Data Stacking Visualization for Well Log Interpretation QC
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The oil and gas industry faces challenges in efficiently identifying and correcting misinterpretations in large volumes of data generated from subsurface formations, particularly in well logs, which is a time-consuming and labor-intensive process for geoscientists.
Innovation Solution
The method involves generating a display representation of related data sets with markers for common entities, such as formation features, and using data stacking to visualize misalignments, allowing for quick identification and correction of misinterpretations through user input and analytical tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If machine learning is used to generate large quantities of data interpretations quickly, then productivity is improved, but quality control becomes more difficult and time-consuming
Solution Approach 1:
The patent combines multiple well logs and their interpretations into a single stacked visualization display. This merging allows quality control personnel to view and compare multiple data sets simultaneously in one interface, enabling efficient identification of misinterpretations across multiple wells without requiring separate review of each log individually.
Solution Approach 2:
The patent introduces an intermediary visualization layer that stacks well logs and highlights misalignments between markers representing common formation features. This intermediary display serves as a mediator between the raw data interpretations and the quality control process, automatically flagging potential errors and facilitating rapid verification without requiring manual comparison of each log pair.
2Reliability
If manual quality control of data interpretations is performed, then reliability is improved, but productivity decreases due to labor intensity
Solution Approach 1:
The patent implements self-service quality control by automatically stacking well logs and highlighting misalignments between markers. The system performs the initial quality control analysis autonomously, presenting only the problematic areas for human review. This eliminates the need for manual inspection of entire data sets while maintaining high reliability through automated detection of interpretation errors.
Solution Approach 2:
The patent uses visual highlighting and color changes in the stacked display to mark misaligned markers and potential interpretation errors. By automatically applying visual cues to indicate problems, the system enables rapid human verification without requiring analysts to manually scan through all data, significantly improving productivity while maintaining thorough quality control.
3Measurement precision
If data from multiple wells are reviewed individually, then measurement precision is maintained, but the complexity of the review process increases
Solution Approach 1:
The patent merges multiple well log displays into a single integrated stacked view where formation features from different wells are aligned and compared simultaneously. This unified display maintains measurement precision by preserving the accuracy of individual log interpretations while reducing process complexity through consolidated visualization and automated alignment, eliminating the need to manually switch between separate well reviews.
Data Source
AI summary
Methods, apparatuses, and computer-readable media utilize data stacking to facilitate identification and/or correction of data interpretation conducted for a subsurface formation. Related data sets, such as well logs, may be displayed along with markers representing a common entity in the related data sets, such as formation features in a surface formation, and a visualization of stacked data may be generated and centered on the markers to highlight mis-alignment of any of the markers.