Digital Twin Reservoir Training With Iterative Development Feedback
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Solution Overview
Problem
Current training methods for reservoir engineers are inefficient, labor-intensive, and time-consuming, lacking realistic simulation of reservoir development conditions, leading to limited practical experience and significant resource consumption.
Innovation Solution
A system and method utilizing digital twin technology integrates reservoir models with data operation workstations, data distribution servers, and intelligent terminals for iterative simulation and training, allowing trainees to issue development instructions and receive feedback, thereby simulating real-world scenarios and enhancing practical knowledge application.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional training methods (lectures or on-site training) are used for reservoir engineers, then training can be delivered with simple systems, but the training efficiency is low and practical experience is limited
Solution Approach 1:
The patent creates a digital twin system that copies and simulates real reservoir development conditions, allowing trainees to practice in a virtual environment that replicates actual field scenarios. This enables high-fidelity training without the constraints of physical location and time, dramatically improving training efficiency while maintaining system accessibility
Solution Approach 2:
The system pre-establishes a comprehensive digital twin model integrating geological models, reservoir physical property models, and development models before training begins. This preliminary preparation creates a ready-to-use virtual training environment that can immediately provide realistic training scenarios without requiring actual field deployment
2Reliability
If real-world reservoir development projects are used for training, then practical experience can be gained, but time and economic costs are significantly consumed
Solution Approach 1:
By creating a digital twin that replicates real reservoir conditions, the system allows trainees to gain practical experience in a virtual copy of the actual development environment. This copying approach provides authentic training value without the time and economic costs of actual field projects, as mistakes in the virtual environment do not result in real financial losses
3Loss of information
If real reservoir development is used for training, then authentic feedback can be obtained, but the process is labor-intensive and cannot be scaled
Solution Approach 1:
The digital twin system incorporates feedback mechanisms that provide trainees with production performance data and development outcomes based on their decisions. This feedback loop replicates the information flow from real reservoir development, maintaining feedback accuracy while enabling unlimited parallel training instances through the virtual environment
Solution Approach 2:
The system copies the entire feedback mechanism from real reservoir development into the digital twin environment, allowing multiple trainees to simultaneously receive authentic-style feedback on their development decisions without requiring actual field operations for each training session
4Reliability
If iterative practical implementation is required for mastery, then deep understanding can be achieved, but the process consumes significant resources
Solution Approach 1:
The digital twin creates a reusable virtual environment where iterative practice can occur without consuming physical resources. Trainees can repeatedly implement and refine their understanding of reservoir engineering concepts through multiple simulation cycles, achieving deep knowledge internalization while the system consumes only computational rather than physical resources
Data Source
AI summary
Disclosed are a system and a method for training reservoir engineers based on digital twin technology. The training system includes a data operation workstation, a data distribution server and an intelligent terminal; trainees view initial data of reservoir geology by the intelligent terminal to form a preliminary understanding of the reservoir, and then issue reservoir development instructions; according to the development instructions, the reservoir numerical simulation operation module sends feedback data to the intelligent terminal after simulation calculation for the trainees to view, and the trainees analyze and determine reservoir feedback information, thereby forming a new understanding of the reservoir. After having updated understanding of the reservoir, the trainees issue a reservoir development instruction again by the intelligent terminal until the oil and gas field development is completed. After completion, the data operation workstation outputs recovery factor and profit amount of this development simulated by the trainees as simulation results.