{"title":"阿联酋阿布扎比海上油田现场作业数字化转型之旅","authors":"Talha Rafi Ahmed, Bastien Januel, Morealvin Fuenmayor","doi":"10.2118/207386-ms","DOIUrl":null,"url":null,"abstract":"\n Field operations generate large volumes of data from various equipment and associated Meta data such as inspection due dates, maintenance schedule, people on board, etc. The data is often stored in silos with a data guardian for each entity. The objective of this project was to volarize the data by developing engineered KPI's to drive decision making and make data accessible for everyone in the organization to foster cross collaboration.\n Data analytics and visualization solutions were developed to automate low value-added tasks either using robotic process automation scripts or business intelligence reporting tool. Data was residing either in spreadsheet or native applications. With support of IT, centralized database was established. Scrum agile project management techniques were used to develop digital solutions. A high-level digital road map was created consulting all teams including stake holders. Use cases were identified and captured in lean A3 problem solving format. Each use case clearly identified the benefits to organization, and this was used to prioritize the use cases. A sprint was set-up with agile team and products were developed as per end user's expectation. The constant feedback loop via daily stand-up meetings helped the team deliver value added products.\n Digital solutions were developed to automate low value-added tasks so employees can focus on improving systems instead of producing reports. By developing engineering KPI's and predictive analytics, technical authority could shift from reactive maintenance to pro-active maintenance. Using linear regression machine learning, early warning digital solution was developed to monitor and notify technical authority to clean strainers. The production team achieved 0.75 full time equivalent (FTE) in time savings by automating reports. By visualizing operations data such as flaring, production profiles; the team minimized flaring leading to 1% OPEX cost saving. Around 10% of chemical budget was saved by monitoring chemical injections at all platforms. Similar cost savings were achieved by visualizing data for other disciplines such as maintenance and HSE teams. By being better informed about wells annuli pressure build-up via email notifications, wells integrity team reduced the associated risk. By forming a multi-disciplinary agile team with business and delivery team, digital team deployed 20+ digital products over a short time frame of 2 years.","PeriodicalId":10967,"journal":{"name":"Day 1 Mon, November 15, 2021","volume":"17 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Digital Transformation Journey of Field Operations at Abu Dhabi Offshore Field in UAE\",\"authors\":\"Talha Rafi Ahmed, Bastien Januel, Morealvin Fuenmayor\",\"doi\":\"10.2118/207386-ms\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Field operations generate large volumes of data from various equipment and associated Meta data such as inspection due dates, maintenance schedule, people on board, etc. The data is often stored in silos with a data guardian for each entity. The objective of this project was to volarize the data by developing engineered KPI's to drive decision making and make data accessible for everyone in the organization to foster cross collaboration.\\n Data analytics and visualization solutions were developed to automate low value-added tasks either using robotic process automation scripts or business intelligence reporting tool. Data was residing either in spreadsheet or native applications. With support of IT, centralized database was established. Scrum agile project management techniques were used to develop digital solutions. A high-level digital road map was created consulting all teams including stake holders. Use cases were identified and captured in lean A3 problem solving format. Each use case clearly identified the benefits to organization, and this was used to prioritize the use cases. A sprint was set-up with agile team and products were developed as per end user's expectation. The constant feedback loop via daily stand-up meetings helped the team deliver value added products.\\n Digital solutions were developed to automate low value-added tasks so employees can focus on improving systems instead of producing reports. By developing engineering KPI's and predictive analytics, technical authority could shift from reactive maintenance to pro-active maintenance. Using linear regression machine learning, early warning digital solution was developed to monitor and notify technical authority to clean strainers. The production team achieved 0.75 full time equivalent (FTE) in time savings by automating reports. By visualizing operations data such as flaring, production profiles; the team minimized flaring leading to 1% OPEX cost saving. Around 10% of chemical budget was saved by monitoring chemical injections at all platforms. Similar cost savings were achieved by visualizing data for other disciplines such as maintenance and HSE teams. By being better informed about wells annuli pressure build-up via email notifications, wells integrity team reduced the associated risk. By forming a multi-disciplinary agile team with business and delivery team, digital team deployed 20+ digital products over a short time frame of 2 years.\",\"PeriodicalId\":10967,\"journal\":{\"name\":\"Day 1 Mon, November 15, 2021\",\"volume\":\"17 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Day 1 Mon, November 15, 2021\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2118/207386-ms\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 1 Mon, November 15, 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/207386-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Digital Transformation Journey of Field Operations at Abu Dhabi Offshore Field in UAE
Field operations generate large volumes of data from various equipment and associated Meta data such as inspection due dates, maintenance schedule, people on board, etc. The data is often stored in silos with a data guardian for each entity. The objective of this project was to volarize the data by developing engineered KPI's to drive decision making and make data accessible for everyone in the organization to foster cross collaboration.
Data analytics and visualization solutions were developed to automate low value-added tasks either using robotic process automation scripts or business intelligence reporting tool. Data was residing either in spreadsheet or native applications. With support of IT, centralized database was established. Scrum agile project management techniques were used to develop digital solutions. A high-level digital road map was created consulting all teams including stake holders. Use cases were identified and captured in lean A3 problem solving format. Each use case clearly identified the benefits to organization, and this was used to prioritize the use cases. A sprint was set-up with agile team and products were developed as per end user's expectation. The constant feedback loop via daily stand-up meetings helped the team deliver value added products.
Digital solutions were developed to automate low value-added tasks so employees can focus on improving systems instead of producing reports. By developing engineering KPI's and predictive analytics, technical authority could shift from reactive maintenance to pro-active maintenance. Using linear regression machine learning, early warning digital solution was developed to monitor and notify technical authority to clean strainers. The production team achieved 0.75 full time equivalent (FTE) in time savings by automating reports. By visualizing operations data such as flaring, production profiles; the team minimized flaring leading to 1% OPEX cost saving. Around 10% of chemical budget was saved by monitoring chemical injections at all platforms. Similar cost savings were achieved by visualizing data for other disciplines such as maintenance and HSE teams. By being better informed about wells annuli pressure build-up via email notifications, wells integrity team reduced the associated risk. By forming a multi-disciplinary agile team with business and delivery team, digital team deployed 20+ digital products over a short time frame of 2 years.