We propose an integrated method of data-driven and mechanism models for well logging formation evaluation,explicitly focusing on predicting reservoir parameters,such as porosity and water saturation.Accurately interpr...We propose an integrated method of data-driven and mechanism models for well logging formation evaluation,explicitly focusing on predicting reservoir parameters,such as porosity and water saturation.Accurately interpreting these parameters is crucial for effectively exploring and developing oil and gas.However,with the increasing complexity of geological conditions in this industry,there is a growing demand for improved accuracy in reservoir parameter prediction,leading to higher costs associated with manual interpretation.The conventional logging interpretation methods rely on empirical relationships between logging data and reservoir parameters,which suffer from low interpretation efficiency,intense subjectivity,and suitability for ideal conditions.The application of artificial intelligence in the interpretation of logging data provides a new solution to the problems existing in traditional methods.It is expected to improve the accuracy and efficiency of the interpretation.If large and high-quality datasets exist,data-driven models can reveal relationships of arbitrary complexity.Nevertheless,constructing sufficiently large logging datasets with reliable labels remains challenging,making it difficult to apply data-driven models effectively in logging data interpretation.Furthermore,data-driven models often act as“black boxes”without explaining their predictions or ensuring compliance with primary physical constraints.This paper proposes a machine learning method with strong physical constraints by integrating mechanism and data-driven models.Prior knowledge of logging data interpretation is embedded into machine learning regarding network structure,loss function,and optimization algorithm.We employ the Physically Informed Auto-Encoder(PIAE)to predict porosity and water saturation,which can be trained without labeled reservoir parameters using self-supervised learning techniques.This approach effectively achieves automated interpretation and facilitates generalization across diverse datasets.展开更多
Existing sandstone rock structure evaluation methods rely on visual inspection,with low efficiency,semi-quantitative analysis of roundness,and inability to perform classified statistics in particle size analysis.This ...Existing sandstone rock structure evaluation methods rely on visual inspection,with low efficiency,semi-quantitative analysis of roundness,and inability to perform classified statistics in particle size analysis.This study presents an intelligent evaluation method for sandstone rock structure based on the Segment Anything Model(SAM).By developing a lightweight SAM fine-tuning method with rank-decomposition matrix adapters,a multispectral rock particle segmentation model named CoreSAM is constructed,which achieves rock particle edge extraction and type identification.Building upon this,we propose a comprehensive quantitative evaluation system for rock structure,assessing parameters including particle size,sorting,roundness,particle contact and cementation types.The experimental results demonstrate that CoreSAM outperforms existing methods in rock particle segmentation accuracy while showing excellent generalization across different image types such as CT scans and core photographs.The proposed method enables full-sample,classified particle size analysis and quantitative characterization of parameters like roundness,advancing reservoir evaluation towards more precise,quantitative,intuitive,and comprehensive development.展开更多
In our study, entropy weight coefficients, based on Shannon entropy, were determined for an attribute recognition model to model the quality of groundwater sources. The model follows the theory previously proposed by ...In our study, entropy weight coefficients, based on Shannon entropy, were determined for an attribute recognition model to model the quality of groundwater sources. The model follows the theory previously proposed by Chen Q S. In the model, firstly, the author establishes the attribute space matrix and determines the weight based on Shannon entropy theory; secondly, calculates attribute measure; thirdly, evaluates that with confidence criterion and score criterion; finally, an application example is given. The results show that the water quality of the groundwater sources for the city comes up to the grade II or III standard. There is no pollution that obviously exceeds the standard and the water can meet people’s needs .The results from an evaluation of this model are in basic agreement with the observed situation and with a set pair analysis (SPA) model.展开更多
The use of ultra-high molecular weight polyethylene(UHMWPE)composite in the design of lightweight protective equipment,has gained a lot of interest.However,there is an urgent need to understand the ballistic response ...The use of ultra-high molecular weight polyethylene(UHMWPE)composite in the design of lightweight protective equipment,has gained a lot of interest.However,there is an urgent need to understand the ballistic response mechanism and theoretical prediction model of performance.This paper explores the ballistic response mechanism of UHMWPE composite through experimental and simulation analyses.Then,a resistance-driven modeling method was proposed to establish a theoretical model for predicting the bulletproof performance.The ballistic response mechanism of UHMWPE composite encompassed three fundamental modes:local response,structural response,and coupled response.The occurrence ratio of these fundamental response modes during impact was dependent on the projectile velocity and laminate thickness.The bulletproof performance of laminate under different response modes was assessed based on the penetration depth of the projectile,the bulging height on the rear face of the laminate,the thickness of remaining sub-laminate,and residual velocity of the projectile.The absolute deviations of bulletproof performance indicator between theoretical value and experimental value were well within 11.13%,demonstrating that the established evaluation model possessed high degree of prediction accuracy.展开更多
A comprehensive and objective risk evaluation model of oil and gas pipelines based on an improved analytic hierarchy process(AHP)and technique for order preference by similarity to an ideal solution(TOPSIS)is establis...A comprehensive and objective risk evaluation model of oil and gas pipelines based on an improved analytic hierarchy process(AHP)and technique for order preference by similarity to an ideal solution(TOPSIS)is established to identify potential hazards in time.First,a barrier model and fault tree analysis are used to establish an index system for oil and gas pipeline risk evaluation on the basis of five important factors:corrosion,external interference,material/construction,natural disasters,and function and operation.Next,the index weight for oil and gas pipeline risk evaluation is computed by applying the improved AHP based on the five-scale method.Then,the TOPSIS of a multi-attribute decision-making theory is studied.The method for determining positive/negative ideal solutions and the normalized equation for benefit/cost indexes is improved to render TOPSIS applicable for the comprehensive risk evaluation of pipelines.The closeness coefficient of oil and gas pipelines is calculated by applying the improved TOPSIS.Finally,the weight and the closeness coefficient are combined to determine the risk level of pipelines.Empirical research using a long-distance pipeline as an example is conducted,and adjustment factors are used to verify the model.Results show that the risk evaluation model of oil and gas pipelines based on the improved AHP–TOPSIS is valuable and feasible.The model comprehensively considers the risk factors of oil and gas pipelines and provides comprehensive,rational,and scientific evaluation results.It represents a new decision-making method for systems engineering in pipeline enterprises and provides a comprehensive understanding of the safety status of oil and gas pipelines.The new system engineering decision-making method is important for preventing oil and gas pipeline accidents.展开更多
