Distributed Acoustic Sensing Noise Removal via Quality Factor Analysis
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Solution Overview
Problem
Distributed Acoustic Sensing (DAS) data for hydrocarbon wellbores suffers from noise artifacts such as horizontal and vertical noise events, which reduce the accuracy of seismic data and hinder precise monitoring of hydrocarbon formations.
Innovation Solution
A method for identifying and removing noise events in DAS data sets using quality factor calculations and noise pilot traces, combined with variance-based weighted stacking schemes, to enhance the accuracy of seismic data collected from fiber optic cables in wellbores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If DAS data is collected using fiber optic cables in wellbores, then seismic data can be obtained for monitoring hydrocarbon formations, but noise artifacts such as horizontal and vertical noise events reduce the accuracy of the seismic data
Solution Approach 1:
The patent extracts and removes noise events from DAS data sets by identifying them through quality factor calculations and separating them from the seismic data using variance-based weighted stacking schemes, thereby improving measurement precision
Solution Approach 2:
The patent introduces quality factor calculations and variance-based weighted stacking as intermediary processing steps between data acquisition and final analysis, which mediate to reduce noise artifacts and improve seismic data accuracy
2Measurement precision
If traditional geophone deployments are used to collect seismic data, then measurement accuracy can be maintained, but the system becomes more complex and expensive
Solution Approach 1:
The patent uses fiber optic cables as a simplified copy or alternative to traditional geophone systems, leveraging optical sensing to achieve seismic data collection with reduced deployment complexity and cost while maintaining measurement precision through advanced noise processing
Solution Approach 2:
The patent replaces the mechanical geophone system with an optical-based DAS system using fiber optic cables and light pulse transmission, substituting mechanical sensing with optical sensing to reduce device complexity while maintaining measurement capability
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 proposed method effectively reduces noise in DAS data, improving the accuracy and quality of seismic data, allowing for more precise monitoring of hydrocarbon formations without the need for expensive geophone deployments.
Implementation Method 1
Acoustic sensing based on DAS may use the Rayleigh backscatter property of a fiber's optical core and may spatially detect disturbances that are distributed along a length of fiber positioned within a wellbore
Data Source
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AI summary
An example method includes at least partially positioning within a wellbore an optical fiber of a distributed acoustic sensing (DAS) data collection system. Seismic data from the DAS data collection system may be received. The seismic data may include seismic traces associated with a plurality of depths in the wellbore. A quality factor may be determined for each seismic trace. One or more seismic traces may be removed from the seismic data based, at least in part, on the determined quality factors.