Geoenergy Science and Engineering最新文献_第5页

Investigation on rock-breaking and debris transport of high-pressure water jet drilling using the discrete element method (DEM)

0 ENERGY & FUELS

Geoenergy Science and Engineering

Pub Date : 2025-02-13 DOI: 10.1016/j.geoen.2025.213750

Qi Zeng , Xianpeng Yang , Jie Tu , Huaizhou Wei , Xiaohong Yuan , Can Cai , Hao Chen

To address the problems of low drilling efficiency and high cost in deep formation drilling, a new method combining high-pressure water jet and PDC (polycrystalline diamond compact) tools is proposed. However, the rock-breaking and debris transport of composite rock-breaking technology of high-pressure water jets and PDC cutter in jet drilling are still unknown. In this paper, a numerical model of high-pressure water jet and PDC tooth composite rock-breaking is established by the discrete element method and verified with experimental results. Combined with the research results, the rock-breaking mechanism is investigated from the perspectives of crack extension, interfacial friction angle and cutting force. Additionally, the effects of water jet parameters (jet velocity, jet diameter, jet angle, and striking distance) and confining pressure on composite rock-breaking are investigated. Research results show that as jet velocity increases, the impact force on the rock also increases, resulting in greater pit depth and diameter in the impact area, indicating that water jets can cause pre-damage to the rock; The optimal jet parameters are 75° jet angle, 50 m/s jet velocity, 1–1.5 mm jet diameter, and 10–15 mm stand-off distance, which was 10–15 times of the nozzle diameter, respectively; Applying a certain axial confining pressure can improve the efficiency of rock-breaking, and axial confining pressure is easier to load in the range of 0–10 MPa. The above research can provide theoretical support and technical guidance for composite rock-breaking, which is helpful for the improvement of water jet drilling technology and the design of composite drill bits.

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引用次数: 0

Deep learning framework for history matching CO2 storage with 4D seismic and monitoring well data

0 ENERGY & FUELS

Geoenergy Science and Engineering

Pub Date : 2025-02-12 DOI: 10.1016/j.geoen.2025.213736

Nanzhe Wang, Louis J. Durlofsky

Geological carbon storage entails the injection of megatonnes of supercritical CO

_{2}

into subsurface formations. The properties of these formations are usually highly uncertain, which makes design and optimization of large-scale storage operations challenging. In this paper we introduce a history matching strategy that enables the calibration of formation properties based on early-time observations. Early-time assessments are essential to assure the operation is performing as planned. Our framework involves two fit-for-purpose deep learning surrogate models that provide predictions for in-situ monitoring well data and interpreted time-lapse (4D) seismic saturation data. These two types of data are at very different scales of resolution, so it is appropriate to construct separate, specialized deep learning networks for their prediction. This approach results in a workflow that is more straightforward to design and more efficient to train than a single surrogate that provides global high-fidelity predictions. The deep learning models are integrated into a hierarchical Markov chain Monte Carlo (MCMC) history matching procedure. History matching is performed on a synthetic case with and without 4D seismic data, which allows us to quantify the impact of 4D seismic on uncertainty reduction. The use of both data types is shown to provide substantial uncertainty reduction in key geomodel parameters and to enable accurate predictions of CO

_{2}

plume dynamics. The overall history matching framework developed in this study represents an efficient way to integrate multiple data types and to assess the impact of each on uncertainty reduction and performance predictions.

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引用次数: 0

Digital rock super-resolution reconstruction with efficient 3D spatial-adaptive feature modulation network

0 ENERGY & FUELS

Geoenergy Science and Engineering

Pub Date : 2025-02-08 DOI: 10.1016/j.geoen.2025.213748

Jinye Wang , Yongfei Yang , Fugui Liu , Lei Zhang , Hai Sun , Junjie Zhong , Kai Zhang , Jun Yao

High-quality digital rock images are important for studying the micropore structure and flow characteristics of reservoirs, these images should be characterized by high resolution and large field of view (FOV). However, due to the limited imaging capability of the hardware equipment, high resolution and large FOV are often in conflict with each other. The super-resolution (SR) reconstruction techniques, which can extract features from low-resolution images to restore high-resolution details, are currently the main means of improving image resolution. For reconstructing high-quality 3D digital rock images, we propose a new 3D Spatial-Adaptive Feature Modulation Network (3DSAFMN), which inherits the spatial modelling capability of Transformer, fuses the multi-scale input information, and accomplishes the optimization of efficiency and accuracy. The evaluation results show that compared with the current advanced deep learning algorithm, the number of parameters of 3DSAFMN is reduced by 45.5%, the reconstruction speed is increased by 1.70 times, and the reconstruction effect is better. Visualization shows that 3DSAFMN can eliminate noise and blur to the maximum extent and highlight valuable features such as pores, fractures and minerals. Furthermore, we apply 3DSAFMN to external sandstone samples to verify the generalization ability of the model. The pore structure parameters calculation and direct flow simulation demonstrate that the reconstruction results are very close to the real samples in terms of both geometric topology and connectivity. In summary, this work provides an effective and reliable novel model based on deep learning for resolution enhancement of digital rock images.

