Well Site Test Data Knowledge Graph Construction
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Solution Overview
Problem
The petroleum and natural gas drilling industry faces challenges in managing and searching for valuable data files due to complex data management, lack of standardized record-keeping, and inefficient sharing of knowledge and files during well site tests, leading to difficulties in quickly positioning and applying valuable information.
Innovation Solution
A processing method and device based on a knowledge graph that identifies file formats, generates mind maps, and creates knowledge graphs to organize and process structured, semi-structured, and unstructured data, enhancing storage, management, sharing, and querying efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional file management methods are used, then data storage capacity is maintained, but data querying efficiency deteriorates
Solution Approach 1:
The patent introduces a knowledge graph as an intermediary layer between traditional file storage and data querying operations. The knowledge graph establishes semantic relationships among data files, enabling efficient querying through relationship traversal rather than traditional file system search. This intermediary structure resolves the contradiction by providing fast query access without fundamentally changing the underlying storage system.
Solution Approach 2:
The patent adds a semantic relationship dimension to the traditional flat file management structure. By constructing a knowledge graph that represents data files as nodes and their relationships as edges, the system enables multi-dimensional querying capabilities. This dimensional enhancement allows users to query data through semantic relationships rather than relying solely on file path hierarchies, significantly improving query efficiency.
2Productivity
If multiple data formats are managed separately, then data integrity is maintained, but management efficiency deteriorates
Solution Approach 1:
The patent implements a universal knowledge graph structure that can accommodate multiple data formats (structured, semi-structured, and unstructured) through a unified representation model. The knowledge graph uses standardized entities, relationships, and attributes that can represent diverse data types without requiring separate management systems for each format, thereby improving management efficiency while maintaining adaptability to various data types.
Solution Approach 2:
The patent creates a composite data management approach by combining traditional file storage with knowledge graph technology. The system maintains the strengths of different data format handlers while integrating them through the knowledge graph framework, which synthesizes information from structured databases, semi-structured files, and unstructured documents into a unified semantic model, achieving both efficiency and versatility.
3Loss of information
If knowledge graphs are integrated with file management, then knowledge sharing capability is improved, but system complexity increases
Solution Approach 1:
The patent segments the knowledge management system into distinct functional modules: a knowledge graph construction module that processes data from multiple sources, a relationship extraction module that identifies connections between data elements, and a querying interface that leverages the knowledge graph. This segmentation allows the system to provide advanced knowledge sharing capabilities while isolating complexity into manageable, independent components that can be developed and maintained separately.
Data Source
AI summary
The present invention provides a processing method and device for data of a well site test based on a knowledge graph. The processing method for the data of the well site test based on the knowledge graph comprises: carrying out format identification on received historical data of the well site test to generate format identification results; establishing a mind map according to the format identification results; generating the knowledge graph of the data of the well site test according to the mind map; and processing the historical data of the well site test and new data of the well site test according to the knowledge graph.