Probabilistic Label Placement for Well Log Data Visualization
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Solution Overview
Problem
Field engineers face a time-consuming task in labeling well logs from energy industry operations, as they need to label multiple logs daily at various depth levels without obscuring important data, and existing methods lack efficiency in positioning labels effectively.
Innovation Solution
A method and system that utilize a probabilistic algorithm, such as simulated annealing, to iteratively determine suitable locations for visual indicators on a display area, ensuring they do not overlap or obscure data, using a processor to generate and position labels on well logs for optimal visibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If field engineers manually label well logs multiple times daily at various depth levels, then labeling completeness is improved, but time consumption increases significantly
Solution Approach 1:
The system enables automatic self-labeling of well logs through computational algorithms that process data and generate labels without human intervention. The probabilistic algorithm automatically determines optimal label positions and content based on the well log data, eliminating the need for manual labeling while maintaining completeness.
Solution Approach 2:
The patent replaces the mechanical manual labeling process with an automated computational system. The processor executes algorithms that analyze well log data, determine appropriate labels, and position them automatically on the display, substituting human manual operations with automated digital processing.
2Loss of information
If labels are positioned manually to avoid obscuring important data, then data readability is improved, but positioning accuracy and consistency deteriorate
Solution Approach 1:
The system incorporates feedback mechanisms where the probabilistic algorithm continuously evaluates potential label positions and adjusts based on data characteristics. The algorithm considers the impact of labels on data visibility and iteratively optimizes positioning to maintain both readability and precision.
Solution Approach 2:
The patent employs parameter changes in the probabilistic algorithm to adapt label positioning based on different data conditions. The algorithm adjusts positioning parameters dynamically according to the well log data characteristics, ensuring optimal label placement that maintains data readability while achieving precise positioning.
3Productivity
If automated labeling is implemented using probabilistic algorithms, then labeling speed is improved, but system complexity increases
Solution Approach 1:
The system segments the labeling process into distinct functional modules: data reception, probabilistic algorithm processing, label generation, and display rendering. This segmentation allows each component to be optimized independently and simplifies the overall system architecture while maintaining high productivity through automated processing.
Data Source
AI summary
A method of delivering data from an energy industry or formation operation includes: receiving a data set representing parameter values generated during at least a portion of the operation; generating at least one data structure on a display area, the at least one data structure providing a visual representation of at least a portion of the data set; selecting a visual indicator associated with each of the at least one data structure, the visual indicator including information identifying an associated data structure; iteratively determining a suitable location for placement of the visual indicator on the display area by a processor using a probabilistic algorithm; and generating the display including the visual indicator located at the suitable position.