Research status and application of artificial intelligence large models in the oil and gas industry

This article elucidates the concept of large model technology,summarizes the research status of large model technology both domestically and internationally,provides an overview of the application status of large models in vertical industries,outlines the challenges and issues confronted in applying large models in the oil and gas sector,and offers prospects for the application of large models in the oil and gas industry.The existing large models can be briefly divided into three categories:large language models,visual large models,and multimodal large models.The application of large models in the oil and gas industry is still in its infancy.Based on open-source large language models,some oil and gas enterprises have released large language model products using methods like fine-tuning and retrieval augmented generation.Scholars have attempted to develop scenario-specific models for oil and gas operations by using visual/multimodal foundation models.A few researchers have constructed pre-trained foundation models for seismic data processing and interpretation,as well as core analysis.The application of large models in the oil and gas industry faces challenges such as current data quantity and quality being difficult to support the training of large models,high research and development costs,and poor algorithm autonomy and control.The application of large models should be guided by the needs of oil and gas business,taking the application of large models as an opportunity to improve data lifecycle management,enhance data governance capabilities,promote the construction of computing power,strengthen the construction of“artificial intelligence+energy”composite teams,and boost the autonomy and control of large model technology.

Experimental investigation on migration and retention mechanisms of elastic gel particles(EGPs)in pore-throats using multidimensional visualized models

Knowledge of migration and retention mechanisms of elastic gel particles(EGPs)in pore-throats is essential for the effective application of EGPs as a smart sweep improvement and profile control agent for enhanced oil recovery(EOR).The matching coefficient(defined as the ratio of particle size to pore-throat size)is used to investigate its influence on migration,retention and profile control performance of EGPs.A 1-D continuous pore-throat visualization model(PTVM),a 2-D heterogeneous PTVM and a 3-D heterogeneous core model were constructed and used to investigate pore-scale migration,retention and controlling mechanism of migration and retention characteristics on EGPs profile control.The results of the 1-D continuous PTVM indicated that while the matching coefficient was in the optimal range(i.e.,0.20-0.32),the EGPs could not only smoothly migrate to the deeper pore-throats,but also form stable retention in the pores to resist the erosion of injected water,which was conducive to the effective indepth profile control.The results of the 2-D heterogeneous PTVM verified that the sweep efficiency in low-permeability regions could be significantly improved by in-depth migration and stable retention of EGPs in the pore-throats with an optimal matching coefficient(0.29),which was much better than that in cases with a smaller matching coefficient(0.17)or an excessive matching coefficient(0.39).Moreover,the NMR displacement experiments of 3-D heterogeneous cores were carried out to simulate the EGPs profile control in actual reservoir porous media.Saturation images and T2 spectrum curves of crude oil showed that EOR in the low-permeability layer was highest(56.1%)using EGPs profile control with an optimal matching coefficient,attributing to the in-depth migration and stable retention of EGPs.

Chromatic and achromatic differences of melanin-and carotenoid-based plumage coloration in five minivet species(Pericrocotus spp.)under conspecific and predator visual systems

Adaptive mate choice has been accepted as the leading theory to explain the colorful plumage of birds.This theory hypothesizes that conspicuous colors act as signals to advertise the qualities of the owners.However,a dilemma arises in that conspicuous colors may not only attract mates,but also alert predators.The"private channels of communication"hypothesis proposes that some intraspecific signals may not be visible to heterospecific animals because of different visual systems.To better understand the evolution of plumage colors and sexual selection in birds,here we studied the chromatic difference and achromatic differences of melanin-and carotenoid-based plumage coloration in five minivet species(Pericrocotus spp.)under conspecific and predator visual systems.We found that either the chromatic or achromatic difference among male or female minivets’plumage was consistently higher under conspecific vision than under predator vision for all five studied species of minivets.This result indicated that individual differences in plumage colors of minivets were visible to the conspecific receivers and hidden from potential predators as a result of evolution under predation risk and conspecific communication.However,males were under a higher risk of predation because they were more conspicuous than females to the vision of a nocturnal predator.

