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Information Journal Paper

Title

Using a Novel Method for Attenuating Random Noises from Seismic Data

Pages

  65-72

Keywords

Signal-to-noise Ratio (S/N) 

Abstract

 Random or incoherent noise is an important type of seismic noise, which can seriously affect the quality of the data. Therefore, decreasing the level of this category of noises is necessary for increasing the signal-to-noise ratio (SNR) of seismic records. Random Noises and other events overlap each other in time domain, which makes it difficult to attenuate them from seismic records. In this research, a new technique is produced, by joining FX Deconvolution (FXD) and a special kind of Median Filter in order to suppress Random Noise from seismic records. The technique is operated in some stages; firstly, FXD is tried to eliminate the Gaussian noise, and the Median Filter is fixed to diminish the spike-like noise. The synthetic dataset and field data examples (from an oil field in the southwest of Iran) have been employed to demonstrate that Random Noise reduction can be attained, while the signal content will not be destroyed considerably. The final results indicate the authority of the proposed strategy in suppressing Random Noises, whereas signal information is almost protected during the filtering.

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  • Cite

    APA: Copy

    BAGHERI, MAJID, & RIAHI, MOHAMMAD ALI. (2018). Using a Novel Method for Attenuating Random Noises from Seismic Data. IRANIAN JOURNAL OF OIL & GAS SCIENCE AND TECHNOLOGY, 7(3), 65-72. SID. https://sid.ir/paper/354919/en

    Vancouver: Copy

    BAGHERI MAJID, RIAHI MOHAMMAD ALI. Using a Novel Method for Attenuating Random Noises from Seismic Data. IRANIAN JOURNAL OF OIL & GAS SCIENCE AND TECHNOLOGY[Internet]. 2018;7(3):65-72. Available from: https://sid.ir/paper/354919/en

    IEEE: Copy

    MAJID BAGHERI, and MOHAMMAD ALI RIAHI, “Using a Novel Method for Attenuating Random Noises from Seismic Data,” IRANIAN JOURNAL OF OIL & GAS SCIENCE AND TECHNOLOGY, vol. 7, no. 3, pp. 65–72, 2018, [Online]. Available: https://sid.ir/paper/354919/en

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