Enhanced Inversion for Distributed Acoustic Sensing: A Robust Approach with HOLp-OGS Regularization.
Wenhua Xu1, Jingye Li1, Yaning Wu2
1State Key Laboratory of Petroleum Resources and Prospecting, College of Geophysics, China University of Petroleum (Beijing), Beijing 102249, China.
Sensors (Basel, Switzerland)
|July 15, 2026
Summary
Converting distributed acoustic sensing (DAS) strain-rate data to geophone-equivalent particle velocity is crucial for seismic analysis. A new framework combining high-order Lp and overlapping group sparsity regularizations improves data fidelity, especially in noisy, low signal-to-noise ratio conditions.
Area of Science:
- Geophysics
- Seismic data acquisition and processing
Background:
- Distributed Acoustic Sensing (DAS) measures strain or strain rate, unlike conventional geophones measuring particle velocity.
- Integrating DAS data into existing seismic workflows requires converting strain-rate measurements to particle velocity.
- Standard conversion methods struggle with noise amplification, especially at low signal-to-noise ratios (SNRs), impacting data fidelity.
Purpose of the Study:
- To develop an advanced inverse reconstruction framework for accurate DAS-to-geophone conversion.
- To overcome limitations of existing single-regularization methods in noise attenuation and waveform preservation.
- To enhance the integration of DAS measurements into conventional seismic processing.
Main Methods:
- Proposed an inverse reconstruction framework combining high-order Lp (HOLp) and overlapping group sparsity (OGS) regularizations.
- HOLp regularization suppresses incoherent fluctuations and promotes compact second-order differences.
- OGS regularization exploits local coherence to preserve weak events and reduce artifacts.
- Solved the objective function using the alternating direction method of multipliers (ADMM).
Main Results:
- The proposed method effectively restores amplitude and waveform fidelity in low SNR conditions.
- Demonstrated robust and reliable conversion of DAS strain-rate data to geophone-equivalent particle velocity.
- Numerical and field experiments validated the framework's performance.
Conclusions:
- The combined HOLp and OGS regularization framework offers superior performance for DAS-to-geophone conversion compared to single-regularization methods.
- This approach enhances the utility of DAS data in seismic exploration, particularly in challenging field environments.
- The method provides a reliable solution for integrating DAS measurements into established seismic workflows.
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