POROSITY ESTIMATION BY 3D SEISMIC DATA USING ARTIFICIAL NEURAL NETWORKS

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JAMALI JAVAD; SADRI MARYAM

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Seminar Paper

Paper Information

Seminar: IRANIAN GEOPHYSICS CONFERENCE
Year:2006 | Issue:12

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Title

POROSITY ESTIMATION BY 3D SEISMIC DATA USING ARTIFICIAL NEURAL NETWORKS

Author(s)

JAMALI JAVAD | SADRI MARYAM

Keywords

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Abstract

RESERVOIR PROPERTIES SUCH AS POROSITY COULD BE PREDICTED, PRECISELY, BY INTEGRATION OF SEISMIC DATA AND INVERSION RESULT. IN THIS STUDY, FIRST BY USING 3D SEISMIC DATA, HORIZON INTERPRETATIONS AND WELL LOGS, 3D ACOUSTIC IMPEDANCE MODEL OF RESERVOIR WAS GENERATED. THEN SOME SINGLE ATTRIBUTES EXTRACTED FROM SEISMIC DATA. AFTER THAT LINEAR STEP WISE REGRESSION METHOD WAS USED TO GENERATE SEISMIC MULTI-ATTRIBUTES. LATER, THE THREE LAYERED ARTIFICIAL NEURAL NETWORK, WITH THREE NODES IN INPUT LAYER, EIGHT NODES IN HIDDEN LAYER AND ONE IN OUTPUT DESIGNED. FINALLY, 3D POROSITY MODEL ESTIMATED APPLYING NEURAL NETWORK, SEISMIC MULTI-ATTRIBUTES AND WELL LOGS.

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APA: Copy

JAMALI, JAVAD, & SADRI, MARYAM. (2006). POROSITY ESTIMATION BY ٣D SEISMIC DATA USING ARTIFICIAL NEURAL NETWORKS. IRANIAN GEOPHYSICS CONFERENCE. SID. https://sid.ir/paper/906533/en

Vancouver: Copy

JAMALI JAVAD, SADRI MARYAM. POROSITY ESTIMATION BY ٣D SEISMIC DATA USING ARTIFICIAL NEURAL NETWORKS. 2006. Available from: https://sid.ir/paper/906533/en

IEEE: Copy

JAVAD JAMALI, and MARYAM SADRI, “POROSITY ESTIMATION BY ٣D SEISMIC DATA USING ARTIFICIAL NEURAL NETWORKS,” presented at the IRANIAN GEOPHYSICS CONFERENCE. 2006, [Online]. Available: https://sid.ir/paper/906533/en

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