We have developed a new methodology for predictingand removing multiples in the postmigration depth domainbased on wavefield extrapolation and attribute-based subtraction.The inputs for the multiple prediction are a 3D prestackdepth-migrated stack volume and the corresponding migrationvelocity volume. The output is the predicted multiplemodel in the migration depth domain. In some cases, thestrong residual top of salt multiple may be erroneously pickedas the base of salt reflection. With the predicted multiplemodel available for comparison during the salt model buildingstage, there is a better chance of building an accurate salt modeland avoid picking multiple events. In an effort to furtherimprove the final migrated images, the predicted multiplemodel is used to remove residual multiples in the migrationdepth domain. A poststack wavefield extrapolation-basedmultiple prediction is used to identify and confirm the multipleevents in the migration depth domain. Once multipleevents are identified, an effective and efficient demultipletechnique is applied to remove the residual multiples fromthe final migration. The key ingredient of this new demultiplemethodology is the attribute-based subtraction. We describethe main steps of this methodology and demonstrate its effectivenessby showing some field data applications.
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