Geologic Formation Data Ingestion via GUI Template Validation
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Solution Overview
Problem
Current methods for data ingestion in geologic formation operations lack efficiency and automation, leading to suboptimal data processing and integration, particularly in complex drilling and well planning workflows.
Innovation Solution
A system and method for data ingestion using a graphical user interface (GUI) that initiates a data ingestion process, validates data descriptors, and stores a data ingestion template, enabling automated data ingestion and integration with computational frameworks for subsurface modeling, well planning, and resource production.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual data ingestion methods are used, then system complexity is reduced, but data processing efficiency and automation level deteriorate
Solution Approach 1:
The system enables self-service data ingestion through automated template generation and validation. The graphical user interface automatically generates data descriptors, validates data against templates, and processes data without requiring manual intervention in complex processing steps, thereby improving productivity while keeping the user interface simple
Solution Approach 2:
The system performs preliminary actions by pre-defining data templates and schemas before actual data ingestion occurs. These pre-configured templates guide the automated data processing, allowing efficient data ingestion without complex real-time processing logic, thus resolving the contradiction between productivity and system complexity
2Measurement precision
If automated data validation is implemented, then data processing accuracy is improved, but operation time increases
Solution Approach 1:
Data validation templates and schemas are prepared in advance before data ingestion. This preliminary configuration allows rapid validation of incoming data against pre-defined criteria, achieving high accuracy without time-consuming validation logic, thus resolving the contradiction between measurement precision and time loss
Solution Approach 2:
The system implements feedback mechanisms where data validation results are immediately fed back to users through the graphical user interface. This allows rapid iteration and correction of data issues, improving overall validation accuracy while minimizing time loss through immediate feedback loops
3Loss of information
If comprehensive data integration is performed, then information completeness is improved, but processing complexity increases
Solution Approach 1:
The data integration process is segmented into distinct modules within the graphical user interface: data ingestion, template generation, validation, and storage. Each module handles a specific aspect of data processing independently, making the overall complex process manageable and maintainable while ensuring complete data integration through systematic coverage of all processing stages
Data Source
AI summary
A method can include receiving a selection for data via a graphical user interface rendered to a display; via the graphical user interface, initiating a data ingestion process for the selected data; via the graphical user interface, rendering data descriptors generated by the data ingestion process; via the graphical user interface, issuing a validation instruction that validates the data descriptors; and, via the graphical user interface, issuing an instruction that stores a data ingestion template that includes the validated data descriptors.