simulation « The Westernmost Tethys Blog

08/29/2022

K-nearest neighbors algorithm used for classifying geological variables.

Filed under: PID2020-114381GB-I00,simulation — Tags: 3d stratigraphic architecture, granulometry, KNN algorithm, Llobregat River Delta, Python libraries — messinianalicante @ 12:08 PM

The k-nearest neighbors (KNN) algorithm is a non-parametric supervised machine learning classifier; which uses proximity and similarity to make classifications or predictions about the grouping of an individual data point. This ability makes the KNN algorithm ideal for classifying datasets of geological variables and parameters prior to 3D visualization. This paper introduces a machine learning KNN algorithm and Python libraries for visualizing the 3D stratigraphic architecture of sedimentary porous media in the Quaternary onshore Llobregat River Delta (LRD) in northeastern Spain. A first HTML model showed a consecutive 5 m-equispaced set of horizontal sections of the granulometry classes created with the KNN algorithm from 0 to 120 m below sea level in the onshore LRD. A second HTML model showed the 3D mapping of the main Quaternary gravel and coarse sand sedimentary bodies (lithosomes) and the basement (Pliocene and older rocks) top surface created with Python libraries. These results reproduce well the complex sedimentary structure of the LRD reported in recent scientific publications and proves the suitability of the KNN algorithm and Python libraries for visualizing the 3D stratigraphic structure of sedimentary porous media, which is a crucial stage in making decisions in different environmental and economic geology disciplines.

The 3D stratigraphic architecture (coarse lithosomes and the basement top surface (BTS)) of the onshore LRD. (A) Gravel and coarse sand lithosomes and BTS. (B) Gravel lithosomes and BTS. (C) Coarse sand lithosomes and BTS. (D) Basement top surface. The color assigned to each granulometry class is cyan for gravel, yellow for coarse sand, and reddish-brownish for the basement. An interactive 3D HTML version of this model is included in Supplementary Materials

Interactive figures here

Cite as: Bullejos, M., Cabezas, D., Martín-Martín, M., Alcalá, F.J., 2022. A K-Nearest Neighbors Alborithm in Python for Visualizing the 3D Stratigraphic Architecture of the Llobregat River Delta in NE Spain. J. Mar. Sci. Eng. https://doi.org/10.3390/jmse10070986

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06/30/2022

A Python Application for Visualizing the 3D Stratigraphic Architecture

Filed under: PID2020-114381GB-I00,simulation,Tectonosedimentary model — Tags: 3D modeling application, convex hull algorithm, granulometry, IDW interpolation algorithm, Llobregat River Delta, Python programming language, stratigraphic architecture — messinianalicante @ 7:17 AM

A Python application for visualizing the 3D stratigraphic architecture of porous sedimentary media has been developed. The application uses the parameter granulometry deduced from borehole lithological records to create interactive 3D HTML models of essential stratigraphic elements.

The 3D distribution of the granulometry classes along the Z axis in each of the 433 compiled boreholes in the LRD. The plotting adopted a 1:1:50 (x = 2, y = 2 and z = 0.5) aspect ratio for better display. The color assigned to each granulometry class is cyan for gravel, yellow for coarse sand, gray for silt–clay, and red for the basement.

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 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 Llobregat Delta sector, middle (20–50 m b.s.l.) in the central Llobregat, and upper (<20mb.s.l.) spread over the entire Llobregat. 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.

Cite as: Bullejos, M., Cabezas, D., Martín-Martín, M., Alcalá, F.J., 2022. A Python Application for Visualizing the 3D Stratigraphic Architecture of the Onshore Llobregat River Delta in NE Spain. Water . https://doi.org/10.3390/w14121882

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01/29/2020

Compactation in sedimentary basins

Filed under: basin analysis,simulation — Tags: geotechnics-engeenering software, sediment compactation, Sierra Espuña — messinianalicante @ 8:59 AM

Subsidence analysis is an important technique in the study of sedimentary basins but the effects of compaction must be “backstripped”. The compaction of sediments is also of importance for petroleum and water reservoir research with very important economic derivations. Most methods for calculating compaction are based on empirically derived porosity-depth relationships from a variety of known sediment types. The challenge of this paper is to apply alternative methods for calculating compaction in sedimentary basins based on: physical calculation with elastic by Steinbrenner, oedometric and change of the specific weight of the sediment methods; and use of Loadcap software.

The Triassic to Lower Miocene 3025m thick succession of Sierra Espuña (SE Spain) is used as case study for the calculations. In this succession former mineralogical studies and apatite fission-track suggested an original thickness between 4 and 6km. The validity of each one of the proposed methods is discussed, as well as, compared for the whole succession compaction but also separately for hard vs soft sediments and for thick vs thin beds.

Accumulate thickness-age (My) graphic with the comparative of the measured thickness and the results of original accumulate thickness along time of the studied succession after decompaction with the whole methods. The mean thickness with the whole methods is also represented with dash line. Key: ESM: elastic by Steinbrenner; SWM: specific weight of the sediment methods; OM: oedometric method; PCM: porosity change method (Bond et al., 1983); LSM: use of Loadcap software method.

The compaction values obtained with the alternative methods are similar to those resulting with the lower-limit curves of the porosity-depth change method. The new methods have provided values slightly higher than 4km for the whole original thickness using the geotechnical software and the change of the sediments specific weigh methods; meanwhile values below 4km for other methods. So, in our opinion, the geotechnical software and the change of the specific weight of the sediment methods are compatible with mineralogical constraints and also, the input data are usually better known and easier to determinate. Otherwise, the elastic method seems only accurate for soft sediments; meanwhile the oedometric method is highly influenced by the thickness of the considered beds.

Cite as: Martín-Martín, M., and Robles-Marín, P. (2020): Alternative methods for calculating compaction in sedimentary basins. Mar. Pet. Geol. 113, 104132. doi: 10.1016/j.marpetgeo.2019.104132

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11/19/2019

shallow water stratified simulation

Filed under: simulation — Tags: finite volumes, shallow-water — messinianalicante @ 2:28 PM

The computational simulation of shallow stratified fluids is a very active research topic because these types of systems are very common in a variety of natural environments. The simulation of such systems can be modeled using multilayer shallow-water equations but do impose important computational requirements, especially when applied to large domains.

General Purpose Computing on Graphics Processing Units (GPGPU) has become a vivid research field due to the arrival of massively parallel hardware platforms (based on graphics cards) and adequate programming frameworks which have allowed important speed-up factors with respect to not only sequential but also parallel CPU based simulation systems.

In this work we present simulation of shallow stratified fluids with an arbitrary number of layers using GPUs. The designed system does fully adapt to the many-core architecture of modern GPUs and several experiments have been carried out to illustrate its scalability and behavior on different GPU models. We propose a new multilayer computational scheme for an underlying 2D mathematical model. This scheme is capable of handling an arbitrary number of layers. The system adds no overhead when used for two-layer scenarios, compared to an existing 2D system specifically designed for just two layers.

In this image we show a scheme for the initial configuration of a 6 layers simulation, along with a screenshot of the program.

The GPU computes the evolution in time of the interfaces between several layered fluid types (for a given initial configuration) and displays those interfaces as solid surfaces, as soon as the output from each computing step is available. The user can rotate the view interactively, so he can better observe the layers’ evolution.

Here you can view two screen-shots taken from the simulation program while running. First one the initial layers configuration is shown.

Then It is shown the resulting layers configuration after the simulation has been running for some time.

These screen captured videos (see links below) show the simulation program running in real-time, for various scenerarios. You can observe how the user is able to manipulate the view: