3D View Research Articles

Quantitative characterization of organic and inorganic pores in shale based on deep learning

Organic matter (OM) maturity is closely related to organic pores in shales. Quantitative characterization of organic and inorganic pores in shale is crucial for rock-physics modeling and reservoir porosity and permeability evaluation. Focused ion beam-scanning electron microscopy (FIB-SEM) can capture high-precision three-dimensional (3D) images and directly describe the types, shapes, and spatial distribution of pores in shale gas reservoirs. However, due to the high scanning cost, wide 3D view field, and complex microstructure of FIB-SEM, more efficient segmentation for the FIB-SEM images is required. For this purpose, a multiphase segmentation workflow in conjunction with a U-net is developed to segment pores from the matrix and distinguish organic pores from inorganic pores simultaneously in the entire 3D image stack. The workflow is repeated for FIB-SEM data sets of 17 organic-rich shales with various characteristics. The analysis focuses on improving the efficiency and relevance of the workflow, that is, quantifying the minimum number of training slices while ensuring accuracy and further combining the fractal dimension (FD) and lacunarity to study a simple and objective method of selection. Meanwhile, the computational efficiency, accuracy, and robustness to noise of the 2D U-net model are discussed. The intersection over the union of automatic segmentation can amount to 80%–95% in all data sets with manual labels as ground truth. In addition, calculated by the FIB-SEM multiphase segmentation, the organic porosity is used to quantitatively evaluate the OM decomposition level. Deep-learning-based segmentation shows great potential for characterizing shale pore structures and quantifying OM maturity.

Nonlinear complex generalized zakharov dynamical system inconformal sense utilizing new kudryashov method

We take into account the nonlinear complex generalized Zakharov dynamical system which models the spread of the Langmuir waves in ionized plasma, in the conformal sense in this manuscript. Fractional wave transformation is enforced to convert the nonlinear fractional system to a nonlinear ordinary differential equation system. The new Kudryashov method which was recently introduced and is an efficient method, is implemented to the presented equation to acquire analytical solutions. The required constraint conditions are offered to ensure the validity of the obtained solutions. To analyze the physical interpretations for some of the produced solutions, we illustrate some graphical representations. We derive the bright and singular solitons. Furthermore, 2D views of the behavior of the solitons are represented to investigate the effect of the values of the parameters in the proposed model and fractional parameters. Also, the modulation instability of the model is investigated to ensure the obtained results are stable.

A Testbed Platform to Support an IoT City Lab

This paper describes the development activity that has been carried out for a living laboratory for the city of Cagliari aimed at functioning as a learning center for local SMEs willing to improve their skills in IoT and create applications that will be integrated in an open innovation ecosystem. The many users belonging to the various SMEs involved in the project required an ICT laboratory with a platform that could manage them and provide a multi-tenant environment for the development of IoT applications. The architecture also had to be scalable and interoperable, and the resulting platform had to collect many kinds of data from sensors or other data sources, elaborate them, and show georeferenced information on a 3D satellite interactive view along with statistics on side panels. This work was based on a platform already developed by CRS4 for a previous project. Preserving the concept of the decision-making tool for Smart Cities, almost every component was redesigned, and, in this paper, we describe the new solutions that have been implemented. Starting from the former structure, further features were added in a novel way in order to offer an enhanced framework that can deal with the activities of the laboratory, exploiting the scalability of the open-source systems involved, their robustness and flexibility, and leveraging domain standards. In this article, the main challenges involved in the development of the platform are described, as well as the solutions that have been implemented so far.

Fourier transform-based method for quantifying the three-dimensional orientation distribution of fibrous units

Several materials and tissues are characterized by a microstructure composed of fibrous units embedded in a ground matrix. In this paper, a novel three-dimensional (3D) Fourier transform-based method for quantifying the distribution of fiber orientations is presented. The method allows for an accurate identification of individual fiber families, their in-plane and out-of-plane dispersion, and showed fast computation times. We validated the method using artificially generated 3D images, in terms of fiber dispersion by considering the error between the standard deviation of the reconstructed and the prescribed distributions of the artificial fibers. In addition, we considered the measured mean orientation angles of the fibers and validated the robustness using a measure of fiber density. Finally, the method is employed to reconstruct a full 3D view of the distribution of collagen fiber orientations based on in vitro second harmonic generation microscopy of collagen fibers in human and mouse skin. The dispersion parameters of the reconstructed fiber network can be used to inform mechanical models of soft fiber-reinforced materials and biological tissues that account for non-symmetrical fiber dispersion.

Sample Size and Geometric Morphometrics Methodology Impact the Evaluation of Morphological Variation.

Geometric morphometrics has had a profound impact on our understanding of morphological evolution. However, factors such as sample size and the views and elements selected for two-dimensional geometric morphometric (2DGM) analyses, which are often dictated by specimen availability and time rather than study design, may affect the outcomes of those analyses. Leveraging large intraspecific sample sizes (n>70) for two bat species, Lasiurus borealis and Nycticeius humeralis, we evaluate the impact of sample size on calculations of mean shape, shape variance, and centroid size. Additionally, we assessed the concordance of multiple skull 2D views with one another and characterized morphological variation in skull shape in L. borealis and N. humeralis, as well as a closely related species, Lasiurus seminolus. Given that L. seminolus is a morphologically cryptic species with L. borealis, we assessed whether differences in skull shape and in 2DGM approach would allow species discrimination. We found that reducing sample size impacted mean shape and increased shape variance, that shape differences were not consistent across views or skull elements, and that trends shown by the views and elements were not all strongly associated with one another. Further, we found that L. borealis and L. seminolus were statistically different in shape using 2DGM in all views and elements. These results underscore the importance of selecting appropriate sample sizes, 2D views, and elements based on the hypothesis being tested. While there is likely not a generalizable sample size or 2D view that can be employed given the wide variety of research questions and systems evaluated using 2DGM, a generalizable solution to issues with 2DGM presented here is to run preliminary analyses using multiple views, elements, and sample sizes, thus ensuring robust conclusions.

Retrieval-Specific View Learning for Sketch-to-Shape Retrieval

Sketch-based 3D shape retrieval (SBSR) can be approached by learning domain-invariant descriptors or ranking metrics from sketches and 2D view images of 3D shapes rendered through numerous viewpoints. However, determining the most appropriate viewpoints that convey discriminative geometric features to benefit the task of SBSR became an essential yet not fully explored area. Existing works extract 3D features from multi-view images observed through pre-defined viewpoints to match 2D sketches. Those methods, however, fail to dynamically select viewpoints by considering the SBSR task. In this work, we introduce a fully differentiable viewpoint learning paradigm driven by the downstream SBSR task, which supports the task-aware and sketch-dependent dynamic viewpoint determination process. We naturally integrate this task-specific and sketch-dependent viewpoint learning process into a meta-learning framework to develop a novel Dynamic Viewer (DV) module for SBSR. DV module comprises a Meta View Learner (MVL) block and a View Generator (VG) block. Specifically, as the first part of the DV module, the MVL block learns to initiate the necessary network parameters of the VG block. Then, the VG block that serves as the second part learns the best viewpoints to render 2D images. To learn the optimal viewpoints for SBSR, we further introduce a view mining loss that aims to maximize the similarity of feature-level information among rendered 2D views and the query sketch. Further, we adopt a variational autoencoder (VAE) to retrieve 3D shapes by setting the newly rendered images and query sketch as inputs. As evidenced by the comprehensive experimental results conducted on popular SBSR datasets, the proposed framework has been demonstrated to outperform recent methods in both category-level sketch-based and fine-grained SBSR.

RecHap: An Interactive Recommender System for Navigating a Large Number of Mid-Air Haptic Designs.

Designing haptics is a difficult task especially when the user attempts to design a sensation from scratch. In the fields of visual and audio design, designers often use a large library of examples for inspiration, supported by intelligent systems like recommender systems. In this work, we contribute a corpus of 10 000 mid-air haptic designs (500 hand-designed sensations augmented 20x to create 10 000), and we use it to investigate a novel method for both novice and experienced hapticians to use these examples in mid-air haptic design. The RecHap design tool uses a neural-network based recommendation system that suggests pre-existing examples by sampling various regions of an encoded latent space. The tool also provides a graphical user interface for designers to visualize the sensation in 3D view, select previous designs, and bookmark favourites, all while feeling designs in real-time. We conducted a user study with 12 participants suggesting that the tool enables people to quickly explore design ideas and experience them immediately. The design suggestions encouraged collaboration, expression, exploration, and enjoyment, which improved creativity support.

LoopGrafter: Visual Support for the Grafting Workflow of Protein Loops.

