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Revealing Patterns within the Drilling Reports Using Text Mining Techniques for Efficient Knowledge Management

机译:使用文本挖掘技术揭示钻探报告中的模式,以实现有效的知识管理

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In the current market conditions, foreseeing drilling risks and mitigating all the surprises beforehand will greatly reduce development costs. Rig personnel use the risk and message object in WITSML schema and daily drilling reports to capture rig activity, findings, unfavorable events, 24 hours well summary, etc. All the information from these objects are not extracted and effectively utilized in well planning exercise. This paper focuses on a collaborative approach of using text mining and knowledge management practices to mine unfavorable events and best practices from daily drilling reports and integrating them with subsurface information management system for maintaining risk inventory and Geospatial analysis. The proposed approach applies Information retrieval, Extraction, Clustering, Pattern Identification and Knowledge Management on daily drilling reports from offset wells to identify any data that might be relevant to drilling anomalies and best practices. Text mining converts unstructured information within the reports to structured data that can be then stored within existing subsurface data management systems. The results of text mining can be integrated with Geospatial techniques to perform risk assessment by leveraging spatially distributed large datasets from offset wells. This collaborative approach improves extracting and sharing of the risks and best practices among experts across the globe and alerting users of upcoming risks. This approach also enables building an effective risk inventory that can be reused for future well planning purposes. Using this approach, risk assessment can be executed for every rig activity, user defined depth range, hole section / size and upcoming formation markers. The results from text mining approach can also be visualized on advanced User Interfaces providing a bird's eye view of well operations. This approach streamlines the evaluation of risks in the planning stage of the well and enables effective collaboration between the drilling, geological and geophysical teams during execution. It also improves risk management and knowledge management practices. With the proper training, a well-defined drilling process, sufficient data and tools for interpretation; drilling a well should become a routine process.
机译:在目前的市场条件下,预见风险钻探和缓解所有的惊喜事先将大大降低开发成本。井队人员使用WITSML架构和日常的钻井报告捕获钻井活动,结果,不利事件的24小时以及汇总等风险和报文对象所有的这些对象的信息不被提取,并在良好规划工作有效利用。本文主要介绍如何使用文本挖掘和知识管理实践,以我的不利事件和日常的钻井报告的最佳实践,并与地下信息管理系统集成维护风险清单和地理空间分析的协作方式。所提出的方法应用于信息检索,提取,聚类,模式识别和知识管理对邻井的钻井日报报道,以确定可能是相关的钻井异常和最佳实践的任何数据。文本挖掘转换报告,以结构化数据可以然后存储现有的地下数据管理系统中的内非结构化信息。文本挖掘的结果可以与地理空间信息技术集成通过邻井的利用空间分布的大型数据集进行风险评估。这种合作方式提高了提取和世界各地的专家之间共享的风险和最佳做法,并警告即将到来的风险的用户。这种方法还能够建立,可以为未来的良好规划目的被重复使用有效的风险清单。使用这种方法,风险评估可以为每个钻井活动被执行,用户定义的深度范围,孔部/尺寸和即将形成标记物。从文本挖掘方法的结果也可以在高级用户界面,提供良好操作的鸟瞰可视化。这种方法简化了在井的规划阶段的风险评估,使钻井,地质和地球物理团队执行过程中的有效合作。它也提高了风险管理和知识管理实践。与适当的训练,定义良好的钻进过程中,有足够的数据和工具解释;钻井应该成为常规流程。

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