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.

[img] Text
1113100025-Undergraduate_Theses.pdf
Restricted to Repository staff only

Download (3MB) | Request a copy

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. ============================================================================================ 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

Actions (login required)

View Item View Item