Increasing the production and utilization of shale gas is of great significance for building a clean and low-carbon energy system.Sharp decline of gas production has been widely observed in shale gas reservoirs.How to...Increasing the production and utilization of shale gas is of great significance for building a clean and low-carbon energy system.Sharp decline of gas production has been widely observed in shale gas reservoirs.How to forecast shale gas production is still challenging due to complex fracture networks,dynamic fracture properties,frac hits,complicated multiphase flow,and multi-scale flow as well as data quality and uncertainty.This work develops an integrated framework for evaluating shale gas well production based on data-driven models.Firstly,a comprehensive dominated-factor system has been established,including geological,drilling,fracturing,and production factors.Data processing and visualization are required to ensure data quality and determine final data set.A shale gas production evaluation model is developed to evaluate shale gas production levels.Finally,the random forest algorithm is used to forecast shale gas production.The prediction accuracy of shale gas production level is higher than 95%based on the shale gas reservoirs in China.Forty-one wells are randomly selected to predict cumulative gas production using the optimal regression model.The proposed shale gas production evaluation frame-work overcomes too many assumptions of analytical or semi-analytical models and avoids huge computation cost and poor generalization for numerical modelling.展开更多
Based on fuzzy set theory, a fuzzy trust model is established by using membership function to describe the fuzziness of trust. The trust vectors of subjective trust are obtained based on a mathematical model of fuzzy ...Based on fuzzy set theory, a fuzzy trust model is established by using membership function to describe the fuzziness of trust. The trust vectors of subjective trust are obtained based on a mathematical model of fuzzy synthetic evaluation. Considering the complicated and changeable relationships between various subjects, the multi-level mathematical model of fuzzy synthetic evaluation is introduced. An example of a two-level fuzzy synthetic evaluation model confirms the feasibility of the multi-level fuzzy synthesis evaluation model. The proposed fuzzy model for trust evaluation may provide a promising method for research of trust model in open networks.展开更多
This study aims at determining the optimal CO2 separation technology for Chinese refineries, based on current available technologies, by the method of comprehensive evaluation. Firstly, according to the characteristic...This study aims at determining the optimal CO2 separation technology for Chinese refineries, based on current available technologies, by the method of comprehensive evaluation. Firstly, according to the characteristics of flue gas from Chinese refineries, three feasible CO2 separation technologies are selected. These are pressure swing adsorption （PSA）, chemical absorption （CA）, and membrane absorption （MA）. Secondly, an economic assessment of these three techniques is carried out in accordance with cash flow analysis. The results show that these three techniques all have economic feasibility and the PSA technique is the best. Finally, to further optimize the three techniques, a two-level fuzzy comprehensive evaluation model is established, including economic, technological, and environmental factors. Considering all the factors, PSA is optimal for Chinese refineries, followed by CA and MA. Therefore, to reduce Chinese refineries carbon emission, it is suggested that CO2 should be captured from off-gases using PSA.展开更多
Hydrocarbon expulsion features and resource potential evaluation of source rocks are crucial for the petroleum exploration.High-maturity marine source rocks have not exhibited a hydrocarbon expulsion mode owing to the...Hydrocarbon expulsion features and resource potential evaluation of source rocks are crucial for the petroleum exploration.High-maturity marine source rocks have not exhibited a hydrocarbon expulsion mode owing to the lack of low-maturity source rocks in deep petroliferous basins.We considered the Ediacaran microbial dolomite in the Sichuan Basin,the largest high-maturity marine gas layer in China,to exhibit a method that quantitatively characterizes the hydrocarbon expulsion of high-maturity marine source rocks.The experiment of fluid inclusion,rock pyrolysis,and vitrinite reflectance(Ro)of 119 microbial dolomite core samples obtained from the Dengying Formation were performed.A hydrocarbon expulsion model of high-maturity source rock was established,and its resource potential was evaluated.The results showed that the Ediacaran microbial dolomite in the Sichuan Basin is a good source rock showing vast resource potential.The hydrocarbon expulsion threshold is determined to be vitrinite reflectance at 0.92%.The hydrocarbon expulsion intensities in the geologic history is high with maximum of 1.6×10^(7)t/km^(2).The Ediacaran microbial dolomite expelled approximately 1.008×10^(12)t of hydrocarbons,and the recoverable resource was 1.5×10^(12)m^(3).The region can be categorized into areasⅠ,Ⅱ,Ⅲ,andⅣ,in decreasing order of hydrocarbon expulsion intensity.Areas with a higher hydrocarbon expulsion intensity have a lower drilling risk and should be prioritized for exploration in the orderⅠ>Ⅱ>Ⅲ>Ⅳ.Two areas,northern and central parts of Ediacaran in the Sichuan Basin,were selected as prospects which had the drilling priority in the future gas exploration.The production data of 55 drilled wells verified the high reliability of this method.This model in this study does not require low-maturity samples and can be used for evaluating high-maturity marine source rocks,which has broad applicability in deep basins worldwide.展开更多
