Petroleum Research最新文献

{"title":"Economic and environmental impact assessment of carbon storage in Malaysia","authors":"Sitti Khadijah Shahul Hamid,&nbsp;M. Hasanuzzaman,&nbsp;Hossain Al Tanjil","doi":"10.1016/j.ptlrs.2025.12.004","DOIUrl":"10.1016/j.ptlrs.2025.12.004","url":null,"abstract":"<div><div>The global carbon emissions resulting from the combustion of fossil fuels have had a negative impact on the environment. This research presents an in-depth analysis of the economic and environmental impacts associated with carbon storage initiatives in Malaysia. It also explores the distributional effects of carbon pricing and the perception of its regressive nature as a significant challenge. Urgent and thorough measures are necessary to reduce carbon emissions from oil and gas, thereby mitigating the catastrophic consequences of climate change and facilitating a transition towards a more sustainable and environmentally responsible energy system. A comprehensive assessment of the potential impacts of Malaysia's carbon pricing policy on the Organization's economy and environment. Four cases were analyzed: (1) New Field Development, (2) New Field Development with Carbon Tax, (3) New Field Development with CCS and Carbon Tax, and (4) New Field Development with CCS, Carbon Tax, and Subsidy. The results show Internal Rates of Return (IRR) of approximately 16.5%, 14.5%, 12.8%, and 15.0–15.5% respectively. These findings highlight that a combined policy mix (carbon tax + CCS + subsidies) substantially improves economic viability, aligning with global best practices and offering a strong policy pathway for Malaysia.</div></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"11 3","pages":"Pages 695-711"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic loads on energy pipelines: Origins, mitigation strategies, and future research directions","authors":"Ardeshir Savari,&nbsp;Arameh Eyvazian,&nbsp;Narinderjit Singh Sawaran Singh","doi":"10.1016/j.ptlrs.2025.12.005","DOIUrl":"10.1016/j.ptlrs.2025.12.005","url":null,"abstract":"<div><div>Pipelines are an indispensable part of the global infrastructure for energy transportation, and their integrity poses a significant risk as the dynamic loads generated throughout their life cycle might result in catastrophic failures if not properly managed. A systematic review is presented, including the sources, effects, and mitigation measures of dynamic loads classified into four categories: environmental, mechanical, accidental, and human-induced. A thorough literature review highlights computational methods, particularly finite element method and computational fluid dynamics, contribute to estimating failure modes and developing preventive measures. Primary mitigation measures comprise flexible joints for the seismic response of pipelines, vortex-induced vibration suppressors for offshore applications, and protective barriers against impact loads. There are gaps in modeling coupled multi-axial loads and aging infrastructure under seismic loading conditions, with limitations in real-time monitoring. Adaptive computational frameworks integrating FSI with probabilistic risk assessments should be developed, with innovative technologies such as self-healing coatings and IoT-enabled monitoring requiring rigorous attention. This study aims to serve as a guide to enhancing pipeline resilience in extreme environments, thus directing future endeavors toward safe and sustainable transportation of energy through resilient infrastructures.</div></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"11 3","pages":"Pages 949-973"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inversion method for multi-section friction factors in horizontal wells based on Fisher optimal segmentation and SSA","authors":"Hu Yin,&nbsp;Qianyi Xia,&nbsp;Qiang Wei,&nbsp;Xiuwen Zhao,&nbsp;Qian Li","doi":"10.1016/j.ptlrs.2026.01.008","DOIUrl":"10.1016/j.ptlrs.2026.01.008","url":null,"abstract":"<div><div>The friction factor plays a critical role in drag and torque calculations. In the drag and torque model, the friction factor is typically treated as an average value, or the wellbore is roughly divided into casedhole and openhole segments with different values assigned. Such simplified model parameters fail to account for variations in the friction factor across different well segments, impacting the accuracy of the computations. Precise drag and torque calculations are significant, and the prerequisite for accurate drag prediction is the inverse analysis of realistic friction factor parameters. This study proposes a friction factor inverse analysis method based on morphological characteristics of measured data. The Fisher optimal segmentation method is employed to divide the field-measured data into multiple reasonable subsegments based on curve morphology features, indirectly determining the segmentation of the friction factor. The 3D stiff-string drag and torque model is used to establish friction factors inverse model, with corresponding friction factors introduced separately for the segmented well sections. The sparrow search algorithm, enhanced by opposition-based learning strategy, is utilized to optimize the segmented friction factors, with the optimization evaluation criteria simultaneously assessing the deviation and similarity between simulated and actual curves. Case studies demonstrate that the friction factor inverse analysis method proposed in this study, leveraging the curve morphology features of real-time drilling data, can efficiently obtain high-precision segmented friction coefficients. This method significantly reduces the error between simulated and field-measured data, improving calculation accuracy by about 50%, thus providing robust data support for accurate drag and torque prediction. Furthermore, the division approach can be applied during a round trip to optimize drilling parameters, enhancing the efficiency of drilling parameter control.