Desarrollo de un lenguaje de dominio específico para el análisis de variables de petróleo y gas

Este proyecto se enfoca en el desarrollo de un lenguaje de dominio específico que tiene como propósito facilitar el análisis de variables en el sector ‘Upstream’ de la industria de petróleo y gas. Dentro de estas variables se incluyen elementos como los pozos petroleros y sus tipos, las reservas, cá...

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Autores:: Garcia Palomares, Jorge Luis
Cuadros Bacca, Andres Cuadros

Tipo de recurso:: https://purl.org/coar/resource_type/c_7a1f

Fecha de publicación:: 2024

Institución:: Universidad El Bosque

Repositorio:: Repositorio U. El Bosque

Idioma:: spa

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dc.title.none.fl_str_mv	Desarrollo de un lenguaje de dominio específico para el análisis de variables de petróleo y gas
dc.title.translated.none.fl_str_mv	Development of a domain-specific language for the analysis of oil and gas variables
title	Desarrollo de un lenguaje de dominio específico para el análisis de variables de petróleo y gas
spellingShingle	Desarrollo de un lenguaje de dominio específico para el análisis de variables de petróleo y gas Lenguage de dominio especifico Petroleo Meta Programming System Gas 621.3 Domain specific language Oil Meta Programming System Gas
title_short	Desarrollo de un lenguaje de dominio específico para el análisis de variables de petróleo y gas
title_full	Desarrollo de un lenguaje de dominio específico para el análisis de variables de petróleo y gas
title_fullStr	Desarrollo de un lenguaje de dominio específico para el análisis de variables de petróleo y gas
title_full_unstemmed	Desarrollo de un lenguaje de dominio específico para el análisis de variables de petróleo y gas
title_sort	Desarrollo de un lenguaje de dominio específico para el análisis de variables de petróleo y gas
dc.creator.fl_str_mv	Garcia Palomares, Jorge Luis Cuadros Bacca, Andres Cuadros
dc.contributor.advisor.none.fl_str_mv	Romero Alvarez, Fran Ernesto
dc.contributor.author.none.fl_str_mv	Garcia Palomares, Jorge Luis Cuadros Bacca, Andres Cuadros
dc.subject.none.fl_str_mv	Lenguage de dominio especifico Petroleo Meta Programming System Gas
topic	Lenguage de dominio especifico Petroleo Meta Programming System Gas 621.3 Domain specific language Oil Meta Programming System Gas
dc.subject.ddc.none.fl_str_mv	621.3
dc.subject.keywords.none.fl_str_mv	Domain specific language Oil Meta Programming System Gas
description	Este proyecto se enfoca en el desarrollo de un lenguaje de dominio específico que tiene como propósito facilitar el análisis de variables en el sector ‘Upstream’ de la industria de petróleo y gas. Dentro de estas variables se incluyen elementos como los pozos petroleros y sus tipos, las reservas, cálculo de variables como la presión hidrostática y barriles por día (BPD), entre otros. Para el desarrollo del lenguaje, se implementa la metodología BATIC3S, junto con el tablero Kanban para la organización de las actividades. Hasta el momento, se ha logrado definir los requerimientos base del lenguaje y se ha desarrollado un prototipo inicial usando la herramienta MPS de JetBrains. Luego se implementó el prototipo para presentarlo ante los profesionales de la industria petrolera con el fin de realizar un proceso de retroalimentación con base en las opiniones de los respectivos profesionales.
