Hydraulic Fracturing Event Detection With Closed-Loop Control
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Solution Overview
Problem
Existing fracturing processes struggle with accurately and consistently detecting and reporting events during hydraulic fracturing, making it difficult to automate and achieve consistency, safety, reliability, and efficiency.
Innovation Solution
A system that includes a controller to monitor and manage fracturing equipment, using sensors to determine the relationship between process and manipulated variables, allowing for precise adjustments based on the fracturing spread's behavior and response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If operator manually monitors diagnostic data and flags events, then flexibility in event detection is maintained, but measurement precision and consistency deteriorate
Solution Approach 1:
The system continuously monitors diagnostic data and automatically compares it against predefined thresholds and patterns, creating a closed-loop feedback mechanism that detects events without human intervention. This automated feedback loop ensures consistent and precise event detection while reducing reliance on manual operator monitoring.
Solution Approach 2:
The patent replaces the manual mechanical process of operator monitoring and event flagging with an automated electronic system that processes diagnostic data through algorithms and computational logic. This substitution eliminates human variability and improves measurement precision while managing complexity through software-based solutions.
2Productivity
If automation is implemented for fracturing process control, then efficiency and safety are improved, but reliability deteriorates due to inaccurate event detection
Solution Approach 1:
The automated system uses continuous feedback from multiple diagnostic data sources to validate events before triggering process changes. This multi-layered feedback approach ensures that automation actions are based on accurate event detection, thereby improving both efficiency and reliability simultaneously.
Solution Approach 2:
The system performs preliminary analysis of diagnostic data trends and patterns before automatically initiating fracturing process changes. By pre-processing and validating data beforehand, the system ensures that automation decisions are reliable and based on accurate event detection, not just raw data fluctuations.
3Stability of the object's composition
If automated control is implemented, then consistency is improved, but difficulty of detecting and measuring events increases
Solution Approach 1:
The automated detection system divides complex diagnostic data into distinct segments or categories, each monitored by specific detection algorithms. This segmentation makes event detection more manageable and systematic, improving consistency while reducing the overall difficulty of monitoring by breaking down the complexity into smaller, specialized detection tasks.
Solution Approach 2:
The patent implements a universal automated detection platform that handles multiple types of events and diagnostic parameters through a single integrated system. This multi-functional approach improves process consistency across different event types while reducing the cumulative difficulty of detection by providing a unified detection mechanism rather than separate systems for each event type.
Data Source
AI summary
Aspects of the subject technology relate to systems, methods, and computer-readable media for determining the response or behavior of the fracturing system on a fracturing spread level and utilizing the determined response or behavior to adjust a process variable. An example computing system may be configured to receive reference data, process variable data and manipulated variable data. Additionally, the computing system may be configured to generating sensitivity data based on the manipulated variable data and the process variable data. Moreover, the computing system may be configured to adjust one or more controller parameters based on the sensitivity data. Further, the computing system may be configured to adjust a setpoint of the first manipulated variable based on the one or more adjusted controller parameters, the reference data, and the process variable data.