Smart Grouping Legend for Drilling Analysis Comparison
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Solution Overview
Problem
Existing drilling operation modeling and analysis software can only handle a single analysis at a time, discarding previous results and making it difficult for users to compare changes in operational parameters across multiple analyses.
Innovation Solution
A computer-implemented method and system that allows users to run and retain multiple models and analyses within a given session, using a flexible database structure to store operational parameters and provide a graphical interface for easy comparison of results across different drilling depth or time ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the software allows multiple analyses to be run simultaneously, then the ability to compare operational parameters across different analyses is improved, but the system complexity and data management requirements increase
Solution Approach 1:
The software divides the analysis management system into separate modules: a database layer for storing multiple analysis instances, a processing layer for executing individual analyses, and a presentation layer for displaying and comparing results. This segmentation allows the system to handle multiple analyses independently while maintaining organized data structures and reducing overall system complexity.
Solution Approach 2:
The system creates and stores copies of analysis results and operational parameters in a structured database format. Each analysis instance is preserved as a discrete record, allowing users to retrieve, compare, and re-analyze previous results without re-running the entire analysis process, thus managing complexity through efficient data replication.
2Ease of operation
If the software retains previous analysis results for comparison, then the ease of operation is improved, but the memory and storage requirements increase
Solution Approach 1:
The system extracts only the essential operational parameters and key results from each analysis instance for storage and comparison, rather than retaining all raw data and intermediate calculation steps. This selective extraction maintains the ability to compare analyses while minimizing storage requirements by keeping only the most relevant information.
Solution Approach 2:
The software transforms detailed analysis results into condensed parameter summaries that capture the essential differences between analyses. By changing the representation from comprehensive raw data to standardized parameter sets, the system enables efficient storage and rapid comparison while preserving the ability to retrieve detailed information when needed.
3Speed
If the software requires re-entry of operational parameters for each analysis, then the processing speed is improved, but the productivity decreases
Solution Approach 1:
The system performs preliminary storage of operational parameters and analysis configurations in a structured database during the first analysis. This preliminary action creates a reusable template that can be automatically loaded for subsequent analyses, eliminating the need for users to re-enter parameters and significantly improving productivity while maintaining fast processing speeds.
Solution Approach 2:
The software implements a feedback mechanism where previous analysis results and parameter settings are automatically retrieved and presented as starting points for new analyses. Users can review and modify these pre-loaded parameters before running new analyses, reducing repetitive data entry while maintaining the ability to adjust parameters as needed for each specific analysis case.
Data Source
AI summary
A smart legend groups plot lines that reflect the same type of drill string analysis. The smart legend includes parent level legend entries, each parent level legend entry including child level legend entries. The child level legend entries for a given parent level legend entry correspond to plot lines that reflect a particular type of drill string analysis. Each child level legend entry corresponds to a plot line that reflects the particular drill string analysis performed over a different depth range. This allows users easily to view and compare the analyses at the different drilling depth ranges.