Visual modeling reveals cryptic aspect in egg mimicry of Himalayan Cuckoo(Cuculus saturatus) on its host Blyth's Leaf Warbler(Phylloscopus reguloides)

Brood parasitism and egg mimicry of Himalayan Cuckoo（Cuculus saturatus） on its host Blyth＇s Leaf Warbler（Phylloscopus reguloides） were studied in south-western China from April to July 2009.The cuckoo laid a white egg with fine brown markings on the blunt end.The eggs were conspicuously bigger than the host＇s own,with 2.06 g in mass and 1.91 cm3 in volume.Visual modeling showed that the cuckoo eggs,which from the human eye appeared to mimic the host eggs to a great extent,were completely different from the host eggs in both hue and chroma.The characters of the Himalayan Cuckoo nestling,reported for the first time,included two triangular and black patches on its gape,which appeared from four days old and became darker with age and growth.While this character also exists in nestlings of Oriental Cuckoo（C.optatus）,it has not been found for other Cuculus species.Our results reveal cryptic aspects in the cuckoo-host egg color matching,which are not visible to the naked human eye,and indicate that high mimetic cuckoo eggs rejected by hosts,as determined by human observers in previous studies,might not be mimetic as birds see them.

Foundation models meet visualizations: Challenges and opportunities

Recent studies have indicated that foundation models, such as BERT and GPT, excel atadapting to various downstream tasks. This adaptability has made them a dominant force in buildingartificial intelligence (AI) systems. Moreover, a newresearch paradigm has emerged as visualizationtechniques are incorporated into these models. Thisstudy divides these intersections into two researchareas: visualization for foundation model (VIS4FM)and foundation model for visualization (FM4VIS).In terms of VIS4FM, we explore the primary roleof visualizations in understanding, refining, and evaluating these intricate foundation models. VIS4FMaddresses the pressing need for transparency, explainability, fairness, and robustness. Conversely, in termsof FM4VIS, we highlight how foundation models canbe used to advance the visualization field itself. Theintersection of foundation models with visualizations ispromising but also introduces a set of challenges. Byhighlighting these challenges and promising opportunities, this study aims to provide a starting point forthe continued exploration of this research avenue.

A ROBUST ADAPTIVE VIDEO ENCODER BASED ON HUMAN VISUAL MODEL

A Robust Adaptive Video Encoder (RAVE) based on human visual model is proposed. The encoder combines the best features of Fine Granularity Scalable (FGS) coding, framedropping coding, video redundancy coding, and human visual model. According to packet loss and available bandwidth of the network, the encoder adjust the output bit rate by jointly adapting quantization step-size instructed by human visual model, rate shaping, and periodically inserting key frame. The proposed encoder is implemented based on MPEG-4 encoder and is compared with the case of a conventional FGS algorithm. It is shown that RAVE is a very efficient robust video encoder that provides improved visual quality for the receiver and consumes equal or less network resource. Results are confirmed by subjective tests and simulation tests.

Vehicle Detection Based on Visual Saliency and Deep Sparse Convolution Hierarchical Model

Traditional vehicle detection algorithms use traverse search based vehicle candidate generation and hand crafted based classifier training for vehicle candidate verification.These types of methods generally have high processing times and low vehicle detection performance.To address this issue,a visual saliency and deep sparse convolution hierarchical model based vehicle detection algorithm is proposed.A visual saliency calculation is firstly used to generate a small vehicle candidate area.The vehicle candidate sub images are then loaded into a sparse deep convolution hierarchical model with an SVM-based classifier to perform the final detection.The experimental results demonstrate that the proposed method is with 94.81% correct rate and 0.78% false detection rate on the existing datasets and the real road pictures captured by our group,which outperforms the existing state-of-the-art algorithms.More importantly,high discriminative multi-scale features are generated by deep sparse convolution network which has broad application prospects in target recognition in the field of intelligent vehicle.

