Mixed Fracturing Fleet Control for Fuel and Power Optimization
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Solution Overview
Problem
Existing hydraulic fracturing systems with mixed fleets of mechanical and electrical rigs face challenges in optimizing operations, leading to inefficiencies and wasted resources such as fuel and power.
Innovation Solution
A hydraulic fracturing system that includes a non-transitory computer-readable medium storing instructions to optimize the operation of both electric and mechanical rigs using a cost function and a particle swarm algorithm to iteratively tune operational parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple hydraulic fracturing rigs operate independently without optimization, then each rig can function autonomously, but fuel and power resources are wasted and operational efficiency decreases
Solution Approach 1:
The patent combines multiple independent hydraulic fracturing rigs into a coordinated fleet managed by a central controller. The controller receives operational data from all rigs and iteratively optimizes their operation using a cost function that balances fuel consumption, power usage, and production objectives. This merging of control systems transforms independently operating rigs into a unified optimized fleet, simultaneously improving productivity and reducing energy waste.
Solution Approach 2:
The system implements continuous feedback loops where the controller monitors operational parameters from each rig, evaluates performance against the cost function, and adjusts operational parameters in real-time. This feedback mechanism enables the system to learn from actual performance data and iteratively improve fuel efficiency and power utilization while maintaining or enhancing productivity.
2Adaptability or versatility
If a mixed fleet of mechanical and electrical rigs is used, then operational flexibility increases, but system complexity and difficulty of control increase
Solution Approach 1:
The controller is designed as a universal management system that can handle both mechanical and electrical hydraulic fracturing rigs through a unified interface and optimization algorithm. The cost function and iterative optimization process are agnostic to the specific rig type, allowing the same control system to manage diverse equipment. This universal approach maintains operational flexibility across different rig types while reducing the perceived complexity through standardized control procedures.
Solution Approach 2:
The central controller acts as an intermediary between the diverse mechanical and electrical rigs and the optimization objectives. It translates various rig-specific operational parameters into a common framework that can be evaluated by the cost function, then translates optimized parameters back to rig-specific controls. This intermediary layer shields operators from the underlying complexity while preserving the benefits of having a mixed fleet.
3Loss of energy
If iterative optimization is implemented across the fleet, then fuel and power efficiency improve, but computational requirements and processing time increase
Solution Approach 1:
The system implements iterative optimization at appropriate levels of detail without over-processing. The controller evaluates the cost function and adjusts parameters iteratively, but stops when sufficient optimization is achieved or when operational constraints require immediate action. This partial action approach balances the computational effort against the actual energy savings achieved, avoiding unnecessary processing time while still capturing the majority of efficiency improvements.
Solution Approach 2:
The system performs preliminary optimization calculations based on expected operational conditions and historical data before actual operations begin. By pre-calculating optimal parameter ranges and preparing optimization strategies in advance, the system reduces the real-time computational burden during actual fracturing operations, thereby minimizing processing time delays while maintaining optimization benefits.
Data Source
AI summary
A method may include receiving a set of inputs for operation of at least one electric hydraulic fracturing rig and at least one mechanical hydraulic fracturing rig of a hydraulic fracturing system. The method may further include optimizing operation of the at least one electric hydraulic fracturing rig and the at least one mechanical hydraulic fracturing rig based on at least the set of inputs. The method may further include iterating the optimization using a cost function for an operation mode of the hydraulic fracturing system.