Abstract
The technology of 3D geological modeling is a powerful tool for representing the geological structures and subsurface strata distribution, which can effectively assist in the geological interpretation and analysis work. However, most existing modeling methods usually need the supports of professional geological modeling software. These systems often have tedious data preprocessing, complex modeling and visualization processes, and non-professionals have difficulty mastering them in a short time. In order to improve the operability and intuitiveness for 3D geological modeling and visualization, this paper proposes a semi-automatic method for 3D modeling and visualizing complex geological bodies by combining typical GIS systems and 3D modeling software such as ArcGIS and SketchUp. First, the Python object-oriented program language and Arcpy package are combined for preprocessing borehole data automatically. Next, the multiple 3D analysis and file conversion tools of Arctoolbox and ModelBuilder are combined for constructing a model to generate strata interfaces. Then, the makefaces and Boolean plug-ins of SketchUp are combined for semi-automatically constructing the 3D model of complex geological bodies and implementing various forms of visualization. Last, the borehole data and geological maps acquired from the geological survey are used for testing our modeling method. The modeling processes and results show that the method can quickly construct the 3D model of complex geological bodies with very complex geological structures such as missing strata, faults and lenses. This paper shows the simplicity and practicality of the proposed method for modeling and visualizing complex geological bodies.
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Introduction
In recent years, the technology of three-dimensional (3D) geological modeling has attracted much more attention from the field of mining, geology, surveying and mapping, geographic information, engineering construction and other geoscience fields since it can more intuitively help interpret the 3D geological structures and spatial distributions of underground rock than the technology of traditional two-dimensional (2D) geological mapping (Alan and Norman 2003; Martin-Izard et al. 2015; Kaufmann and Martin 2008; Xiao et al. 2015; Choi et al. 2009; Gong et al. 2004; Galera et al. 2003; Hou et al. 2016). However, most existing modeling methods usually need the supports of a professional geological modeling system such as GOCAD (Zanchi et al. 2009) and FLAC3D (Xu et al. 2011). The associated data preprocessing is very tedious and their operation processes are very complex, and non-professional users must spend much time training to master them. Meanwhile, the prices of commercial geological modeling systems are such that high- and small-scale enterprises can not afford to buy them. Some researchers and experts seek to develop 3D geological modeling software by 3D graphic platforms such as OpenGL (Wang and Huang 2012; Wu et al. 2005; Zhu et al. 2012) and Java3D (Yang et al. 2006). This kind of modeling method is often very time-consuming and costly, and users not only have to design complex data structures and algorithms from scratch, but also have to spend much time on mastering many programming skills. Meanwhile, the stability and availability of the constructed systems are often very poor compared with commercial 3D geological modeling software systems. In addition, some experts have constructed simple 3D geological data visualization application (Mccarthy and Graniero 2006; Choi et al. 2009) and even developed 3D modeling systems based on the existing GIS system such as ArcGIS and MapGIS (Zhu et al. 2006). The defects of existed modeling methods have extremely limited its further promotion in the fields of geosciences research and engineering. Especially, complex geological objects are often involved in the fields of mining, geology and engineering construction, it is very necessary to develop a simple and practical modeling method for meeting the wide requirements of the above fields.
At present, great progress has been made based on the foundational theories (Houlding 1994; Mallet 2002), but it is still challenging work to achieve fully automatic 3D geological modeling and visualization since there remain many difficulties when dealing with various geological formations within a single software system. Through systematically analyzing the existing modeling methods and their implementations, their operation processes mainly include three phases: data preprocessing, modeling and visualization. Meanwhile, many technicians have been accustomed to managing their geological data by using the traditional GIS systems. Meanwhile, they prefer creating 3D models with 3D modeling software such as AutoCAD (Tonini et al. 2008) and 3dsMax (Wang et al. 2009). In fact, the whole processes of data processing, modeling and visualization can be performed by combining the above GIS systems and 3D modeling software, which can not only easily manage and analyze the geological data, but also guarantee the efficiency and reliability of the modeling results.