CO2 flooding not only triggers an increase in oil production,but also reduces the amount of CO2 released to the atmosphere （by storing it permanently in the formations）.It is one of the best ways to use and store CO...CO2 flooding not only triggers an increase in oil production,but also reduces the amount of CO2 released to the atmosphere （by storing it permanently in the formations）.It is one of the best ways to use and store CO2.This paper firstly selects the key factors after analyzing the factors influencing the CO2 storage potential in the formations and oil recovery,and then introduces a series of dimensionless variables to describe reservoir characteristics.All influencing factors with varying values are calculated through a Box-Behnken experimental design.The results are interpreted by a response surface method,and then a quick screening model is obtained to evaluate the oil recovery and CO2 storage potential for an oil reservoir.Based on the evaluation model,sensitivity analysis of each factor is carried out.Finally,research on CO2 sequestration and flooding in a typical reservoir indicates that the evaluation model fits well with the numerical simulation,which proves that the evaluation model can provide criteria for screening attractive candidate reservoirs for CO2 sequestration and flooding.展开更多
With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distributi...With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distribution network based on the combination weighting and cloud model of the improved Fuzzy Analytic Hierarchy-Entropy Weight Method(FAHP-EWM).First,we establish comprehensive evaluation indexes of a 5G+smart distribution network from five dimensions:reliable operation,economic operation,efficient interaction,technological intelligence,and green emission reduction.Second,by introducing the principle of variance minimization,we propose a combined weighting method based on the improved FAHP-EWM to calculate the comprehensive weight,so as to reduce the defects of subjective arbitrariness and promote objectivity.Finally,a comprehensive evaluation model of 5G+smart distribution network based on cloud model is proposed by considering the uncertainty of distribution network node information and equipment status information.The example analysis indicates that the overall operation of the 5G+smart distribution network project is decent,and the weight value calculated by the combined weighting method is more reasonable and accurate than that calculated by the single weighting method,which verifies the effectiveness and rationality of the proposed evaluation method.Moreover,the proposed evaluation method has a certain guiding role for the large-scale application of 5G communication technology in smart distribution networks.展开更多
Purpose: This study aims to present the key systemic changes in the Polish book evaluation model to focus on the publisher list, as inspired by the Norwegian Model. Design/methodology/approach: In this study we recons...Purpose: This study aims to present the key systemic changes in the Polish book evaluation model to focus on the publisher list, as inspired by the Norwegian Model. Design/methodology/approach: In this study we reconstruct the framework of the 2010 and 2018 models of book evaluation in Poland within the performance-based research funding system. Findings: For almost 20 years the book evaluation system in Poland has been based on the verification of various technical criteria(e.g. length of the book). The new 2018 model is based on the principle of prestige inheritance(a book is worth as much as its publisher is) and is inspired by the publisher list used in the Norwegian Model. In this paper, we argue that this solution may be a more balanced policy instrument than the previous 2010 model in which neither the quality of the publisher nor the quality of the book played any role in the evaluation.Research limitations: We work from the framework of the 2018 model of book evaluation specified in the law on higher education and science from 20 July 2018, as implementation acts are not available yet. Practical implications: This study may provide a valuable point of reference on how structural reforms in the research evaluation model were implemented on a country level. The results of this study may be interesting to policy makers, stakeholders and researchers focused on science policy. Originality/value: This is the very first study that presents the new framework of the Polish research evaluation model and policy instruments for scholarly book evaluation. We describe what motivated policy makers to change the book evaluation model, and what arguments were explicitly raised to argue for the new solution.展开更多
Virtual reality(VR) environment can provide immersive experience to viewers.Under the VR environment, providing a good quality of experience is extremely important.Therefore, in this paper, we present an image quality...Virtual reality(VR) environment can provide immersive experience to viewers.Under the VR environment, providing a good quality of experience is extremely important.Therefore, in this paper, we present an image quality assessment(IQA) study on omnidirectional images. We first build an omnidirectional IQA(OIQA) database, including 16 source images with their corresponding 320 distorted images. We add four commonly encountered distortions. These distortions are JPEG compression, JPEG2000 compression, Gaussian blur, and Gaussian noise. Then we conduct a subjective quality evaluation study in the VR environment based on the OIQA database. Considering that visual attention is more important in VR environment, head and eye movement data are also tracked and collected during the quality rating experiments. The 16 raw and their corresponding distorted images,subjective quality assessment scores, and the head-orientation data and eye-gaze data together constitute the OIQA database. Based on the OIQA database, we test some state-of-the-art full-reference IQA(FR-IQA) measures on equirectangular format or cubic formatomnidirectional images. The results show that applying FR-IQA metrics on cubic format omnidirectional images could improve their performance. The performance of some FR-IQA metrics combining the saliency weight of three different types are also tested based on our database. Some new phenomena different from traditional IQA are observed.展开更多
A driver-pickup probe possesses better sensitivity and flexibility due to individual optimization of a coil.It is fre-quently observed in an eddy current(EC)array probe.In this work,a tilted non-coaxial driver-pickup ...A driver-pickup probe possesses better sensitivity and flexibility due to individual optimization of a coil.It is fre-quently observed in an eddy current(EC)array probe.In this work,a tilted non-coaxial driver-pickup probe above a multilayered conducting plate is analytically modeled with spatial transformation for eddy current nondestructive evalua-tion.Basically,the core of the formulation is to obtain the projection of magnetic vector potential(MVP)from the driver coil onto the vector along the tilted pickup coil,which is divided into two key steps.The first step is to make a projection of MVP along the pickup coil onto a horizontal plane,and the second one is to build the relationship between the pr,ojected MVP and the MVP along the driver coil.Afterwards,an analytical model for the case of a layered plate is established with the reflection and transmission theory of electromagnetic fields.The calculated values from the resulting model indicate good agreement with those from the finite element model(FEM)and experiments,which validates the developed analytical model.展开更多
