67, pp. 43-55, 2019.
[30] A. M. Attia, A. M. Ghaithan, y S. O. Duffuaa, «A multi-objective optimization model for tactical planning of upstream oil & gas supply chains», Computers & Chemical Engineering, vol. 128, pp. 216-227, 2019.
[31] R. E. Franzoi, B. C. Menezes, J. D. Kelly, y J. A. W. Gut, «Design for Online Process and Blend Scheduling Optimization», en Proceedings of the 9th International Conference on Foundations of Computer-Aided Process Design, vol. 47, S. G. Muñoz, C. D. Laird, y M. J. Realff, Eds. Elsevier, 2019, pp. 187-192.
[32] M. Quinteros, M. Guignard, A. Weintraub, M. Llambias, y C. Tapia, «Optimizing the pipeline planning system at the national oil company», European Journal of Operational Research, vol. 277, n.o 2, pp. 727-739, 2019.
[33] S. Xin et al., «A two-stage strategy for the pump optimal scheduling of refined products pipelines», Chemical Engineering Research and Design, vol. 152, pp. 1-19, 2019.
[34] F. Bayu, D. Panda, M. A. Shaik, y M. Ramteke, «Scheduling of Gasoline Blending and Distribution using Graphical Genetic Algorithm», Computers & Chemical Engineering, p. 106636, 2019.
[35] R. Qiu et al., «A multi-scenario and multi-objective scheduling optimization model for liquefied light hydrocarbon pipeline system», Chemical Engineering Research and Design, vol. 141, pp. 566-579, 2019.
[36] H. Zhang, Y. Liang, Q. Liao, J. Gao, X. Yan, y W. Zhang, «Mixed-time mixed-integer linear programming for optimal detailed scheduling of a crude oil port depot», Chemical Engineering Research and Design, vol. 137, pp. 434-451, 2018.
[37] A. Zaghian y H. Mostafaei, «An MILP model for scheduling the operation of a refined petroleum products distribution system», Operational Research, vol. 16, n.o 3, pp. 513-542, oct. 2016.
[38] W. Abdellaoui, A. Berrichi, D. Bennacer, F. Maliki, y L. Ghomri, «Optimal Scheduling of Multiproduct Pipeline System Using MILP Continuous Approach», en Computational Intelligence and Its Applications, Cham, 2018, pp. 411-420.
[39] H. Qu, J. Xu, S. Wang, y Q. Xu, «A novel MINLP model of front-end crude scheduling for refinery with consideration of inherent upset minimization», Computers & Chemical Engineering, vol. 117, pp. 42-62, 2018.
[40] T. Kirschstein, «Planning of multi-product pipelines by economic lot scheduling models», European Journal of Operational Research, vol. 264, n.o 1, pp. 327-339, 2018.
[41] H.-R. Zhang, Y.-T. Liang, Q. Liao, J. Ma, y X.-H. Yan, «An MILP approach for detailed scheduling of oil depots along a multi-product pipeline», Petroleum Science, vol. 14, n.o 2, pp. 434-458, may 2017.
[42] V. R. Rosa, E. Camponogara, y V. J. M. F. Filho, «Design optimization of oilfield subsea infrastructures with manifold placement and pipeline layout», Computers & Chemical Engineering, vol. 108, pp. 163-178, 2018.
[43] M. Jalanko y V. Mahalec, «Supply-demand pinch based methodology for multi-period planning under uncertainty in components qualities with application to gasoline blend planning», Computers & Chemical Engineering, vol. 119, pp. 425-438, 2018.
[44] O. Akgul, N. Shah, y L. G. Papageorgiou, «An MILP Model for the Strategic Design of the UK Bioethanol Supply Chain», en 21st European Symposium on Computer Aided Process Engineering, vol. 29, E. N. Pistikopoulos, M. C. Georgiadis, y A. C. Kokossis, Eds. Elsevier, 2011, pp. 1799-1803.
[45] A. Bittante, F. Pettersson, y H. Saxén, «Optimization of a small-scale LNG supply chain», Energy, vol. 148, pp. 79-89, 2018.
[46] P. Gutiérrez et al, «Análisis Nodal para determinar el punto óptimo de operación entre producción de petróleo y producción de GLP, maximizando el recurso energético de la Estación de producción de Petróleo, Aguarico», Revista Técnica "energía", Edición No. 16, Vol. 16 Núm. 2 (2020).
[47] S. Golla et al, «Primer Estudio para una Transición Energética Completa y Sostenible para Ecuador “El Fin del Petróleo”», Revista Técnica “energía”. No. 14, Pp. 246-255.
[48] Susana Relvas and Suelen N. et al, «Integrated scheduling and inventory management of an oil products distribution system», Revista Omega. No. 6, Pp. 955 - 968.
