Innovative Automated Data Driven Daily Drilling Reporting Using Automated Data-Driven Models and a Digital Execution Platform

Hamdi Mohamad, Felicity Anai Anak Michael Mulok, Douwe Franssens, Nurfitrah Mat Noh, Diego Patino, Janna Tiong Mang Ing
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Abstract

Currently, Automated Reporting leverages rig-sensors to produce ‘Activity’ and populated the Daily Drilling Report (DDR), replacing the labour-intensive manual entries. However, Surface and non-drilling activities cannot be detected in this way. The case study documents the complimentary use of a digital execution platform in filling these gaps. The automated daily drilling reporting solely on real-time rig sensors input causes a substantial number of non-drilling activities to be excluded and the data is not sufficient to produce solid 24-hour activities as required. Therefore, this paper presents a reporting solution that combines both real-time rig sensors input and activity tracking from a digital execution platform thus enabling the next level of reporting automation. Furthermore, the combination of these two sources ensures reporting accuracy and provides granularity for the next level of performance benchmarking. The paper documents the vision, methodology, implementation steps, challenges, and benefits of automating daily drilling reporting. The results of the case study were thoroughly discussed. The overall approach that was undertaken is straightforward where observation was conducted by identifying the similarity and differences of activities detected in the manual DDR and the improved automated reporting activities. The gap between the drilling activities (rig states) and non-drilling activities is corrected through a process of "cut and split" to capture the 24 hours activities. The planned activities were imported and monitored in the Digital Execution Platform, translated into WITSML (Wellsite Information Transfer Standard Markup Language) Drillreport object. Simultaneously, the real-time rig sensors data are available as WITSML log objects. DrillOps Report executes three tasks: Populate the sensor activities (Referred to as Automated Rig State Activity) by utilizing the "Fixed Text Remark" capability.Filter DrillReport object for actual activities on the rig marked as completed (Referred to as External Activity) by supervisors on the rig to populate all valid activities on rig.Overlapped activities in (1) and (2) will be cut and split accordingly where (1) supersedes the (2) as the single source of truth is the rig states detected by the rig sensors. On non-drilling days, (2) supersedes. This is referred to as Machine Activity Record (MAR). Other DDR information required is populated via FileBridge where the readily available information is parsed from the contractors' own reports into Automated Operational Reporting Solution. By utilizing the automated daily drilling reporting capabilities, rigsite users were able to reduce the time spent in capturing and entering the information required as part of the DDR. The rigsite personnel was then able to direct their attention on running daily data QA/QC prior to the daily report submission. This then allows them to put more focus on optimizing their wellsite operational performance and plan on any potential outcomes from the current activities. The structured data will enable post drilling actionable insights analysis.
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采用自动化数据驱动模型和数字执行平台的创新自动化数据驱动每日钻井报告
目前,自动化报告利用钻机传感器生成“活动”并填充每日钻井报告(DDR),取代了劳动密集型的人工输入。然而,地面和非钻井活动无法通过这种方式检测到。该案例研究记录了数字执行平台在填补这些空白方面的免费使用。仅根据实时钻机传感器输入的自动每日钻井报告导致大量非钻井活动被排除在外,数据不足以产生所需的24小时稳定活动。因此,本文提出了一种报告解决方案,结合了实时钻机传感器输入和数字执行平台的活动跟踪,从而实现了更高水平的报告自动化。此外,这两个来源的组合确保了报告的准确性,并为下一级性能基准测试提供了粒度。该文件记录了自动化每日钻井报告的愿景、方法、实施步骤、挑战和好处。对案例研究的结果进行了深入的讨论。所采取的总体方法是直接的,通过确定在手动DDR和改进的自动报告活动中检测到的活动的相似性和差异性来进行观察。钻井活动(钻机状态)和非钻井活动之间的差距通过“切割和分割”过程来纠正,以捕获24小时的活动。计划的活动在数字执行平台中被导入和监控,并转化为WITSML(井场信息传输标准标记语言)钻井报告对象。同时,实时钻机传感器数据可作为WITSML测井对象使用。drilllops Report执行三个任务:利用“Fixed Text Remark”功能填充传感器活动(称为自动化钻机状态活动)。过滤DrillReport对象,将钻机上的实际活动标记为已完成(称为外部活动),以填充钻机上的所有有效活动。(1)和(2)中的重叠活动将被相应地切割和分割,其中(1)取代(2),因为事实的单一来源是钻机传感器检测到的钻机状态。在非钻井日,(2)取代。这被称为机器活动记录(MAR)。其他所需的DDR信息通过FileBridge进行填充,在FileBridge中,可以将承包商自己的报告中的现成信息解析为自动化操作报告解决方案。通过利用自动化的每日钻井报告功能,现场用户能够减少捕获和输入DDR所需信息所花费的时间。在提交日常报告之前,现场人员可以将注意力集中在运行日常数据QA/QC上。这使得他们能够更加专注于优化井场作业性能,并计划当前活动的任何潜在结果。结构化数据将使钻井后的可操作洞察分析成为可能。
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