DAS Near-Well Screen-Out Prediction via Friction Coefficients
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Solution Overview
Problem
Current methods for monitoring and predicting early screen-out in the near-well zone during multi-stage hydraulic fracturing in horizontal wells are inaccurate, making it difficult to assess connectivity and fracture development, leading to potential operational failures.
Innovation Solution
A method and system using distributed fiber acoustic sensing (DAS) to monitor acoustic signals and pressure data, calculating fracturing fluid flow velocity, friction resistance, and near-well friction resistance coefficients to predict the risk of early screen-out and generate treatment instructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If chemical tracers or micro-seismic monitoring techniques are used to monitor fracture propagation, then fracture development can be evaluated, but the accuracy is insufficient and only rough estimation of fluid distribution can be achieved
Solution Approach 1:
The patent replaces traditional mechanical monitoring methods (chemical tracers, micro-seismic sensors) with distributed fiber optic acoustic sensing technology. The DAS system uses optical fibers to detect acoustic signals along the wellbore, converting mechanical/acoustic measurements into optical signal processing, which provides higher precision in monitoring fracture propagation and fluid distribution in real-time during hydraulic fracturing operations.
Solution Approach 2:
The patent introduces distributed optical fiber acoustic sensing as an intermediary between the fracturing process and measurement systems. The optical fiber acts as a continuous sensor along the wellbore, capturing acoustic signals from fracture propagation and fluid flow, thereby enabling accurate monitoring of fluid distribution and fracture development without direct mechanical interference in the fracturing process.
2Strength
If proppant is injected to maintain fracture conductivity, then fracture integrity is improved, but proppant may accumulate in near-well zone causing early screen-out and increasing frictional resistance
Solution Approach 1:
The patent applies preliminary action by using DAS monitoring to detect early signs of proppant accumulation and near-well zone screen-out risk before they become critical problems. The system continuously monitors acoustic signals during fracturing operations, enabling operators to take corrective actions (such as adjusting injection rates or proppant characteristics) in advance to prevent complete screen-out and maintain fracture conductivity throughout the treatment.
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
The system provides accurate and reliable predictions of early screen-out risk, enhancing the efficiency and effectiveness of unconventional oil and gas reservoir development by improving decision-making and preventing operational failures.
Implementation Method 1
determining, based on a location of a perforation cluster, and acoustic signal of the perforation cluster, fracturing fluid flow velocity data of the perforation cluster
Implementation Method 2
Methods and systems for predicting risk of early-screen-out in near-well zone based on distributed fiber acoustic sensing (DAS)
Data Source
AI summary
A method for predicting a risk of early screen-out in a near-well zone based on distributed fiber acoustic sensing (DAS) is provided. The method comprises: obtaining an acoustic signal during a fracturing process based on distributed optical fibers deployed in a well to be fractured, and obtaining pressure monitoring data based on at least one sensor deployed in the well to be fractured; determining, based on a location of a perforation cluster, and an acoustic signal of the perforation cluster, fracturing fluid flow velocity data of the perforation cluster by a first predetermined algorithm; determining, based on the fracturing fluid flow velocity data of the perforation cluster and perforation parameters of the perforation cluster, a perforation friction resistance pressure drop of the perforation cluster by a second predetermined algorithm; determining a near-well friction resistance pressure drop of the perforation cluster based on a fluid pressure, the perforation friction resistance pressure drop, a slit fluid pressure; determining a near-well friction resistance coefficient of the perforation cluster based on the near-well friction resistance pressure drop of the perforation cluster; and determining, based on the near-well friction resistance coefficient, whether the perforation cluster has the risk of early screen-out in the near-well zone.