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引用次数: 0

Optimization of drilling rate based on genetic algorithms and machine learning models

0 ENERGY & FUELS

Geoenergy Science and Engineering

Pub Date : 2025-02-08 DOI: 10.1016/j.geoen.2025.213747

Fang Shi , Hualin Liao , Shuaishuai Wang , Omar Alfarisi , Fengtao Qu

During the oil and gas exploration phase, the drilling rate is a key indicator for assessing efficiency, and its accurate prediction is crucial for optimizing exploration and production. By constructing multiple data-driven intelligent drilling rate prediction models, including Decision Tree (DT), Random Forest (RF), Support Vector Regression (SVR), LassoCV, K-Nearest Neighbors (KNN), Multi-Layer Perceptron (MLP), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LGBM), and combining them with Genetic Algorithm (GA) to explore the globally optimal model parameter combinations, the accuracy of drilling rate predictions is enhanced. The models are compared and analyzed based on Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R-squared (R²), with GA-LGBM identified as the optimal intelligent drilling rate prediction model. The GA-LGBM model demonstrated good generalization ability and robustness in field tests on two wells. SHapley Additive exPlanations (SHAP) plots are used to analyze the contribution and impact of parameter features on the predictions. Adjustments to positively impactful parameters are made to optimize the drilling rate. Additionally, two-dimensional contour plots illustrate the variation trends of drilling rate under different Weight on Bit (WOB) and RPM conditions, providing reliable data support and visual guidance for optimizing drilling rate. This research provides engineers with reliable data support and strategic guidance, aiding them in strategy control and optimal parameter adjustments for drilling operations under complex conditions.

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引用次数: 0

Time series production forecasting of natural gas based on transformer neural networks

0 ENERGY & FUELS

Geoenergy Science and Engineering

Pub Date : 2025-02-08 DOI: 10.1016/j.geoen.2025.213749

Mandella Ali M. Fragalla, Wei Yan, Jingen Deng, Liang Xue, Fathelrahman Hegair, Wei Zhang, Guangcong Li

Time series forecasting of gas production plays a crucial role in enhancing the stability of production, optimizing development strategies, and effectively increase the life cycle of gas wells. However, the precision of these forecasts is often compromised by two primary factors: (1) the complexity and randomness inherent in production time series data and (2) the limited ability to model dependencies within temporal sequences, especially in the context of long-term, multi-step forecasts, which can lead to instability in the prediction model's results. To address these challenges, this paper introduces a novel method. Initially, Multilevel Discrete Wavelet Decomposition (MDWD) is employed to mitigate the raw gas production series' instability, complexity, and randomness. This is achieved by decomposing the input signals into their respective periodic and trend components. Subsequently, gas production modeling is executed using transformer neural networks equipped with a multi-head attention mechanism to learn sequential dependencies effectively, irrespective of the temporal distance. The architecture of this model is built upon an encoder-decoder framework. The encoder is designed to generate representations of historical gas production sequences of any length, while the decoder can generate arbitrarily long future gas production sequences. The interconnection between the encoder and decoder through the multi-head attention mechanism is a crucial aspect of this model. In two distinct experiments focusing on gas filed production data, the RMSE for one-step forecasting results produced by the proposed method was remarkably low, at 0.1911 and 0.3816, respectively. Moreover, the RMSE for 7-day multi-step predictions stood at 1.7358 and 1.2146, respectively, showcasing significant improvements over other methods. With accurate results of multi-step forecasting, this work contributes to the effective utilization of conventional and unconventional energy resources.