</div></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"11 3","pages":"Pages 1021-1036"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new model of predicting the optimal mud density for maximizing the open-hole extension capacity in offshore extended-reach horizontal well drilling","authors":"Xuyue Chen,&nbsp;Gengchen Li,&nbsp;Qiqi Yang,&nbsp;Jin Yang,&nbsp;Deli Gao,&nbsp;Qinyi He","doi":"10.1016/j.ptlrs.2026.01.016","DOIUrl":"10.1016/j.ptlrs.2026.01.016","url":null,"abstract":"<div><div>The pressure fluctuation caused by the axial movement of the string easily causes the bottomhole pressure to exceed the safe pressure window, which seriously restricts the horizontal open-hole extension capacity (OHEC) of the offshore extended-reach horizontal wells (ERHWs). In this work, in order to improve the horizontal OHEC for ERHWs, an optimal mud density model in extended-reach horizontal drilling (ERHD) was established based on the prediction and analysis of horizontal OHEC of ERHWs under string tripping operations. The results show that with the increase of mud density, the horizontal OHEC has a trend of first increasing and then decreasing in both tripping operations and casing tripping operations, and there exists an optimal mud density to maximize the horizontal OHEC. The optimal mud density of the two operations is obtained when the horizontal OHEC of the two operations is equal, and it is positively correlated with pull out of hole (POOH) speed, diameter of the wellbore and drill string, whereas it is negatively correlated with diameter of the casing and casing running speed. Controlling the tripping speed and optimizing the rheological properties are crucial to improve the horizontal OHEC. This model can provide scientific basis for optimization design of ERHD and the improvement of horizontal OHEC of ERHWs.</div></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"11 3","pages":"Pages 995-1007"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced machine learning approaches for optimizing waterflooding: A focus on injector-producer dynamics","authors":"Samuel Nashed,&nbsp;Oluchi Ejehu,&nbsp;Rouzbeh Moghanloo","doi":"10.1016/j.ptlrs.2026.01.001","DOIUrl":"10.1016/j.ptlrs.2026.01.001","url":null,"abstract":"<div><div>Waterflooding persists as the primary secondary oil recovery method, although its efficiency evaluation is often hindered by limitations from reservoir heterogeneities alongside non-uniform sweep efficiency and uncertainty in predicting well-to-well connectivity. To improve the evaluation of waterflooding, this research develops and validates nine advanced machine learning models, covering key types such as neural networks, linear models, tree-based models, ensemble learning, and support vector machines. This research utilized a dataset of 6592 observations collected across four wells over 2000 days to train and evaluate these machine learning models for fluid production rate forecasting and injector-producer connectivity assessments. The most successful model was AdaBoost since it delivered both a minimum root mean squared error (RMSE) of 0.004 and a coefficient of determination (R²) of 0.99, surpassing traditional methods. Furthermore, SHapley Additive Explanations (SHAP) analysis provided interpretability by quantifying injection wells’ relative influence on production rates, facilitating the construction of a connectivity-driven contour map. Traditional evaluation methods of empirical and analytical approaches, as well as capacitance-resistance models and numerical simulators, function under restrictive assumptions, extensive computational requirements, and significant data demands. This study is novel in uniting multiple ML algorithms with SHAP interpretability and a connectivity-driven contour map for injector–producer dynamics, providing a practical, real-time workflow for field-scale waterflood optimization. The results of this study demonstrate that ML models surpass traditional methods in terms of predictive accuracy, computer processing speed, and scalability when applied for real-time waterflood optimization. This study illustrates the transformative potential of ML in reservoir engineering by enabling data-driven decision-making and improving the injection optimization process.</div></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"11 3","pages":"Pages 827-837"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new prediction model of bottomhole weight on bit in offshore extended-reach drilling based on the integration of intelligent algorithms and the physical models of rate of penetration","authors":"Shuohang Xue,&nbsp;Yanan Geng,&nbsp;Xuyue Chen,&nbsp;Yi Wu,&nbsp;Changsuo Zhou,&nbsp;Bingxuan Li,&nbsp;Pengbo Li","doi":"10.1016/j.ptlrs.2026.01.005","DOIUrl":"10.1016/j.ptlrs.2026.01.005","url":null,"abstract":"<div><div>Offshore extended-reach drilling is widely employed for the efficient development of deepwater hydrocarbon fields. However, the complex subsea formation environment and downhole frictional losses lead to significant inaccuracies and limitations in bottomhole weight on bit (WOB) calculations, severely impacting drilling operations. Therefore, this study proposes an improved bottomhole WOB prediction model that combines CNN-BiLSTM networks with Transformer encoders. By introducing a loss function (named DRE) based on the rate of penetration equation into the intelligent algorithm, four models were constructed: CNN-BiLSTM, CNN-Encoder-BiLSTM, CNN-BiLSTM (DRE), and CNN-Encoder-BiLSTM (DRE). The eight models were compared and evaluated, including both the established models and conventional models. Experimental results show that the newly developed CNN-Encoder-BiLSTM (DRE) model parameters' influence degree basically conforms to the DRE with high generalization capability. On the test well, it achieved MAE of 0.859, MRE of 0.1, MAPE of 10%, MSE of 1.201, and R² of 0.867, demonstrating good performance. The research results prove that the new model is suitable for bottomhole WOB prediction in offshore extended-reach wells, which is expected to improve drilling efficiency and enable subsequent complex situation analysis, providing new ideas for intelligent drilling research in the marine sector.