In the process of understanding and redesigning the function of proteins in modern biochemistry, protein engineers are increasingly focusing on the exploration of regions in proteins called loops. Analyzing various characteristics of these regions helps the experts to design the transfer of the desired function from one protein to another. This process is denoted as loop grafting. As this process requires extensive manual treatment and currently there is no proper visual support for it, we designed LoopGrafter: a web-based tool that provides experts with visual support through all the loop grafting pipeline steps. The tool is logically divided into several phases, starting with the definition of two input proteins and ending with a set of grafted proteins. Each phase is supported by a specific set of abstracted 2D visual representations of loaded proteins and their loops that are interactively linked with the 3D view onto proteins. By sequentially passing through the individual phases, the user is shaping the list of loops that are potential candidates for loop grafting. In the end, the actual in-silico insertion of the loop candidates from one protein to the other is performed and the results are visually presented to the user. In this way, the fully computational rational design of proteins and their loops results in newly designed protein structures that can be further assembled and tested through in-vitro experiments. LoopGrafter was designed in tight collaboration with protein engineers, and its final appearance reflects many testing iterations. We showcase the contribution of LoopGrafter on a real case scenario and provide the readers with the experts' feedback, confirming the usefulness of our tool.

Semi-automatic A.I.-Specified Stereographic Scene Rendering Techniques Across Various Displays

Semi-automatic, A.I.-specified stereographic scene processing is achieved by extending Blender with ChatGPT. We can generate objects and set scenes in Blender semi-automatically by invoking appropriate text prompts. Stereography techniques include anaglyphy, chromastereoscopy, and side-by-side display using binocular viewing. One can create a similar scene by copying and pasting the prompt used. It cannot always work identically, but it behaves roughly the same. First, we established Skybox and added scene Objects (Camera, Cube, etc.) in 3D view, materials, and animation with prompt. Stereographic images are created semiautomatically and compared across some qualities. The goal of this research is to validate those various stereographic techniques as rendered automatically in Blender.

Endoscopic Vitrectomy Combined with 3D Heads-Up Viewing System in Treating Traumatic Ocular Injury.

To investigate effects and complications of endoscopic vitrectomy combined with 3D heads-up viewing system in treating traumatic ocular injury. Patients and Methods. This is a retrospective interventional case series in a tertiary referral center in Taiwan, and we included patients of traumatic ocular injury, and they underwent endoscopic vitrectomy combined with a 3D heads-up viewing system. Fourteen eyes of traumatic globe injury from 14 patients were studied over a 30-month period. Preoperative VA ranged from no light perception (NLP) to 6/6. Postoperative visual acuity improved in 11 of the 14 eyes (79%). Until 6 months after surgery, all eyes had attached retina. The median logMAR BCVA was 2.4 at the first visit and 1.19 at the last visit (p = 0.0028). No subject suffered from retinal detachment, endophthalmitis, or other severe complications. Vitrectomy using endoscopy combined with 3D heads-up viewing system allowed early evaluation and intervention in traumatic ocular injuries. Most of our cases showed both anatomical and visual acuity improvements.

SLS4D: Sparse Latent Space for 4D Novel View Synthesis.

Neural radiance fields (NeRF) have achieved great success in novel view synthesis and 3D representation for static scenarios. Existing dynamic NeRFs usually exploit a locally dense grid to fit the deformation fields; however, they fail to capture the global dynamics and concomitantly yield models of heavy parameters. We observe that the 4D space is inherently sparse. Firstly, the deformation fields are sparse in spatial but dense in temporal due to the continuity of motion. Secondly, the radiance fields are only valid on the surface of the underlying scene, usually occupying a small fraction of the whole space. We thus represent the 4D scene using a learnable sparse latent space, a.k.a. SLS4D. Specifically, SLS4D first uses dense learnable time slot features to depict the temporal space, from which the deformation fields are fitted with linear multi-layer perceptions (MLP) to predict the displacement of a 3D position at any time. It then learns the spatial features of a 3D position using another sparse latent space. This is achieved by learning the adaptive weights of each latent feature with the attention mechanism. Extensive experiments demonstrate the effectiveness of our SLS4D: It achieves the best 4D novel view synthesis using only about 6% parameters of the most recent work.

Learning Virtual View Selection for 3D Scene Semantic Segmentation.