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引用次数: 0

A hierarchical approach for modeling regional pressure interference in multi-site CO2 operations

0 ENERGY & FUELS

Geoenergy Science and Engineering

Pub Date : 2025-02-06 DOI: 10.1016/j.geoen.2025.213733

Svenn Tveit, Sarah E. Gasda, David Landa-Marbán, Tor Harald Sandve

Scale-up of carbon capture and storage (CCS) operations to meet future climate targets will require large-scale, centralized storage of CO

_{2}

in geological formations involving multiple injection sites co-located within the same regional aquifer. Understanding the potential pressure communication and interference between individually operated CO

_{2}

injection sites is crucial to maximize storage capacity of both the region as a whole and the storage targets of each individual site. Typically, simulation models for each site are developed independently from neighboring sites using proprietary data. Moreover, each site model will contain finer details and more complexity than a regional model covering the entire aquifer system. Furthermore, commercial interests may restrict the exchange of information between sites and with a regional model. As such, we propose a simulation workflow where information from the regional model is transferred to the site model in a hierarchical approach. The approach is performed in two stages, where the first stage is to simulate multi-site injection on a regional model, obtaining a coarse pressure solution. The second stage is projecting regional pressure or flux information as dynamic boundary conditions for the site simulation model. The two-stage approach is validated in terms of performance and accuracy on several numerical test cases based on the open Troll Aquifer model dataset. The numerical results show that the two-stage approach is able to reliably approximate the reference solution in most cases, with projecting pressure values being the overall best approach. Finally, the two-stage approach is applied to the Troll Aquifer regional model, a real site in the Norwegian North Sea, indicating good performance in presence of challenging grid geometries and realistic heterogeneity.

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引用次数: 0

Factors affecting the attenuation of mud positive pulse signals in measurement while drilling and optimization strategies

0 ENERGY & FUELS

Geoenergy Science and Engineering

Pub Date : 2025-02-04 DOI: 10.1016/j.geoen.2025.213726

Wenbo Chen , Chao Wang , Feng Zheng , Jun Li , Gonghui Liu , Shuangjin Zheng

During measurement while drilling (MWD), mud pulse signals experience significant attenuation as they propagate upward due to the properties of drilling fluid and frictional losses. This makes decoding surface signals challenging, while the downward propagation of signals to the wellbore can lead to formation blowout. Therefore, it is essential to analyze the factors influencing mud positive pulse attenuation and develop an optimization method to enhance surface signal reception while mitigating bottom-hole pressure fluctuations This paper establishes a mud positive pulse transmission attenuation model based on one-dimensional water hammer theory, solved using the method of characteristic lines. Wavelet decomposition and reconstruction are applied to extract positive pulse amplitudes from the simulation results. The study employs control variates to investigate the effects of drilling fluid density, consistency coefficient, liquidity index, mud pump rate, and well depth on mud pulse signal attenuation. These factors are further used as decision variables in the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to propose a dual-objective optimization method tailored for ultra-deep wells with narrow safe density windows. The results demonstrate strong agreement between the model predictions and measured bottom-hole pressure in terms of amplitude and inflection point timing, validating the model’s accuracy. Within certain ranges, increasing drilling fluid density leads to greater attenuation of the positive pulse amplitude transmitted to the surface. The attenuation rate shows a pattern of initial increase, followed by a decrease, and then another increase. Additionally, increases in the consistency coefficient, liquidity index, mud pump rate, or well depth result in higher attenuation of the positive pulse amplitude, with a corresponding rise in attenuation rate. In a 7000-m vertical well, the proposed optimization method reduces the bottom-hole negative pulse amplitude by approximately 90.7% to 92.6% and enhances the positive pulse amplitude at the riser by 33.3% to 50.7%. This study provides significant theoretical and methodological guidance for the application of MWD systems in drilling operations

