Field Data Graph Structuring From Well Operation Reports
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Solution Overview
Problem
Challenges exist in extracting meaningful information from reports related to field operations in sedimentary basins, particularly in hydrocarbon reservoirs, which hinders effective data utilization and decision-making.
Innovation Solution
A method and system utilizing a large language model to transform input text from field operations into a graph structure with nodes and edges, representing relationships between chunks of text, facilitating data extraction and integration with machine learning models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional text extraction methods are used on field operation reports, then the extraction process is simple, but the meaningful information extraction is insufficient
Solution Approach 1:
The patent introduces an intermediary system comprising a processing circuit that acts as a mediator between the raw field operation reports and the final structured output. This intermediary system includes components for receiving reports, generating summaries, extracting entities and relationships, and storing structured data, thereby enabling meaningful information extraction without requiring direct complex processing of the original text
Solution Approach 2:
The patent replaces traditional mechanical text extraction methods with an AI-based natural language processing system. The processing circuit uses machine learning models to automatically understand, interpret, and extract meaningful information from unstructured field reports, substituting manual or rule-based text processing with intelligent automated analysis
2Ease of operation
If data is stored in unstructured format, then storage is straightforward, but future access and machine learning training are hindered
Solution Approach 1:
The patent segments unstructured field operation reports into structured components including entities (such as equipment, locations, events), relationships between entities, and contextual information. The processing circuit divides the text data into discrete meaningful units and organizes them into a structured format that can be easily accessed and utilized for machine learning training
Solution Approach 2:
The patent transforms data from an unstructured parameter state to a structured parameter state. The processing circuit changes the organizational parameters of the data by converting free-text reports into standardized formats with defined fields, relationships, and metadata, thereby improving data accessibility and usability while managing the complexity through systematic transformation
Data Source
AI summary
A method can include receiving input text associated with field operations at a field site that includes at least one well in fluid communication with a reservoir; assessing the input text with respect to one or more criteria to generate one or more chunks of text from the input text; directing the one or more chunks of text and a prompt to a large language model to generate corresponding output; and transforming the corresponding output into a graph structure, where the graph structure includes nodes and edges, and where each of the edges describes a relationship between a pair of the nodes.