Hydraulic Fracturing Advisors for Real-Time Fracture Optimization
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Solution Overview
Problem
Existing well stimulation jobs, such as hydraulic fracturing, face challenges in optimizing parameters in real-time to enhance fracture performance and minimize detrimental physical influences between adjacent wells, particularly in complex well architectures.
Innovation Solution
A control system with processors executing software modules to optimize hydraulic stimulation job parameters in real-time, utilizing advisors for material loading, fracture optimization, and job performance, incorporating machine learning and rule-based algorithms to advise on adjustments during the stimulation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple wells are stimulated within the vicinity of other wells (pad of wells), then well density and productivity are improved, but detrimental physical influence effects occur between adjacent wells
Solution Approach 1:
The system continuously monitors stimulation job parameters and fracture propagation in real-time, using feedback loops to detect when adjacent wells are experiencing detrimental physical influences. The monitoring system tracks pressure, flow rate, and fracture geometry data, and automatically adjusts stimulation parameters when negative interactions are detected between pad wells, thereby maintaining productivity while minimizing harmful effects.
Solution Approach 2:
The system dynamically changes stimulation parameters (injection rate, fluid viscosity, proppant concentration, pump pressure) based on real-time conditions and detected interactions between adjacent wells. By adjusting these parameters during the stimulation process, the system optimizes fracture performance for each well while accounting for the presence and status of neighboring wells in the pad.
2Productivity
If real-time optimization of hydraulic stimulation parameters is implemented, then fracture performance is improved, but system complexity and computational requirements increase
Solution Approach 1:
The control system is divided into modular software components, each handling specific functions such as data acquisition, real-time monitoring, fracture propagation modeling, parameter optimization, and control actuation. This segmentation allows the complex system to be developed, tested, and maintained independently in manageable modules while achieving real-time optimization of fracture performance.
Solution Approach 2:
The system employs intermediate software layers and APIs that facilitate communication between different control modules and external systems. These intermediaries manage data flow and coordination between monitoring sensors, computational models, and actuation systems, reducing the complexity of direct integration while enabling real-time optimization capabilities.
3Productivity
If real-time monitoring and adjustment of stimulation parameters is performed, then operational efficiency is improved, but data processing requirements and computational resources increase
Solution Approach 1:
The system performs preliminary processing and filtering of sensor data before full analysis, pre-computing fracture propagation models based on expected conditions, and establishing baseline parameters in advance. This preliminary action reduces the computational burden during real-time operation by preparing data structures and models beforehand, enabling efficient real-time optimization without overwhelming data processing requirements.
Data Source
AI summary
Systems and methods to enable stimulation job design and execution advisors for optimal fracture performance. For example, a control system may include one or more processors configured to execute processor-executable instructions stored on memory of the control system, wherein the processor-executable instructions, when executed by the one or more processors, cause the control system to initiate and implement one or more software modules in a modular manner to optimize parameters of a hydraulic stimulation job, and to provide advice regarding one or more adjustments to the parameters of the hydraulic stimulation job in substantially real-time during performance of the hydraulic stimulation job.