Dynamic Visual Image Modeling Based on Mobile RobotSelf- Organizing Network in Internetof Things Perception Layer

The dynamic multichannel binocular visual image modeling is studied based on Internet of Things (IoT) Perception Layer, using mobile robot self-organizing network. By employing multigroup mobile robots with binocular visual system, the real visual images of the object will be obtained. Then through the mobile self-organizing network, a three-dimensional model is rebuilt by synthesizing the returned images. On this basis, we formalize a novel algorithm for multichannel binocular visual three-dimensional images based on fast three-dimensional modeling. Compared with the method based on single binocular visual system, the new algorithm can improve the Integrity and accuracy of the dynamic three-dimensional object modeling. The simulation results show that the new method can effectively accelerate the modeling speed, improve the similarity and not increase the data size.

Vehicle Real-time Location Based on Visual Perception Model

Vehicle recognition system (VRS) plays a very important role in the field of intelligent transportation systems.A novel and intuitive method is proposed for vehicle location.The method we provide for vehicle location is based on human visual perception model technique. The perception color space HSI in this algorithm is adopted.Three color components of a color image and more potential edge patterns are integrated for solving the feature extraction problem.A fast and automatic threshold technique based on human visual perception model is also developed.The vertical edge projection and horizontal edge projection are adopted for locating left-right boundary of vehicle and top-bottom boundary of vehicle, respectively. Very promising experimental results are obtained using real-time vehicle image sequences, which have confirmed that this proposed location vehicle method is efficient and reliable, and its calculation speed meets the needs of the VRS.

Modeling Tracer Flow Characteristics in Different Types of Pores: Visualization and Mathematical Modeling

Structure of porous media and fluid distribution in rocks can significantly affect the transport characteristics during the process of microscale tracer flow.To clarify the effect of micro heterogeneity on aqueous tracer transport,this paper demonstrates microscopic experiments at pore level and proposes an improved mathematical model for tracer transport.The visualization results show a faster tracer movement into movable water than it into bound water,and quicker occupancy in flowing pores than in storage pores caused by the difference of tracer velocity.Moreover,the proposed mathematical model includes the effects of bound water and flowing porosity by applying interstitial flow velocity expression.The new model also distinguishes flowing and storage pores,accounting for different tracer transport mechanisms(dispersion,diffusion and adsorption)in different types of pores.The resulting analytical solution better matches with tracer production data than the standard model.The residual sum of squares(RSS)from the new model is 0.0005,which is 100 times smaller than the RSS from the standard model.The sensitivity analysis indicates that the dispersion coefficient and flowing porosity shows a negative correlation with the tracer breakthrough time and the increasing slope,whereas the superficial velocity and bound water saturation show a positive correlation.

INDUSTRIAL ENGINEERING AND VISUALISATION—A PRODUCT DEVELOPMENT PERSPECTIVE

Taking the actual project of teaching and researching process for example, the relationship between the industrial engineering and product development is discussed. And use the novel visualization technology to support the industrial engineering and product development. How to use the new computer modeling and simulating technologies to support the product development and industrial engineering, is introduced especially. The support includes both domestic products and industrial systems. The visualization and computer technologies take a very impo[tant role in some system or multi-direction modeling, those technologies mentioned above can help the industrial engineers study the effect of design on the whole life circle, including the producing steps. So the engineers can avoid making the wrong decision which may cause bad effects on the whole industrial engineering.

Application of Three-Dimensional Visual Simulation in Tidal Defense Engineering

Any tidal defense engineering involves the collection and analysis of massive information about engineering structures and their surrounding environment. Traditional method, which is carried out mainly by means of twodimensional drawings and textures, is not efficient and intuitive enough to analyze the whole project and reflect its spatial relationship. Three-dimensional visual simulation provides an advanced technical means of solving this problem. In this paper, triangular irregular network (TIN) model simplified by non-uniform rational B-splines (NURBS) technique was used to establish the digital terrain model (DTM) of a super large region. Simulation of dynamic water surface was realized by combining noise function with sine wave superposition method. Models of different objects were established with different modeling techniques according to their characteristics. Application of texture mapping technology remarkably improved the authenticity of the models. Taking the tidal defense engineering in the new coastal region of Tianjin as a case study, three-dimensional visual simulation and dynamic roaming of the study area were realized, providing visual analysis and visible demonstration method for the management and emergency decision-making associated with construction.

