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    Deconvolution

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    Sumanyu Dixit
    Predictive deconvolution is a method that uses the autocorrelation of seismic trace data to design a filter that can predict reverberations and multiples in the data. This prediction is then subtracted from the original trace, leaving behind the trace with multiples removed while primaries remain. Spiking deconvolution aims to concentrate the energy of seismic pulses near the front of the wavelet. Adaptive deconvolution is based on adaptive linear filtering to remove multiples that have varying periods with travel time while preserving primary reflections.

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    Deconvolution

    Uploaded by

    Sumanyu Dixit
    308 views19 pages
    Predictive deconvolution is a method that uses the autocorrelation of seismic trace data to design a filter that can predict reverberations and multiples in the data. This prediction is then subtracted from the original trace, leaving behind the trace with multiples removed while primaries remain. Spiking deconvolution aims to concentrate the energy of seismic pulses near the front of the wavelet. Adaptive deconvolution is based on adaptive linear filtering to remove multiples that have varying periods with travel time while preserving primary reflections.

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    Predictive deconvolution is a method that uses the autocorrelation of seismic trace data to design a filter that can predict reverberations and multiples in the data. This prediction is then subtracted from the original trace, leaving behind the trace with multiples removed while primaries remain. Spiking deconvolution aims to concentrate the energy of seismic pulses near the front of the wavelet. Adaptive deconvolution is based on adaptive linear filtering to remove multiples that have varying periods with travel time while preserving primary reflections.

    Copyright:

    © All Rights Reserved
    Download as PPT, PDF, TXT or read online from Scribd
    Download as ppt, pdf, or txt
    308 views19 pages

    Deconvolution

    Uploaded by

    Sumanyu Dixit
    Predictive deconvolution is a method that uses the autocorrelation of seismic trace data to design a filter that can predict reverberations and multiples in the data. This prediction is then subtracted from the original trace, leaving behind the trace with multiples removed while primaries remain. Spiking deconvolution aims to concentrate the energy of seismic pulses near the front of the wavelet. Adaptive deconvolution is based on adaptive linear filtering to remove multiples that have varying periods with travel time while preserving primary reflections.

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    © All Rights Reserved
    Download as PPT, PDF, TXT or read online from Scribd
    Download as ppt, pdf, or txt
    of 19

    PREDICTIVE DECONVOLUTION

    • Autocorrelation of a trace to ascertain periodicity within data

    • Filter designed from the autocorrelation when convolved with data


    trace predicts reverberations and multiples.

    • Predicted trace is subtracted from observed trace to give prediction


    error.

    • Which should be the trace with the predicted reverberations and


    multiples removed.

    • Primaries are considered as unpredictable so they remain.


    Autocorrelation is the cross correlation of a trace with itself
    Amplitude

    Multiple period

    Time

    Primary energy Multiple energy Multiple energy

    The autocorrelation function of a seismic signal is an effective tool for


    determining the presence and time lag (duration) of reverberations/multiples.
    Given the input x(t), we want to predict its value at some future
    time (t+a), where ‘a’ is prediction lag.

    (a) Recorded signature


    (b) Desired output
    (c) Shaping operator
    (d) Shaped signature
    FLOW CHART OF PREDICTIVE DECONVOLUTION
    SPIKING DECONVOLUTION

    • Type of predictive deconvolution in which the operator is to predict


    energy within a sample or two, or at the first zero crossing , after the
    zero lag value of autocorrelation.

    • Concentrate the energy of the pulse as near as possible to the front


    of wavelet - turns a wavelet into spike.

    • Data assumed to be minimum phase.

    • Earths reflectivity series is assumed to be random and earth’s


    impulse response to be minimum phase.
    VIBROSEIS DECONVOLUTION

    • Vibroseis produces chirp signal which when convolved


    with earths reflectivity series gives a complicated wavelet
    from which earths reflectivity series is hard to interpret.

    • Cross correlate this observed signal with the chirp signal


    to get the approximate of earths reflectivity series.
    ADAPTIVE DECONVOLUTION

    • Based on adaptive linear filtering techniques in


    which the operator coefficients are updated
    using a simple adaptive algoritm.
    • Applicable for use in preprocessing reflection
    seismic data which contains multiples with
    periods that vary with travel time. So it removes
    multiples with varying periods while leaving
    primary reflections relatively undistorted.
    Simplified diagram of a hard water-bottom model
    showing the raypathsfor some of the arrivals
    Plot showing near-offsets traces for several
    adjacent shotpoints from lina A with offset
    equal to 914 ft and water depth equal to 300 ft

    Tp=traveltime of primary reflection


    Tm1=traveltime of first water-bottom arrival
    REFERENCES

    • Adaptive Deconvolution-
    L.J.GRIFFITHS,F.R.SMOLIKA and
    L.D.TREMBLY –Geophysics Vol 42
    • Yilmaaz

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