James Ramsay, L. Noble, Glynn Lockyer, Mohand Alyan, A. Al Shmakhy
{"title":"Addressing the Limitations of Oil and Gas 4.0 Surrounding Distributed Fiber Optic Data Streams","authors":"James Ramsay, L. Noble, Glynn Lockyer, Mohand Alyan, A. Al Shmakhy","doi":"10.2118/207848-ms","DOIUrl":null,"url":null,"abstract":"\n This paper outlines how the problem of previously unmanageable data volumes produced by distributed fiber optic well monitoring systems is solved through the use of the latest sensing and analytics platform.\n The platform significantly reduces fiber optic data volumes enabling data to be streamed, processed, stored and visualized; all in real-time. The platform was effectively utilized for real-time data processing and visualization of well injection profiles of fields in the Middle East.\n The platform addresses the big data challenge associated with streaming distributed fiber optic data in three key areas: Edge processing reduces Distributed Fiber Optic (DFO) data rates by orders of magnitude so it can be streamed from the edge to the end user in real-time.Tiled data storage utilizes innovative data storage strategy to enable fast query responses whether visualizing years or just seconds of DFO data.Elastic infrastructure of processing and storage enables the platform to seamlessly scale and handle variable data rates.\n Raw Distributed Acoustic Sensing (DAS) data can be generated at rates of 100 MBs per second and cannot feasibly be transferred over a standard internet connection. The sensing and analytics platform's algorithms extract features at the edge which reduce data rates by three orders of magnitude whilst still preserving all key information from the data.\n Processed DFO data is aggregated and tiled in real-time at tens of different resolutions with respect to both time and fiber length. This enables sub-second query response times even when requesting DFO data across years of historical data.\n All platform processing logic is designed to run asynchronously on serverless infrastructure. This enables the platform's infrastructure to rapidly scale up or down in response to variable data rates.\n The result is a cloud-based visualization dashboard capable of displaying DFO data in near real-time across any time range and fiber length.\n Use of this sensing and analytics platform allowed for seamless streaming of fiber optic data on the Middle East field for injection monitoring, allowing the operator to visualize injection profiles and optimize the injection program in real-time.\n This sensing and analytics fiber management platform enables the user to highly successfully stream and visualize DFO data in real-time. It enables visibility into the subsurface for production and injection wells, enabling field-wide efficiencies and optimization.","PeriodicalId":10967,"journal":{"name":"Day 1 Mon, November 15, 2021","volume":"11 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 1 Mon, November 15, 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/207848-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper outlines how the problem of previously unmanageable data volumes produced by distributed fiber optic well monitoring systems is solved through the use of the latest sensing and analytics platform.
The platform significantly reduces fiber optic data volumes enabling data to be streamed, processed, stored and visualized; all in real-time. The platform was effectively utilized for real-time data processing and visualization of well injection profiles of fields in the Middle East.
The platform addresses the big data challenge associated with streaming distributed fiber optic data in three key areas: Edge processing reduces Distributed Fiber Optic (DFO) data rates by orders of magnitude so it can be streamed from the edge to the end user in real-time.Tiled data storage utilizes innovative data storage strategy to enable fast query responses whether visualizing years or just seconds of DFO data.Elastic infrastructure of processing and storage enables the platform to seamlessly scale and handle variable data rates.
Raw Distributed Acoustic Sensing (DAS) data can be generated at rates of 100 MBs per second and cannot feasibly be transferred over a standard internet connection. The sensing and analytics platform's algorithms extract features at the edge which reduce data rates by three orders of magnitude whilst still preserving all key information from the data.
Processed DFO data is aggregated and tiled in real-time at tens of different resolutions with respect to both time and fiber length. This enables sub-second query response times even when requesting DFO data across years of historical data.
All platform processing logic is designed to run asynchronously on serverless infrastructure. This enables the platform's infrastructure to rapidly scale up or down in response to variable data rates.
The result is a cloud-based visualization dashboard capable of displaying DFO data in near real-time across any time range and fiber length.
Use of this sensing and analytics platform allowed for seamless streaming of fiber optic data on the Middle East field for injection monitoring, allowing the operator to visualize injection profiles and optimize the injection program in real-time.
This sensing and analytics fiber management platform enables the user to highly successfully stream and visualize DFO data in real-time. It enables visibility into the subsurface for production and injection wells, enabling field-wide efficiencies and optimization.