Fracture Geometry Control via Acoustic RLC Inversion
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Solution Overview
Problem
Current methods for monitoring and controlling fracture geometry during hydraulic fracturing operations are limited by the availability of optical fiber installations and face challenges in accurately interpreting acoustic interference from perforations, requiring intensive training and data integration.
Innovation Solution
The use of a Resistance, Inductance, and Capacitance (RLC) model and poro-elastic inversion to estimate dominant fracture dimensions, combined with real-time monitoring of pressure and slurry flow rates, allows for the adjustment of hydraulic fracturing parameters to control fracture geometry and prevent well interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fiber optic DAS cable installation is performed, then fracture monitoring capability is improved, but installation complexity and cost increase
Solution Approach 1:
The patent uses acoustic signals as an intermediary to transmit fracture information without requiring physical fiber optic cables in the wellbore. The acoustic signals propagate through the formation and are detected by surface sensors, eliminating the need for complex downhole fiber optic installations while maintaining monitoring capability.
Solution Approach 2:
The patent replaces the mechanical fiber optic cable installation system with an acoustic signal-based monitoring system. Instead of installing physical cables downhole, the system uses acoustic waves to carry information about fracture geometry and propagation, substituting a complex mechanical installation with a simpler acoustic field-based approach.
2Loss of information
If DAS data is used to detect flow through perforations, then fracture information can be obtained, but acoustic interference from cavitation noise reduces measurement precision
Solution Approach 1:
The patent extracts and isolates the useful acoustic signals carrying fracture information from the noisy acoustic field containing cavitation interference. By using signal processing techniques and acoustic modeling, the system separates the meaningful fracture propagation signals from the harmful cavitation noise, enabling accurate measurement despite the presence of acoustic interference.
Solution Approach 2:
The patent converts the harmful cavitation noise into a beneficial indicator of fracture activity. The acoustic signals generated by cavitation, while interfering with direct flow measurement, actually provide information about the mechanical stress and fluid dynamics within the fracture system, which can be used to infer fracture geometry and propagation status.
3Measurement precision
If intensive training and data integration are performed to interpret DAS data, then interpretation accuracy is improved, but time consumption and operational complexity increase
Solution Approach 1:
The patent implements self-service through automated acoustic signal processing and fracture parameter calculation. The system automatically processes acoustic signals, models fracture geometry, and provides real-time monitoring without requiring extensive human training or manual data integration. The automated algorithms handle the complex signal processing and interpretation that would otherwise require intensive training.
Solution Approach 2:
The patent uses feedback mechanisms where the system continuously monitors acoustic signals, compares them against modeled fracture behavior, and provides real-time feedback on fracture propagation status. This automated feedback loop eliminates the need for manual interpretation and training, providing accurate results through algorithmic processing rather than human expertise.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables real-time monitoring and control of fracture geometry, improving the quality of hydraulic fracturing services by accurately determining fracture dimensions and adjusting operational parameters to achieve desired fracture geometries without the need for extensive hardware installations.
Implementation Method 1
The use of a Resistance, Inductance, and Capacitance (RLC) model and poro-elastic inversion to estimate dominant fracture dimensions
Implementation Method 2
Fiber optic distributed acoustic sensor (DAS) technology is commonly used to monitor or evaluate a fracking result. DAS data may disclose a rock stress/strain which may be exerted by a slurry flow
Implementation Method 3
These perforations may cause acoustic interference due to cavitation noise
Data Source
AI summary
Systems and methods generally relate to monitoring, evaluating, and controlling fracture geometry during a hydraulic fracturing operation, in real time. A method comprises measuring a signal representing a condition in a wellbore; inputting the signal into a model for estimating a dimension of a dominant fracture; determining the dimension of the dominant fracture; determining a target dimension for the dominant fracture; and minimizing a difference between the dimension of the dominant fracture and the target dimension in real time, by adjusting at least an injection pressure or flow rate of a hydraulic fracturing fluid into the wellbore.