The simplest form of anisotropic media (VTI (Vertical Transverse Isotropy) was used. Theoretically, this form requires two parameters to describe the media, those are ? (delta) and ? (epsilon). ? is an anisotropy parameter that describe velocity variation near to vertical while ? is an anisotropy parameter that describe velocity variation near to horizontal. Combination of ? and ? describes the non hyperbolic component of moveout and ? also controls the true depth. Estimated value of the initial delta is obtained by calculating the difference in the depth of marker seismic and marker well. Initial value of epsilon is the absolute value of the initial value of delta. Both these values are used to gather semblance analysis for near and far offset by some approximation method. The anisotropic velocity interval is derived from transformation of isotropic velocity interval and ? anisotropic parameters. The anisotropic velocity is used for Pre Stack Depth Migration, and then refines on anisotropic interval velocity, ? interval, and ? interval.The process should be done until getting flattened event on every CRP (Common Reflection Point) gathers.
In this research, the P wave anisotropy depth imaging is applied on real data set. The section resulted from anisotropic Pre Stack Depth Migration method shows a pattern of reflector to be more continuity rather than isotropic Pre Stack Depth Migration. The anisotropic Pre Stack Depth Migration produce a section which has corrected build up image and has change to be the true of reflector in 67 m of depth. Base on well and seismic data calculation process, an anisotropic parameter is in the range of 0.050-0.058. Generally, Anisotropy Pre Stack Depth Migration method gave better result than isotropy Pre Stack Depth Migration.
Telah dibuat sistem pengukur intensitas cahaya untuk menentukan sudut
Penelitian dilakukan menggunakan komputer dengan Microsoft Visual
Studio C#. Pada penelitian ini ada beberapa tahapan yaitu perancangan sensor
cahaya dan aplikasi sistem pengukur sudut polarisasi. LDR sebagai sensor