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

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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.
Title: Innovative Automated Data Driven Daily Drilling Reporting Using Automated Data-Driven Models and a Digital Execution Platform
Description:
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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