Analisa Continuous Wavelet Transform pada Data Well-Log untuk Identfikasi Litofasies

Mulyono, Fertilita Enggarwatie (2017) Analisa Continuous Wavelet Transform pada Data Well-Log untuk Identfikasi Litofasies. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pada analisa well-log, salah sau hal penting ialah
mengidentifikasi atau penentuan batas perlapisan. Umumnya,
batas lapisan ini ditentukan melalui pengukuran data core dan
interpretasi data well-log secara kualitatif. Dalam penelitian ini,
identifikasi batas lapisan dilakukan menggunakan metode
Continuous Wavelet Transform pada data sintetik dan data
lapangan. Wavelet yang digunakan untuk data sintetik yakni
wavelet turunan pertama Gauss, wavelet Haar, Morlet dan turunan
kedua Gauss. Hasilnya ialah, wavelet turunan pertama Gauss lebih
akurat daripada wavelet Haar, Morlet dan turunan kedua Gauss
untuk mengidentifikasi batas lapisan dari data well-log. Pada data
lapanagan digunakan wavelet turunan pertama Gauss, dan metode
Continuous Wavelet Transform menghasilkan jumlah batas lapisan
yang berbeda-beda di masing-masing log. Selain itu juga diketahui
bahwa singularitas dari CWT baik digunakan untuk identifikasi
batas lapisan khususnya pada data GR, RHOB dan Resistivitas.
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In Reservoir characterization, It is important to identify
the boundaries of the lithology. Generally, the determination of the
lithological boundaries is determined by the characteristics of the
core data and the well log analysis. In this research, Lithological
boundaries identification was determined by using Continuous
Wavelet Transform and singularity analysis method on synthetic
data and well log data. In this research, both first and second
derivative of Gaussian wavelet, Haar wavelet, and Morlet Wavelet
are used in synthetic data processing. The result shows that the
first derivative of Gaussian wavelet is more accurate than the the
others on lithological boundaries identification on the well-log
data. In conclusion, the results show that the lithological
boundaries are well-identified by CWT analysis and singularity
analysis, especially in GR, RHOB and Resistivity data.

Item Type:	Thesis (Undergraduate)
Additional Information:	RSFi 515.243 3 Mul a
Uncontrolled Keywords:	Continuous Wavelet Transform, Litofasies, Well- log
Subjects:	Q Science Q Science > QC Physics Q Science > QE Geology
Divisions:	Faculty of Mathematics and Science > Physics > 45201-(S1) Undergraduate Thesis
Depositing User:	Fertilita Enggarwatie Mulyono
Date Deposited:	03 Oct 2017 03:52
Last Modified:	03 Jan 2018 03:36
URI:	http://repository.its.ac.id/id/eprint/43873

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