Evaluation of seismic data quality based on seismic data acquisition result using buried geophone on condition of a thick weathered layer
Abstract
Condition of a thick highly weathered layer at Bunyu Island, Northern Kalimantan, Indonesia creates poor of seismic data quality caused by existence of noise. To overcome the problem, geophones were planted 6 meters deep below the surface using split spread configuration. In this study some filtering technique were used for increasing signal to noise ratio. Band pass filter range 5-8-65-70 Hz was used for noise removal on seismic pre-stack data. On the other hand, despike removal was used for removing spike noise. Radial filter range 100-500 m/s was used for velocity filter. Median filter was used for linear noise filter based on minimum velocity 800 meter/second and maximum velocity 1100 meter/second. Random noise removal based on frequency-offset (fx) filter was used such as fx filter, fx dip and fxcadzow. Deconvolution has operator length of 200 miliseconds and gap of 20 for the processing. Evaluation was done by comparing the buried geophone with the geophones on the surface based on Root Mean Square (RMS) Amplitude and Signal to Noise Ratio. Seismic pre-stack data after denoising shows higher RMS amplitude, higher signal and and has higher frequency at buried geophone than surface geophone. RMS amplitude has a correlation with frequency. High frequency will show a high RMS amplitude because based on calculations that have been done, RMS amplitude is proportional to the frequency. The result of Kirchhoff based on post-stack seismic migration method with buried geophone shows higher quality reflector than seismic section of surface geophone. Seismic section (pre-stack and post-stack) using buried geophone shows good seismic reflector, higher RMS amplitude and better signal to noise ratio than seismic section of surface geophone.
- Publication:
-
Proceedings of the 3rd International Symposium on Current Progress in Mathematics and Sciences 2017 (ISCPMS2017)
- Pub Date:
- October 2018
- DOI:
- 10.1063/1.5064251
- Bibcode:
- 2018AIPC.2023b0254N