ADMM-based full-waveform inversion for microseismic imaging

Abstract

Summary Full waveform inversion (FWI) is beginning to be used to characterize weak seismic events at different scales, an example of which is microseismic event (MSE) characterization. However, FWI with unknown sources is a severely underdetermined optimization problem, and hence requires strong prior information about the sources and/or the velocity model. The frequency-domain wavefield reconstruction inversion method (WRI) has shown promising results to mitigate the nonlinearity of the FWI objective function generated by cycle-skipping. WRI relies on the reconstruction of data-assimilated wavefields, which approach the true wavefields near the receivers, a helpful feature when the source is added as an additional optimization variable. We present an adaptation of a recently proposed version of WRI based on the alternating direction method of multipliers (ADMM) that first finds the location of the MSEs and then reconstructs the wavefields and the source signatures jointly. Finally, the subsurface model is updated to focus the MSEs at their true locations. The method does not require prior knowledge of the number of MSEs. The inversion is stabilized by sparsifying regularizations separately tailored to the source location and velocity model subproblems. The method is tested on the Marmousi model using one MSE and two clusters of MSEs with two different initial velocity models, an accurate one and a rough one, as well as with added noise. In all cases, the method accurately locates the MSEs and recovers their source signatures.

Mining Stress Distribution in Stope and Overlying Rock Fracture Characteristics and Its Disaster-Pregnant Mechanism of Coal Mine Earthquake

“…Te high and low energy microseismic signals were monitored at the same time. According to the layout principle of microseismic monitoring network [37], a total of 16 microseismic monitoring stations were arranged in the Dongtan coal mine, which mainly monitor the frst mining section, fourth mining section, and fourteen mining section where the working face is excavated or mined. Te microseismic events of efective monitoring were 4 or more stations from the actual monitoring situation, and mostly used P wave positioning.…”

An Energy Focusing-Based Scanning and Localization Method for Shallow Underground Explosive Sources

“…According to the fitness function shown in Equation (22), the fitness values of particles in the initial population are calculated. The particle with the largest fitness value is selected as the global optimal g best by comparison, and the average optimal position m best of the current initial population is calculated.…”

“…Wavefront tomography also requires a wide range of high-density sensor arrays with a sufficient aperture for tomography inversion to obtain a high-precision velocity model; otherwise, it may lead to source localization failure [19,20]. The full waveform inversion (FWI) localization method is used to acquire the source location by minimizing the residual between the observed waveform and the synthesized waveform to complete waveform matching [21,22]. However, FWI requires continuous forward modeling and velocity updates, which have a high computational cost and require a more accurate initial velocity model.…”

Securing Fast and High-Precision Localization for Shallow Underground Explosive Source: A Curiosity-Driven Deep Reinforcement Learning Approach

“…The location of the shallow underground explosive source is relatively shallow, generally no more than 100 m [3]. The explosive source can be the active source caused by humans (such as artificial explosion and the explosion of penetration projectiles) or the passive source caused by nature (such as rock burst and gas explosion in coal mine) [4], [5]. This paper focuses on the study of strong vibration events caused by explosion.…”