2D-3D joint learning is essential and effective for fundamental 3D vision tasks, such as 3D semantic segmentation, due to the complementary information these two visual modalities contain. Most current 3D scene semantic segmentation methods process 2D images "as they are", i.e., only real captured 2D images are used. However, such captured 2D images may be redundant, with abundant occlusion and/or limited field of view (FoV), leading to poor performance for the current methods involving 2D inputs. In this paper, we propose a general learning framework for joint 2D-3D scene understanding by selecting informative virtual 2D views of the underlying 3D scene. We then feed both the 3D geometry and the generated virtual 2D views into any joint 2D-3D-input or pure 3D-input based deep neural models for improving 3D scene understanding. Specifically, we generate virtual 2D views based on an information score map learned from the current 3D scene semantic segmentation results. To achieve this, we formalize the learning of the information score map as a deep reinforcement learning process, which rewards good predictions using a deep neural network. To obtain a compact set of virtual 2D views that jointly cover informative surfaces of the 3D scene as much as possible, we further propose an efficient greedy virtual view coverage strategy in the normal-sensitive 6D space, including 3-dimensional point coordinates and 3-dimensional normal. We have validated our proposed framework for various joint 2D-3D-input or pure 3D-input based deep neural models on two real-world 3D scene datasets, i.e., ScanNet v2 and S3DIS, and the results demonstrate that our method obtains a consistent gain over baseline models and achieves new top accuracy for joint 2D and 3D scene semantic segmentation. Code is available at https://github.com/smy-THU/VirtualViewSelection.

A comprehensive performance evaluation of bifacial photovoltaic modules: insights from a year-long experimental study conducted in the Canadian climate

Bifacial photovoltaic (PV) modules, capable of capturing solar energy from both sides of the cells, are becoming increasingly popular as their manufacturing costs approach those of traditional monofacial modules. Accurate estimation of their power generation capacity is essential for optimizing their use. This study evaluates a power production model for bifacial PV modules using local irradiance data from Razon+ in Sherbrooke, Canada, and Solcast irradiance data derived from satellite imagery and weather models. The model's performance was assessed throughout the year, with particular attention to the impact of snow coverage during winter. To address computational efficiency, the study evaluated ray tracing and a 2D view factor model, selecting the more time-efficient method. Experimental validation showed that, using local irradiance data, the model achieved Normalized Root Mean Square Errors (NRMSE) of 18.77%, 4.94%, 3.93%, and 6.22% for winter, spring, summer, and fall, respectively. With Solcast data, the NRMSEs were 22.76%, 15.32%, 14.72%, and 17.78% for the corresponding seasons. While the model performed satisfactorily in spring, summer, and fall, it was less accurate in winter. To enhance winter accuracy, the model incorporated snow coverage, using snow depth as a metric to detect snow on the front surface. This adjustment improved the accuracy by 51.1%.

Visual Support for the Loop Grafting Workflow on Proteins.

In understanding and redesigning the function of proteins in modern biochemistry, protein engineers are increasingly focusing on exploring regions in proteins called loops. Analyzing various characteristics of these regions helps the experts design the transfer of the desired function from one protein to another. This process is denoted as loop grafting. We designed a set of interactive visualizations that provide experts with visual support through all the loop grafting pipeline steps. The workflow is divided into several phases, reflecting the steps of the pipeline. Each phase is supported by a specific set of abstracted 2D visual representations of proteins and their loops that are interactively linked with the 3D View of proteins. By sequentially passing through the individual phases, the user shapes the list of loops that are potential candidates for loop grafting. Finally, the actual in-silico insertion of the loop candidates from one protein to the other is performed, and the results are visually presented to the user. In this way, the fully computational rational design of proteins and their loops results in newly designed protein structures that can be further assembled and tested through in-vitro experiments. We showcase the contribution of our visual support design on a real case scenario changing the enantiomer selectivity of the engineered enzyme. Moreover, we provide the readers with the experts' feedback.

Paper] Construction of 3D Image and Visibility Improvement of 2D Image Outside 3D Viewing Zone by Edge-Based Depth-Fused 3D Display Using Aerial Image and Rear Display

Paper] Construction of 3D Image and Visibility Improvement of 2D Image Outside 3D Viewing Zone by Edge-Based Depth-Fused 3D Display Using Aerial Image and Rear Display