Traffic danger detection by visual attention model of sparse sampling

A method to detect traffic dangers based on visual attention model of sparse sampling was proposed. The hemispherical sparse sampling model was used to decrease the amount of calculation which increases the detection speed. Bayesian probability model and Gaussian kernel function were applied to calculate the saliency of traffic videos. The method of multiscale saliency was used and the final saliency was the average of all scales, which increased the detection rates extraordinarily. The detection results of several typical traffic dangers show that the proposed method has higher detection rates and speed, which meets the requirement of real-time detection of traffic dangers.

Optimized Modeling Method for Unbalanced Data in High-Level Visual Semantic Concept Classification

To solve the unbalanced data problems of learning models for semantic concepts, an optimized modeling method based on the posterior probability support vector machine （PPSVM） is presented. A neighborbased posterior probability estimator for visual concepts is provided. The proposed method has been applied in a high-level visual semantic concept classification system and the experiment results show that it results in enhanced performance over the baseline SVM models, as well as in improved robustness with respect to high-level visual semantic concept classification.

Effective Video Summarization Approach Based on Visual Attention

Video summarization is applied to reduce redundancy and developa concise representation of key frames in the video, more recently, video summaries have been used through visual attention modeling. In these schemes,the frames that stand out visually are extracted as key frames based on humanattention modeling theories. The schemes for modeling visual attention haveproven to be effective for video summaries. Nevertheless, the high cost ofcomputing in such techniques restricts their usability in everyday situations.In this context, we propose a method based on KFE (key frame extraction)technique, which is recommended based on an efficient and accurate visualattention model. The calculation effort is minimized by utilizing dynamicvisual highlighting based on the temporal gradient instead of the traditionaloptical flow techniques. In addition, an efficient technique using a discretecosine transformation is utilized for the static visual salience. The dynamic andstatic visual attention metrics are merged by means of a non-linear weightedfusion technique. Results of the system are compared with some existing stateof-the-art techniques for the betterment of accuracy. The experimental resultsof our proposed model indicate the efficiency and high standard in terms ofthe key frames extraction as output.

Natural Scene Classification Inspired by Visual Perception and Cognition Mechanisms

The process of human natural scene categorization consists of two correlated stages: visual perception and visual cognition of natural scenes.Inspired by this fact,we propose a biologically plausible approach for natural scene image classification.This approach consists of one visual perception model and two visual cognition models.The visual perception model,composed of two steps,is used to extract discriminative features from natural scene images.In the first step,we mimic the oriented and bandpass properties of human primary visual cortex by a special complex wavelets transform,which can decompose a natural scene image into a series of 2D spatial structure signals.In the second step,a hybrid statistical feature extraction method is used to generate gist features from those 2D spatial structure signals.Then we design a cognitive feedback model to realize adaptive optimization for the visual perception model.At last,we build a multiple semantics based cognition model to imitate human cognitive mode in rapid natural scene categorization.Experiments on natural scene datasets show that the proposed method achieves high efficiency and accuracy for natural scene classification.

The establishment of 3D visualization modeling for the jointed slope

The 3D visualization model of slop with structural plane can displayed the characters of structural plane in slop directly, and illustrated the spatial combination. It is a modem and critical question in the field of geotechnical engineering. Based on the peculiarity of the reconnaissance and the research of the visualization by formers, systemized the method fit for building 3D visualization model of slop with structural plane. Write the special program with Visual C^-＋ computer language and illustrated it by OpenGL, the program can displayed and captured the random section plane. The program has a satisfied result by proving with the real projects.

