Erismar Rubio, M. Y. Alklih, N. Reddicharla, Abobaker Albelazi, Melike Dilsiz, Mohamed Ali Al-Attar, R. Davila, K. Khan
{"title":"二氧化碳项目管理的集成自动化和数据驱动工作流——来自中东智能油田的案例研究","authors":"Erismar Rubio, M. Y. Alklih, N. Reddicharla, Abobaker Albelazi, Melike Dilsiz, Mohamed Ali Al-Attar, R. Davila, K. Khan","doi":"10.2118/207422-ms","DOIUrl":null,"url":null,"abstract":"\n Automation and data-driven models have been proven to yield commercial success in several oil fields worldwide with reported technical advantages related to improved reservoir management. This paper demonstrates the implementation of an integrated workflow to enhance CO2 injection project performance in a giant onshore smart oil field in Abu Dhabi. Since commissioning, proactive evaluation of the reservoir management strategy is enabled via smart-exception-based surveillance routines that facilitate reservoir/pattern/well performance review and supporting the decision making process. Prolonging the production sustainability of each well is a key pillar of this work, which has been made more quantifiable using live-tracking of the produced CO2 content and corrosion indicators.\n The intensive computing technical tasks and data aggregation from different sources; such as well testing and real time production/injection measurements; are integrated in an automatic workflow in a single platform. Accordingly, real-time visualizations and dashboards are also generated automatically; to orchestrate information, models and multidisciplinary knowledge in a systematic and efficient manner; allowing engineers to focus on problematic wells and giving attention to opportunity generation in a timely manner. Complemented with numerical techniques and other decision support tools, the intelligent system data-driven model assist to obtain a reliable short-term forecast in a shorter time and help making quick decisions on day-to-day operational optimization aspects.\n These dashboards have allowed measuring the true well/pattern performance towards operational objectives and production targets. A complete set of KPI's has helped to identify well health-status, potential risks and thus mitigate them for short/long term recovery to obtain an optimum reservoir energy balance in daily bases. In case of unexpected well performance behaviors, the dashboards have provided data insights on the root causes of different well issues and thus remedial actions were proposed accordingly.\n Maintaining CO2 miscibility is also ensured by having the right pressure support around producers, taking proactive actions from continues evaluation of producer-injector connectivity/interdependency, improving injection/production schedule, validating/tuning streamline model based on surveillance insights, avoiding CO2 recycling, optimizing data acquisition plan with potential cost saving while taking preventive measures to minimize well/facility corrosion impact.\n In this work, best reservoir management practices have been implemented to create a value of 12% incremental oil recovery from the field. The applied methodology uses an integrated automation and data-driven modeling approach to tackle CO2 injection project management challenges in real-time.","PeriodicalId":11069,"journal":{"name":"Day 2 Tue, November 16, 2021","volume":"20 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrated Automation and Data-Driven Workflow for CO2 Project Management – Case Study from a Smart Oil Field in the Middle-East\",\"authors\":\"Erismar Rubio, M. Y. Alklih, N. Reddicharla, Abobaker Albelazi, Melike Dilsiz, Mohamed Ali Al-Attar, R. Davila, K. Khan\",\"doi\":\"10.2118/207422-ms\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Automation and data-driven models have been proven to yield commercial success in several oil fields worldwide with reported technical advantages related to improved reservoir management. This paper demonstrates the implementation of an integrated workflow to enhance CO2 injection project performance in a giant onshore smart oil field in Abu Dhabi. Since commissioning, proactive evaluation of the reservoir management strategy is enabled via smart-exception-based surveillance routines that facilitate reservoir/pattern/well performance review and supporting the decision making process. Prolonging the production sustainability of each well is a key pillar of this work, which has been made more quantifiable using live-tracking of the produced CO2 content and corrosion indicators.\\n The intensive computing technical tasks and data aggregation from different sources; such as well testing and real time production/injection measurements; are integrated in an automatic workflow in a single platform. Accordingly, real-time visualizations and dashboards are also generated automatically; to orchestrate information, models and multidisciplinary knowledge in a systematic and efficient manner; allowing engineers to focus on problematic wells and giving attention to opportunity generation in a timely manner. Complemented with numerical techniques and other decision support tools, the intelligent system data-driven model assist to obtain a reliable short-term forecast in a shorter time and help making quick decisions on day-to-day operational optimization aspects.\\n These dashboards have allowed measuring the true well/pattern performance towards operational objectives and production targets. A complete set of KPI's has helped to identify well health-status, potential risks and thus mitigate them for short/long term recovery to obtain an optimum reservoir energy balance in daily bases. In case of unexpected well performance behaviors, the dashboards have provided data insights on the root causes of different well issues and thus remedial actions were proposed accordingly.\\n Maintaining CO2 miscibility is also ensured by having the right pressure support around producers, taking proactive actions from continues evaluation of producer-injector connectivity/interdependency, improving injection/production schedule, validating/tuning streamline model based on surveillance insights, avoiding CO2 recycling, optimizing data acquisition plan with potential cost saving while taking preventive measures to minimize well/facility corrosion impact.\\n In this work, best reservoir management practices have been implemented to create a value of 12% incremental oil recovery from the field. 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Integrated Automation and Data-Driven Workflow for CO2 Project Management – Case Study from a Smart Oil Field in the Middle-East
Automation and data-driven models have been proven to yield commercial success in several oil fields worldwide with reported technical advantages related to improved reservoir management. This paper demonstrates the implementation of an integrated workflow to enhance CO2 injection project performance in a giant onshore smart oil field in Abu Dhabi. Since commissioning, proactive evaluation of the reservoir management strategy is enabled via smart-exception-based surveillance routines that facilitate reservoir/pattern/well performance review and supporting the decision making process. Prolonging the production sustainability of each well is a key pillar of this work, which has been made more quantifiable using live-tracking of the produced CO2 content and corrosion indicators.
The intensive computing technical tasks and data aggregation from different sources; such as well testing and real time production/injection measurements; are integrated in an automatic workflow in a single platform. Accordingly, real-time visualizations and dashboards are also generated automatically; to orchestrate information, models and multidisciplinary knowledge in a systematic and efficient manner; allowing engineers to focus on problematic wells and giving attention to opportunity generation in a timely manner. Complemented with numerical techniques and other decision support tools, the intelligent system data-driven model assist to obtain a reliable short-term forecast in a shorter time and help making quick decisions on day-to-day operational optimization aspects.
These dashboards have allowed measuring the true well/pattern performance towards operational objectives and production targets. A complete set of KPI's has helped to identify well health-status, potential risks and thus mitigate them for short/long term recovery to obtain an optimum reservoir energy balance in daily bases. In case of unexpected well performance behaviors, the dashboards have provided data insights on the root causes of different well issues and thus remedial actions were proposed accordingly.
Maintaining CO2 miscibility is also ensured by having the right pressure support around producers, taking proactive actions from continues evaluation of producer-injector connectivity/interdependency, improving injection/production schedule, validating/tuning streamline model based on surveillance insights, avoiding CO2 recycling, optimizing data acquisition plan with potential cost saving while taking preventive measures to minimize well/facility corrosion impact.
In this work, best reservoir management practices have been implemented to create a value of 12% incremental oil recovery from the field. The applied methodology uses an integrated automation and data-driven modeling approach to tackle CO2 injection project management challenges in real-time.