Furthermore, considering comprehensively from the perspective of the software market occupancy, functionality and usability of existing GIS systems, ArcGIS is the most widely used GIS system. ArcGIS not only has the basic functions for data processing and mapping, but also provides the powerful capabilities for modeling, visualization and spatial analysis. Especially, its embedded Arcpy site package can be combined with the Python object-oriented programming language and the visual modeling tools of ModelBuilder, which can greatly improve the efficiency of data processing and modeling. Meanwhile, SketchUp is simple and practical 3D modeling software directly oriented to the architectural scheme designs, and it is so easy to use that it can be mastered in a very short time. In addition, it provides a lot of auxiliary drawing plug-ins, which can greatly improve the modeling efficiency and make up for the shortages of ArcGIS for modeling complex geological objects.
In summary, in order to promote the further popularization in the fields of mining, geology and engineering construction widely, this paper attempts to explore a semi-automatic method for 3D modeling and visualizing complex geological bodies by combing a typical GIS system and 3D modeling software such as ArcGIS and SketchUp. The main merits are brought out to make the modeling and visualization processes more convenient, intuitive and reliable, and the main implementing technologies related to data preprocessing, modeling and visualization are discussed in detail.
Methodology
The term geological body is a loose term commonly used in geological fields, usually referring to earth crusts occupying a certain space, with inherent ingredients that can be distinguished from the surrounding geological materials. The shape and spatial distribution of geological bodies are often very complex because they have gone through extensive periods of geological action and processes, but they usually can be classified into stratified and non-stratified geological bodies (Li 2000). The general model for describing geological bodies can be classified into four types (Wu et al. 2002), which mainly include wireframe-based models (Xu and Tian 2009), surface-based models (Lázaro et al. 2014), volume-based models (Wu 2004; Gong et al. 2004) and surface-volume mixed models (Cheng et al. 2005).
Complex geological bodies can be seen as a series of closed geometrical strata objects divided by different structural surfaces such as strata interfaces, fault surfaces and modeling boundary surfaces, and can be described with the boundary representation (B-rep) model. The main modeling ideas of this paper reference the modeling method of constructive solid geometry (CSG) for building complex geological bodies, and its principle and implementation can be described as follows: First, complex geological bodies are decomposed into a series of simple strata objects such as strata interfaces (Fig. 1a), fault surfaces and modeling boundary surfaces (Fig. 1b); Next, a CSG tree is constructed for describing the complex geological bodies with a series of simple strata bodies (Fig. 1c) and faults bodies (Fig. 1d). Then, some Boolean operations such as Boolean (∪), intersection (∩) and difference (–) are combined for generating a 3D model of complex geological bodies (Fig. 1e). Last, the above operations can be easily implemented by the Boolean plug-ins of SketchUp; its modeling principle and implementing method are shown in Fig. 1.
Implementation of modeling and visualization
Designing the work flows
The work flows designed for data preprocessing, modeling and visualization are based on the existing modeling methods, but are different from them since the operability, intuitiveness and practicability are considered adequately. Meanwhile, the special situations of missing strata and local lenses are dealt with at the stage of data processing, and the fault formation is taken as the major consideration in the processes of modeling and visualization.
The modeling method not only can be operated automatically for creating the strata interfaces, but also can automatically deal with the strata intersections efficiently by the script tool implemented by combining the Python program language and Arcpy site package. In addition, it provides a semi-automatic approach to create the 3D modeling of complex geological bodies by the Boolean plug-ins of SketchUp. In addition, it can rapidly implement various types of visualization operations such as cutting, excavating and tunneling. The work flow includes five steps, as shown in Fig. 2.
Data acquisition, preprocessing and defining the modeling boundary
The modeling data are acquired from the geological exploration and survey for urban subway constructing projects, which mainly include various types of borehole data and geological maps. The borehole data are stored in different Excel files and can be classified into four types of borehole data such as geological, engineering, seismic and high-density. First, the DBF tables, such as basic borehole information, strata codes and strata lithology (Tables 1, 2 and 3), are extracted by displaying XY data and exporting files. Next, the borehole 3D points and 3D polylines (Fig. 3a and b) are created with the script tools implemented with the Python program language and the Arcpy site package (Fig. 4).
Then, the 2D polylines of faults are extracted from the geological maps with the automatic vectorization tool of ArcScan, and the convex polygon for defining the modeling boundary is extracted from the original borehole data with the tool of minimum bounding geometry (MBG), as shown in Fig. 5.
Furthermore, different types of modeling data, such as borehole 3D points, 2D fault lines and the 2D polygon of modeling boundary, are exported centrally into the GIS database, which will be used as the initial sample data for subsequent data preprocessing, modeling and visualization.
Finally, a series of virtual strata are added into borehole data respectively for dealing with the missing strata and local lenses (Fig. 5), and the zero thick values are used for replacing the missing values of every stratum in the borehole data. For example, the stratum Q2 is missing from the borehole data for boreholes BH10053 to BH10058. Thus, in order to construct a continuous stratum of Q2, all the thick values of the stratum Q2 among them are replaced with the zero thick values for dealing with the missing data.
Constructing a 3D model of complex geological bodies
Creating strata interfaces automatically
ModelBuilder is one of the most useful tools of ArcGIS, which can provide an automatic approach for creating the strata interfaces by designing a model that can be run automatically, and its operation steps mainly include: First, the 3D points of the borehole are inserted into ModelBuilder (Fig. 6a). Next, the iterator of feature selection and the tools of Arctoolbox such as "Select", "Kriging interpolation" (Fig. 6b), "RasterToPoint" (Fig. 6c), "CreateTin" (Fig. 6d), "TinTriangle" (Fig. 6e) and "TriangleToCAD" (Fig. 6f) are added and their generated intermediate files of the processes are shown in Table 4. Then, the borehole data, the iterator and tools are connected sequentially with the connection tool. Further, the input, output, workspace and other related parameters of the iterator and the tools are configured. Finally, the constructed model can be run automatically and create a series of DWG files of the strata interfaces after validating the constructed model; the designed model is shown in Fig. 6g.
It should be noted that there will be some intersections partially among the strata interfaces after the kriging interpolation (Fig. 7a). For example, the stratum interface of Q3 passes through the strata interfaces of Q2, N, FH, J-T1-T2 and R5. Here, the strata intersections among them are handled after converting the raster files of all strata into strata points. Meanwhile, the converted strata points are reprocessed with a Python script tool (Fig. 7c), and the heights of the strata such as Q2, N, FH, J-T1-T2 and R5 are accessed orderly and their heights are replaced with the values of above strata if their values are greater than them, The main implementing codes are shown as follows and the processed results are shown in Fig. 7b.
Then, the reprocessed strata points are used as the input data of the model for creating the strata interfaces again.
Constructing the simple strata model
The Makefaces plug-ins and the tool of intersecting faces are combined for creating the simple strata semi-automatically, and its operation steps mainly include: First, the DWG files of strata interfaces created previously by ModelBuilder are sequentially imported into the visual modeling environment of SketchUp (Fig. 8a); Next, the strata surfaces and the boundary surface are created, respectively, with the polylines of strata interfaces and modeling boundary by the makefaces plug-ins (Fig. 8b). Then, the boundary polyhedrons are created by the push/pull tool, while the intersect lines between the strata surfaces and boundary polyhedron can be easily generated by the intersect faces tool. Further, the side surfaces of the modeling boundary are generated automatically by the explode tool, and the excess structure faces are erased for constructing the B-rep model of a single stratum. Last, the same operation method is adopted for constructing the B-rep models of other strata and composing them to the simple strata model, and different color materials are assigned to stratum model respectively, as shown in Fig. 8f.
Creating the complex strata model with faults
The geometric shape and structure of a single fault can be described with a spatial curved surface and approximated with a complicated surfaces made up of a series of small facets (Wu and Xu 2003). Here, considering the feasibility and practicality of the modeling operation, the spatial planes are used for describing the faults surfaces since there are only the data of 2D fault polylines. Meanwhile, in order to intuitively represent their spatial distribution and topological relations in the 3D model of complex geological bodies, a series of polyhedrons are used for depicting the faults bodies. Initially, a series of polygons are generated from the 2D fault polylines by the buffer tool of ArctoolBox (Fig. 9a) and exported as the DWG file of the faults; Next, it is imported to SketchUp, and the surfaces of the faults are created automatically by the makefaces plug-ins; Then, an auxiliary line perpendicular to the surface of a fault surface is drawn manually; meanwhile, a spatial curve depicting its tendency is also drawn with a certain angle by the "Uniform B-Spline" plug-in along the auxiliary line (Fig. 9b). Furthermore, the polyhedron of the fault is drawn along the curves by the follow-me tool (Fig. 9c), and other faults polyhedrons are also created by the same operations (Fig. 9d) and embedded into the constructed simple strata model previously (Fig. 9e). Last, a series of Boolean operations between fault polyhedrons and the simple strata model are performed for generating the complex strata model with faults by the Boolean plug-ins, as shown in Fig. 9f.
