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 …

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 …

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 …

Lithology identification is of great importance in reservoir characterization. Recently, many
researchers have applied machine-learning techniques to solve lithology identification …

Recent years have witnessed the development of the applications of machine learning
technologies to well logging-based lithology identification. Most of the existing work …

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 …

In recent years, geoscientists have been employing machine learning techniques to
automate lithological identification by integrating well logging data. However, in geologically …

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 …

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 …

摘要机器学习算法是岩性识别领域重点研究内容之一. 与传统岩性识别方法相比,
通过监测随钻参数变化进行岩性识别, 具有高精度, 多信息, 集成化, 智能化的优点. 近年来 …