publishDate	2024
dc.date.accessioned.none.fl_str_mv	2024-12-10T20:16:27Z
dc.date.available.none.fl_str_mv	2024-12-10T20:16:27Z
dc.date.issued.none.fl_str_mv	2024-11
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dc.type.driver.none.fl_str_mv	info:eu-repo/semantics/bachelorThesis
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dc.identifier.instname.spa.fl_str_mv	instname:Universidad El Bosque
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url	https://hdl.handle.net/20.500.12495/13673
identifier_str_mv	instname:Universidad El Bosque reponame:Repositorio Institucional Universidad El Bosque repourl:https://repositorio.unbosque.edu.co
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dc.relation.references.none.fl_str_mv	[1] W. Zhang, Application of Big Data in Oil and Gas Exploration and Development. 2022. doi: 10.1007/978-981-19-2149-0_363. [2] G. Panaedova, S. Frumina, and I. Mityushina, Digital Technologies in the Oil and Gas Industry: Main Directions and Development Trends, vol. 443. 2022. doi: 10.1007/978-3-031-07067-9_6. [3] X. Zhang, Y. Yang, S. Jia, Q. Zhang, and R. Wei, Research on Smart Pipeline Network Architecture Based on Pipeline Lifecycle Integrity Management, vol. 212. 2023. doi: 10.1007/978-981-19-4067-5_15. [4] K. Zanbouri, M. Razoughi Bastak, S. M. Alizadeh, N. Jafari Navimipour, and S. Yalcin, “A New Energy-Aware Method for Gas Lift Allocation in IoT-Based Industries Using a Chemical Reaction-Based Optimization Algorithm,” Electronics (Switzerland), vol. 11, no. 22, 2022, doi: 10.3390/electronics11223769. [5] J. Lyu, M. Qiu, H. Yang, D. Zhou, and J. Liu, “Blockchain applications in upstream oil and gas industry,” in Society of Petroleum Engineers - Abu Dhabi International Petroleum Exhibition and Conference 2020, ADIP 2020, 2020. [6] B. Sahovic et al., “A study on the relationship between upstream and downstream conditions in swirling two-phase flow,” Flow Measurement and Instrumentation, vol. 74, 2020, doi: 10.1016/j.flowmeasinst.2020.101767. [7] N. Bahrami, S. Soroush, M. Hossain, A. Lashari, M. Daloma, and A. Kabir, “Evaluation of damage mechanisms in tight gas reservoirs: Field example from perth Basin,” in Society of Petroleum Engineers - SPE Saudi Arabia Section Annual Technical Symposium and Exhibition, 2015. doi: 10.2118/178018-ms. [8] N. T. B. Nguyen et al., “Integrated modeling for assisted history matching and robust optimisation in mature reservoirs,” in Society of Petroleum Engineers - SPE/IATMI Asia Pacific Oil and Gas Conference and Exhibition, APOGCE 2015, 2015. doi: 10.2118/176290-ms. [9] X. Dou et al., “Analysis on traditional reserve estimation methods in stress-sensitive gas reservoir: Error analysis and modification,” in Society of Petroleum Engineers - SPE Nigeria Annual International Conference and Exhibition, NAICE 2015, 2015. doi: 10.2118/178284-ms. [10] J. D. Williams-Kovacs and C. R. Clarkson, “A modified approach for modelling 2-phase flowback from multi-fractured horizontal shale gas wells,” in Society of Petroleum Engineers - Unconventional Resources Technology Conference, URTeC 2015, 2015. doi: 10.2118/178511-ms. [11] A. Dastan and R. N. Horne, “A new look at nonlinear regression in well test interpretation,” in Proceedings - SPE Annual Technical Conference and Exhibition, 2010, pp. 5462–5475. doi: 10.2118/135606-ms. [12] S. M. Schrader, R. S. Balch, and T. Ruan, “Using neural networks to estimate monthly production: A case study for the Devonian Carbonates, Southeast New Mexico,” in SPE Production and Operations Symposium, Proceedings, 2005, pp. 227–231. doi: 10.2118/94089-ms. [13] S. Lieberman, “Automated continuous fluid level monitoring,” in SPE Production and Operations Symposium, Proceedings, 2005, pp. 69–86. doi: 10.2118/93832-ms. [15] O. Gurpinar and C. A. Kossack, “Realistic