From neurogenesis to neuronal regeneration: the amphibian olfactory system as a model to visualize neuronal development in vivo

How do individual neurons develop and how are they in- tegrated into neuronal circuitry？ To answer this question is essential to understand how the nervous system develops and how it is maintained during the adult life. A neural stem cell must go through several stages of maturation, including proliferation, migration, differentiation, and integration, to become fully embedded to an existing neuronal circuit. The knowledge on this topic so far has come mainly from cell culture studies. Studying the development of individual neurons within intact neuronal networks in vivo is inherently difficult. Most neurons are generated form neural stem cells during embryonic and early postnatal development.

A bibliometric analysis of research on nursing models in countries other than China

Objectives＂ To deepen our understanding of the status quo and to identify the hot topics and develop- mental trends of research on nursing models in countries other than China in the most recent decade. Methods： The study subjects were the publications retrieved from the PubMed database using the MeSH terms of ＂Models, Nursing＂. Bibliographic item co-occurrence mining system （BICOMS） software was used for conventional bibliometric analysis of publications during two time periods, 2005-2009 and 2010-2014. The number of published journal articles, journal distribution, authors of publications, country of origin of journals, and language of publications were analyzed to establish a high-frequency keyword profile and co-occurrence matrix. Graphical clustering toolkit （gCLUTO） software was applied for two-way clustering analysis and visualized analysis. Results： A total of 1472 journal articles with a key theme of nursing models were retrieved for final analysis, including 771 published during 2005-2009 and 701 during 2010-2014. The bibliometric analysis revealed that publications other than China concerning nursing models were mostly concentrated in the United States and the United Kingdom and that the number of relevant publications has been continuously decreasing. The two-way clustering analysis showed that there were mainly four types of research themes in the relevant publications in countries other than China during 2005-2009, i.e., nursing education and theoretical research, clinical nursing and psychological care, nursing administration, and models of nursing education, whereas there were five types during 2010-2014, i.e., nursing theories and clinical nursing practice, nursing administration models and assessments of nurses＇ knowledge and skills, community nursing administration models, nursing human resource management, and nursing education models and approaches. Conclusions： Research on nursing models in countries other than China is relatively mature and stable with a broader view, but it has shown a declining trend in recent years. It emphasizes both theory and practice, with research content tending to be structured into four modules, i.e., nursing education, administration, clinical practice, and theoretical research. Community nursing models may become a key research direction in the international research on nursing models in the future.

Educational Assistance Through Modeling in Tsukuba University of Technology-Professional Education for the Hearing or Visually Impaired

The National University Corporation Tsukuba University of Technology（NTUT） is the only institute of higher education for the hearing and the visually impaired in Japan. In our university, hearing or visually impaired students are studying to be technicians after they graduate, toward social independence. From previous experience of higher education for students with disabilities, effects are increased when modeling is used by the teachers involved in professional education. In the Mechanical Engineering Course, we are using modeling, to match the drawing and shape for beginning students. It includes support for enhancing one＇s view, and how to draw out the ability of mechanical engineering students for the basics. For students to study Mechanical Design and Drawing, Modeling of Gear Pump, Jack and Globe Valve are easily shown through drawings and the operation of each mechanism through sample drawings in the textbook. It is possible to make an opportunity to think about the machine mechanism. It will be shown by students＇ works. The assembling of the model triggers the need for form accuracy by making a function, and improves the quality of learning. It is possible that a three-dimensional molding machine can be produced through experiential learning by the model, and modeling with the dimension numerical data. Moreover, it is also embodied in a three-dimensional modeling which results in the image processing programming created. Confirming the improvement of the program through the shape with the quality. In the Department of Synthetic Design, students have chances to realize and self-evaluate from the design of the lamp shade with a complicated shape. In the Faculty of Health Science from Department of Health, high quality teaching of visually-impaired students through the use of bone model teaching materials has become possible in the medical-related courses.