Waveform-based source location method using a source parameter isolation strategy

Abstract

We have developed a novel acoustic-wave-equation-based full-waveform source location method to locate microseismic events. With the acoustic-wave equation and source signature independent inversion strategy, source location parameters (hypocenter locations) can be isolated from others and can then be retrieved independently and accurately, even when the origin time and source signature are not correct. Based on the acoustic-wave equation, new Fréchet derivatives of seismic waveforms with respect to the location parameters are derived to better accelerate the inversion process. To ease the cycle-skipping problem, a correlation is applied to select the best starting source positions. Some 2D and 3D numerical examples are presented to demonstrate the validity of our method. Compared with the waveform-based grid-search method, our method is effective in isolating the hypocenter locations from the source signature and origin time. The computational cost is nearly negligible compared with the waveform-based grid-search method. The robustness of our method is also tested for cases with inaccurate velocity models or using microseismic data with a signal-to-noise ratio of ≥[Formula: see text]. Finally, field data are used to indicate the practical applicability of our method.

Passive seismic imaging of subsurface natural fractures: application to Marcellus shale microseismic data

“…One solution is to locate hypocentres of microearthquake events before migration (Zhang et al 2009;Reshetnikov et al 2010). However, accurate predictions of the source location in passive seismic applications (microseismic or earthquakes) are still challenging, and the errors of the source location are unavoidable, even with sophisticated source-location methods (Waldhauser & Ellsworth 2000;Zhang & Thurber 2003;Huang et al 2017). Defocusing or missimaging of the pre-existing fractures can be caused by the inaccurate source locations (Zhu 2019), which makes the existing SDFI methods not applicable to passive seismic data directly.…”

Recent Advances and Challenges of Waveform‐Based Seismic Location Methods at Multiple Scales

“…Then these inverted source parameters could be further incorporated into the FWI for velocity model updates as shown in simple 2‐D acoustic model. Huang et al (, ) developed an acoustic‐wave‐equation‐based FWI method to locate microseismic events. They proposed to evaluate Frechet derivatives with respect to location parameters and apply the truncated Gauss‐Newton method to accelerate the inversion process.…”

“…All current methods of uncertainty assessment are limited to testing a fixed velocity model. We argue that the estimation of location uncertainty should also consider the uncertainty of the velocity model, which may be a main contributor (Gesret et al, ; Huang et al, ). For traveltime‐based methods, the velocity uncertainty can be implicitly contained in the observed or theoretical traveltime, while it is not straightforward to estimate velocity uncertainty with waveforms.…”

High-Accuracy Location of Microseismic Events in a Strong Inhomogeneous Mining Environment by Optimized Global Full Waveform Inversion

“…They tested the proposed location algorithm through 2D and 2.5D (a 2D velocity model is adopted in the vertical plane determined by the source location and sensor location) field and regional velocity models. While Huang et al [38,39] derived a waveform inversion-based location method that is independent from source-time characteristics, and they successfully applied the fast convergent truncated Newton method for microseismic source location based on 2D and 3D velocity models. Iteration-based optimization technique is often used in the above nonlinear waveform inversion-based location problem, which may be strongly affected by the initial model choice and cannot fully search the whole model space to obtain global convergence.…”