Data envelopment analysis(DEA) model is widely used to evaluate the relative efficiency of producers. It is a kind of objective decision method with multiple indexes. However, the two basic models frequently used at p...Data envelopment analysis(DEA) model is widely used to evaluate the relative efficiency of producers. It is a kind of objective decision method with multiple indexes. However, the two basic models frequently used at present, the C2R model and the C2GS2 model have limitations when used alone,resulting in evaluations that are often unsatisfactory. In order to solve this problem, a mixed DEA model is built and is used to evaluate the validity of the business efficiency of listed companies. An explanation of how to use this mixed DEA model is offered and its feasibility is verified.展开更多
The generation method of three-dimensional fractal discrete fracture network(FDFN)based on multiplicative cascade process was developed.The complex multi-scale fracture system in shale after fracturing was characteriz...The generation method of three-dimensional fractal discrete fracture network(FDFN)based on multiplicative cascade process was developed.The complex multi-scale fracture system in shale after fracturing was characterized by coupling the artificial fracture model and the natural fracture model.Based on an assisted history matching(AHM)using multiple-proxy-based Markov chain Monte Carlo algorithm(MCMC),an embedded discrete fracture modeling(EDFM)incorporated with reservoir simulator was used to predict productivity of shale gas well.When using the natural fracture generation method,the distribution of natural fracture network can be controlled by fractal parameters,and the natural fracture network generated coupling with artificial fractures can characterize the complex system of different-scale fractures in shale after fracturing.The EDFM,with fewer grids and less computation time consumption,can characterize the attributes of natural fractures and artificial fractures flexibly,and simulate the details of mass transfer between matrix cells and fractures while reducing computation significantly.The combination of AMH and EDFM can lower the uncertainty of reservoir and fracture parameters,and realize effective inversion of key reservoir and fracture parameters and the productivity forecast of shale gas wells.Application demonstrates the results from the proposed productivity prediction model integrating FDFN,EDFM and AHM have high credibility.展开更多
Digital libraries are complex systems and this brings difficulties for their evaluation. This paper proposes a hierarchical model to solve this problem, and puts the entangled matters into a clear-layered structure. F...Digital libraries are complex systems and this brings difficulties for their evaluation. This paper proposes a hierarchical model to solve this problem, and puts the entangled matters into a clear-layered structure. Firstly, digital libraries(DLs thereafter)are classified into 5 groups in ascending gradations, i.e. mini DLs, small DLs, medium DLs,large DLs, and huge DLs by their scope of operation. Then, according to the characteristics of DLs at different operational scope and level of sophistication, they are further grouped into unitary DLs, union DLs and hybrid DLs accordingly. Based on this simulated structure,a hierarchical model for digital library evaluation is introduced, which evaluates DLs differentiatingly within a hierarchical scheme by using varying criteria based on their specific level of operational complexity such as at the micro-level, medium-level, and/or at the macro-level. Based on our careful examination and analysis of the current literature about DL evaluation system, an experiment is conducted by using the DL evaluation model along with its criteria for unitary DLs at micro-level. The main contents resulting from this evaluation experimentation and also those evaluation indicators and relevant issues of major concerns for DLs at medium-level and macro-level are also to be presented at some length.展开更多
A new stochastic volatility（SV）method to estimate the conditional value at risk（CVaR）is put forward.Firstly,it makes use of SV model to forecast the volatility of return.Secondly,the Markov chain Monte Carlo（MCMC...A new stochastic volatility（SV）method to estimate the conditional value at risk（CVaR）is put forward.Firstly,it makes use of SV model to forecast the volatility of return.Secondly,the Markov chain Monte Carlo（MCMC）simulation and Gibbs sampling have been used to estimate the parameters in the SV model.Thirdly,in this model,CVaR calculation is immediate.In this way,the SV-CVaR model overcomes the drawbacks of the generalized autoregressive conditional heteroscedasticity value at risk（GARCH-VaR）model.Empirical study suggests that this model is better than GARCH-VaR model in this field.展开更多
Purpose: This study expands on the results of a stakeholder-driven research project on quality indicators and output assessment of art and design research in Flanders-the Northern, Dutchspeaking region of Belgium. Her...Purpose: This study expands on the results of a stakeholder-driven research project on quality indicators and output assessment of art and design research in Flanders-the Northern, Dutchspeaking region of Belgium. Herein, it emphasizes the value of arts & design output registration as a modality to articulate the disciplinary demarcations of art and design research.Design/methodology/approach: The particularity of art and design research in Flanders is first analyzed and compared to international examples. Hereafter, the results of the stakeholderdriven project on the creation of indicators for arts & design research output assessment are discussed. Findings: The findings accentuate the importance of allowing an assessment culture to emerge from practitioners themselves, instead of imposing ill-suited methods borrowed from established scientific evaluation models(Biggs & Karlsson, 2011)-notwithstanding the practical difficulties it generates. They point to the potential of stakeholder-driven approaches for artistic research, which benefits from constructing a shared metadiscourse among its practitioners regarding the continuities and discontinuities between "artistic" and "traditional" research, and the communal goals and values that guide its knowledge production(Biggs & Karlsson, 2011;Hellstr?m, 2010;Ysebaert & Martens, 2018). Research limitation: The central limitation of the study is that it focuses exclusively on the "Architecture & Design" panel of the project, and does not account for intra-disciplinary complexities in output assessment. Practical implications: The goal of the research project is to create a robust assessment system for arts & design research in Flanders, which may later guide similar international projects. Originality/value: This study is currently the only one to consider the productive potential of(collaborative) PRFSs for artistic research.展开更多
