Microseismic anisotropic velocity calibration by using both direct and reflected arrivals

Pei, Donghong; Carmichael, J. H. E.; Waltman, Charlie; Warpinski, N.R.

doi:10.1190/segam2014-0097.1

Cited by 6 publications

(2 citation statements)

References 6 publications

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“…Ideally, the velocity model should be three dimensional (3D) to be able to effectively represent the subsurface geology and rock physics. However, most often the final model used to locate microseismic events is either one dimensional or at best two dimensional and rarely 3D (Oye et al ., 2004, 2014; Le Calvez et al ., 2013; Albaric et al ., 2014; Pei et al ., 2014; Akram and Eaton, 2017).…”

Section: Theorymentioning

confidence: 99%

Comparison of hypocentre locations from the reprocessing of a downhole microseismic dataset

Akram

Yang

Peter

2022

Geophysical Prospecting

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Focusing on a single vertical‐well microseismic monitoring dataset, the aim here is to objectively look at the hypocentre location determination workflow and compare results from another independent processing effort of the same dataset. To that end, we use the Akaike information criterion–based picker followed by the cross‐correlation‐based refinement for P‐ and S‐wave arrival times. We apply a particle swarm optimization algorithm to calibrate a one‐dimensional velocity model using a single ball‐drop event. Due to the absence of any a priori information, we obtain three different local solutions for the velocity model using the particle swarm optimization algorithm with different upper and lower bounds on the search space. We also use the particle swarm optimization algorithm to determine hypocentre locations for microseismic events. In addition, we perform a waveform‐similarity‐based analysis to identify clusters of closely located microseismic events. Our results show that the hypocentre locations from all three local solutions exhibit similar fracture orientations and dimensions, as compared to the results from another independent processing effort. However, random differences with mean and standard deviation values in x, y, z as (53.9, −23.2, −6.2 m) and (35.5, 42.6, 17.6 m) exist between the two processing versions. These differences can be explained by the combined effect of errors in arrival times, back‐azimuths and velocity models, and the use of different algorithms in the two processing efforts. We also find that the comparison of event clusters other than full event distributions is an effective way of identifying any systematic differences between the two processing results.

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Section: Theorymentioning

confidence: 99%

Comparison of hypocentre locations from the reprocessing of a downhole microseismic dataset

Akram

Yang

Peter

2022

Geophysical Prospecting

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“…This polarization direction uncertainty can be a major source of microseismic event location uncertainty in downhole moni-toring. Multiple arrivals can be used to improve location accu-racy in downhole microseismic survey (Pei et al, 2014;Zhang et al, 2015;Zimmer, 2011), however, the identification of some phases can be hindered by the resonance from their preced-ing phases. In addition, source parameters are useful for mi-croseismic characterization (Cipolla et al, 2012;Du et al, 2011;Eisner et al, 2007;Rutledge and Phillips, 2003;Urban-cic et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

Resonance in downhole microseismic data and its removal

Zhang

Nava

Rector

2016

SEG Technical Program Expanded Abstracts 2016

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We identified resonance due to poor geophone-borehole coupling in downhole microseismic data and proposed to use spik-ing deconvolution and relative spectrum analysis to remove its effect. The resonance may hinder the arrival time picking and contaminate microseismic waveform spectrum. We designed a spiking deconvolution filter to recover the impulse response of the earth. Also, we proposed to use relative spectrum analysis to study microseismic source parameters. The application of deconvolution on Marcellus shale dataset improved the identifiability of the multiple arrivals. Additionally, the relative spectrum analysis is more effective in revealing the actual spectrum characteristics of microseismic waveforms.

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Passive Seismic Complete Session

2016

SEG Technical Program Expanded Abstracts 2016

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Microseismic anisotropic velocity calibration by using both direct and reflected arrivals

Cited by 6 publications

References 6 publications

Comparison of hypocentre locations from the reprocessing of a downhole microseismic dataset

Comparison of hypocentre locations from the reprocessing of a downhole microseismic dataset

Resonance in downhole microseismic data and its removal

Passive Seismic Complete Session

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