A Full-waveform, Migration-based Deconvolution Approach to Locating Micro-seismic Events

Haldorsen, J.; Milenkovic, M.; Brooks, N.; Crowell, C.; Farmani, M. Bagher

doi:10.3997/2214-4609.20148210

Cited by 2 publications

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“…[8,26,37]. Alternatively, one can use the migration based methods [14,27,28,29,38,4,21,31,46], among which using the time-reversal imaging (TRI) to migrate the micro-seismic signals to the source locations is a popular one. With TRI, less user input is required compared to the traveltime based methods.…”

Section: Introductionmentioning

confidence: 99%

Elastic Micro-Seismic Full Waveform Inversion with an Unknown Source

Wang¹,

Alkhalifah²

2018

Proceedings

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In micro-seismic event measurements, pinpointing the passive source's exact spatial and temporal location is paramount. This research advocates for the combined use of both P-and S-wave data, captured by geophone monitoring systems, to improve source inversion accuracy. Drawing inspiration from the secondary source concept in Elastic Reflection Full Waveform Inversion (ERFWI), we introduce an equivalent source term. This term combines source functions and source images. Our optimization strategy iteratively refines the spatial locations of the source, its temporal functions, and associated velocities using a full waveform inversion framework. Under the premise of an isotropic medium with consistent density, the source is defined by two spatial and three temporal components. This offers a nuanced source representation in contrast to the conventional seismic moment tensor. To address gradient computation, we employ the adjoint-state method. However, we encountered pronounced non-linearity in waveform inversion of micro-seismic events, primarily due to the unknown source origin time, resulting in cycle skipping challenges. To counteract this, we devised an objective function that is decoupled from the source origin time. This function is formulated by convolving reference traces with both observed and predicted data. Through the concurrent inversion of the source image, source time function, and velocity model, our method offers precise estimations of these parameters, as validated by a synthetic 2D example based on a modified Marmousi model. This nested inversion approach promises enhanced accuracy in determining the source image, time function, and velocity model.Preprint. Under review.

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Section: Introductionmentioning

confidence: 99%

Elastic Micro-Seismic Full Waveform Inversion with an Unknown Source

Wang¹,

Alkhalifah²

2018

Proceedings

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Locating microseismic sources using migration-based deconvolution

Haldorsen¹,

Brooks²,

Milenkovic³

2013

GEOPHYSICS

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We have developed a method for finding microseismic hypocenters from data recorded by arrays of triaxial motion sensors. The method reconstructs the elastic time-series signatures for possible microseismic sources at any point in 3D space, using full-waveform migration of the recorded vector wavefield. The imaging condition for the migration is based on a semblance-weighted deconvolution between two or more reconstructed source signatures, requiring similarity and simultaneity of the reconstructed signatures. This imaging condition eliminates the need for an absolute timing of the data, gives optimum resolution for the location of the microseismic sources—better than correlation-based approaches—and ensures numerical stability by adapting to the signal and noise conditions of the data. Because the method eliminates time-consuming phase picking and traditional event association, it should be well suited for fully or semiautomated data processing. The method was tested by an application to field data acquired with arrays of three-component receivers in two deep wells. Nevertheless, the formulation is equally applicable to data acquired by a distribution of single three-component receivers, or local arrays of these, deployed at the surface or in one or several shallow wells.

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A Full-waveform, Migration-based Deconvolution Approach to Locating Micro-seismic Events

Cited by 2 publications

References 0 publications

Elastic Micro-Seismic Full Waveform Inversion with an Unknown Source

Elastic Micro-Seismic Full Waveform Inversion with an Unknown Source

Locating microseismic sources using migration-based deconvolution

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