Electronic Theses and Dissertation

Analisis pemilihan jenis ekstraksi wavelet merupakan tahapan kritis dalam proses well to seismic tie untuk menghasilkan seismogram sintetik yang optimal. Penelitian ini dilakukan pada Lapangan "X" di Cekungan Sumatera Utara dengan menggunakan data seismik 2D dan data sumur. Tujuan penelitian ini adalah untuk menganalisis dan menentukan jenis ekstraksi wavelet yang paling sesuai untuk karakteristik data pada daerah penelitian. Metodologi yang digunakan meliputi analisis empat jenis ekstraksi wavelet yaitu Statistical Wavelet, Ricker Wavelet, Bandpass Wavelet, dan Use Well Wavelet. Data yang digunakan terdiri dari data seismik 2D PSTM dengan jumlah 9 lintasan, serta data sumur yang meliputi log gamma ray, log neutron porosity, log resistivity, log densitas, dan checkshot dari 1 sumur. Proses well to seismic tie dilakukan dengan membandingkan hasil seismogram sintetik dari keempat jenis wavelet tersebut. Hasil penelitian menunjukkan bahwa Ricker wavelet menghasilkan korelasi tertinggi dengan nilai 0.539, diikuti oleh Use well wavelet (0.533), Bandpass wavelet (0.528), dan statistical wavelet (0.503). Perbedaan nilai korelasi ini dipengaruhi oleh karakteristik geologi lokal, kualitas data seismik, dan kondisi data sumur pada daerah penelitian. Hasil penelitian ini dapat digunakan sebagai acuan dalam pemilihan jenis ekstraksi wavelet untuk studi seismik lanjutan di Cekungan Sumatera Utara.

Kata kunci: Ekstraksi wavelet, well to seismic tie, seismogram sintetik, Cekungan Sumatera Utara.

Wavelet extraction type selection analysis is a critical stage in the well to seismic tie process to produce optimal synthetic seismograms. This study was conducted in Field "X" in the North Sumatra Basin using 2D seismic data and well data. The purpose of this study was to analyze and determine the most appropriate type of wavelet extraction for the characteristics of the data in the study area. The methodology used includes the analysis of four types of wavelet extraction, namely Statistical Wavelet, Ricker Wavelet, Bandpass Wavelet, and Use Well Wavelet. The data used consisted of 2D PSTM seismic data with a total of 9 trajectories, as well as well data including gamma ray logs, neutron porosity log, resistivity log, density logs, and checkshots from 1 well. The well to seismic tie process was carried out by comparing the results of synthetic seismograms from the four types of wavelets. The results showed that Ricker wavelet produced the highest correlation with an average value of 0.539, followed by Use well wavelet (0.533), Bandpass wavelet (0.528), and statistical wavelet (0.503). The difference in correlation values is influenced by local geological characteristics, seismic data quality, and well data conditions in the study area. The results of this study can be used as a reference in selecting the type of wavelet extraction for further seismic studies in the North Sumatra Basin. Keywords: Wavelet extraction, well to seismic tie, synthetic seismogram, North Sumatra Basin. Wavelet extraction type selection analysis is a critical stage in the well to seismic tie process to produce optimal synthetic seismograms. This study was conducted in Field "X" in the North Sumatra Basin using 2D seismic data and well data. The purpose of this study was to analyze and determine the most appropriate type of wavelet extraction for the characteristics of the data in the study area. The methodology used includes the analysis of four types of wavelet extraction, namely Statistical Wavelet, Ricker Wavelet, Bandpass Wavelet, and Use Well Wavelet. The data used consisted of 2D PSTM seismic data with a total of 9 trajectories, as well as well data including gamma ray logs, neutron porosity log, resistivity log, density logs, and checkshots from 1 well. The well to seismic tie process was carried out by comparing the results of synthetic seismograms from the four types of wavelets. The results showed that Ricker wavelet produced the highest correlation with an average value of 0.539, followed by Use well wavelet (0.533), Bandpass wavelet (0.528), and statistical wavelet (0.503). The difference in correlation values is influenced by local geological characteristics, seismic data quality, and well data conditions in the study area. The results of this study can be used as a reference in selecting the type of wavelet extraction for further seismic studies in the North Sumatra Basin. Keywords: Wavelet extraction, well to seismic tie, synthetic seismogram, North Sumatra Basin.