Because of explosive growth in Internet traffic and high complexity of heterogeneous networks, improving the routing and wavelength assignment （RWA） algorithm in underlying optical networks has become very important...Because of explosive growth in Internet traffic and high complexity of heterogeneous networks, improving the routing and wavelength assignment （RWA） algorithm in underlying optical networks has become very important. Where there are multiple links between different the node pairs, a traditional wavelength-assignment algorithm may be invalid for a wavelength-switched optical networks （WSON） that has directional blocking constraints. Also, impairments in network nodes and subsequent degradation of optical signals may cause modulation failure in the optical network. In this paper, we propose an RWA algorithm based on a novel evaluation model for a WSQN that has multiple constraints. The algorithm includes comprehensive evaluation model （CEM） and directional blocking constraint RWA based on CEM （DB-RWA）. Diverse constraints are abstracted into various constraint conditions in order to better assign routing and wavelength. We propose using the novel CEM to optimize routing according to an assessed value of constraints on transmission performance. This eliminates the effects of physical transmission impairments in a WSON. DB-RWA based on CEM abstracts directional blocking conditions in multiple links between network nodes into directional blocking constraints. It also satisfies rigorous network specifications and provides flexibility, scalability, and first-fit rate for the backbone, especially in multiple links between WSON nodes.展开更多
基金supported by National Key Research and Development Program (2019YFA0708301)National Natural Science Foundation of China (51974337)+2 种基金the Strategic Cooperation Projects of CNPC and CUPB (ZLZX2020-03)Science and Technology Innovation Fund of CNPC (2021DQ02-0403)Open Fund of Petroleum Exploration and Development Research Institute of CNPC (2022-KFKT-09)
文摘We propose an integrated method of data-driven and mechanism models for well logging formation evaluation,explicitly focusing on predicting reservoir parameters,such as porosity and water saturation.Accurately interpreting these parameters is crucial for effectively exploring and developing oil and gas.However,with the increasing complexity of geological conditions in this industry,there is a growing demand for improved accuracy in reservoir parameter prediction,leading to higher costs associated with manual interpretation.The conventional logging interpretation methods rely on empirical relationships between logging data and reservoir parameters,which suffer from low interpretation efficiency,intense subjectivity,and suitability for ideal conditions.The application of artificial intelligence in the interpretation of logging data provides a new solution to the problems existing in traditional methods.It is expected to improve the accuracy and efficiency of the interpretation.If large and high-quality datasets exist,data-driven models can reveal relationships of arbitrary complexity.Nevertheless,constructing sufficiently large logging datasets with reliable labels remains challenging,making it difficult to apply data-driven models effectively in logging data interpretation.Furthermore,data-driven models often act as“black boxes”without explaining their predictions or ensuring compliance with primary physical constraints.This paper proposes a machine learning method with strong physical constraints by integrating mechanism and data-driven models.Prior knowledge of logging data interpretation is embedded into machine learning regarding network structure,loss function,and optimization algorithm.We employ the Physically Informed Auto-Encoder(PIAE)to predict porosity and water saturation,which can be trained without labeled reservoir parameters using self-supervised learning techniques.This approach effectively achieves automated interpretation and facilitates generalization across diverse datasets.
基金Supported by the National Natural Science Foundation of China(42372175,72088101)PetroChina Science and Technology Project of(2023DJ84)Basic Research Cooperation Project between China National Petroleum Corporation and Peking University.
文摘Existing sandstone rock structure evaluation methods rely on visual inspection,with low efficiency,semi-quantitative analysis of roundness,and inability to perform classified statistics in particle size analysis.This study presents an intelligent evaluation method for sandstone rock structure based on the Segment Anything Model(SAM).By developing a lightweight SAM fine-tuning method with rank-decomposition matrix adapters,a multispectral rock particle segmentation model named CoreSAM is constructed,which achieves rock particle edge extraction and type identification.Building upon this,we propose a comprehensive quantitative evaluation system for rock structure,assessing parameters including particle size,sorting,roundness,particle contact and cementation types.The experimental results demonstrate that CoreSAM outperforms existing methods in rock particle segmentation accuracy while showing excellent generalization across different image types such as CT scans and core photographs.The proposed method enables full-sample,classified particle size analysis and quantitative characterization of parameters like roundness,advancing reservoir evaluation towards more precise,quantitative,intuitive,and comprehensive development.
文摘In our study, entropy weight coefficients, based on Shannon entropy, were determined for an attribute recognition model to model the quality of groundwater sources. The model follows the theory previously proposed by Chen Q S. In the model, firstly, the author establishes the attribute space matrix and determines the weight based on Shannon entropy theory; secondly, calculates attribute measure; thirdly, evaluates that with confidence criterion and score criterion; finally, an application example is given. The results show that the water quality of the groundwater sources for the city comes up to the grade II or III standard. There is no pollution that obviously exceeds the standard and the water can meet people’s needs .The results from an evaluation of this model are in basic agreement with the observed situation and with a set pair analysis (SPA) model.
基金supported by the National Key Research and Development of China(Grant No.2022YFB4601901)the National Natural Science Foundation of China(Grant No.12122202)。
文摘The use of ultra-high molecular weight polyethylene(UHMWPE)composite in the design of lightweight protective equipment,has gained a lot of interest.However,there is an urgent need to understand the ballistic response mechanism and theoretical prediction model of performance.This paper explores the ballistic response mechanism of UHMWPE composite through experimental and simulation analyses.Then,a resistance-driven modeling method was proposed to establish a theoretical model for predicting the bulletproof performance.The ballistic response mechanism of UHMWPE composite encompassed three fundamental modes:local response,structural response,and coupled response.The occurrence ratio of these fundamental response modes during impact was dependent on the projectile velocity and laminate thickness.The bulletproof performance of laminate under different response modes was assessed based on the penetration depth of the projectile,the bulging height on the rear face of the laminate,the thickness of remaining sub-laminate,and residual velocity of the projectile.The absolute deviations of bulletproof performance indicator between theoretical value and experimental value were well within 11.13%,demonstrating that the established evaluation model possessed high degree of prediction accuracy.
