LLM Hybrid Data Generator for Wellbore Cement Job Design
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Solution Overview
Problem
The design of cement compositions for wellbore use is complex, requiring satisfaction of multiple physical and non-physical process variables, and is often iterative, with documentation scattered across various systems, leading to inefficiencies and reduced productivity.
Innovation Solution
The use of hybrid data generators, including Large Language Models, to aid in the creation of wellbore cement job designs, which synthesize industry best practices, company work methods, and safety standards, and incorporate historical multi-disciplinary datasets to optimize cement job designs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional iterative cement design methods are used, then multiple process variables can be satisfied, but the design process requires repeated changes and convergence iterations, leading to increased time and reduced productivity
Solution Approach 1:
The patent replaces the traditional manual iterative design process with an automated computer-based system that uses machine learning models and algorithms to generate and evaluate cement job designs, eliminating the need for repeated manual iterations while maintaining satisfaction of all process variables
Solution Approach 2:
The system enables self-service by automatically generating multiple cement job design options, evaluating them against all process variables, and providing recommendations without requiring manual intervention for each iteration, thereby significantly improving design creation efficiency
2Loss of information
If documentation of cement design processes is scattered across various systems, then comprehensive information is available, but accessing and integrating this information becomes complex and time-consuming
Solution Approach 1:
The patent merges previously scattered documentation and data from various systems into a unified computer-based platform that centralizes all cement job design information, making it easily accessible and integrable without losing any comprehensive design information
Solution Approach 2:
The system provides multi-functionality by serving as a centralized repository, analysis tool, and design generation platform simultaneously, eliminating the need to access multiple separate systems while maintaining all necessary information
Data Source
AI summary
A method may include: providing one or more inputs to a hybrid data generator, wherein one of the one or more inputs is based at least in part on a wellsite location, wherein the hybrid data generator comprises a large language model, and wherein the large language model is based at least in part on a machine learning algorithm; utilizing an information handling system to generate a cement job design based at least in part on the one or more inputs and the hybrid data generator; performing at least a portion of a cementing operation based at least in part on the cement job design; and collecting at least one measurement from at least one sensor during the cementing operation.