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All Journal Jurnal Geosaintek JOURNAL OF EARTH ENERGY ENGINEERING Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Rekayasa Geofisika Indonesia
Eki Komara
Institut Teknologi Sepuluh Nopember
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Earth & Planetary Sciences Education Energy Engineering Materials Science & Nanotechnology Physics

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ANALISIS PETROFISIKA DAN IDENTIFIKASI ZONA HIDROKARBON PADA FORMASI NGIMBANG, CEKUNGAN JAWA TIMUR UTARA Eki Komara; Vahira Tri Kemalasari; Widya Utama
Jurnal Rekayasa Geofisika Indonesia Vol 3, No 03 (2021): Edisi Desember JRGI (Jurnal Rekayasa Geofisika Indonesia)
Publisher : Jurnal Rekayasa Geofisika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Analisis petrofisika memegang peranan penting dalam karakterisasi reservoir hidrokarbon yaitu untuk mengidentifikasi zona litologi permeabel dan non permeabel dan potensi kandungan hidrokarbon. Analisis petrofisika secara kualitatif dilakukan pada sumur A Formasi Ngimbang berdasarkan data log caliper, gamma ray, density porosity (RHOB), neutron porosity (NPHI), resistivity shallow (RESS) dan resistivity deep (RESD). Analisis zona permeabel berdasarkan log gamma ray yang memiliki nilai kurang dari 50 gAPI dengan zona permeabel 1 pada kedalaman 1351,76–1590,59 m dan zona permeabel 2 kedalaman 1755,68–1885,11 m. Analisis zona permeabel berdasarkan log NPHI dan RHOB dengan zona crossover 1 kedalaman 1352,09–1517,80 m dan zona crossover 2 kedalaman 1755,68–1882,59 m. Analisis kandungan fluida berdasarkan log RESS dan RESD mengidentifikasi terdapat hidrokarbon pada kedalaman 1369,50–1467,3 m, kedalaman 1488,20–1566,00 m, dan kedalaman 1775,00–1880,70 m. Dari ketiga analisis ini, disimpulkan bahwa terdapat 2 zona utama sebagai zona potensi reservoir hidrokarbon yaitu pada kedalaman 1351,76–1517,80 m dan pada kedalaman 1755,00–1880,70 m.
PREDICTION OF CO2 GAS SATURATION DISTRIBUTION BASED ON DEEP LEARNING USING DEEP NEURAL NETWORK (DNN) ALGORITHM Eki Komara; Zahrotuts Tsaniyah; Widya Utama
Jurnal Geosaintek Vol 9, No 2 (2023)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25023659.v9i2.18089

Abstract

Multiphase flow analysis is essential for resolving subsurface flow issues in CO2 capture and storage (CCS) systems. Predicting the distribution of CO2 gas saturation is one example that is quite useful for evaluating multiphase flow. Multiphase flow simulation is typically performed using numerical simulations, such as the TOUGH2 simulator. Ordinary numerical simulations, on the other hand, have some limitations, such as high grid spatial resolution and significant processing costs. One option for estimating the distribution of CO2 gas saturation is to employ deep learning with specific algorithms. A deep neural network (DNN) is a highly effective deep learning approach. A deep neural network is a network structure made up of three interconnected layers: input, hidden, and output. DNN learns from the input data about the previously constructed architecture. As input, DNN requires a significant amount of data train. The trained DNN model is then used to automatically estimate the distribution of CO2 gas saturation. This algorithm is capable of dealing with complex data patterns, particularly gas saturation in multiphase flow issues. The reconstruction loss results revealed that the loss value lowers as the number of epochs grows. Furthermore, the model with 5 epochs and 0.001 regularization weight had the least error value 0.43. As a result, while this model is adequate for predicting the distribution of CO2 gas saturation, additional research is required to achieve more ideal outcomes.
Identification of Reservoir Distribution Using Extended Elastic Impedance (EEI) Inversion in the "Z" Field of the Kutai Basin Zikra Miftahul Haq; Eki Komara; Wien Lestari
Journal of Earth Energy Engineering Vol. 12 No. 2s (2023): IC-UPERTAIN 2022
Publisher : Universitas Islam Riau (UIR) Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jeee.2023.13955

Abstract

This research was conducted using EEI inversion on seismic data in Z Field, Kutai Basin. The EEI inversion is effectively used to determine the reservoir distribution by eliminating the angle limit on the elastic impedance to the Chi angle so that it can be correlated with petrophysical parameters that are sensitive to lithology and fluids. The data used in this study are well data, checkshots, horizons, and partial-stack angle gather 3D seismic data. The data obtained is processed to obtain the target zone first based on log interpretation. Based on data processing, the target zone is obtained at 1513 m to 1531 m. Sensitivity analysis was conducted to determine the sensitive parameters, which can separate the lithology of the formation. In the sensitivity analysis, the most sensitive log to separate lithology is the Vp/VS log, which can separate sandstone, shale, and coal. Furthermore, the EEI inversion analysis was carried out to obtain the most suiTable model for the inversion, the Based Hard Constraint model was obtained with a correlation reaching 0.997 and an error value of 0.078. Based on the EEI inversion, the target zone in the Z-field at a depth of 1258 ms - 1269 ms with a sandstone reservoir in the EEI range of 6000 (m/s)(g/cc) - 7500 (m/s)(g/cc) which spreads from northeast to south. The distribution of the sandstone reservoir is surrounded by coal with a range of EEI 7500 (m/s)(g/cc) - 12000 (m/s)(g/cc), and also the distribution of shale in the EEI range of 7500(m/s)( g/cc) - 9200(m/s)(g/cc).
Penerapan Koefisien Aliran untuk Mendukung Budidaya Tanaman Bernilai Ekonomi Tinggi (Studi Kasus: Kwanyar Bangkalan, Indonesia) Widya Utama; Anicetus Wihardjaka; Nourma Al Viandari; Dwa Desa Warnana; Wien Lestari; Eki Komara; Sherly Ardhya Garini; Rista Fitri Indriani; Dhea Pratama Novian Putra; Annisa R. Varhana
Jurnal Penelitian Pendidikan IPA Vol. 9 No. 9 (2023): September
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i9.3307

Abstract

The initial study that we carried out regarding the Kwanyar sub-district area, Bangkalan, East Java, shows the need to optimize land productivity and analyze the potential for farming to build the welfare of the people of the Kwanyar subdistrict. Preliminary spatial data analysis related to the topography as a result of Digital Elevation Model (DEM) data processing shows that: the Kwanyar sub-district is dominated by flat slopes (0-8°) compared to the northern region of the Kwanyar sub-district, while runoff water analysis shows a low flow coefficient (0- 0.25) which means that most of the Kwanyar area has low absorption capacity and a high potential for stagnant water. In addition, the Kwanyar region has a Regosol soil type. Regosol soil has a coarse texture and low organic matter, which makes it unable to properly hold water and minerals for plants, so it tends to be infertile. The initial study then became the basis for this research.
Co-Authors Anicetus Wihardjaka Annisa R. Varhana Dhea Pratama Novian Putra Dwa Desa Warnana Nourma Al Viandari Rista Fitri Indriani Sherly Ardhya Garini Vahira Tri Kemalasari Widya Utama Widya Utama Zahrotuts Tsaniyah Zikra Miftahul Haq