Seismic Data Management for Big Data Era

Anik Pal, P. Kumar, Faridullah Shah
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引用次数: 1

Abstract

Seismic data is one of earliest data acquired in a prospect evaluation and the data are utilized throughout the exploration and production stages of a prospect. With recent advances in the handling of big data, it is essential to re-evaluate the best practices in the seismic data ecosystem. This paper presents the idea to leveragingthe technology advancement in big data and cloud computing for Seismic data ecosystem with the aim to providing an improve user experience. This new seismic platform would be capable of handling, managing and delivering the full spectrum of seismic data varieties starting from acquired field data to interpretation ready processed data. The system to have the following capabilities: Capability to entitle the right portion of data to every user as per interestOrganization of seismic data as per the business unitsData security by sharing data only with legitimate users/groups.Direct or indirect integration with all the data sources and applications who are consuming and/or generating dataSharing of and collaboration on data within company and/or across organization for shareholding partner, perspective seismic buyer for trading and relinquishment, regulatory agency resource certifying agencies and service providers etc. over limited network connectivity.Provide intergration/data deliverivey to End Users applications where this seismic data will be utilizaed Implementation of Seismic ecosystem will enable: Sharing of seismic data by the acquisition, quality control, data processing and interpretation with user communities from one centralized storageCollaboration of stake holders in real time over an encrypted networkLeveraging cloud and mobility technology advancement for agility and interaction. The system will be connected and interactive yet has the power of complex high-performance computing infrastructure on the background.Data delivery and auditing to wider and more diverse user community that consumes data from different platforms.Secure data access based on organizational business units to make sure data does not fall into unauthorized hand.Reduction in seismic data turnaround time by reading and ingesting large volume of data through parallel input/output operation.Improved data delivery and map interface with contextual information out of the centralized data store.Augment traditional workflows with machine learning and artificial intelligence for example automated fault detection, etc., The proposed best practice aims to bring all of the different disciplines working with seismic data to one centralized seismic data repository and enable them to consume and share seismic data from big data lake. This is live and interactive when compared to traditional technologies of using the archive and restore system in standalone application.
面向大数据时代的地震数据管理
地震数据是勘探评价中最早获得的数据之一,在勘探和生产的各个阶段都会用到地震数据。随着大数据处理的最新进展,有必要重新评估地震数据生态系统中的最佳实践。本文提出了在地震数据生态系统中利用大数据和云计算技术进步的想法,旨在提供更好的用户体验。这个新的地震平台将能够处理、管理和提供各种地震数据,从获得的现场数据到解释准备处理的数据。系统需要具备以下能力:能够根据兴趣将数据的正确部分分配给每个用户,按照业务单元组织地震数据,仅与合法用户/组共享数据,从而保证数据的安全性。在有限的网络连接下,直接或间接地与所有正在消费和/或生成数据的数据源和应用程序集成,并在公司内部和/或跨组织内为股东、交易和放弃的前瞻性地震买方、监管机构、资源认证机构和服务提供商等进行数据共享和协作。地震生态系统的实施将实现以下功能:通过采集、质量控制、数据处理和解释与用户社区共享地震数据;通过加密网络实现利益相关者的实时协作;利用云和移动技术的进步,实现敏捷性和交互性。该系统将相互连接和交互,但在后台具有复杂的高性能计算基础设施的能力。向使用来自不同平台的数据的更广泛、更多样化的用户群体提供数据交付和审计。基于组织业务单元保护数据访问,确保数据不会落入未经授权的人手中。通过并行输入/输出操作读取和摄取大量数据,减少地震数据周转时间。改进了数据传递和映射接口,使其具有来自集中式数据存储的上下文信息。通过机器学习和人工智能增强传统的工作流程,例如自动故障检测等,建议的最佳实践旨在将所有处理地震数据的不同学科集中到一个集中的地震数据存储库中,使他们能够使用和共享来自大数据湖的地震数据。与在独立应用程序中使用存档和恢复系统的传统技术相比,这是实时的和交互式的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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