Multiphase Flow Simulator Submodeling for Production Networks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for simulating oil and gas production systems are complex and inefficient, particularly in modeling multiphase flow through large networks of flowlines and production equipment, which hinders optimal production optimization and decision-making.
Innovation Solution
A method and system for simulating oil and gas production systems using a flow simulation model that includes equations for multiphase flow, nodal analysis, and equipment modeling, allowing for the creation of network models that account for various types of wells and equipment, and a scheduler to manage simulation time steps and data transfer between sub-models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive multiphase flow simulation is performed across the entire production network, then accuracy of production analysis is improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The production network is divided into multiple sub-networks, each simulated independently by separate simulation engines. This segmentation allows complex multiphase flow simulation to be performed on manageable portions of the system, maintaining accuracy while reducing overall computational complexity and enabling parallel processing.
2Productivity
If detailed equipment modeling is included in the simulation, then production optimization capability is improved, but simulation processing time increases
Solution Approach 1:
Equipment modeling is distributed across multiple simulation engines, each handling specific sub-networks with their associated equipment. This allows detailed equipment modeling to be performed in parallel, improving optimization capability while reducing total simulation time through concurrent processing.
Solution Approach 2:
The simulation operates in discrete time steps with periodic updates of equipment states and flow conditions. This periodic action allows the system to maintain detailed equipment models while managing computational load by updating simulations at specific intervals rather than continuously.
3Reliability
If real-time data transfer between sub-models is implemented, then system coordination is improved, but data management complexity increases
Solution Approach 1:
A central scheduler acts as an intermediary between multiple simulation engines, coordinating data transfer and synchronization. This mediator manages the complexity of real-time data exchange by providing a standardized interface and communication protocol, ensuring system coordination while abstracting away the complexity of direct peer-to-peer data management.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method can include receiving a model of a fluid production network where the model includes a plurality of sub-models; synchronizing simulation of the plurality of sub-models with respect to time; and outputting values for fluid flow variables of the model.