Hydraulic Fracturing Pump Time Optimization via Real-Time Feedback
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Solution Overview
Problem
Current hydraulic fracturing operations lack an effective method to determine when the maximum number of hydraulic fractures have reached their target dimension, leading to inefficient pumping processes that continue beyond necessary, wasting time and resources.
Innovation Solution
The method involves analyzing fracture diagnostic and model data to estimate the optimal pumping parameters, such as pump time, volume, and rate, and adjusting the treatment schedule based on this data to ensure that hydraulic fractures reach their target dimension efficiently, utilizing graphs generated from measured data to determine when to cease pumping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the pumping process continues until the end of the planned treatment schedule, then all perforation clusters are intended to experience identical fracture growth, but this results in significant waste of time and resources since minimal fracture growth is still occurring
Solution Approach 1:
The system continuously monitors fracture growth in real-time during the pumping process and uses this feedback to dynamically adjust the treatment schedule. When the monitored fracture growth indicates that the target dimension has been achieved, the system automatically terminates pumping, eliminating the need to continue pumping until the end of the planned schedule and thereby reducing time waste.
Solution Approach 2:
The treatment schedule is transformed from a static, predetermined plan into a dynamic, adaptive process that responds to real-time fracture growth conditions. The system continuously adjusts pumping parameters based on monitored data, allowing the treatment to be extended or terminated at any point during the process rather than following a fixed schedule.
2Manufacturing precision
If the pumping process continues until the end of the planned treatment schedule, then all perforation clusters are intended to experience identical fracture growth, but this results in significant waste of resources
Solution Approach 1:
The system continuously monitors fracture growth in real-time during the pumping process and uses this feedback to dynamically adjust the treatment schedule. When the monitored fracture growth indicates that the target dimension has been achieved, the system automatically terminates pumping, eliminating the need to continue pumping until the end of the planned schedule and thereby reducing fracturing fluid waste.
Solution Approach 2:
The treatment schedule is transformed from a static, predetermined plan into a dynamic, adaptive process that responds to real-time fracture growth conditions. The system continuously adjusts pumping parameters based on monitored data, allowing the treatment to be extended or terminated at any point during the process rather than following a fixed schedule.
3Loss of time
If real-time monitoring of fracture growth is implemented, then the optimal pump time can be determined, but this increases the complexity of the treatment schedule management
Solution Approach 1:
The system automatically monitors fracture growth, analyzes the data, determines when the target dimension is achieved, and terminates pumping without requiring continuous manual intervention. The treatment schedule management performs self-service functions by autonomously adjusting parameters and making termination decisions based on real-time feedback.
Solution Approach 2:
The patent replaces manual treatment schedule management with an automated electronic system that uses sensors, data processing, and control algorithms to monitor fracture growth and adjust pumping parameters. This substitution of mechanical/manual operations with electronic automation reduces the perceived complexity despite adding technological components.
Data Source
AI summary
A method for adjusting the treatment schedule for a hydraulic fracturing operation corresponding to a hydrocarbon well to limit one or more pumping parameters (e.g., the pump time, pump volume, and/or pump rate) includes analyzing fracture diagnostic data and/or fracture model data to estimate the pumping parameter(s) at which the maximum number of hydraulic fractures will approximate a target fracture dimension during the hydraulic fracturing operation. The method also includes adjusting the treatment schedule for the hydraulic fracturing operation based on the estimated pumping parameter(s) and then hydraulic fracturing the hydrocarbon well according to the adjusted treatment schedule.


