Fiber-Optic DAS Coupling Warnings for Above-Array Sources
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Solution Overview
Problem
Existing methods for analyzing fiber optic-based borehole seismic measurements lack effective techniques to identify sensor coupling issues, especially when the surrounding medium is unknown, leading to noise and distortion in data acquisition, and are costly and inefficient.
Innovation Solution
A method involving obtaining normalized amplitudes from fiber optic-based borehole seismic measurements, computing depth derivatives, and performing outlier detection to identify coupling defects using statistical or deep learning methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional analysis methods using sonic logs and synthetic methods are used, then data analysis can be performed, but the method requires exact knowledge of the formation and cannot analyze unknown surrounding media
Solution Approach 1:
The system uses the DAS data itself to identify coupling issues through automated outlier detection algorithms, eliminating the need for external reference data or formation knowledge. The method self-calibrates by analyzing the statistical characteristics of the recorded signals to detect anomalies in coupling conditions.
Solution Approach 2:
The patent replaces conventional mechanical/physical analysis methods (sonic logs, synthetic modeling) with computational statistical methods. By using signal processing and outlier detection algorithms, the system identifies coupling issues without requiring physical core samples or detailed formation models.
2Productivity
If traditional quality control methods are used, then data quality can be assessed, but the process is costly and inefficient
Solution Approach 1:
The system performs continuous automated monitoring of coupling conditions throughout the acquisition process. By detecting issues in real-time rather than conducting post-acquisition analysis, the system identifies coupling problems immediately, enabling quick corrective action and reducing overall operational costs.
Solution Approach 2:
The automated outlier detection system performs quality control functions independently without requiring manual intervention or expensive external analysis services. The system self-diagnoses coupling issues using built-in algorithms, eliminating the need for costly third-party review or detailed formation modeling.
3Measurement precision
If coupling analysis is performed without automated warning systems, then complete data acquisition can occur, but noise and distortion in the data increases
Solution Approach 1:
The system continuously monitors coupling conditions and provides real-time feedback about the quality of the DAS signals. By detecting statistical outliers that indicate coupling issues, the system alerts operators to potential problems, enabling corrective action before significant noise and distortion accumulate in the data.
Solution Approach 2:
The patent replaces complex physical monitoring systems with computational signal analysis. By using statistical methods and outlier detection algorithms to identify coupling issues, the system achieves high measurement precision without requiring complex hardware or multiple sensor types.
Data Source
AI summary
Embodiments presented provide for a warning system and method that detects sensor coupling issues. The coupling issues sensed are for fiber optic based seismic measurements wherein the source is located above a distributed acoustic sensor array and the medium within which the sensors are located has unknown physical parameters.