APPLICATION COMMON REFLECTION SURFACE AS REGULARIZATION METHOD TO VELOCITY VARIATION WITH AZIMUTH (VVAZ) INVERSION OF NARROW AZIMUTH LAND 3D SEISMIC DATA

The orientation and intensity of fracture are increasingly becoming vital properties in exploration and development field, especially related to basement reservoir lead and prospect or other play types which related to them. Velocity variation with azimuth (VVAz) is well-known as method to estima...

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Bibliographic Details
Main Author: Kriski Muhtar, Lucky
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/48248
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:The orientation and intensity of fracture are increasingly becoming vital properties in exploration and development field, especially related to basement reservoir lead and prospect or other play types which related to them. Velocity variation with azimuth (VVAz) is well-known as method to estimate the properties. This method is widespread interest due to capability to predict the properties based on seismic data without well constraint in inversion process. Despite this interest, the method require a rich-azimuth 3D seismic data that is rarely owned by company. This thesis present a new approach to VVAz inversion using narrow azimuth 3D seismic data regulated by common reflection surface (CRS) to enhance the conventional data with relatively low folds in COV. To validate our idea, we applied the methodology to 3D full elastic anisotropy synthetic data and analyzed it. Then similar sequence processing, we applied to real seismic data. Our result on synthetic data show that inversion after regularization keep the preservation of amplitude versus offset (AVO) and VVAz anomalies equal to synthetic model. Moreover, a significant positive correlation between fracture intensity of FMI and real seismic data with coefficient correlation above 0.92 is obtained. Therefore, CRS is able to be used as regularization method to VVAz inversion of narrow azimuth 3D seismic data.