BibTex Citation Data :
@article{YPJ168, author = {Galih Candra Kusuma and Teguh Suroso and Udi Harmoko}, title = {EVALUASI MODEL KECEPATAN HASIL METODE TOMOGRAFI REFLEKSI MENGGUNAKAN ATRIBUT KINEMATIK WAVEFIELD PADA DATA SEISMIK LAPANGAN AREA JAWA TIMUR LINE “Σ01”}, journal = {Youngster Physics Journal}, volume = {1}, number = {1}, year = {2012}, keywords = {}, abstract = { A commonly used tool for the construction of such velocity models is reflection tomography by velocity analysis. One of the drawbacks of that method is, however, that it requires picking of reflection events in the seismic prestack data to provide the traveltime information for the tomographic inversion. This picking is extremely time-consuming and can become difficult or even impossible if the signal-to-noise ratio in the data is low. In this study, other tomographic inversion is presented that use of traveltime information in the form of kinematic wavefield attributes. These attributes are the coefficients of second-order traveltime approximation by coherence analysis with the common-reflection-surface (CRS) stack. The research has been carried out with real seismic data of East Java area which has been processed until pre-processing. Process is started with determining kinematic wavefield attributes. Then, the attributes is calculated to get CRS stack. Based on the CRS stack, one can determine information about normal ray travel time, spatial coordinate, first spatial travel time derivatives or slowness, and second spatial travel time derivatives. That information is reconstructed by tomographic inversion modeling to get velocity model of subsurface structure. Initial model is constructed by defining the near surface velocity and velocity gradient as a function of depth. Tomographic inversion tries to minimize the misfit between observed data and calculated modeling data. The final model is accepted if the misfit is already reached its minimum value. Apart from the tomographic inversion with kinematic wavefield attributes, data is also processed with conventional method to get velocity model by velocity analysis. Both of the velocity models then be compared. The advantages of using tomographic inversion method is to reduce subjectivity in generating velocity model for the process carried out using a mathematical calculation. Picking is further simplified by the fact that, the pick locations do not need to follow continuous of reflector events but are independent of each other and may be placed on locally coherent events. However, if the data input that used in tomographic inversion is bad, such as in this study, then the obtained velocity model become less precise. Whereas the conventional method, the velocity values can be directed to obtain velocity model according to most likely section. Key words : velocity model, CRS stack, reflection tomography, kinematic wavefield attributes }, issn = {2302-7371}, url = {https://ejournal3.undip.ac.id/index.php/bfd/article/view/168} }
Refworks Citation Data :
A commonly used tool for the construction of such velocity models is reflection tomography by velocity analysis. One of the drawbacks of that method is, however, that it requires picking of reflection events in the seismic prestack data to provide the traveltime information for the tomographic inversion. This picking is extremely time-consuming and can become difficult or even impossible if the signal-to-noise ratio in the data is low. In this study, other tomographic inversion is presented that use of traveltime information in the form of kinematic wavefield attributes. These attributes are the coefficients of second-order traveltime approximation by coherence analysis with the common-reflection-surface (CRS) stack.
The research has been carried out with real seismic data of East Java area which has been processed until pre-processing. Process is started with determining kinematic wavefield attributes. Then, the attributes is calculated to get CRS stack. Based on the CRS stack, one can determine information about normal ray travel time, spatial coordinate, first spatial travel time derivatives or slowness, and second spatial travel time derivatives. That information is reconstructed by tomographic inversion modeling to get velocity model of subsurface structure. Initial model is constructed by defining the near surface velocity and velocity gradient as a function of depth. Tomographic inversion tries to minimize the misfit between observed data and calculated modeling data. The final model is accepted if the misfit is already reached its minimum value. Apart from the tomographic inversion with kinematic wavefield attributes, data is also processed with conventional method to get velocity model by velocity analysis. Both of the velocity models then be compared.
The advantages of using tomographic inversion method is to reduce subjectivity in generating velocity model for the process carried out using a mathematical calculation. Picking is further simplified by the fact that, the pick locations do not need to follow continuous of reflector events but are independent of each other and may be placed on locally coherent events. However, if the data input that used in tomographic inversion is bad, such as in this study, then the obtained velocity model become less precise. Whereas the conventional method, the velocity values can be directed to obtain velocity model according to most likely section.
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