{"title":"Factors affecting the attenuation of mud positive pulse signals in measurement while drilling and optimization strategies","authors":"Wenbo Chen , Chao Wang , Feng Zheng , Jun Li , Gonghui Liu , Shuangjin Zheng","doi":"10.1016/j.geoen.2025.213726","DOIUrl":"10.1016/j.geoen.2025.213726","url":null,"abstract":"<div><div>During measurement while drilling (MWD), mud pulse signals experience significant attenuation as they propagate upward due to the properties of drilling fluid and frictional losses. This makes decoding surface signals challenging, while the downward propagation of signals to the wellbore can lead to formation blowout. Therefore, it is essential to analyze the factors influencing mud positive pulse attenuation and develop an optimization method to enhance surface signal reception while mitigating bottom-hole pressure fluctuations This paper establishes a mud positive pulse transmission attenuation model based on one-dimensional water hammer theory, solved using the method of characteristic lines. Wavelet decomposition and reconstruction are applied to extract positive pulse amplitudes from the simulation results. The study employs control variates to investigate the effects of drilling fluid density, consistency coefficient, liquidity index, mud pump rate, and well depth on mud pulse signal attenuation. These factors are further used as decision variables in the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to propose a dual-objective optimization method tailored for ultra-deep wells with narrow safe density windows. The results demonstrate strong agreement between the model predictions and measured bottom-hole pressure in terms of amplitude and inflection point timing, validating the model’s accuracy. Within certain ranges, increasing drilling fluid density leads to greater attenuation of the positive pulse amplitude transmitted to the surface. The attenuation rate shows a pattern of initial increase, followed by a decrease, and then another increase. Additionally, increases in the consistency coefficient, liquidity index, mud pump rate, or well depth result in higher attenuation of the positive pulse amplitude, with a corresponding rise in attenuation rate. In a 7000-m vertical well, the proposed optimization method reduces the bottom-hole negative pulse amplitude by approximately 90.7% to 92.6% and enhances the positive pulse amplitude at the riser by 33.3% to 50.7%. This study provides significant theoretical and methodological guidance for the application of MWD systems in drilling operations</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"247 ","pages":"Article 213726"},"PeriodicalIF":0.0,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143218676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Retraction notice to “Impact of nozzle size on shale gas productivity in the Longmaxi formation, Sichuan basin, China” [Geoenergy Sci. Eng. 227C (2023) 211836]

0 ENERGY & FUELS

Geoenergy Science and Engineering

Pub Date : 2025-02-01 DOI: 10.1016/j.geoen.2024.213465

Tong Zhou , Haibo Wang , Yakai Tian , Ning Li , Ruyue Wang

引用次数: 0

Pore-scale investigation of supercritical multi-component thermal fluid flooding in deep heavy oil reservoirs

0 ENERGY & FUELS

Geoenergy Science and Engineering

Pub Date : 2025-02-01 DOI: 10.1016/j.geoen.2025.213734

Qingjun Du , Jie Shen , Yu Xue , Haizhong Yang , Qiyu Wang , Ruixin Liu , Xiangquan Lu , Teng Lu , Jian Hou , Xinru Zhao

Supercritical multi-component thermal fluid (SCMTF) flooding, which is an innovative technology for the development of deep heavy oil reservoirs, characterized by its high heat-carrying capacity, enhanced miscibility, and environmental sustainability, includes supercritical water (SC-W), supercritical carbon dioxide (SC-CO₂), and supercritical nitrogen (SC-N₂). Due to the existence of various mechanisms such as heavy oil component reactions, coking, miscible phase interaction, and multi-component synergistic effects during the SCMTF displacement process, the microscopic interaction mechanisms at the pore throat level are extremely complex. Currently, there is a lack of effective simulation means in this regard. This work has developed a pore-scale modeling workflow for SCMTF flooding. Firstly, a multi-component molecular model of heavy oil was developed to determine the diffusion coefficients of SCMTF in heavy oil. Subsequently, a numerical simulation model characterizing the reaction of heavy oil in a supercritical water atmosphere is established. Finally, a rapid conversion process from porous media images to models was established to characterize the influence of coke deposition on rock pore structure. In addition, the influence of reservoir and fluid properties on the oil displacement efficiency of SCMTF was analyzed. The accuracy of the model has been proven by comparing with experiments or analytical solutions. The results indicate that: The increase of SC-W and SC-CO₂ will increase the diffusion coefficient of SCMTF and heavy oil. A higher Péclet number results in weak miscibility between the injected fluid and heavy oil. The increase in permeability contrast will destroy the stability of the displacement front and lead to a decrease in recovery. As the reaction time increases, the light components content in heavy oil increases, and coke begins to be produced after 110 min, reducing the permeability and porosity of the rock. The increase in reaction temperature will reduce the light components content.