Numerical Models for Fractured Reservoirs,” in Proceedings of the SPE International Petroleum Conference and Exhibition of Mexico, 2000, pp. 461–471. doi: 10.2523/59041-ms. [14] J. M. Degraff, M. E. Meurer, L. H. Landis, and S. Lyons, “Fracture network modeling and dual-permeability simulation of carbonate reservoirs,” in 2005 International Petroleum Technology Conference Proceedings, 2005, pp. 1643–1649. doi: 10.2523/iptc-10954-ms. [16] M. R. Islam, “Emerging technologies in subsurface monitoring of oil reservoirs,” in Canadian International Petroleum Conference 2000, CIPC 2000, 2000. doi: 10.2118/2000-089. [17] G. Tsapko, V. Komagorov, and P. Kondratev, “The up-to-date development conceptions of integrated distributed databases of the oil-and-gas production enterprises,” in Proceedings - KORUS 2000: 4th Korea-Russia International Symposium on Science and Technology, Institute of Electrical and Electronics Engineers Inc., 2000, pp. 34 – 38. doi: 10.1109/KORUS.2000.865989. [18] K. H. Hashmy, T. Hefter, and R. Chicko, “Quantitative Log Evaluation in the Devonian Shales of the Northeast United States,” Society of Petroleum Engineers - SPE Unconventional Gas Recovery Symposium, UGR 1982, pp. 55 – 59, 1982, doi: 10.2118/10795-ms. [19] G. H. Fancher, J. A. Lewis, and K. B. Barnes, “Physical tests and properties of oil and gas sands,” World Petroleum Congress Proceedings, vol. 1933-July, pp. 322 – 333, 1933, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055967886&partnerID=40&md5=d929036ec2676d63dd8765e28cdca48f [20] V. E. Althaus and J. D. Lea, “Computer programs for application to large volumes of digitized well logs,” Society of Petroleum Engineers - Gas Industry Symposium, GIS 1970, 1970, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059171370&partnerID=40&md5=cdedddc8100aa2857939cfe1b7e2f42c [21] P. F. V Williams, “Oil shales and their analysis,” Fuel, vol. 62, no. 7, pp. 756 – 771, 1983, doi: 10.1016/0016-2361(83)90025-X. [22] P. P. Reichertz, W. C. Skinner, W. L. Wahl, and G. C. Wallick, “The role of computers in studying reservoir performance and petroleum conservation,” World Petroleum Congress Proceedings, vol. 1963-June, pp. 89 – 99, 1963, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058213352&partnerID=40&md5=937d659725c1bdcac5f25b60fd866d91 [23] M. Risoldi, A methodology for the development of complex domain specific languages. PhD thesis, Geneva U., 2010. [24] L. Over ̊a, “Semantic technology in the oil and gas drilling domain,” 2010. [25] J. Wosowei and C. Shastry, “A domain specific modelling for monitoring operations in a digital oil field,” Australian Journal of Wireless Technologies, Mobility and Security, vol. 1, 2019. [26] J. B. Richard and A. O. Prince, “Oil and gas pipeline design management system: A case study for domain-specific modeling,” American Journal of Software Engineering and Applications, vol. 4, pp. 92–98, 2015. [27] X. Tang, Z. Feng, Y. Xiao, M. Wang, T. Ye, Y. Zhou, J. Meng, B. Zhang, and D. Zhang, “Construction and application of an ontology-based domain-specific knowledge graph for petroleum exploration and development,” Geoscience Frontiers, vol. 14, p. 101426, 2023. [28] I. Giden, “Petroleum production solutions using a domain specific language,” 2011. [29] M. Risoldi and V. Amaral, ‘Towards a formal, model-based framework for control systems interaction prototyping’, in International Workshop on Rapid Integration of Software Engineering Techniques, 2006, pp. 144–159. [30] J. L. S. Rodríguez and A. S. Cabezuelo, “ILSA (Ingeniería de Lenguajes Software y Aplicaciones), UCM,” Dialnet, 2012. [31] “How Does MPS Work? - Concepts \| MPS by JetBrains,” JetBrains. https://www.jetbrains.com/mps/concepts/ [32] “MPS Help,” MPS Help, 2024. https://www.jetbrains.com/help/mps/basic-notions.html.
