Applications of Machine Learning in Sweet-Spots Identification: A Review
H Khanjar - SPE Journal, 2024 - onepetro.org
The identification of sweet spots, areas within a reservoir with the highest production
potential, has been revolutionized by the integration of machine learning (ML) algorithms …
potential, has been revolutionized by the integration of machine learning (ML) algorithms …
Porosity prediction from prestack seismic data via deep learning: incorporating a low-frequency porosity model
Porosity prediction from seismic data is of considerable importance in reservoir quality
assessment, geological model building, and flow unit delineation. Deep learning …
assessment, geological model building, and flow unit delineation. Deep learning …
Comparison of commingled and sequential production schemes by sensitivity analysis for Gulf of Mexico Paleogene Deepwater turbidite oil fields: A simulation study
A commingled production scheme, where wells are simultaneously completed in multiple
reservoir units, offers a cost-effective alternative worldwide. However, their behavior can be …
reservoir units, offers a cost-effective alternative worldwide. However, their behavior can be …
Enhancing seismic porosity estimation through 3D sequence-to-sequence deep learning with data augmentation, spatial constraints, and geologic constraints
Estimating porosity from seismic data is critical for studying underground rock properties,
assessing energy reserves, and subsequent reservoir exploration and development. For …
assessing energy reserves, and subsequent reservoir exploration and development. For …
Uncertainty Quantification Based on Deep-Learning Approach Integrating Time-Lapse Seismic Data for Geological Carbon Storage
Carbon capture and storage (CCS) is a crucial technology for reducing greenhouse gas
emissions to achieve net-zero goals by 2050. Reasonable assessment of CO2 plume …
emissions to achieve net-zero goals by 2050. Reasonable assessment of CO2 plume …
U-Net++ Based Subshallow Gas-Scattered Image Conditioning: Small-Scale Case Study of Seismic Data Acquired in the Korean East Sea
Data acquired through seismic surveys suffers from information loss for various reasons.
Among these, shallow gas affects signals beneath it and causes distortion of seismic wave …
Among these, shallow gas affects signals beneath it and causes distortion of seismic wave …
Method for Predicting Transverse Wave Velocity Using a Gated Recurrent Unit Based on Spatiotemporal Attention Mechanism
J Huang, G Gao, X Li, Y Li, Z Gui - Lithosphere, 2023 - pubs.geoscienceworld.org
Transverse wave velocity plays an important role in seismic exploration and reservoir
assessment in the oil and gas industry. Due to the lack of transverse wave velocity data from …
assessment in the oil and gas industry. Due to the lack of transverse wave velocity data from …
이산화탄소지중저장을위한기계학습기반4-D 탄성파자료통합및배사구조채널대수층특성화
김현민， 김남화， 신현돈， 조홍근 - 한국자원공학회지, 2024 - dbpia.co.kr
본 연구에서는 채널대수층의 이산화탄소 지중저장에서 4-D 탄성파자료를 통합해 불확실성을
정량화하고 신뢰도를 향상하기 위해 기계학습의 하나인 Pix2Pix 기반의 4-D 탄성파자료 …
정량화하고 신뢰도를 향상하기 위해 기계학습의 하나인 Pix2Pix 기반의 4-D 탄성파자료 …
Remoção de múltiplas do dado sísmico por modelos de aprendizado de máquina
TP Carneiro, MP de Albuquerque, EL de Faria - NOTAS TÉCNICAS, 2023 - revistas.cbpf.br
Reflexões múltiplas são um ruído de tratamento complexo e caro no imageamento sísmico,
o qual é ferramenta fundamental para diversas atividades econômicas, como a indústria de …
o qual é ferramenta fundamental para diversas atividades econômicas, como a indústria de …