DAS Strain to Displacement Spectrum Model for Moment Magnitude
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Solution Overview
Problem
Current seismic sensing technologies, such as geophones and accelerometers, have limitations in spatio-temporal resolution and sensor density, which hinder accurate moment magnitude estimation in seismic data analysis, especially with distributed acoustic sensing (DAS) systems that measure strain rather than ground motion.
Innovation Solution
A method involving the conversion of DAS data to displacement data using a specific algorithm, generating a displacement spectrum model, and estimating moment magnitude without relying on empirical relations, by assuming a gauge length of 0 and employing power-law spectrum models with compensation factors to improve accuracy in noisy conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If DAS systems are used to measure strain instead of ground motion, then sensor density and spatio-temporal resolution are improved, but the ability to directly estimate moment magnitude is worsened due to measuring strain rather than displacement
Solution Approach 1:
The patent introduces an intermediary conversion process that transforms DAS strain measurements into displacement spectrum models through a series of algorithmic steps including deconvolution, spectral estimation, and moment calculation. This intermediary framework bridges the gap between strain measurement and moment magnitude estimation, allowing the DAS system to achieve both high resolution and accurate magnitude estimation.
Solution Approach 2:
The patent changes the measurement parameter from strain (direct DAS output) to displacement spectrum (through conversion algorithms). By transforming the physical quantity being measured and applying parameter transformations including gauge length correction and spectral normalization, the system achieves accurate moment magnitude estimation while maintaining the high sensor density and spatio-temporal resolution benefits of DAS.
2Device complexity
If empirical relations are used for moment magnitude estimation, then the estimation process is simplified, but accuracy is worsened due to reliance on approximate relationships
Solution Approach 1:
The patent replaces empirical mechanical relationships with a physics-based spectral analysis approach. Instead of using approximate empirical formulas, the system performs first-principles calculations by computing displacement spectrum models from DAS data and calculating moment magnitude through integral relationships with the spectrum. This substitution increases computational complexity but significantly improves estimation accuracy by eliminating empirical approximations.
3Loss of time
If noisy DAS data is processed directly, then processing time is reduced, but measurement precision is worsened due to noise contamination
Solution Approach 1:
The patent applies preliminary signal processing actions including deconvolution, spectral estimation, and model fitting before final moment magnitude calculation. By performing these preparatory steps to clean and characterize the signal early in the process, the system reduces the need for subsequent iterative refinement, thereby limiting time loss while significantly improving measurement precision through noise reduction and signal characterization.
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
This approach enhances the accuracy of moment magnitude estimation by effectively handling noisy data and improving model fitting, leading to reliable signal moment calculations and reduced operational costs in borehole seismic operations.
Implementation Method 1
optical fiber-based seismic sensing technologies such as DAS provide industries (e.g., oil and gas industry) with new options for seismic sensing... DAS data of strain measurements from a plurality of sensors
Implementation Method 2
converting the DAS data to displacement data using a conversion algorithm
Implementation Method 3
generating a displacement spectrum model based on the displacement data... estimating a moment magnitude of a seismic moment using the displacement spectrum model
Data Source
AI summary
Systems and methods may be used to process seismic data acquired using a sensor array including optical fiber sensors in a seismic acquisition environment for modeling displacement spectrums from distributed acoustic sensing (DAS) of strain measurements for moment magnitude estimation. For example, a method may include receiving DAS data of strain measurements from a plurality of sensors of an oil and gas well system, converting the DAS data to displacement data using a conversion algorithm, generating a displacement spectrum model based on the displacement data, and estimating a moment magnitude of a seismic moment using the displacement spectrum model.