Paper Information

Title: 

POROSITY ESTIMATION BY ٣D SEISMIC DATA USING ARTIFICIAL NEURAL NETWORKS

Type: PAPER
Author(s): JAMALI JAVAD,SADRI MARYAM
 
 
 
Name of Seminar: CONFRANCE ZHEOFIZIKE IRAN
Type of Seminar:  CONFERENCE
Sponsor:  ANJOMANE MELI ZHEOFIZIK IRAN
Date:  2006Volume 12
 
 
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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