A borehole clustering based method for lithological identification using logging data
H Liu, XL Zhang, ZL Li, ZP Weng, YP Song - Earth Science Informatics, 2024 - Springer
In recent years, geoscientists have been employing machine learning techniques to
automate lithological identification by integrating well logging data. However, in geologically …
automate lithological identification by integrating well logging data. However, in geologically …
Lithofacies identification in carbonate reservoirs by multiple kernel Fisher discriminant analysis using conventional well logs: A case study in A oilfield, Zagros Basin …
S Dong, L Zeng, X Du, J He, F Sun - Journal of Petroleum Science and …, 2022 - Elsevier
Lithofacies identification in carbonate reservoirs using conventional well logs is a typically
complex nonlinear problem due to influences of multiple factors, such as fluids and fractures …
complex nonlinear problem due to influences of multiple factors, such as fluids and fractures …
Semi-supervised learning for lithology identification using Laplacian support vector machine
Z Li, Y Kang, D Feng, XM Wang, W Lv, J Chang… - Journal of Petroleum …, 2020 - Elsevier
Lithology identification is a fundamental task in well log interpretation. Considering the
presence of substantial unlabeled data in the field of petroleum exploration, this paper …
presence of substantial unlabeled data in the field of petroleum exploration, this paper …
Lithology identification using graph neural network in continental shale oil reservoirs: A case study in Mahu Sag, Junggar Basin, Western China
The continental shale oil reservoir of Fengcheng Formation in the northern slope area of
Mahu Sag, Junggar Basin, Western China is very heterogeneous in lithology. Thus, the …
Mahu Sag, Junggar Basin, Western China is very heterogeneous in lithology. Thus, the …
Lithology identification from well-log curves via neural networks with additional geologic constraint
Lithology identification is of great importance in reservoir characterization. Recently, many
researchers have applied machine-learning techniques to solve lithology identification …
researchers have applied machine-learning techniques to solve lithology identification …
Well logging based lithology identification model establishment under data drift: A transfer learning method
H Liu, Y Wu, Y Cao, W Lv, H Han, Z Li, J Chang - Sensors, 2020 - mdpi.com
Recent years have witnessed the development of the applications of machine learning
technologies to well logging-based lithology identification. Most of the existing work …
technologies to well logging-based lithology identification. Most of the existing work …
Borehole lithology modelling with scarce labels by deep transductive learning
J Wang, J Li, K Li, Z Li, Y Kang, J Chang, W Lv - Computers & Geosciences, 2024 - Elsevier
Geophysical logging is a geo-scientific instrument that detects information such as electric,
acoustic, and radioactive properties of a well. Its data plays a vital role in interpreting …
acoustic, and radioactive properties of a well. Its data plays a vital role in interpreting …
A lithology identification approach based on machine learning with evolutionary parameter tuning
CM Saporetti, LG da Fonseca… - IEEE Geoscience and …, 2019 - ieeexplore.ieee.org
Identification of underground formation lithology from well-log data is an important task in
petroleum exploration and engineering. Due to the cost or imprecision of some methods …
petroleum exploration and engineering. Due to the cost or imprecision of some methods …
Data-driven lithology prediction for tight sandstone reservoirs based on new ensemble learning of conventional logs: A demonstration of a Yanchang member, Ordos …
Y Gu, D Zhang, Y Lin, J Ruan, Z Bao - Journal of Petroleum Science and …, 2021 - Elsevier
Lithologies are significant indicators to get deep insight of depositional and mineralogical
properties of target formations, and the classic approach of achieving them is crossplot …
properties of target formations, and the classic approach of achieving them is crossplot …
An improved lithology identification approach based on representation enhancement by logging feature decomposition, selection and transformation
As the accumulation of logging data and the enhancement of computational power, machine
learning technology has been progressively applied to logging interpretation field such as …
learning technology has been progressively applied to logging interpretation field such as …