Unveiling the 3D structure of nova shells with MUSE: The case of RR Pic

Context. Nova eruptions occur in cataclysmic variables when enough material has been accreted onto the surface of the white dwarf primary. As a consequence, the material that has been accumulated until then is expelled into the interstellar medium, forming an expanding nova shell around the system. Understanding the physical process that shapes the morphology of nova shells is essential to fully comprehend how the ejection mechanism operates during nova eruptions. Because of its closeness and age, the nova shell around the classical nova RR Pic (Nova Pic 1925) is an ideal target for studying the evolving morphology of nova shells. Aims. The use of integral field spectroscopy (IFS) is a technique that has received little attention in the study of nova shells, despite the advantages in using it when studying the morphology and kinematics of nova shells. In this work, we present an IFS study of the RR Pic nova shell, with a particular emphasis on the extraction of the 3D morphology of the shell. Methods. The nova shell was observed by the Multi-Unit Spectroscopic Explorer (MUSE) instrument placed at the ESO-VLT. By measuring the extension of the nova shell in these new observations, and comparing it against previous measurements, we were able to determine the expansion history of the ejected material. We used this information, together with the distance to the system based on Gaia EDR3 parallaxes, and the systemic velocity of the system reported in the literature to obtain the physical 3D view of the shell. Results. The MUSE datacube confirms the presence of the nova shell in Hα, Hβ and [OIII], and very faintly in [NII]. A comparison with previous observations suggests that the shell continues in its free-expansion phase but with the different parts of the shell apparently expanding at different rates. The data analysis corroborates the previous vision that the shell is composed of an equatorial ring and polar filaments traced by Hα. At the same time, the new data also reveal that [OIII] is confined in gaps located in the tropical regions of the shell where no Hydrogen is observed. The flux measurements indicate that ~99% of the shell flux is confined to the equatorial ring, while the polar filaments show a flux asymmetry between the NE and SW filaments, with the latter being ~2.5 times brighter. We have estimated the mass of the shell to be ~5 × 10−5 M⊙. From the analysis of the 3D-extracted data, we determine that the ring structure extends ~8000 au from the central binary, and has a position angle of ~155 deg and an inclination of ~74 deg. The analysis of the equatorial ring reveals it is composed of a main ring and several small clouds, extending up to a height of ~4000 au above and below the main plane of the equatorial ring. The radial profile of the whole ring structure is reminiscent of a bow shock. Conclusions. Our data have proven the capabilities of observing nova shells using IFS, and how the nova shell around RR Pic is an interesting object of study. Further and continuous observations of the shell across the electromagnetic spectrum are required to confirm the results and ideas presented in this work.

DeepMesh: Differentiable Iso-Surface Extraction.

Geometric Deep Learning has recently made striking progress with the advent of continuous deep implicit fields. They allow for detailed modeling of watertight surfaces of arbitrary topology while not relying on a 3D euclidean grid, resulting in a learnable parameterization that is unlimited in resolution. Unfortunately, these methods are often unsuitable for applications that require an explicit mesh-based surface representation because converting an implicit field to such a representation relies on the Marching Cubes algorithm, which cannot be differentiated with respect to the underlying implicit field. In this work, we remove this limitation and introduce a differentiable way to produce explicit surface mesh representations from Deep Implicit Fields. Our key insight is that by reasoning on how implicit field perturbations impact local surface geometry, one can ultimately differentiate the 3D location of surface samples with respect to the underlying deep implicit field. We exploit this to define DeepMesh - an end-to-end differentiable mesh representation that can vary its topology. We validate our theoretical insight through several applications: Single view 3D Reconstruction via Differentiable Rendering, Physically-Driven Shape Optimization, Full Scene 3D Reconstruction from Scans and End-to-End Training. In all cases our end-to-end differentiable parameterization gives us an edge over state-of-the-art algorithms.

Development of Hand Gesture Command Using Leap Motion for Floorplanner Application

Architecture is part of the art of life and works best when it seems to give expression to the life that inhabits it. As technology has developed a lot, the field of architecture has also experienced many developments supported by technology such as making architectural designs. The development experienced in making architectural designs is that it is no longer required to draw design choices with side views on a lot of paper but instead use a simulation application for making architectural designs that are displayed through a monitor layer in 3D so that they can see more realistically. After many innovations emerged regarding simulation applications which generally still use hardware such as a mouse, then these innovations shifted to connecting the simulation application with the virtual world where hardware such as a mouse has been replaced by using gestures or limb movements such as parts of the hand or other parts of the body. While other fields like medic already use virtual tool interaction, architecture fields still just use mouse and keyboard. One of the virtual interaction devices used to be able to detect fingers and palms to interact with 3D simulation applications is Leap Motion. Leap Motion is starting to be widely used to carry out various ways of interacting with hands because it is more interactive and interesting to use even many people think that it can be used for hand rehabilitation or therapy too. However, even though many innovations have developed, there is still no innovation in the use of a hand gesture command system using Leap Motion for simulation applications to design architectural designs in 3D views. Based on these things, the authors designed and developed hand gesture commands using Leap Motion for Architectural Design App. The hand gesture command system used for the Floorplanner simulation application will be tested using a system usability scale by users with architectural, informatics, and unfamiliar backgrounds. Based on the tests carried out, it can be seen that the system is running properly even though it requires getting used to the device first and getting a score from the System Usability Scale of 59,167 out of scale from 0 to 100 which means it is still accepted by users or declared as "Marginally Acceptable" category.

