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The Coniacian–Santonian Matulla Formation is one of the important reservoirs in the July oilfield, Gulf of Suez Basin. However, this formation is characterized by uncertainty due to the complexity of reservoir architecture, various lithologies, lateral facies variations and heterogeneous reservoir quality. These reservoir challenges, in turn, affect the effectiveness of further exploitation of this reservoir along the Gulf of Suez Basin. In this work, we conduct an integrated study using multidisciplinary datasets and techniques to determine the precise structural, petrophysical, and facies characteristics of the Matulla Formation and predict their complex geometry in 3D space. To complete this study, 30 2D seismic sections, five digital well logs, and core samples of 75 ft (ft = 0.3048 m) length were used to build 3D models for the Matulla reservoir. The 3D structural model shows strong lateral variation in thickness of the Matulla Formation with NW–SE, NE–SW and N–S fault directions. According to the 3D facies model, shale beds dominate the Matulla Formation, followed by sandstone, carbonate, and siltstone beds. The petrophysical model demonstrates the Matulla reservoir's ability to store and produce oil; its upper and lower zones have good quality reservoir, whereas its middle zone is a poor quality reservoir. The most promising areas for hydrocarbon accumulation and production via the Matulla reservoir are located in the central, southeast, and southwest sectors of the oilfield. In this approach, we combined multiple datasets and used the most likely parameters calibrated by core measurements to improve the reservoir modeling of the complex Matulla reservoir. In addition, we reduced many of the common uncertainties associated with the static modeling process, which can be applied elsewhere to gain better understanding of a complex reservoir.

To understand the current application and development of 3D modeling in Digital Twins (DTs), abundant literatures on DTs and 3D modeling are investigated by means of literature review. The transition process from 3D modeling to DTs modeling is analyzed, as well as the current application of DTs modeling in various industries. The application of 3D DTs modeling in the fields of smart manufacturing, smart ecology, smart transportation, and smart buildings in smart cities is analyzed in detail, and the current limitations are summarized. It is found that the 3D modeling technology in DTs has broad prospects for development and has a huge impact on all walks of life and even human lifestyles. At the same time, the development of DTs modeling relies on the development and support capabilities of mature technologies such as Big Data, Internet of Things, Cloud Computing, Artificial Intelligence, and game technology. Therefore, although some results have been achieved, there are still limitations. This work aims to provide a good theoretical support for the further development of 3D DTs modeling.

For plant breeding and growth monitoring, accurate measurements of plant structure parameters are very crucial. We have, therefore, developed a high efficiency Multi-Camera Photography (MCP) system combining Multi-View Stereovision (MVS) with the Structure from Motion (SfM) algorithm. In this paper, we measured six variables of nursery paprika plants and investigated the accuracy of 3D models reconstructed from photos taken by four lens types at four different positions. The results demonstrated that error between the estimated and measured values was small, and the root-mean-square errors (RMSE) for leaf width/length and stem height/diameter were 1.65 mm (R2 = 0.98) and 0.57 mm (R2 = 0.99), respectively. The accuracies of the 3D model reconstruction of leaf and stem by a 28-mm lens at the first and third camera positions were the highest, and the number of reconstructed fine-scale 3D model shape surfaces of leaf and stem is the most. The results confirmed the practicability of our new method for the reconstruction of fine-scale plant model and accurate estimation of the plant parameters. They also displayed that our system is a good system for capturing high-resolution 3D images of nursery plants with high efficiency.

The work of 3D garden geo-geological modelling is very tedious and complicated, in order to reduce the labour intensity of the operators and improve the visualization effect of the model. This article proposes a method for 3D stratum visualization based on the combination of limited Delaunay triangulation and OpenGL. We can use the limited triangulation algorithm to generate stratum surface triangulations with any boundary shape, any size, or with multiple holes. At the same time, the paper uses OpenGL’s object picking mechanism to realize the visualization management of drilling data and human-computer interaction stratum modelling. Finally, we applied the model to garden geology, and the results showed that the system can quickly and accurately construct a three-dimensional model of the stratum. At the same time, the model realizes the three-dimensional visualization processing of garden geology.

This paper presents an approach for leveraging the abundance of images posted on social media like Twitter for large scale 3D reconstruction of cultural heritage landmarks. Twitter allows users to post short messages, including photos, describing a plethora of activities or events, e.g., tweets are used by travelers on vacation, capturing images from various cultural heritage assets. As such, a great number of images are available online, able to drive a successful 3D reconstruction process. However, reconstruction of any asset, based on images mined from Twitter, presents several challenges. There are three main steps that have to be considered: (i) tweets’ content identification, (ii) image retrieval and filtering, and (iii) 3D reconstruction. The proposed approach first extracts key events from unstructured tweet messages and then identifies cultural activities and landmarks. The second stage is the application of a content-based filtering method so that only a small but representative portion of cultural images are selected to support fast 3D reconstruction. The proposed methods are experimentally evaluated using real-world data and comparisons verify the effectiveness of the proposed scheme.

