Results 21 to 30 of about 19,078 (305)

A geological 3D structural model of the Hessian Northern Phyllite Zone

, 2022
Large scaled geothermal potential assessments often require geological 3D-structural models of the area of interest. For assessing petrothermal potentials of the Hessian basement, a regional scaled geological 3D-structural model of the hessian basement ...
Sass, Ingo, Bär, Kristian, Weinert, Sebastian   +2 more
core   +1 more source

Advance of basin modeling key techniques: hydrocarbon migration and accumulation simulation

Shiyou shiyan dizhi, 2020
This paper summarizes traditional basin modeling, points out new application fields and technical problems, and discusses the present situation and progress of three kinds of hydrocarbon migration and accumulation simulation techniques.(a) Flowpath ...
Qiulin GUO, Ningsheng CHEN, Zhuangxiaoxue LIU, Jifeng LIU, Jingdu YU   +4 more
doaj   +1 more source

A geological 3D structural model of the Hessian Mid-German Crystalline High basement

, 2022
Large scaled geothermal potential assessments often require geological 3D-structural models of the area of interest. For assessing petrothermal potentials of the Hessian basement, a regional scaled geological 3D-structural model of the hessian basement ...
Sass, Ingo, Bär, Kristian, Weinert, Sebastian   +2 more
core   +1 more source

Construction of a 3D Stratum Model Based on a Solid Model

IEEE Access, 2021
A three-dimensional stratum model stratum model is a useful auxiliary tool for geotechnical engineering and other exploration work. The existing methods for stratum model construction lack complete topological descriptions of entities, so it is difficult
Qinghe Zeng, Weihua Ming, Zhilong Zhang, Zichun Du, Zhen Liu, Cuiying Zhou   +5 more
doaj   +1 more source

3D geological model report for Liverpool, Warrington and Irlam superficial and bedrock model [PDF]

, 2023
This report describes the data and methodology used to construct the 3D geological model of the artificially modified ground, superficial deposits and bedrock of Liverpool, Warrington and Irlam, NW England (Figure 1).
Cullen-Gow, H., Terrington, R., Thorpe, S., Kearsey, T., Burke, H.   +4 more
core  

Three-Dimensional Geological Modeling of the Shallow Subsurface and Its Application: A Case Study in Tongzhou District, Beijing, China

Applied Sciences, 2023
Three-dimensional (3D) geological models are currently needed and used independently for urban development. The main difficulty in constructing a 3D geological model of a shallow subsurface is to determine the stratigraphic distribution.
Hanhan He, Jingze Xiao, Jing He, Bo Wei, Xiaogang Ma, Fan Huang, Xiangmin Cai, Yuanxin Zhou, Jingyi Bi, Yiting Zhao, Chunjun Wang, Jingran Wei   +11 more
doaj   +1 more source

Intelligent Generation of Cross Sections Using a Conditional Generative Adversarial Network and Application to Regional 3D Geological Modeling

Mathematics, 2022
The cross section is the basic data for building 3D geological models. It is inefficient to draw a large number of cross sections to build an accurate model. This paper reports the use of multi-source and heterogeneous geological data, such as geological
Xiangjin Ran, Linfu Xue, Xuejia Sang, Yao Pei, Yanyan Zhang   +4 more
doaj   +1 more source

Geological-geothermal 3D model of the Cenozoic graben fill of the northern Upper Rhine Graben, Germany

, 2022
This data publication is part of the Hessen 3D 2.0 joint research project, funded by the German ministry of Economics and Energy (Bundesministerium für Wirtschaft und Energie, BMWi) and provides a geological-geothermal 3D model of the Neogene and ...
Sass, Ingo, Bott, Judith, Hintze, Meike, Bär, Kristian   +3 more
core   +1 more source

An Automated Mapping Method of 3D Geological Cross-Sections Using 2D Geological Cross-Sections and a DEM

ISPRS International Journal of Geo-Information, 2023
With the three-dimensional (3D) geological information system development, 3D geological cross-sections (GCs) have become the primary data for geological work and scientific research.
Hao Shang, Yan-Gen Shen, Shuang Li, An-Bo Li, Tao Zhang   +4 more
doaj   +1 more source

GeoPDNN 1.0: a semi-supervised deep learning neural network using pseudo-labels for three-dimensional shallow strata modelling and uncertainty analysis in urban areas from borehole data [PDF]

Geoscientific Model Development
Borehole data are essential for conducting precise urban geological surveys and large-scale geological investigations. Traditionally, explicit modelling and implicit modelling have been the primary methods for visualizing borehole data and constructing ...
J. Guo, X. Xu, L. Wang, X. Wang, L. Wu, M. Jessell, M. Jessell, M. Jessell, V. Ogarko, V. Ogarko, V. Ogarko, Z. Liu, Y. Zheng   +12 more
doaj   +1 more source