Wide & deep learning for predicting relative mineral compositions of sediment…
This study develops a method to use deep learning models to predict the mineral assemblages and their relative abundances in paleolake cores using high-resolution XRF core scan elemental data and X…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 13 hlm PDF, 6.502 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
When linear inversion fails: Neural-network optimization for sparse-ray trave…
In this study, we present an artificial neural network (ANN)-based approach for travel-time tomography of a volcanic edifice under sparse-ray coverage. We employ ray tracing to simulate the propaga…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 12 hlm PDF, 11.246 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Water resource forecasting with machine learning and deep learning: A sciento…
Water prediction plays a crucial role in modern-day water resource management, encompassing both hydrological patterns and demand forecasts. To gain insights into its current focus, status, and eme…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 12 hlm PDF, 4.935 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Transfer learning for well logging formation evaluation using similarity weights
Machine learning has been widely applied in well logging formation evaluation studies. However, several challenges negatively impacted the generalization capabilities of machine learning models in …
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 16 hlm PDF, 22.2488 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
The role of artificial intelligence and IoT in prediction of earthquakes: Review
Earthquakes are classified as one of the most devastating natural disasters that can have catastrophic effects on the environment, lives, and properties. There has been an increasing interest in th…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 19 hlm PDF, 5.965 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
The 3-billion fossil question: How to automate classification of microfossils
Microfossil classification is an important discipline in subsurface exploration, for both oil & gas and Carbon Capture and Storage (CCS). The abundance and distribution of species found in sediment…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 9 hlm PDF, 3.014 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Robust high frequency seismic bandwidth extension with a deep neural network …
Geophysicists interpreting seismic reflection data aim for the highest resolution possible as this facilitates the interpretation and discrimination of subtle geological features. Various determini…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 18 hlm PDF, 23.132 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Reservoir evaluation using petrophysics informed machine learning: A case study
We propose a novel machine learning approach to improve the formation evaluation from logs by integrating petrophysical information with neural networks using a loss function. The petrophysical inf…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 18 hlm PDF, 19.964 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Research on the prediction method for fluvial-phase sandbody connectivity bas…
The connectivity of sandbodies is a key constraint to the exploration effectiveness of Bohai A Oilfield. Conventional connectivity studies often use methods such as seismic attribute fusion, while …
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 8 hlm PDF, 6.809 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Reconstruction of lithofacies using a supervised Self-Organizing Map: Applica…
Recently, machine learning (ML) has been considered a powerful technological element of different society areas. To transform the computer into a decision maker, several sophisticated methods and a…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 13 hlm PDF, 3.426 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
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