基金supported by the National Key Research and Development Program of China(Grant Nos.2017YFC0805804,2017YFC0805801)
文摘A comprehensive and objective risk evaluation model of oil and gas pipelines based on an improved analytic hierarchy process(AHP)and technique for order preference by similarity to an ideal solution(TOPSIS)is established to identify potential hazards in time.First,a barrier model and fault tree analysis are used to establish an index system for oil and gas pipeline risk evaluation on the basis of five important factors:corrosion,external interference,material/construction,natural disasters,and function and operation.Next,the index weight for oil and gas pipeline risk evaluation is computed by applying the improved AHP based on the five-scale method.Then,the TOPSIS of a multi-attribute decision-making theory is studied.The method for determining positive/negative ideal solutions and the normalized equation for benefit/cost indexes is improved to render TOPSIS applicable for the comprehensive risk evaluation of pipelines.The closeness coefficient of oil and gas pipelines is calculated by applying the improved TOPSIS.Finally,the weight and the closeness coefficient are combined to determine the risk level of pipelines.Empirical research using a long-distance pipeline as an example is conducted,and adjustment factors are used to verify the model.Results show that the risk evaluation model of oil and gas pipelines based on the improved AHP–TOPSIS is valuable and feasible.The model comprehensively considers the risk factors of oil and gas pipelines and provides comprehensive,rational,and scientific evaluation results.It represents a new decision-making method for systems engineering in pipeline enterprises and provides a comprehensive understanding of the safety status of oil and gas pipelines.The new system engineering decision-making method is important for preventing oil and gas pipeline accidents.
基金funded by National Natural Science Foundation of China(52004238)China Postdoctoral Science Foundation(2019M663561).
文摘Increasing the production and utilization of shale gas is of great significance for building a clean and low-carbon energy system.Sharp decline of gas production has been widely observed in shale gas reservoirs.How to forecast shale gas production is still challenging due to complex fracture networks,dynamic fracture properties,frac hits,complicated multiphase flow,and multi-scale flow as well as data quality and uncertainty.This work develops an integrated framework for evaluating shale gas well production based on data-driven models.Firstly,a comprehensive dominated-factor system has been established,including geological,drilling,fracturing,and production factors.Data processing and visualization are required to ensure data quality and determine final data set.A shale gas production evaluation model is developed to evaluate shale gas production levels.Finally,the random forest algorithm is used to forecast shale gas production.The prediction accuracy of shale gas production level is higher than 95%based on the shale gas reservoirs in China.Forty-one wells are randomly selected to predict cumulative gas production using the optimal regression model.The proposed shale gas production evaluation frame-work overcomes too many assumptions of analytical or semi-analytical models and avoids huge computation cost and poor generalization for numerical modelling.
文摘Based on fuzzy set theory, a fuzzy trust model is established by using membership function to describe the fuzziness of trust. The trust vectors of subjective trust are obtained based on a mathematical model of fuzzy synthetic evaluation. Considering the complicated and changeable relationships between various subjects, the multi-level mathematical model of fuzzy synthetic evaluation is introduced. An example of a two-level fuzzy synthetic evaluation model confirms the feasibility of the multi-level fuzzy synthesis evaluation model. The proposed fuzzy model for trust evaluation may provide a promising method for research of trust model in open networks.
基金the China University of Petroleum Foundationthe Research Institute of Safety and Environment TechnologyChina National Petroleum Corporation
文摘This study aims at determining the optimal CO2 separation technology for Chinese refineries, based on current available technologies, by the method of comprehensive evaluation. Firstly, according to the characteristics of flue gas from Chinese refineries, three feasible CO2 separation technologies are selected. These are pressure swing adsorption （PSA）, chemical absorption （CA）, and membrane absorption （MA）. Secondly, an economic assessment of these three techniques is carried out in accordance with cash flow analysis. The results show that these three techniques all have economic feasibility and the PSA technique is the best. Finally, to further optimize the three techniques, a two-level fuzzy comprehensive evaluation model is established, including economic, technological, and environmental factors. Considering all the factors, PSA is optimal for Chinese refineries, followed by CA and MA. Therefore, to reduce Chinese refineries carbon emission, it is suggested that CO2 should be captured from off-gases using PSA.
基金supported by the Open Fund Project of State Key Laboratory of Lithospheric Evolution [SKL-K202103]support of the Exploration and Development Research Institute of Petro China Southwest Oil & Gas Field
文摘Hydrocarbon expulsion features and resource potential evaluation of source rocks are crucial for the petroleum exploration.High-maturity marine source rocks have not exhibited a hydrocarbon expulsion mode owing to the lack of low-maturity source rocks in deep petroliferous basins.We considered the Ediacaran microbial dolomite in the Sichuan Basin,the largest high-maturity marine gas layer in China,to exhibit a method that quantitatively characterizes the hydrocarbon expulsion of high-maturity marine source rocks.The experiment of fluid inclusion,rock pyrolysis,and vitrinite reflectance(Ro)of 119 microbial dolomite core samples obtained from the Dengying Formation were performed.A hydrocarbon expulsion model of high-maturity source rock was established,and its resource potential was evaluated.The results showed that the Ediacaran microbial dolomite in the Sichuan Basin is a good source rock showing vast resource potential.The hydrocarbon expulsion threshold is determined to be vitrinite reflectance at 0.92%.The hydrocarbon expulsion intensities in the geologic history is high with maximum of 1.6×10^(7)t/km^(2).The Ediacaran microbial dolomite expelled approximately 1.008×10^(12)t of hydrocarbons,and the recoverable resource was 1.5×10^(12)m^(3).The region can be categorized into areasⅠ,Ⅱ,Ⅲ,andⅣ,in decreasing order of hydrocarbon expulsion intensity.Areas with a higher hydrocarbon expulsion intensity have a lower drilling risk and should be prioritized for exploration in the orderⅠ>Ⅱ>Ⅲ>Ⅳ.Two areas,northern and central parts of Ediacaran in the Sichuan Basin,were selected as prospects which had the drilling priority in the future gas exploration.The production data of 55 drilled wells verified the high reliability of this method.This model in this study does not require low-maturity samples and can be used for evaluating high-maturity marine source rocks,which has broad applicability in deep basins worldwide.
