Hydraulic Fracturing Breakdown Effectiveness Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Hydraulic fracturing job plans in the hydrocarbon production industry face challenges in optimizing fluid pumping parameters, leading to inefficient fracture development, increased maintenance costs, and uneven flow distribution, making it difficult to determine effective HF fluid pumping strategies for well systems.
Innovation Solution
A method and system that analyze historical HF data from similar well systems to calculate fitted functions and compute effectiveness parameters, allowing for the selection of optimal HF fluid pressure, flow rate, and composition inputs for current well systems, thereby modifying the job plan to minimize costs and maximize fracture efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If HF fluid pressure is ramped up to maximum pressure quickly, then fracture development speed is improved, but equipment wear and maintenance costs increase
Solution Approach 1:
The patent applies dynamics by implementing a ramp-up rate parameter that controls the rate of pressure increase over time. Instead of applying maximum pressure immediately, the system dynamically adjusts pressure according to a controlled rate, optimizing the balance between fracture development speed and equipment protection. This is achieved through the optimization algorithm that determines optimal HF job plan parameters including pressure ramp-up rates.
Solution Approach 2:
The patent changes the pressure parameter from a static maximum value to a dynamic parameter with controlled ramp-up rates. The optimization process determines optimal pressure profiles that include controlled increase rates, transforming the pressure application from an abrupt single-value parameter to a time-dependent parameter profile that balances effectiveness and equipment protection.
2Productivity
If HF fluid pressure is ramped up to maximum pressure quickly, then fracture development efficiency is improved, but operational costs increase
Solution Approach 1:
The system dynamically optimizes pressure ramp-up rates to achieve the most efficient fracture development within acceptable timeframes. Rather than using fixed high-pressure protocols, the system adapts pressure application rates based on formation characteristics and real-time conditions, improving productivity while minimizing unnecessary energy expenditure on excessively rapid pressurization.
Solution Approach 2:
The patent implements feedback through an optimization algorithm that analyzes formation response and adjusts pressure ramp-up rates accordingly. By monitoring fracture development progress and formation characteristics, the system provides feedback to determine optimal pressure application rates, ensuring efficient energy utilization while achieving productivity goals.
3Ease of operation
If HF job plan is based on operator bias and experience, then implementation simplicity is maintained, but determination accuracy of optimal pumping parameters deteriorates
Solution Approach 1:
The patent introduces an intermediary optimization algorithm that acts as a mediator between formation data and job plan parameters. This computational intermediary processes formation characteristics, pressure data, and flow rate information to objectively determine optimal pumping parameters, replacing subjective operator judgment with data-driven algorithms while maintaining ease of implementation through automated calculations.
Solution Approach 2:
The patent replaces the mechanical system of human operator judgment and experience-based decision-making with a computational algorithm. This substitution eliminates the limitations of human bias and experience variability, providing more accurate and consistent determination of optimal pumping parameters through mathematical optimization based on formation data and observed performance.
Data Source
AI summary
The disclosure improves the analysis of the hydraulic fracturing (HF) break down process of a well system. The analysis can use as inputs collected HF data such as the HF fluid pressure, HF fluid flow rate, and HF fluid composition over one or more time intervals. In some aspects, the perforation parameters and stratigraphic well placement can also be used as inputs. The analysis can also use as inputs the HF model inputs that were used in collecting the HF data. The analysis can determine an effectiveness parameter of the received inputs. HF model inputs can be selected that would best fit a HF job plan goal for the current well system. In some aspects, the HF model inputs can be communicated to a well system controller of the current well system to further direct HF job plan operations.