Ditapis dengan
MLReal: Bridging the gap between training on synthetic data and real data app…
Among the biggest challenges we face in utilizing neural networks trained on waveform (i.e., seismic, electromagnetic, or ultrasound) data is its application to real data. The requirement for accurate labels often forces us to train our networks using synthetic data, where labels are readily available. However, synthetic data often fail to capture the reality of the field/real experiment, and w…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 14 hlm PDF, 3.698 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
High resolution pre-stack seismic inversion using few-shot learning
We propose to use a Few-Shot Learning (FSL) method for the pre-stack seismic inversion problem in obtaining a high resolution reservoir model from recorded seismic data. Recently, artificial neural network (ANN) demonstrates great advantages for seismic inversion because of its powerful feature extraction and parameter learning ability. Hence, ANN method could provide a high resolution inversio…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 6 hlm PDF, 5.168 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Ensemble hybrid machine learning methods for gully erosion susceptibility map…
Gully erosion is one of the important problems creating barrier to agricultural development. The present research used the radial basis function neural network (RBFnn) and its ensemble with random sub-space (RSS) and rotation forest (RTF) ensemble Meta classifiers for the spatial mapping of gully erosion susceptibility (GES) in Hinglo river basin. 120 gullies were marked and grouped into four-f…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 18 hlm PDF, 7.028 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
A study on small magnitude seismic phase identification using 1D deep residua…
Reliable seismic phase identification is often challenging especially in the circumstances of low-magnitude events or poor signal-to-noise ratio. With improved seismometers and better global coverage, a sharp increase in the volume of recorded seismic data has been achieved. This makes handling seismic data rather daunting by using traditional approaches and therefore fuels the need for more ro…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 8 hlm PDF, 2.201 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Wavefield solutions from machine learned functions constrained by the Helmhol…
Solving the wave equation is one of the most (if not the most) fundamental problems we face as we try to illuminate the Earth using recorded seismic data. The Helmholtz equation provides wavefield solutions that are dimensionally reduced, per frequency, compared to the time domain, which is useful for many applications, like full waveform inversion. However, our ability to attain such wavefield…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 9 hlm PDF, 3.131 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Hydrocarbon detections using multi-attributes based quantum neural networks i…
A direct hydrocarbon detection is performed by using multi-attributes based quantum neural networks with gas fields. The proposed multi-attributes based quantum neural networks for hydrocarbon detection use data clustering and local wave decomposition based seismic attenuation characteristics, relative wave impedance features of prestack seismic data as the selected multiple attributes for one …
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 8 hlm PDF, 3.472 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Data-driven approaches for time series prediction of daily production in the …
The Sulige tight gas field is presently the largest gas field in China. Owing to the ultralow permeability and strong heterogeneity of the reservoirs in Sulige, the number of production wells has exceeded 3,000, keeping the stable gas supply in the decade. Thus, the daily production prediction of gas wells is significant for monitoring production and for implementing and evaluating stimulation …
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 6 hlm PDF, 1.029 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Application of neural network to speed-up equilibrium calculations in composi…
Injecting carbon dioxide (CO2) into reservoirs is a widely recognized method for enhanced oil recovery (EOR) and carbon storage. This study introduces an innovative Artificial neural network (ANN)-based proxy model that significantly enhances the speed of determining equilibrium states in fluid systems, especially in the complex phase behavior of the CO2-hydrocarbon system. Notably, the model c…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 13 hlm PDF, 1.456 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Relationships between fault friction, slip time, and physical parameters expl…
Understanding the relationship between fault friction and physical parameters is crucial for comprehending earthquake physics. Despite various friction models developed to explain this relationship, representing the relationships in a friction model with greater detail remains a challenge due to intricate correlations, including the nonlinear interplay between physical parameters and friction. …
- Edisi
- Vol.25, February 2025
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 14 hlm PDF, 9.549 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Land use and land cover classification for change detection studies using con…
Efficient land use land cover (LULC) classification is crucial for environmental monitoring, urban planning, and resource management. This study investigates LULC changes in Nanjangud taluk, Mysuru district, Karnataka, India, using remote sensing (RS) and geographic information systems (GIS). This paper mainly focuses on the classification and change detection analysis of LULC in 2010 and 2020 …
- Edisi
- Vol.25, February 2025
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 17 hlm PDF, 11.125 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Batas Wilayah 
Ekologi 
Fotogrametri 
Geografi 
Geologi 
GIS 
Ilmu Tanah 
Kartografi 
Manajemen Bencana 
Oceanografi 
Penginderaan Jauh 
Peta