基金support from the National Basic Research Program of China (2006CB705805)
文摘CO2 flooding not only triggers an increase in oil production,but also reduces the amount of CO2 released to the atmosphere （by storing it permanently in the formations）.It is one of the best ways to use and store CO2.This paper firstly selects the key factors after analyzing the factors influencing the CO2 storage potential in the formations and oil recovery,and then introduces a series of dimensionless variables to describe reservoir characteristics.All influencing factors with varying values are calculated through a Box-Behnken experimental design.The results are interpreted by a response surface method,and then a quick screening model is obtained to evaluate the oil recovery and CO2 storage potential for an oil reservoir.Based on the evaluation model,sensitivity analysis of each factor is carried out.Finally,research on CO2 sequestration and flooding in a typical reservoir indicates that the evaluation model fits well with the numerical simulation,which proves that the evaluation model can provide criteria for screening attractive candidate reservoirs for CO2 sequestration and flooding.
基金supported by the State Grid Corporation of China(KJ21-1-56).
文摘With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distribution network based on the combination weighting and cloud model of the improved Fuzzy Analytic Hierarchy-Entropy Weight Method(FAHP-EWM).First,we establish comprehensive evaluation indexes of a 5G+smart distribution network from five dimensions:reliable operation,economic operation,efficient interaction,technological intelligence,and green emission reduction.Second,by introducing the principle of variance minimization,we propose a combined weighting method based on the improved FAHP-EWM to calculate the comprehensive weight,so as to reduce the defects of subjective arbitrariness and promote objectivity.Finally,a comprehensive evaluation model of 5G+smart distribution network based on cloud model is proposed by considering the uncertainty of distribution network node information and equipment status information.The example analysis indicates that the overall operation of the 5G+smart distribution network project is decent,and the weight value calculated by the combined weighting method is more reasonable and accurate than that calculated by the single weighting method,which verifies the effectiveness and rationality of the proposed evaluation method.Moreover,the proposed evaluation method has a certain guiding role for the large-scale application of 5G communication technology in smart distribution networks.
基金supported by the DIALOG Program[grant name“Research into Excellence Patterns in Science and Art”]financed by the Ministry of Science and Higher Education in Poland
文摘Purpose: This study aims to present the key systemic changes in the Polish book evaluation model to focus on the publisher list, as inspired by the Norwegian Model. Design/methodology/approach: In this study we reconstruct the framework of the 2010 and 2018 models of book evaluation in Poland within the performance-based research funding system. Findings: For almost 20 years the book evaluation system in Poland has been based on the verification of various technical criteria(e.g. length of the book). The new 2018 model is based on the principle of prestige inheritance(a book is worth as much as its publisher is) and is inspired by the publisher list used in the Norwegian Model. In this paper, we argue that this solution may be a more balanced policy instrument than the previous 2010 model in which neither the quality of the publisher nor the quality of the book played any role in the evaluation.Research limitations: We work from the framework of the 2018 model of book evaluation specified in the law on higher education and science from 20 July 2018, as implementation acts are not available yet. Practical implications: This study may provide a valuable point of reference on how structural reforms in the research evaluation model were implemented on a country level. The results of this study may be interesting to policy makers, stakeholders and researchers focused on science policy. Originality/value: This is the very first study that presents the new framework of the Polish research evaluation model and policy instruments for scholarly book evaluation. We describe what motivated policy makers to change the book evaluation model, and what arguments were explicitly raised to argue for the new solution.
文摘Virtual reality(VR) environment can provide immersive experience to viewers.Under the VR environment, providing a good quality of experience is extremely important.Therefore, in this paper, we present an image quality assessment(IQA) study on omnidirectional images. We first build an omnidirectional IQA(OIQA) database, including 16 source images with their corresponding 320 distorted images. We add four commonly encountered distortions. These distortions are JPEG compression, JPEG2000 compression, Gaussian blur, and Gaussian noise. Then we conduct a subjective quality evaluation study in the VR environment based on the OIQA database. Considering that visual attention is more important in VR environment, head and eye movement data are also tracked and collected during the quality rating experiments. The 16 raw and their corresponding distorted images,subjective quality assessment scores, and the head-orientation data and eye-gaze data together constitute the OIQA database. Based on the OIQA database, we test some state-of-the-art full-reference IQA(FR-IQA) measures on equirectangular format or cubic formatomnidirectional images. The results show that applying FR-IQA metrics on cubic format omnidirectional images could improve their performance. The performance of some FR-IQA metrics combining the saliency weight of three different types are also tested based on our database. Some new phenomena different from traditional IQA are observed.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61701500,51677187,and 51465024)
文摘A driver-pickup probe possesses better sensitivity and flexibility due to individual optimization of a coil.It is fre-quently observed in an eddy current(EC)array probe.In this work,a tilted non-coaxial driver-pickup probe above a multilayered conducting plate is analytically modeled with spatial transformation for eddy current nondestructive evalua-tion.Basically,the core of the formulation is to obtain the projection of magnetic vector potential(MVP)from the driver coil onto the vector along the tilted pickup coil,which is divided into two key steps.The first step is to make a projection of MVP along the pickup coil onto a horizontal plane,and the second one is to build the relationship between the pr,ojected MVP and the MVP along the driver coil.Afterwards,an analytical model for the case of a layered plate is established with the reflection and transmission theory of electromagnetic fields.The calculated values from the resulting model indicate good agreement with those from the finite element model(FEM)and experiments,which validates the developed analytical model.
基金Supported by Commission of Science Technology and Industry for National Defense(No, C192005C001)
文摘Data envelopment analysis(DEA) model is widely used to evaluate the relative efficiency of producers. It is a kind of objective decision method with multiple indexes. However, the two basic models frequently used at present, the C2R model and the C2GS2 model have limitations when used alone,resulting in evaluations that are often unsatisfactory. In order to solve this problem, a mixed DEA model is built and is used to evaluate the validity of the business efficiency of listed companies. An explanation of how to use this mixed DEA model is offered and its feasibility is verified.
