Unified Drilling Data Visualization for Stuck Pipe Prevention
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Solution Overview
Problem
Traditional methods for visualizing drilling operations data related to stuck pipe events are inadequate as they fail to provide a comprehensive view due to variability in data attributes and units, often requiring separate plots and lacking a holistic understanding.
Innovation Solution
The method involves scaling data values and threshold values for each attribute of interest, allowing for their visualization on a single graph, along with an average value, using a computer processor to facilitate a unified and easily interpretable representation of drilling operations data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional separate variable plots are used to visualize drilling operations data, then each individual attribute can be displayed, but a holistic view of all important data attributes cannot be achieved
Solution Approach 1:
The patent merges multiple separate variable plots into a single comprehensive plot that displays multiple data attributes simultaneously. Each attribute is plotted as a separate line on the same graph, allowing observers to see relationships and patterns across all attributes in one unified visualization rather than requiring multiple separate plots.
Solution Approach 2:
The patent introduces a new dimension to data visualization by plotting multiple attributes with different units and scales on a single two-dimensional graph. This is achieved by normalizing the data to a common scale, allowing different attributes to be displayed together without distortion, thus adding a dimensional aspect that enables holistic viewing.
2Adaptability or versatility
If data from multiple sources with different attributes and units are plotted together, then comprehensive analysis is enabled, but the plot becomes difficult to interpret
Solution Approach 1:
The patent changes the parameter of data scaling by normalizing all attributes to a common scale ranging from 0 to 100. This transformation allows data from multiple sources with different original units and scales to be plotted together while maintaining interpretability, as all values are now on a standardized scale that can be easily compared.
Solution Approach 2:
The patent introduces a scaling factor as an intermediary element that bridges different data attributes with different units. By applying appropriate scaling factors to each attribute, the system creates a common language for visualization, allowing diverse data to be combined without losing meaning or becoming unintelligible.
3Productivity
If multiple data attributes with different units are visualized on a single graph, then real-time insights are achieved, but data normalization is required
Solution Approach 1:
The patent performs data normalization as a preliminary action before visualization. By pre-scaling all attributes to a common 0-100 range, the system prepares the data in advance for efficient plotting and analysis. This preliminary processing enables rapid real-time insights without requiring complex normalization calculations during the actual visualization or analysis process.
Data Source
AI summary
Systems and methods for visualization of quantitative drilling operations data related to a stuck pipe event using scaled data values for each attribute of interest, a scaled predetermined threshold value for each attribute of interest and an average value of the scaled data values for each attribute of interest.