Potential of Fractal Analysis of Earthquakes through Wavelet Analysis and Determination of<i>b</i>Value as an Aftershock Precursor: A Case Study Using Earthquake Data between 2003 and 2011 in Turkey

Srivardhan, V.; Srinu, Uppala

doi:10.1155/2014/123092

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…The multi-scale analysis of geophysical data is a new concept that has been applied to many fields of geophysical signal analysis ranging from earthquake seismology (Dimri et al 2005;Srivardhan and Srinu 2014), magnetotellurics (Telesca et al 2012), electrical methods (Vedanti and Dimri, 2003), gravity and magnetic methods (Maus and Dimri, 1994;Maus and Dimri 1996;Fedi 2003;Fedi et al 1997), reservoir characterization using well logs Aliouane 2013, 2011), and exploration seismology (Ouadfeul and Aliouane 2012;Saraswat et al 2014).…”

Section: Multi-scale Analysismentioning

confidence: 99%

Stratigraphic correlation of wells using discrete wavelet transform with fourier transform and multi-scale analysis

Srivardhan

2016

Geomech. Geophys. Geo-energ. Geo-resour.

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Stratigraphic correlation of wells involves correlation of stratigraphic interfaces which should be continuous across the area between the wells. Stratigraphic correlation of wells comes at an advanced stage of reservoir estimation, where accurate quantitative information is required for prospect evaluation of the target reserve. It requires input from a variety of geophysical surveys ranging from seismic surveys to core analysis. In this work a novel and innovative technique using discrete wavelet transform with fourier transform and multi-scale analysis is demonstrated, which can be utilized for detecting stratigraphic interfaces and correlating them between wells. The technique was first tested on synthetic gamma ray logs for two synthesized wells and was then applied to the well data taken from geophysical surveys undertaken by dGB Earth Sciences in the Netherlands Offshore F3 Block. Discrete wavelet transform and fourier transform was applied to gamma ray logs to identify potential interfaces and then multi-scale analysis was used to characterize each horizon by finding its fractal dimension. Interfaces which had similar lithology and thickness, had similar fractal dimensions and were therefore correlated. This approach was also compared with conventional wavelet based techniques and was proved to be superior. The well correlation was also independently verified by identifying marker beds using seismic data in between the wells, and there was good agreement between the results that were obtained.

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