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spelling	Romero Alvarez, Fran ErnestoGarcia Palomares, Jorge LuisCuadros Bacca, Andres Cuadros2024-12-10T20:16:27Z2024-12-10T20:16:27Z2024-11https://hdl.handle.net/20.500.12495/13673instname:Universidad El Bosquereponame:Repositorio Institucional Universidad El Bosquerepourl:https://repositorio.unbosque.edu.coEste proyecto se enfoca en el desarrollo de un lenguaje de dominio específico que tiene como propósito facilitar el análisis de variables en el sector ‘Upstream’ de la industria de petróleo y gas. Dentro de estas variables se incluyen elementos como los pozos petroleros y sus tipos, las reservas, cálculo de variables como la presión hidrostática y barriles por día (BPD), entre otros. Para el desarrollo del lenguaje, se implementa la metodología BATIC3S, junto con el tablero Kanban para la organización de las actividades. Hasta el momento, se ha logrado definir los requerimientos base del lenguaje y se ha desarrollado un prototipo inicial usando la herramienta MPS de JetBrains. Luego se implementó el prototipo para presentarlo ante los profesionales de la industria petrolera con el fin de realizar un proceso de retroalimentación con base en las opiniones de los respectivos profesionales.Ingeniero de SistemasPregradoThis project focuses on the development of a domain-specific language that aims to facilitate the analysis of variables in the upstream sector of the oil and gas industry. These variables include elements such as oil wells and their types, reserves, calculation of variables such as hydrostatic pressure and barrels per day (BPD), among others. For the development of the language, the BATIC3S methodology is implemented, together with the Kanban board for the organization of the activities. So far, the base requirements of the language have been defined and an initial prototype has been developed using the JetBrains MPS tool. The prototype is then implemented and presented to oil industry professionals for a feedback process based on the opinions of the respective professionals.application/pdfAttribution-NonCommercial-ShareAlike 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-sa/4.0/Acceso abiertohttps://purl.org/coar/access_right/c_abf2http://purl.org/coar/access_right/c_abf2Lenguage de dominio especificoPetroleoMeta Programming SystemGas621.3Domain specific languageOilMeta Programming SystemGasDesarrollo de un lenguaje de dominio específico para el análisis de variables de petróleo y gasDevelopment of a domain-specific language for the analysis of oil and gas variablesIngeniería de SistemasUniversidad El BosqueFacultad de IngenieríaTesis/Trabajo de grado - Monografía - Pregradohttps://purl.org/coar/resource_type/c_7a1fhttp://purl.org/coar/resource_type/c_7a1finfo:eu-repo/semantics/bachelorThesishttps://purl.org/coar/version/c_ab4af688f83e57aa[1] W. Zhang, Application of Big Data in Oil and Gas Exploration and Development. 2022. doi: 10.1007/978-981-19-2149-0_363.[2] G. Panaedova, S. Frumina, and I. Mityushina, Digital Technologies in the Oil and Gas Industry: Main Directions and Development Trends, vol. 443. 2022. doi: 10.1007/978-3-031-07067-9_6.[3] X. Zhang, Y. Yang, S. Jia, Q. Zhang, and R. Wei, Research on Smart Pipeline Network Architecture Based on Pipeline Lifecycle Integrity Management, vol. 212. 2023. doi: 10.1007/978-981-19-4067-5_15.[4] K. Zanbouri, M. Razoughi Bastak, S. M. Alizadeh, N. Jafari Navimipour, and S. Yalcin, “A New Energy-Aware Method for Gas Lift Allocation in IoT-Based Industries Using a Chemical Reaction-Based Optimization Algorithm,” Electronics (Switzerland), vol. 11, no. 22, 2022, doi: 10.3390/electronics11223769.[5] J. Lyu, M. Qiu, H. Yang, D. Zhou, and J. Liu, “Blockchain applications in upstream oil and gas industry,” in Society of Petroleum Engineers - Abu Dhabi International Petroleum Exhibition and Conference 2020, ADIP 2020, 2020.[6] B. Sahovic et al., “A study on the relationship between upstream and downstream conditions in swirling two-phase flow,” Flow Measurement and Instrumentation, vol. 74, 2020, doi: 10.1016/j.flowmeasinst.2020.101767.[7] N. Bahrami, S. Soroush, M. Hossain, A. Lashari, M. Daloma, and A. Kabir, “Evaluation of damage mechanisms in tight gas reservoirs: Field example from perth Basin,” in Society of Petroleum Engineers - SPE Saudi Arabia Section Annual Technical Symposium and Exhibition, 2015. doi: 10.2118/178018-ms.[8] N. T. B. Nguyen et al., “Integrated modeling for assisted history matching and robust optimisation in mature reservoirs,” in Society of Petroleum Engineers - SPE/IATMI Asia Pacific Oil and Gas Conference and Exhibition, APOGCE 2015, 2015. doi: 10.2118/176290-ms.