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Journal : Jurnal Geofisika

Application of Velocity Variation with Angle (VVA) Method on an Anisotropic Model with Thomsen Delta Anisotropy Parameters Waskito Pranowo; Sonny Winardhi
Jurnal Geofisika Vol 16 No 2 (2018): Jurnal Geofisika
Publisher : Himpunan Ahli Geofisika Indonesia (HAGI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (607.788 KB) | DOI: 10.36435/jgf.v16i2.371

Abstract

Anisotropic properties will influence seismic propagation, for example it will affect wave velocity. One of well-known anisotropi equation for Transversaly Isotropic media is weak anisotropy with Thomsen's notation. Supriyono [2011] tried to estimate all of these variables by using velocity variation with angle (VVA) attribute. This research uses synthetic data, which is CMP Gather to know limitations of VVA attribute, to identify the error values, and to determine the best indicator of anisotropic eect. This research also uses another analysis method, which is grid search inversion to estimate VP0. From this research, Both VVA and grid search invesion still produce signcant error. The effects which will appear because of anisotropic property's presence are hockey-stick and over NMO-stretching.
A Python Based Multi-Point Geostatistics by using Direct Sampling Algorithm Edwin Brilliant; Sanggeni Gali Wardhana; Alissa Bilqis; Alda Ressa Nurdianingsih; Rafif Rajendra Widya Daniswara; Waskito Pranowo
Jurnal Geofisika Vol 18 No 2 (2020): Jurnal Geofisika
Publisher : Himpunan Ahli Geofisika Indonesia (HAGI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36435/jgf.v18i2.446

Abstract

Multi-Point Geostatistics (MPS) is a type of geostatistical method used to estimate the value of an unsampled location by utilizing several data points around it simultaneously. The MPS method estimates it by defining a model based on initial data in the form of a training image, which is a collection of data in the form of a geological conceptual model in the research area with the integration of geological and geophysical knowledge. The MPS method is currently starting to develop because it differs from conventional covariance-based geostatistical methods such as simple kriging and ordinary kriging, which only use a variogram based on the relationship between two points rapidly. In this study, we evaluated the use of the MPS method by using a direct sampling algorithm with Python that will directly sample the training image and then retrieve the data based on the sample data. A braided channel training image is used as the initial model to estimate the distribution of reservoir properties in lithology with sand and shale types. This study shows that MPS could reconstruct geological features better than kriging.