Ditapis dengan
A new correlation for calculating wellhead oil flow rate using artificial neu…
A separator and multiphase flow meters are considered the most accurate tools used to measure the surface oil flow rates. However, these tools are expensive and time consuming. Thus, this study aims to develop a correlation for accurate and quick evaluation of well surface flow rates and consequently the well inflow performance relationship. In order to achieve the abovementioned aim, this stud…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 7 hlm PDF, 1.225 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
A convolutional recurrent neural network for strong convective rainfall nowca…
Strong convective systems and the associated heavy rainfall events can trig-ger floods and landslides with severe detrimental consequences. These events have a high spatio-temporal variability, being difficult to predict by standard meteorological numerical models. This work proposes the M5Images method for performing the very short-term prediction (nowcasting) of heavy convective rainfall usin…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 6 hlm PDF, 1.368 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
Unilateral Alignment: An interpretable machine learning method for geophysica…
Most of the existing machine learning studies in logs interpretation do not consider the data distribution discrepancy issue, so the trained model cannot well generalize to the unseen data without calibrating the logs. In this paper, we formulated the geophysical logs calibration problem and give its statistical explanation, and then exhibited an interpretable machine learning method, i.e., Uni…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 10 hlm PDF, 3.656 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Towards a fully data-driven prospectivity mapping methodology: A case study o…
Mineral exploration campaigns are financially risky. Several state-of-the-art methods have been developed to mitigate the risk, including predictive modelling of mineral prospectivity using principal component analysis (PCA) and geographic information systems (GIS). The PCA and GIS approach is currently considered acceptable for generating mineral exploration targets. However, some of its limit…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 20 hlm PDF, 16.632 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
The potential of self-supervised networks for random noise suppression in sei…
Noise suppression is an essential step in many seismic processing workflows. A portion of this noise, particularly in land datasets, presents itself as random noise. In recent years, neural networks have been successfully used to denoise seismic data in a supervised fashion. However, supervised learning always comes with the often unachievable requirement of having noisy-clean data pairs for tr…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 13 hlm PDF, 7.813 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
The benefits and dangers of using artificial intelligence in petrophysics
Artificial Intelligence, or AI, is a method of data analysis that learns from data, identify patterns and makes predictions with the minimal human intervention. AI is bringing many benefits to petrophysical evaluation. Using case studies, this paper describes several successful applications. The future of AI has even more potential. However, if used carelessly there are potentially grave conseq…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 10 hlm PDF, 4.034 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Sparse inversion-based seismic random noise attenuation via self-paced learning
Seismic random noise reduction is an important task in seismic data processing at the Chinese loess plateau area, which benefits the geologic structure interpretation and further reservoir prediction. The sparse inversion is one of the widely used tools for seismic random noise reduction, which is often solved via the sparse approximation with a regularization term. The ℓ1 norm and total vari…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 11 hlm PDF, 3.665 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Site suitability for Aromatic Rice cultivation by integrating Geo-spatial and…
The purpose of this work is to assess the soil fertility for Tulaipanji rice cultivation in Kaliyaganj C.D. Block using the Analytic Hierarchy Process (AHP) and Machine learning algorithms along with the field survey data and GIS. A total of 40 soil samples from Tulaipanji rice fields (from 0 to 40 cm depth) have been randomly collected for the analysis of the soil health condition. For the …
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 13 hlm PDF, 6.223 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Rapid identification of high-quality marine shale gas reservoirs based on the…
The identification of high-quality marine shale gas reservoirs has always been a key task in the exploration and development stage. However, due to the serious nonlinear relationship between the logging curve response and high-quality reservoirs, the rapid identification of high-quality reservoirs has always been a problem of low accuracy. This study proposes a combination of the oversampling m…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 6 hlm PDF, 1.091 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
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