The cultural landscape of Chiang Mai city, which is characterized by the interlinkage between mountain and historical settlement, has faced the adverse impacts of visual intrusion in its buffer zone from urbanization. However, there are challenges to creating a quantitative visual evaluation for decision making in response to rapid urban change. This study evaluated the impact of building height on the city skyline and utilized existing cultural heritage locations on the mountain to define a protected visual zone while conducting a 3D-GIS-based visibility analysis to identify obstruction in three scenarios: the actual condition scenario (ACS) considering current conditions, the land use scenario (LUS) considering the land use ordinance, and the proposed scenario (PPS) considering mountain skyline protection, using computer-generated 3D city modeling. The comparative results from the analysis of viewshed, line of sight, and development area calculations revealed that the number of obstructed locations in the LUS decreased by 48.46%, and in the PPS, they decreased by 77.99%, while the development area increased by similar amounts, demonstrating that the city can grow and develop despite stricter height controls. In addition, based on a visual assessment, this study established a buffer distance and intensity to protect the integrity of the heritage while allowing the city to develop.

The Jiaodong Peninsula hosts the main large gold deposits and was the first gold production area in China; multisource and multiscale geoscience datasets are available. The area is the biggest drilling mineral-exploration zone in China. This study used three-dimensional (3D) modeling, geology, and ore body and alteration datasets to extract and synthesize mineralization information and analyze the exploration targeting in the Zhaoxian gold deposit in the northwestern Jiaodong Peninsula. The methodology and results are summarized as follows: The regional Jiaojia fault is the key exploration criterion of the gold deposit. The compression torsion characteristics and concave–convex section zones in the 3D deep environment are the main indicators of mineral exploration using 3D geological and ore-body modeling in the Zhaoxian gold deposit. The hyperspectral detailed measurement, interpretation, and data mining used drill-hole data (>1000 m) to analyze the vectors and trends of the ore body and ore-forming fault and the alteration-zone rocks in the Zhaoxian gold deposit. The short-wave infrared Pos2200 values and illite crystallinity in the alteration zone can be used to identify 3D deep gold mineralization and potential targets for mineral exploration. This research methodology can be globally used for other deep mineral explorations.

Understanding the strengths and limitations of the modeling capacity of surface flooding in urbanized floodplains is of utmost importance as such events are becoming increasingly frequent and extreme. In this study, we assess two computational models against laboratory observations of surface urban flooding in a reduced‐scale physical model of idealized urban districts. Four urban layouts were considered, involving each three inlets and three outlets as well as a combination of three‐ and four‐branch crossroads together with open spaces. The first model (2D) solves the shallow‐water equations while the second one (3D) solves the Reynolds‐averaged Navier‐Stokes equations. Both models accurately predict the flow depths in the inlet branches. For the discharge partition between the outlets, deviations between the computations and laboratory observations remain close to the experimental uncertainties (maximum 2.5 percent‐points). The velocity fields computed in 3D generally match the measured surface velocity fields. In urban layouts involving mostly a network of streets, the depth‐averaged velocity fields computed by the 2D model agree remarkably well with those of the 3D model, with differences not exceeding 10%, despite the presence of helicoidal flow (revealed by the 3D computations). In configurations with large open areas, the 3D model captures generally well the trajectory and velocity distribution of main surface flow jet and recirculations; but the 2D model does not perform as well as it does in relatively channelized flow regions. Visual inspection of the jet trajectories computed by the 2D model in large open areas reveals that they substantially deviate from the observations. Plain Language Summary Advancing our modeling capacity of urban flooding is of utmost importance for improving the design of risk reduction measures. During extreme urban flooding, complex flow patterns develop in urban environments, involving three‐dimensional flow structures. Though, urban floods are commonly simulated with two‐dimensional computational models. So far, no detailed comparison between flow fields predicted by two‐ and three‐dimensional computational models were conducted and assessed against reference data such as experimental observations for representative configurations of urban flooding. In this study, we assess two computational models against laboratory observations of urban flooding in a reduced‐scale physical model of an idealized district. Key Points Predictions of 2D and 3D computational models were compared against laboratory experiments representing urban flooding in a steady‐state Both models perform equally well to predict upstream flow depth, outlet discharge partition, and velocity field in street networks In urban layouts with large open spaces, only the 3D model accurately predicts the velocity field

Both policy and research highlight the importance of diverse stakeholder input in urban development processes but visualizing future built environments and creating two-way design communication for non-expert stakeholders are challenging. The present study develops an intuitive and simplified 3D modeling platform that integrates web-based desktop, virtual reality and mobile augmented reality technologies for remote simultaneous urban design collaboration. Through iterative prototyping, based on two series of workshops with stakeholders, the study resulted in such an integrated platform as a minimum viable product as well as specifications for a minimum marketable product to be used in real projects. Further study is required to evaluate the minimum level of detail in the 3D modeling necessary for good perception of scale and environmental impact simulation.

Three-dimensional (3D) modeling of tsunami events is intended to promote tsunami safety. However, the developed 3D modeling methods based on Computational Fluid Dynamics and photorealistic particle visualization have some weaknesses, such as not being similar to the original environment, not measuring the wave’s end point, and low image accuracy. The method for 3D modeling of tsunamis that results from this research can fulfil those weaknesses because it has advantages, such as being able to predict the end point of waves, similar to the original environment, and the height and area of inundation. In addition, the method produces more detailed and sharper spatial data. Modeling in this research is conducted using Agisoft Metashape Professional software to a produce 3D orthomosaic from pictures taken with Unmanned Aerial Vehicle (UAV) technique or drone (photogrammetry), and 3ds max software is used for wave simulation. We take a sample of an area in Cilacap, Indonesia that was impacted by the 2006 southwest coast tsunamis and may be vulnerable to future big megathrust earthquakes and tsunamis. The results could be used to provide several benefits, such as the creation of evacuation routes and the determination of appropriate locations for building shelters.