A Python Application for Visualizing the 3D Stratigraphic Architecture of the Onshore Llobregat River Delta in NE Spain

Abstract

This paper introduces a Python application for visualizing the 3D stratigraphic architecture of porous sedimentary media. The application uses the parameter granulometry deduced from borehole lithological records to create interactive 3D HTML models of essential stratigraphic elements. On the basis of the high density of boreholes and the subsequent geological knowledge gained during the last six decades, the Quaternary onshore Llobregat River Delta (LRD) in northeastern Spain was selected to show the application. The public granulometry dataset produced by the Water Authority of Catalonia from 433 boreholes in this strategic coastal groundwater body was clustered into the clay–silt, coarse sand, and gravel classes. Three interactive 3D HTML models were created. The first shows the location of the boreholes granulometry. The second includes the main gravel and coarse sand sedimentary bodies (lithosomes) associated with the identified three stratigraphic intervals, called lower (>50 m b.s.l.) in the distal LRD sector, middle (20–50 m b.s.l.) in the central LRD, and upper (<20 m b.s.l.) spread over the entire LRD. The third deals with the basement (Pliocene and older rocks) top surface, which shows an overall steeped shape deepening toward the marine platform and local horsts, probably due to faulting. The modeled stratigraphic elements match well with the sedimentary structures reported in recent scientific publications. This proves the good performance of this incipient Python application for visualizing the 3D stratigraphic architecture, which is a crucial stage for groundwater management and governance.

A K-Nearest Neighbors Algorithm in Python for Visualizing the 3D Stratigraphic Architecture of the Llobregat River Delta in NE Spain

“…Other proves of the 3D model reliability are as follows. We recently used an algorithm different from KNN to create other 3D models of the LRD; the results being quite similar to these [16]. Moreover, we have determined the horizontal and vertical reliability of our 3D model.…”

“…On the other hand, Python has a wide variety of libraries for data handling (such as Pandas and Numpy) and visualization (such as Matplotlib), including a friendly KNN interface available through the machine learning library scikit-learn to infer the magnitude of a given parameter or variable in points where data could not be collected. As deduced, Python is a suitable programming language for the modeling of geological parameters and variables, as the authors of this paper already proposed in previous research [16]. The created interactive 3D HTML model for visualizing the 3D stratigraphic architecture (coarse lithosomes and the basement top surface) of the LRD is included in Supplementary Materials (3D_Lithosomes_ LRD.html (accessed on 12 July 2022)).…”

“…Some scientific documents develop or apply computer tools to different fields of geology [11][12][13][14], and some social media channels post data analytics and machine learning educational applications focused on geology [15]. The experience of the researchers' team of this paper with Python libraries for geological data handling and 3D visualization [16] was decisive in developing a new application for classifying and visualizing the 3D stratigraphic architecture of sedimentary porous media based on a machine learning KNN algorithm and Python libraries. This application uses (i) the KNN algorithm to create a consecutive 5 m-equispaced set of horizontal sections of the granulometry classes grouped as an interactive 3D HTML model; and (ii) different Python libraries to create an interactive 3D HTML model of the essential stratigraphic elements (coarse lithosomes and basement top surface) of the sedimentary basin.…”

A Python Application for Visualizing an Imbricate Thrust System: Palomeque Duplex (SE, Spain)

“…To get a model of another location, the procedures presented here can be mimicked, but these must be adapted to the new data of the new location, and researchers must make their own choices of how the model should be. Python has been used by us to produce other geological models in the recent past, but with a different perspective and different kind of data, as is the case of the Llobregat River Delta (Barcelona, Spain) [28][29][30][31].…”

“…Our previous experience with Python libraries for 3D visualization, including geological data handling [28][29][30][31], has been very important to develop new applications for visualizing 3D structural and stratigraphic geological features. These new applications included Jupyter notebooks, describing the methodology, and a Python code operative version, which are downloadable from the GitHub repository (https://github.com/bullejos/ visualizing-an-imbricate-thrust-system accessed on 4 July 2023).…”