Inversion for seismic anisotropy using genetic algorithms<sup>1</sup>

Horne, Steve; MacBeth, Colin

doi:10.1111/j.1365-2478.1994.tb00249.x

Cited by 25 publications

(2 citation statements)

References 21 publications

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“…GAs have the characteristics of global optimization, strong adaptability, and strong robustness [22]. They have been widely used in function optimization, nonlinear parameter estimation, pattern recognition, image processing, and other fields [23][24][25][26][27] since they were proposed by John Holland in 1975 [28]. GAs have also been employed for the solution of seismological and other geophysical and environmental problems in the present day [29].…”

Section: Introductionmentioning

confidence: 99%

Precise Identification of Coal Thickness by Channel Wave Based on a Hybrid Algorithm

et al. 2019

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Precise prediction of coal thickness is of the utmost importance in realizing intelligent and unmanned mining. As the channel wave is characterized by an easily recognizable waveform, a long propagation distance, and strong energy, it is widely used for coal thickness inversion. However, most traditional inversion methods are local in nature, and the inversion result is probably not optimal in the global scope. This paper introduces the GA-SIRT hybrid approach, which combines Genetic Algorithms (GA) and Simultaneous Iterative Reconstructive Techniques (SIRT) in order to deal with the above problem and to improve the accuracy of coal thickness inversion. The proposed model takes full advantage of the strong global search capability of GA and of the fast local convergence rate of the SIRT. Moreover, it inhibits the poor local search ability and the local optimal value effect of the GA and the SIRT respectively. The application of the GA-SIRT in the Guoerzhuang coal mine has significantly enhanced its accuracy, stability, and overall computational efficiency. Hence, the introduced novel hybrid model can precisely resolve and identify the coal thickness according to the channel wave. It can also be extended to other geophysical tomographic inversion problems towards the reduction of potential local optimal solutions.

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Section: Introductionmentioning

confidence: 99%

Precise Identification of Coal Thickness by Channel Wave Based on a Hybrid Algorithm

et al. 2019

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“…Inversion of passively acquired shear-wave splitting data was initially performed using genetic algorithms by Horne and MacBeth [1994]. Yang et al [2003] and Rial et al [2005] use shear-wave splitting results from passive and induced seismicity in geothermal areas to invert for strike, dip and density parameters of characteristic fracture sets in their study areas.…”

Section: Anisotropy Modellingmentioning

confidence: 99%

Methods and Computational Techniques for Investigating and Monitoring Seismic Velocities in the Earth's Crust

Shelley¹

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<p>This thesis is concerned with scrutinising the source, distribution and detectability of seismic velocity phenomena that may be used as proxies to study conditions in the crust. Specifically, we develop modelling techniques in order to analyse the directional variation of seismic wave speed in the crust and test them at Mt. Asama in Japan and Canterbury, New Zealand. We also implement both active source and noise interferometry to identify velocity variations at Mt. Ruapehu, New Zealand. Observations of temporal variation of anisotropic seismic velocity parameters at Asama volcano in Japan indicate that there is some process (or processes) affecting anisotropy, attributed to closure of microcracks in the rock as it is subjected to volcanic stress in the crust. To test this assertion, a 3D numerical model is created incorporating volcanic stress, ray tracing and estimation of the anisotropy to produce synthetic shear wave splitting results using a dyke stress model. Anisotropy is calculated in two ways; by considering a basic scenario where crack density is uniform and a case where the strength of anisotropy is related to dry crack closure from deviatoric stress. We find that the approach is sensitive to crack density, crack compliance, and the regional stress field. In the case of dry crack closure, modelled stress conditions produce a much smaller degree of anisotropy than indicated by measurements. We propose that the source of anisotropy changes at Asama is tied to more complex processes that may precipitate from stress changes or other volcanic processes, such as the movement of pore fluid. We develop a generalised anisotropy inversion model based on the linearised, iterative least-squares inversion technique of Abt and Fischer [2008]. The model is streamlined for use with results from the MFAST automatic shear wave splitting software [Savage et al., 2010]. The method iteratively solves for the best fitting magnitude and orientation of anisotropy in each element of the model space using numerically calculated partial derivatives. The inversion is applied to the Canterbury plains in the region surrounding the Greendale fault, using shear-wave splitting data from the 2010 Darfield earthquake sequence. Crustal anisotropy is resolved down to a depth of 20 km at a spatial resolution of 5 km, with good resolution near the Greendale fault. We identify a lateral variation in anisotropy strength across the Greendale fault, possibly associated with post-seismic stress changes. We perform active source and noise interferometry at Ruapehu in order to investigate potential seismic velocity changes and assess their use as a possible eruption forecasting method. Six co-located 100 kg ammonium nitrate fuel oil explosives were set off serially at Lake Moawhango, situated approximately 20 km south-east of Mount Ruapehu. Two methods of interferometry, using moving window cross correlation in the time and frequency domains, respectively, were applied to the recorded signal from each explosion pair in order to determine velocity changes from the signal coda waves. We identify possible diurnal velocity variations of ~ 0:7% associated with strain caused by the solid Earth tide. Synthetic testing of velocity variation recoverability was also performed using both methods. Interferometry of noise cross-correlations during the period was also performed using moving window cross correlation in the frequency domain. Analysis of velocity variations in the ZZ, RR and TT component pairs show little coherency. This, combined with results from synthetic testing that show that the frequency domain interferometry technique employed is unstable above velocity variations of 0.1%, indicate that the method may not be suitable for determining velocity variations at Ruapehu.</p>

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Inverting Shear-Wave Splitting Measurements for Fracture Properties

Verdon

2012

Microseismic Monitoring and Geomechanical Modelling of CO2 Storage in Subsurface Reservoirs

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Inversion for seismic anisotropy using genetic algorithms¹

Cited by 25 publications

References 21 publications

Precise Identification of Coal Thickness by Channel Wave Based on a Hybrid Algorithm

Precise Identification of Coal Thickness by Channel Wave Based on a Hybrid Algorithm

Methods and Computational Techniques for Investigating and Monitoring Seismic Velocities in the Earth's Crust

Inverting Shear-Wave Splitting Measurements for Fracture Properties

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Inversion for seismic anisotropy using genetic algorithms1

Cited by 25 publications

References 21 publications

Precise Identification of Coal Thickness by Channel Wave Based on a Hybrid Algorithm

Precise Identification of Coal Thickness by Channel Wave Based on a Hybrid Algorithm

Methods and Computational Techniques for Investigating and Monitoring Seismic Velocities in the Earth's Crust

Inverting Shear-Wave Splitting Measurements for Fracture Properties

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Inversion for seismic anisotropy using genetic algorithms¹