基金Supported by the National Science and Technology Major Project(2017ZX05063-005)Science and Technology Development Project of PetroChina Research Institute of Petroleum Exploration and Development(YGJ2019-12-04)。
文摘The generation method of three-dimensional fractal discrete fracture network(FDFN)based on multiplicative cascade process was developed.The complex multi-scale fracture system in shale after fracturing was characterized by coupling the artificial fracture model and the natural fracture model.Based on an assisted history matching(AHM)using multiple-proxy-based Markov chain Monte Carlo algorithm(MCMC),an embedded discrete fracture modeling(EDFM)incorporated with reservoir simulator was used to predict productivity of shale gas well.When using the natural fracture generation method,the distribution of natural fracture network can be controlled by fractal parameters,and the natural fracture network generated coupling with artificial fractures can characterize the complex system of different-scale fractures in shale after fracturing.The EDFM,with fewer grids and less computation time consumption,can characterize the attributes of natural fractures and artificial fractures flexibly,and simulate the details of mass transfer between matrix cells and fractures while reducing computation significantly.The combination of AMH and EDFM can lower the uncertainty of reservoir and fracture parameters,and realize effective inversion of key reservoir and fracture parameters and the productivity forecast of shale gas wells.Application demonstrates the results from the proposed productivity prediction model integrating FDFN,EDFM and AHM have high credibility.
文摘Digital libraries are complex systems and this brings difficulties for their evaluation. This paper proposes a hierarchical model to solve this problem, and puts the entangled matters into a clear-layered structure. Firstly, digital libraries(DLs thereafter)are classified into 5 groups in ascending gradations, i.e. mini DLs, small DLs, medium DLs,large DLs, and huge DLs by their scope of operation. Then, according to the characteristics of DLs at different operational scope and level of sophistication, they are further grouped into unitary DLs, union DLs and hybrid DLs accordingly. Based on this simulated structure,a hierarchical model for digital library evaluation is introduced, which evaluates DLs differentiatingly within a hierarchical scheme by using varying criteria based on their specific level of operational complexity such as at the micro-level, medium-level, and/or at the macro-level. Based on our careful examination and analysis of the current literature about DL evaluation system, an experiment is conducted by using the DL evaluation model along with its criteria for unitary DLs at micro-level. The main contents resulting from this evaluation experimentation and also those evaluation indicators and relevant issues of major concerns for DLs at medium-level and macro-level are also to be presented at some length.
基金Sponsored by the National Natural Science Foundation of China(70571010)
文摘A new stochastic volatility（SV）method to estimate the conditional value at risk（CVaR）is put forward.Firstly,it makes use of SV model to forecast the volatility of return.Secondly,the Markov chain Monte Carlo（MCMC）simulation and Gibbs sampling have been used to estimate the parameters in the SV model.Thirdly,in this model,CVaR calculation is immediate.In this way,the SV-CVaR model overcomes the drawbacks of the generalized autoregressive conditional heteroscedasticity value at risk（GARCH-VaR）model.Empirical study suggests that this model is better than GARCH-VaR model in this field.
文摘Purpose: This study expands on the results of a stakeholder-driven research project on quality indicators and output assessment of art and design research in Flanders-the Northern, Dutchspeaking region of Belgium. Herein, it emphasizes the value of arts & design output registration as a modality to articulate the disciplinary demarcations of art and design research.Design/methodology/approach: The particularity of art and design research in Flanders is first analyzed and compared to international examples. Hereafter, the results of the stakeholderdriven project on the creation of indicators for arts & design research output assessment are discussed. Findings: The findings accentuate the importance of allowing an assessment culture to emerge from practitioners themselves, instead of imposing ill-suited methods borrowed from established scientific evaluation models(Biggs & Karlsson, 2011)-notwithstanding the practical difficulties it generates. They point to the potential of stakeholder-driven approaches for artistic research, which benefits from constructing a shared metadiscourse among its practitioners regarding the continuities and discontinuities between "artistic" and "traditional" research, and the communal goals and values that guide its knowledge production(Biggs & Karlsson, 2011;Hellstr?m, 2010;Ysebaert & Martens, 2018). Research limitation: The central limitation of the study is that it focuses exclusively on the "Architecture & Design" panel of the project, and does not account for intra-disciplinary complexities in output assessment. Practical implications: The goal of the research project is to create a robust assessment system for arts & design research in Flanders, which may later guide similar international projects. Originality/value: This study is currently the only one to consider the productive potential of(collaborative) PRFSs for artistic research.
基金supported in part by 973 Program(2010CB328204)NSFC project(60932004)RFDP Project(20090005110013)
文摘Because of explosive growth in Internet traffic and high complexity of heterogeneous networks, improving the routing and wavelength assignment （RWA） algorithm in underlying optical networks has become very important. Where there are multiple links between different the node pairs, a traditional wavelength-assignment algorithm may be invalid for a wavelength-switched optical networks （WSON） that has directional blocking constraints. Also, impairments in network nodes and subsequent degradation of optical signals may cause modulation failure in the optical network. In this paper, we propose an RWA algorithm based on a novel evaluation model for a WSQN that has multiple constraints. The algorithm includes comprehensive evaluation model （CEM） and directional blocking constraint RWA based on CEM （DB-RWA）. Diverse constraints are abstracted into various constraint conditions in order to better assign routing and wavelength. We propose using the novel CEM to optimize routing according to an assessed value of constraints on transmission performance. This eliminates the effects of physical transmission impairments in a WSON. DB-RWA based on CEM abstracts directional blocking conditions in multiple links between network nodes into directional blocking constraints. It also satisfies rigorous network specifications and provides flexibility, scalability, and first-fit rate for the backbone, especially in multiple links between WSON nodes.
