Multi-Temporal Data Conversion for Well Log Analysis
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Solution Overview
Problem
The challenge lies in managing and processing the large and continuously growing amounts of data from well logs, particularly in converting uni-temporal data into multi-temporal data to accurately reflect the properties recorded in well logs, while servicing the flow of data through computing systems.
Innovation Solution
A method that involves receiving configuration data to map agents of a source computing system to nodes of a graph, generating row and column identifiers for time series data, and forming multi-temporal tables by storing this data, allowing for the conversion of uni-temporal data into multi-temporal data that includes additional axes for time and version, enabling effective data management and comparison.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If uni-temporal data is converted to multi-temporal data with additional time and version axes, then data tracking and comparison capability is improved, but data storage complexity and processing overhead increase
Solution Approach 1:
The patent applies dimensionality change by transforming uni-temporal data into multi-temporal data with additional time and version axes. This is achieved through generating row keys that include acquisition time values and column identifiers that include version time values, thereby adding dimensional information without fundamentally changing the underlying data structure.
Solution Approach 2:
The patent segments the temporal information into distinct components: acquisition time (when data was generated) and version time (when data was received). This segmentation is implemented through separate fields in the row key and column identifier, allowing independent tracking and querying of different temporal aspects.
2Productivity
If configuration data mapping agents to nodes and tables is implemented, then data organization and retrieval efficiency is improved, but initial data processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary action by pre-establishing configuration data that maps agents to nodes and nodes to tables before data ingestion occurs. This mapping configuration is prepared in advance, enabling direct and efficient data routing and storage without requiring complex runtime decision-making.
Solution Approach 2:
The patent introduces configuration data as an intermediary layer between the data ingestion system and the underlying storage structure. This intermediary contains pre-defined mappings that mediate between incoming data streams and target storage locations, simplifying the data flow path.
Data Source
AI summary
A method includes receiving configuration data that maps an agent of a source computing system to a node of a graph, maps the node to a table, and maps the agent to an agent topic; and receiving time series data at the agent topic as uni-temporal data from the agent mapped to the node. The method further includes generating a row key, from the configuration data and for the time series data, that includes a value identifier and an acquisition time value; and generating a column identifier, from the configuration data and for the time series data from the agent, that includes a version time value identifying when the time series data is received. The method further includes forming the table as a multi-temporal table by storing the time series data in the table with the row key and with the column identifier.