Drilling Time Segmentation for Invisible Lost Time Measurement
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Solution Overview
Problem
Current drilling operations face inefficiencies due to non-productive time (NPT) and invisible lost time (ILT), which are not effectively measured or mitigated, leading to increased costs and reduced productivity.
Innovation Solution
The method involves using real-time data from sensors to convert drill time and parameter data into segmented data, applying empirical mode decomposition, and optimizing weights to identify and calculate ILT, allowing for analysis of drilling parameters to determine the cause and adjust operations to reduce ILT.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional post-operation comparison methods are used to assess ILT, then the assessment process is simple, but the measurement precision and ability to identify root causes is insufficient
Solution Approach 1:
The patent segments drilling operations into distinct phases (drilling, tripping, cementing, etc.) and further divides them into operational segments. This segmentation allows precise identification of where ILT occurs within specific operations, enabling root cause analysis while maintaining manageable data complexity through structured organization.
Solution Approach 2:
The patent introduces an intermediary computational system that processes raw drilling data, applies empirical mode decomposition, and generates ILT metrics. This intermediary layer transforms complex raw data into actionable insights without requiring direct complex measurement devices at the drilling site, resolving the contradiction between precision and complexity.
2Productivity
If drilling parameters are optimized to reduce ILT, then productivity improves, but the complexity of monitoring and adjusting parameters increases
Solution Approach 1:
The patent implements a feedback system where ILT measurements from actual operations are fed back into the planning process. The system compares planned vs. actual ILT, identifies deviations, and provides feedback for optimizing future drilling parameters and sequences, continuously improving productivity while managing complexity through iterative learning.
Solution Approach 2:
The patent performs preliminary ILT analysis and parameter optimization before drilling operations begin. By pre-calculating optimal drilling parameters, sequences, and schedules that minimize predicted ILT, the system reduces the complexity of real-time monitoring while maintaining high productivity through pre-optimized operations.
3Reliability
If detailed real-time data collection is implemented to identify ILT causes, then the ability to mitigate ILT improves, but the complexity and cost of data collection systems increases
Solution Approach 1:
The patent utilizes existing multi-functional drilling data collection systems that already capture parameters for operational control. By repurposing these existing sensors and data streams for ILT analysis rather than adding dedicated ILT measurement equipment, the system achieves reliable ILT identification without proportionally increasing system complexity or cost.
Data Source
AI summary
A method may comprise drilling a wellbore penetrating a subterranean formation; collecting drill time data for the drilling; converting the drill time data into segmented drill time data; decomposing the segmented drill time data into intrinsic mode functions (IMFs) using an empirical mode decomposition; reconstructing the segmented drill time data by combining the IMFs with different weights, thereby producing modified segmented drill time data; and calculating an invisible lost time for the drilling based on the segmented drill time data and the modified segmented drill time data.