[HTML][HTML] A real-time intelligent lithology identification method based on a dynamic felling strategy weighted random forest algorithm

T Yan, R Xu, SH Sun, ZK Hou, JY Feng - Petroleum Science, 2024 - Elsevier
Real-time intelligent lithology identification while drilling is vital to realizing downhole closed-
loop drilling. The complex and changeable geological environment in the drilling makes …

Utilizing integrated artificial intelligence for characterizing mineralogy and facies in a pre-salt carbonate reservoir, Santos Basin, Brazil, using cores, wireline logs, and …

JCR Gavidia, GF Chinelatto, M Basso… - Geoenergy Science and …, 2023 - Elsevier
In complex carbonate reservoirs, it is crucial to understand the connections between
reservoir compositions (minerals, facies, and properties). Conventionally, core samples …

Porosity prediction using semi-supervised learning with biased well log data for improving estimation accuracy and reducing prediction uncertainty

W Sang, S Yuan, H Han, H Liu… - Geophysical Journal …, 2023 - academic.oup.com
Porosity characterization is of profound significance for seismic inversion and hydrocarbon
prediction. Although semi-supervised learning (SSL) based methods have been used to …

Application of unsupervised learning and deep learning for rock type prediction and petrophysical characterization using multi-scale data

S Iraji, R Soltanmohammadi, GF Matheus… - Geoenergy Science and …, 2023 - Elsevier
This study integrates well log data, routine core analyses, microcomputed X-ray tomography
(μ CT) images, and sedimentary petrography to accurately characterize and evaluate the …

[HTML][HTML] Geological Insights from Porosity Analysis for Sustainable Development of Santos Basin's Presalt Carbonate Reservoir

RG Vásconez Garcia, SM Mohammadizadeh… - Sustainability, 2024 - mdpi.com
Carbonate reservoirs, influenced by depositional and diagenetic processes and
characterized by features like faults and vugs that impact storage capacity, require more …

Porosity prediction with uncertainty quantification from multiple seismic attributes using random forest

C Zou, L Zhao, M Xu, Y Chen… - Journal of Geophysical …, 2021 - Wiley Online Library
Inferring porosity of subsurface from seismic data is of profound significance to many fields
of Earth science and engineering applications, including but not limited to: hydrocarbon …

Estimating shear wave velocity in carbonate reservoirs from petrophysical logs using intelligent algorithms

M Mehrad, A Ramezanzadeh, M Bajolvand… - Journal of Petroleum …, 2022 - Elsevier
Shear-wave velocity (V s) is a key petrophysical data for a wide spectrum of applications in
the upstream oil industry. In many wells, however, the corresponding log cannot be acquired …

Deep carbonate reservoir characterisation using multi-seismic attributes via machine learning with physical constraints

Y Chen, L Zhao, J Pan, C Li, M Xu, K Li… - … of Geophysics and …, 2021 - academic.oup.com
Seismic characterisation of deep carbonate reservoirs is of considerable interest for
reservoir distribution prediction, reservoir quality evaluation and reservoir structure …

Deep neural Helmholtz operators for 3-D elastic wave propagation and inversion

C Zou, K Azizzadenesheli, ZE Ross… - Geophysical Journal …, 2024 - academic.oup.com
Numerical simulations of seismic wave propagation in heterogeneous 3-D media are central
to investigating subsurface structures and understanding earthquake processes, yet are …

Missing sonic logs generation for gas hydrate-bearing sediments via hybrid networks combining deep learning with rock physics modeling

Z Li, J **a, Z Liu, G Lei, K Lee… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Logging-while-drilling (LWD) sonic data are critical for marine gas hydrate reservoir
evaluation and production prediction. However, acquiring complete acoustic logs …