Characterizing cardiac contractile motion for noninvasive radioablation of ventricular tachycardia

BackgroundRespiratory motion management strategies are used to minimize the effects of breathing on the precision of stereotactic ablative radiotherapy for ventricular tachycardia, but the extent of cardiac contractile motion of the human heart has not been systematically explored. ObjectiveWe aim to assess the magnitude of cardiac contractile motion between different directions and locations in the heart. MethodsPatients with intracardiac leads or valves who underwent 4D cardiac computed tomography (4DCT) prior to a catheter ablation procedure for atrial or ventricular arrhythmias at 2 medical centers were studied retrospectively. The displacement of transvenous right atrial appendage (RA), right ventricle (RV) ICD, coronary sinus (CS) lead tips and prosthetic cardiac devices across the cardiac cycle were measured in orthogonal 3D views on a maximal-intensity projection CT reconstruction. ResultsA total of 31 pre-ablation cardiac 4DCTs were analyzed. The LV lead tip had significantly greater motion compared to the RV lead in the anterior-posterior direction (6.0±2.2mm vs 3.8±1.7mm; p=0.01) and superior-inferior direction (4.4±2.9mm vs 3.5±2.0mm; p=0.049). The prosthetic aortic valves had the least movement of all fiducials, specifically compared to the RV lead tip in the left-right direction (3.2±1.2mm vs 6.1±3.8mm, p=0.04) and the LV lead tip in the antero-posterior direction (3.8±1.7mm vs 6.0±2.2mm, p=0.03). ConclusionThe degree of cardiac contractile motion varies significantly (1mm to 15.2 mm) across different locations in the heart. The effect of contractile motion on the precision of radiotherapy should be assessed on a patient-specific basis.

Distribution Patterns and Genesis of Geological Fractures/Microfaults in the Qiongdongnan Basin, North of the South China Sea

The Qiongdongnan Basin (QDNB), located in the north of the South China Sea, is a Cenozoic rift basin with abundant oil and gas resources. Large flake hydrates have been found in the core fractures of Quaternary formations in the deep-water depression of the QDNB. In order to understand the spatial distribution patterns of these fractures, their geneses in sedimentary basins, and their influences on gas migration and accumulation, such fractures have been observed using high-resolution 3D seismic images and visualization techniques. Four types of fractures and their combinations have been identified, namely bed-bounded fractures/microfaults, unbounded fractures, fracture bunches, and fracture clusters. Bed-bounded fractures/microfaults are mainly short and possess high density; they have developed in mass transport depositions (MTDs) or Meishan and Sanya Formations. The unbounded fractures/microfaults that occur in Miocene–Pliocene formations are mainly long and discrete, and are dominantly caused by strong tectonic movements, the concentration of stress, and sustained intense overpressure. The fracture bunches and fracture clusters that occur in Oligocene–Early Miocene formations have commonly developed with the accumulation of large numbers of fractures and may be related to the release of pressure, diapirs, and basement fault blocks (228.9 ± 1 Ma). In this study, six fluid charging or leakage models are proposed based on distinct fracture types, assuming the uniform conductivity of each fracture. In a 3D space view, a vertical decrease in the fracture scale (number or density) will more likely result in gas supply than dispersion, thus promoting the accumulation of gas in the reservoirs. Nevertheless, the fractures above the Bottom Simulating Reflect (BSR)/seismic anomaly are excessively developed, and bed-bounded fractures within a particular layer, such as MTDs, can easily cause seabed leakage. These results are useful for explaining the vertical migration of gas/fluids in areas and formations with less developed gas chimneys, faults, diapirs, and other structures, particularly in post-rifting basins.