{"title":"Pore-scale investigation of supercritical multi-component thermal fluid flooding in deep heavy oil reservoirs","authors":"Qingjun Du , Jie Shen , Yu Xue , Haizhong Yang , Qiyu Wang , Ruixin Liu , Xiangquan Lu , Teng Lu , Jian Hou , Xinru Zhao","doi":"10.1016/j.geoen.2025.213734","DOIUrl":"10.1016/j.geoen.2025.213734","url":null,"abstract":"<div><div>Supercritical multi-component thermal fluid (SCMTF) flooding, which is an innovative technology for the development of deep heavy oil reservoirs, characterized by its high heat-carrying capacity, enhanced miscibility, and environmental sustainability, includes supercritical water (SC-W), supercritical carbon dioxide (SC-CO<sub>2</sub>), and supercritical nitrogen (SC-N<sub>2</sub>). Due to the existence of various mechanisms such as heavy oil component reactions, coking, miscible phase interaction, and multi-component synergistic effects during the SCMTF displacement process, the microscopic interaction mechanisms at the pore throat level are extremely complex. Currently, there is a lack of effective simulation means in this regard. This work has developed a pore-scale modeling workflow for SCMTF flooding. Firstly, a multi-component molecular model of heavy oil was developed to determine the diffusion coefficients of SCMTF in heavy oil. Subsequently, a numerical simulation model characterizing the reaction of heavy oil in a supercritical water atmosphere is established. Finally, a rapid conversion process from porous media images to models was established to characterize the influence of coke deposition on rock pore structure. In addition, the influence of reservoir and fluid properties on the oil displacement efficiency of SCMTF was analyzed. The accuracy of the model has been proven by comparing with experiments or analytical solutions. The results indicate that: The increase of SC-W and SC-CO<sub>2</sub> will increase the diffusion coefficient of SCMTF and heavy oil. A higher Péclet number results in weak miscibility between the injected fluid and heavy oil. The increase in permeability contrast will destroy the stability of the displacement front and lead to a decrease in recovery. As the reaction time increases, the light components content in heavy oil increases, and coke begins to be produced after 110 min, reducing the permeability and porosity of the rock. The increase in reaction temperature will reduce the light components content.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"247 ","pages":"Article 213734"},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143372208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Technical initiatives to develop low-medium temperature geothermal resources in Indonesia: Lessons learned from the United States

0 ENERGY & FUELS

Geoenergy Science and Engineering

Pub Date : 2025-01-31 DOI: 10.1016/j.geoen.2025.213720

Vincentius Adven Brilian , Dorman P. Purba , Daniel W. Adityatama , Triwening Larasati , M. Rizqi Al Asy’ari , Nadya Erichatama , Tracy T. Caesaria , Khasani

The geothermal power plant development in Indonesia reached an installed capacity of 2413 MW at the end of 2023, equivalent to 11% of Indonesia's geothermal potential of 23 GW. However, the development of geothermal energy in Indonesia is still predominantly focused on high-temperature resources, with only 8.29 MW (0.3%) of the total installed capacity coming from low-medium temperature resources. One of the challenges hindering the development of low-medium temperature geothermal resources is the less attractive economic viability of these resources compared to high-temperature resources because the development of low-medium temperature geothermal resources requires the use of downhole pumps to discharge the fluid and the more expensive binary plant technology compared to flash plants.

Meanwhile, 9 low-medium temperature geothermal fields with development plans totaling up to 430 MW are included in Indonesia's National Strategic Project (PSN) pipeline until 2030. Therefore, this study aims to identify potential technical initiatives to develop low-medium temperature geothermal resources in Indonesia by extracting the lessons that can be learned from the United States through literature reviews including targeting shallow outflow zones, utilizing downhole pumps, and implementing well stimulations in the development of low-medium temperature geothermal resources.

{"title":"Technical initiatives to develop low-medium temperature geothermal resources in Indonesia: Lessons learned from the United States","authors":"Vincentius Adven Brilian , Dorman P. Purba , Daniel W. Adityatama , Triwening Larasati , M. Rizqi Al Asy’ari , Nadya Erichatama , Tracy T. Caesaria , Khasani","doi":"10.1016/j.geoen.2025.213720","DOIUrl":"10.1016/j.geoen.2025.213720","url":null,"abstract":"<div><div>The geothermal power plant development in Indonesia reached an installed capacity of 2413 MW at the end of 2023, equivalent to 11% of Indonesia's geothermal potential of 23 GW. However, the development of geothermal energy in Indonesia is still predominantly focused on high-temperature resources, with only 8.29 MW (0.3%) of the total installed capacity coming from low-medium temperature resources. One of the challenges hindering the development of low-medium temperature geothermal resources is the less attractive economic viability of these resources compared to high-temperature resources because the development of low-medium temperature geothermal resources requires the use of downhole pumps to discharge the fluid and the more expensive binary plant technology compared to flash plants.</div><div>Meanwhile, 9 low-medium temperature geothermal fields with development plans totaling up to 430 MW are included in Indonesia's National Strategic Project (PSN) pipeline until 2030. Therefore, this study aims to identify potential technical initiatives to develop low-medium temperature geothermal resources in Indonesia by extracting the lessons that can be learned from the United States through literature reviews including targeting shallow outflow zones, utilizing downhole pumps, and implementing well stimulations in the development of low-medium temperature geothermal resources.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"247 ","pages":"Article 213720"},"PeriodicalIF":0.0,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143218887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0