Operating and visualizing the constructed model
After constructing the complex strata models, some visualizing operation, such as cutting (Fig. 10a and Fig. 10b), excavating and tunneling (Fig. 10c and Fig. 10ed), can be easily achieved with the same Boolean operation by the Boolean plug-ins. Meanwhile, the constructed model can also be exported to ArcScene for further visualization and analysis (Fig. 10e). The detailed operations of these tools will not be introduced in this paper; users can easily learn them through the online plug-in courses of SketchUp.
Publishing and sharing the constructed model
So far, the constructed 3D strata model can only be operated in the environments of SkethUp and ArcScene. In order to publish and share the constructed 3D geological models to the public through the Internet, the users can easily access them by different types of client software such as ArcGlobe, GoogleEarth and Web browsers. The models can be exported as different file formats such as 3DS, COLLADA and VRML for further publishing and sharing. The exported 3D models in the above client software are shown in Fig. 11.
Conclusions and outlook
Many effective modeling methods and some commercial modeling software have been proposed and implemented since the technology of 3D geological modeling was born. The modeling method proposed in this paper combines the merits of a typical GIS system and 3D modeling software such as ArcGIS and SketchUp for semi-automatically 3D modeling and visualizing the complex geological bodies, and it has the following advantages:
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(1)
ArcGIS is one of the most widely used GIS systems, which can effectively help to manage, process and analyze the multi-source geological data based on its powerful functions such as data processing, mapping and visualization since many technicians have been accustomed to the thinking and operation habits of GIS systems.
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(2)
The Python program language, Arcpy site package and the visual modeling tool of ModelBuilder are combined for data preprocessing and modeling, which not only can greatly improve the efficiency of data preprocessing and modeling, but also provide more operational stability and flexibility.
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(3)
SketchUp is simple and practical 3D modeling software which can greatly help to construct complex geological bodies intuitively by using its easy drawing functions and rich plug-in tools, and implement various types of modeling operations; Meanwhile, the constructed strata models can be easily exported to various file formats such as 3DS, COLLADA, VRML, etc.
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(4)
ArcGIS and SketchUp are combined for 3D modeling and visualizing complex geological bodies, which not only can effectively help to improve the efficiency of data preprocessing, modeling and visualization, but also can reduce the labor intensity of technicians, and is very beneficial to promote the popularization of 3D geological modeling technology in the fields of mining, geology and engineering construction.
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(5)
There are still many difficulties for 3D modeling and visualizing complex geological bodies automatically due to the variety of geological settings and data preprocessing. The actual modeling work not only requires automatic processes for data preprocessing, modeling and visualization, but also the constructed models have to be modified manually for making them close to reality.
This paper proposes a semi-automatic method for modeling and visualizing complex geological bodies by combining ArcGIS and SketchUp, and its main purpose is to explore a simple and practical 3D geological modeling method for promoting the further popularization in the fields of mining, geology and engineering constructions widely. The modeling method described in this paper has made modeling experiments on simple stratified geological bodies with the most common formations such as faults and missing stratum. Special complex geological bodies, such as deformed and reversed bodies, has not been studied and will be the emphasis of future research work.
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Acknowledgments
This research was supported by the Natural Science Foundation of China and the Natural Science Foundation of Jiangsu Province of China (grant numbers 41601501 and 13KJD520002). The authors wish to thank the Geological Exploration Technology Institute of Jiangsu Province for providing the borehole data and geological maps used to test the modeling method of this paper, and also thank the editors and reviewers for their work on our paper.
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Song, R., Qin, X., Tao, Y. et al. A semi-automatic method for 3D modeling and visualizing complex geological bodies. Bull Eng Geol Environ 78, 1371–1383 (2019). https://doi.org/10.1007/s10064-018-1244-3
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DOI: https://doi.org/10.1007/s10064-018-1244-3