syntethic correlation petrel

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  • 8/19/2019 Syntethic Correlation Petrel

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    Synthetic seismogram correlationSynthetic seismogram correlation (Petrel 2009.1.1)(Petrel 2009.1.1)

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    Introduction & Objective

    ● Petrel misses a correlation tool for synthetic seismogram

    ● In this presentation we will explain a work around to correlate a synthetic

    seismogram to a real seismic trace based on either Acoustic Impedance or

    Reflection coefficients  P 

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    ● Three processes will be used in Petrel 2009.1.1

    1) Seismic to well tie

    2) Genetic Inversion

    3) Train estimation model

    The objective is to have a numeric correlation indicator for synthetic

    seismogram generation

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    Overview

    ● Generate synthetic seismogram

    ● Output Reflectivity Coefficient and Acoustic Impedance logs

    ● Run G.I to obtain R.C inverted cube (Linear and Non-Linear)

    ● Use Correlation analysis tool under train estimation model (NN)  P 

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    ● Check the correlation factor to quality check the synthetic seismogram

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    Workflow scheme

    Seismic to Well

    Tie

    Genetic

    Inversion

    AI RC AIRC

     

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    Train estimationmodel

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    Step 1 Seismic to well tie

    ● Generate logset

    ● Wavelet extraction

    ● A.I and R.C output

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    Step 2 Genetic Inversion

    ● Generate Acoustic Impedance inverted dataset

    ● Generate Reflection Coefficients inverted dataset

    ● A.I and R.C logs QC

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    Step 3 Train estimation model

    ● Train AI and check the Correlation analysis

    ● Train RC and check the Correlation analysis

    ● A.I and R.C logs QC

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    Summary & Conclusion

    ● The proposed workflow gives a relatively accurate numeric indicator for correlation.

    ● A.I and R.C are major components of a seismic trace that could be used for correlation

    ● The proposed workflow is preliminary and not 100% accurate due to the uncertainty

    in G.I and also using AI or RC rather than the synthetic trace itself   P 

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