[9] X. Dou et al., “Analysis on traditional reserve estimation methods in stress-sensitive gas reservoir: Error analysis and modification,” in Society of Petroleum Engineers - SPE Nigeria Annual International Conference and Exhibition, NAICE 2015, 2015. doi: 10.2118/178284-ms.[10] J. D. Williams-Kovacs and C. R. Clarkson, “A modified approach for modelling 2-phase flowback from multi-fractured horizontal shale gas wells,” in Society of Petroleum Engineers - Unconventional Resources Technology Conference, URTeC 2015, 2015. doi: 10.2118/178511-ms.[11] A. Dastan and R. N. Horne, “A new look at nonlinear regression in well test interpretation,” in Proceedings - SPE Annual Technical Conference and Exhibition, 2010, pp. 5462–5475. doi: 10.2118/135606-ms.[12] S. M. Schrader, R. S. Balch, and T. Ruan, “Using neural networks to estimate monthly production: A case study for the Devonian Carbonates, Southeast New Mexico,” in SPE Production and Operations Symposium, Proceedings, 2005, pp. 227–231. doi: 10.2118/94089-ms.[13] S. Lieberman, “Automated continuous fluid level monitoring,” in SPE Production and Operations Symposium, Proceedings, 2005, pp. 69–86. doi: 10.2118/93832-ms.[15] O. Gurpinar and C. A. Kossack, “Realistic Numerical Models for Fractured Reservoirs,” in Proceedings of the SPE International Petroleum Conference and Exhibition of Mexico, 2000, pp. 461–471. doi: 10.2523/59041-ms.[14] J. M. Degraff, M. E. Meurer, L. H. Landis, and S. Lyons, “Fracture network modeling and dual-permeability simulation of carbonate reservoirs,” in 2005 International Petroleum Technology Conference Proceedings, 2005, pp. 1643–1649. doi: 10.2523/iptc-10954-ms.[16] M. R. Islam, “Emerging technologies in subsurface monitoring of oil reservoirs,” in Canadian International Petroleum Conference 2000, CIPC 2000, 2000. doi: 10.2118/2000-089.[17] G. Tsapko, V. Komagorov, and P. Kondratev, “The up-to-date development conceptions of integrated distributed databases of the oil-and-gas production enterprises,” in Proceedings - KORUS 2000: 4th Korea-Russia International Symposium on Science and Technology, Institute of Electrical and Electronics Engineers Inc., 2000, pp. 34 – 38. doi: 10.1109/KORUS.2000.865989.[18] K. H. Hashmy, T. Hefter, and R. Chicko, “Quantitative Log Evaluation in the Devonian Shales of the Northeast United States,” Society of Petroleum Engineers - SPE Unconventional Gas Recovery Symposium, UGR 1982, pp. 55 – 59, 1982, doi: 10.2118/10795-ms.[19] G. H. Fancher, J. A. Lewis, and K. B. Barnes, “Physical tests and properties of oil and gas sands,” World Petroleum Congress Proceedings, vol. 1933-July, pp. 322 – 333, 1933, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055967886&partnerID=40&md5=d929036ec2676d63dd8765e28cdca48f[20] V. E. Althaus and J. D. Lea, “Computer programs for application to large volumes of digitized well logs,” Society of Petroleum Engineers - Gas Industry Symposium, GIS 1970, 1970, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059171370&partnerID=40&md5=cdedddc8100aa2857939cfe1b7e2f42c[21] P. F. V Williams, “Oil shales and their analysis,” Fuel, vol. 62, no. 7, pp. 756 – 771, 1983, doi: 10.1016/0016-2361(83)90025-X.[22] P. P. Reichertz, W. C. Skinner, W. L. Wahl, and G. C. Wallick, “The role of computers in studying reservoir performance and petroleum conservation,” World Petroleum Congress Proceedings, vol. 1963-June, pp. 89 – 99, 1963, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058213352&partnerID=40&md5=937d659725c1bdcac5f25b60fd866d91[23] M. Risoldi, A methodology for the development of complex domain specific languages. PhD thesis, Geneva U., 2010.[24] L. Over ̊a, “Semantic technology in the oil and gas drilling domain,” 2010.[25] J. Wosowei and C. Shastry, “A domain specific modelling for monitoring operations in a digital oil field,” Australian Journal of Wireless Technologies, Mobility and Security, vol. 1, 2019.[26] J. B. Richard and A. O. Prince, “Oil and gas pipeline design management system: A case study for domain-specific modeling,” American Journal of Software Engineering and Applications, vol. 4, pp. 92–98, 2015.[27] X. Tang, Z. Feng, Y. Xiao, M. Wang, T. Ye, Y. Zhou, J. Meng, B. Zhang, and D. Zhang, “Construction and application of an ontology-based domain-specific knowledge graph for petroleum exploration and development,” Geoscience Frontiers, vol. 14, p. 101426, 2023.[28] I. Giden, “Petroleum production solutions using a domain specific language,” 2011.[29] M. Risoldi and V. Amaral, ‘Towards a formal, model-based framework for control systems interaction prototyping’, in International Workshop on Rapid Integration of Software Engineering Techniques, 2006, pp. 144–159.[30] J. L. S. Rodríguez and A. S. 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