Distributed Acoustic Sensing FWI Using Reciprocal Source Points
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Solution Overview
Problem
Distributed acoustic sensing data transformed to velocity data for full waveform inversion experiences significant noise degradation, leading to a reduced signal-to-noise ratio, which affects the accuracy of subsurface velocity models.
Innovation Solution
Directly utilize strain and strain-rate data within the full waveform inversion algorithm by injecting synthetic source data into a seismic model using reciprocal source points, avoiding the conversion to velocity data and maintaining a higher signal-to-noise ratio.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If strain data is transformed to velocity data for full waveform inversion, then compatibility with conventional FWI workflows is improved, but signal-to-noise ratio deteriorates due to noise boosting from spatial deconvolution
Solution Approach 1:
The patent changes the fundamental parameter used for inversion from velocity to strain/strain-rate. By formulating the FWI algorithm to directly invert strain data without transforming to velocity, the method eliminates the spatial deconvolution step that causes noise boosting, while maintaining compatibility with conventional FWI through the use of reciprocal source points and adjusted source term formulations.
Solution Approach 2:
The patent substitutes the mechanical transformation process (strain to velocity conversion via spatial deconvolution) with a direct inversion approach using strain data. This replacement eliminates the harmful noise boosting effect while preserving the ability to perform full waveform inversion through modified source term formulations and reciprocal source point utilization.
2Manufacturing precision
If spatial deconvolution is applied to transform strain data to velocity data, then velocity data suitable for conventional FWI is produced, but noise is boosted particularly for low-spatial frequencies
Solution Approach 1:
The patent extracts and eliminates the problematic spatial deconvolution step from the workflow. By directly inverting strain data without the intermediate velocity transformation, the method removes the source of noise boosting while retaining the ability to produce accurate subsurface velocity models through direct strain inversion.
Solution Approach 2:
The patent converts the originally harmful strain data (which appeared incompatible with conventional FWI) into a beneficial direct inversion input. By formulating FWI to work directly with strain/strain-rate data using reciprocal source points, the method turns what was considered a limitation into an advantage, eliminating noise boosting while maintaining inversion 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
Maintains a higher signal-to-noise ratio, resulting in more accurate subsurface velocity models through direct inversion of strain and strain-rate data, enhancing the precision of seismic imaging and earth-model building.
Implementation Method 1
Distributed acoustic sensing systems use fiber (e.g., optical fiber) that is sensitive to the strain or strain-rate parallel to the fiber
Data Source
AI summary
A method implements the use of distributed acoustic sensing data with full waveform inversion. The method involves selecting a set of discrete locations along a fiber to act as a set of reciprocal source points, where the fiber provides sensor data sensitive to one or more of strain and strain-rate. The method further involves sorting the sensor data into a set of reciprocal source point gathers to generate sorted data. The method further involves modelling synthetic receiver data via reciprocity by injecting synthetic source data into a seismic model using the set of reciprocal source points. The method further involves updating the seismic model to reduce error between the sorted data and the synthetic receiver data.