Geological Models in Transition

Geostatistics ◽  
1970 ◽  
pp. 143-161 ◽  
Author(s):  
W. C. Krumbein
Keyword(s):  
Geological Models

3D Reservoir Characterisation Workflow Integrating High Angle and Horizontal Well Log Interpretation with Geological Models

2013 ◽  
Author(s):  
V. Polyakov ◽  
D. Omeragic ◽  
S. Shetty ◽  
B. Brot ◽  
T. Habashy ◽  
...  
Keyword(s):  
Horizontal Well ◽  
Well Log ◽  
High Angle ◽  
Geological Models ◽  
Log Interpretation ◽  
Well Log Interpretation

scholarly journals 3D geological models and their hydrogeological applications: supporting urban development a case study in Glasgow-Clyde, UK

2010 ◽  
Vol 161 (2) ◽  
pp. 251-262 ◽  
Author(s):  
S. Diarmad G. Campbell ◽  
Joanne E. Merritt ◽  
Brighid E O Dochartaigh ◽  
Majdi Mansour ◽  
Andrew G. Hughes ◽  
...  
Keyword(s):  
Urban Development ◽  
Geological Models

Simulation of Geological Models Using Multipoint Histogram

1995 ◽  
Author(s):  
W.Y. Qiu ◽  
M.G. Kelkar
Keyword(s):  
Geological Models

Optimisation of geotechnical surveys using a BIM-based geostatistical analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Elham Mahmoudi ◽  
Marcel Stepien ◽  
Markus König
Keyword(s):  
Experimental Design ◽  
Data Structures ◽  
Digital Design ◽  
Ground Model ◽  
Content Type ◽  
Design Environments ◽  
Spatial Estimation ◽  
Computational Performance ◽  
Geological Models ◽  
The Impact

PurposeA principle prerequisite for designing and constructing an underground structure is to estimate the subsurface's properties and obtain a realistic picture of stratigraphy. Obtaining direct measure of these values in any location of the built environment is not affordable. Therefore, any evaluation is afflicted with uncertainty, and we need to combine all available measurements, observations and previous knowledge to achieve an informed estimate and quantify the involved uncertainties. This study aims to enhance the geotechnical surveys based on a spatial estimation of subsoil to customised data structures and integrating the ground models into digital design environments.Design/methodology/approachThe present study's objective is to enhance the geotechnical surveys based on a spatial estimation of subsoil to customised data structures and integrating the ground models into digital design environments. A ground model consisting of voxels is developed via Revit-Dynamo to represent spatial uncertainties employing the kriging interpolation method. The local arrangement of new surveys are evaluated to be optimised.FindingsThe visualisation model's computational performance is modified by using an octree structure. The results show that it adapts the structure to be modelled more efficiently. The proposed concept can identify the geological models' risky locations for further geological investigations and reveal an optimised experimental design. The modifications criteria are defined in global and local considerations.Originality/valueIt provides a transparent and repeatable approach to construct a spatial ground model for subsequent experimental or numerical analysis. In the first attempt, the ground model was discretised by a grid of voxels. In general, the required computing time primarily depends on the size of the voxels. This issue is addressed by implementing octree voxels to reduce the computational efforts. This applies especially to the cases that a higher resolution is required. The investigations using a synthetic soil model showed that the developed methodology fulfilled the kriging method's requirements. The effects of variogram parameters, such as the range and the covariance function, were investigated based on some parameter studies. Moreover, a synthetic model is used to demonstrate the optimal experimental design concept. Through the implementation, alternative locations for new boreholes are generated, and their uncertainties are quantified. The impact of the new borehole on the uncertainty measures are quantified based on local and global approaches. For further research to identify the geological models' risky spots, the development of this approach with additional criteria regarding the search neighbourhood and consideration of barriers and trends in real cases (by employing different interpolation methodologies) should be considered.

Study of Scale-Down Method for Dense Grid Points

2013 ◽  
Vol 734-737 ◽  
pp. 3011-3015
Author(s):  
Sheng Yun Yu ◽  
Chang He Song ◽  
Hai Ying Xu
Keyword(s):  
Numerical Simulation ◽  
Geological Model ◽  
Three Dimension ◽  
Reservoir Heterogeneity ◽  
Geological Models ◽  
Scale Down ◽  
Dense Grid ◽  
Grid Points ◽  
Renormalization Method

The data of three-dimension geological models are very large, this kind of three -dimension geological model can not be directly used for numerical simulation and must be scaled down. The reservoir parameters, especially permeability, are scaled down by the simple renormalization method. The interbeds and parts of strong heterogeneity are filled back. The simple renormalization method is good through evaluation , not only it reduces the number of grid points, but also retains reservoir heterogeneity.

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