</div></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"11 3","pages":"Pages 912-926"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fluid flow mechanisms in tight gas reservoirs: A case study of Xujiahe formation in the central Sichuan basin","authors":"Jia Kang,&nbsp;Gang Liu,&nbsp;Xin Kang,&nbsp;Peng Hu,&nbsp;Licai Qu","doi":"10.1016/j.ptlrs.2026.01.018","DOIUrl":"10.1016/j.ptlrs.2026.01.018","url":null,"abstract":"<div><div>Tight sandstone gas reservoirs exhibit low gas abundance and extensive gas-bearing lithology, presenting promising prospects for future exploration and development. However, their exploitation in the Sichuan Basin is severely constrained by low recovery efficiency, high water saturation, and pronounced retrograde condensation phenomena. In this study, we aim to analyze the complex fluid flow behavior within these reservoirs to overcome these challenges. To achieve this, a comprehensive experimental program is utilized, encompassing nuclear magnetic resonance, micro-computed tomography, core flooding, and retrograde condensation tests. The analysis reveals that tight sandstone reservoirs feature low porosity, low permeability, and poor pore connectivity, with pore structures predominantly composed of nanometer-to 10-μm-size micropores. Pore size distributions in both Type I and Type II reservoirs exhibit multimodal characteristics, rendering them highly sensitive to stress changes and condensate-induced formation damage. Permeability demonstrates significant hysteresis effects during cyclic changes in confining pressure. Precisely, after two complete cycles of increasing and decreasing confining pressure, average permeability damage rates reach 52.08% and 46.1%, respectively. This indicates damage levels ranging from moderate-weak to moderate-strong. In contrast, variations in pore pressure exhibit minimal impact on permeability. Under irreducible water saturation conditions, the average gas phase damage rate is 64%. Furthermore, initiating fluid flow within the reservoir requires a specific threshold pressure. The average damage rate caused by retrograde condensation is 24.7%. This experimental investigation elucidates the reservoir's pore-throat characteristics, the dynamics governing gas-water and gas-oil flow, and the damage patterns associated with retrograde condensation. These insights provide critical foundational data for optimizing development strategies and designing effective stimulation measures to achieve enhanced recovery.</div></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"11 3","pages":"Pages 730-742"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dominant lithofacies and hydrocarbon enrichment characteristics of lacustrine shale reservoirs: A case study of the Qingshankou Formation shale in the Southern Songliao Basin","authors":"Jialin Wan,&nbsp;Lang Liu,&nbsp;Qifeng Jia,&nbsp;Mengmeng Liu,&nbsp;Zhiyu Fang","doi":"10.1016/j.ptlrs.2026.01.004","DOIUrl":"10.1016/j.ptlrs.2026.01.004","url":null,"abstract":"<div><div>With the growing challenges in conventional hydrocarbon exploration, shale oil has emerged as a critical target for future energy supply. The Qingshankou Formation (K₂qn) in the southern Songliao Basin holds significant shale oil potential. However, the complex laminae architecture and poorly constrained lithofacies have hindered a clear understanding of shale oil enrichment mechanisms, thereby limiting efficient exploration and development. This study focuses on the K₂qn shale in the Changling Sag, where a comprehensive characterization of lithofacies and pore structures is carried out using an integrated approach of core description, geochemical analysis, and multi-scale imaging techniques, including thin-section petrography, micro-XRF, MAPS, QEMSCAN, and fluid injection experiments. Three types of argillaceous laminae are identified to reveal significant textural and structural heterogeneity in the shale. Pore systems are dominated by interparticle pores and microfractures, with microfractures playing a crucial role in enhancing pore connectivity and fluid transport. The results also indicate that reservoir quality is jointly controlled by organic matter content, mineral composition, and laminae characteristics. Importantly, two enrichment models are proposed that the layered mixed shale with medium to high organic matter represents a migration-accumulated model influenced by external hydrocarbon input, and the laminated siliceous shale and the mixed shale, both with moderate to high organic content, follow in-situ accumulation patterns dominated by thermal transformation of indigenous organic matter. These findings offer critical geological insights to guide more accurate reservoir prediction and targeted exploration in the lacustrine shale systems.</div></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"11 3","pages":"Pages 712-729"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of grid refinement, foam model, and peaceman model on gas and liquid injectivities during SAG foam EOR: An FFT benchmarking study","authors":"Rodrigo O. Salazar Castillo,&nbsp;Lily Qian,&nbsp;Bibiana Téllez García,&nbsp;William R. Rossen","doi":"10.1016/j.ptlrs.2025.12.001","DOIUrl":"10.1016/j.ptlrs.2025.12.001","url":null,"abstract":"<div><div>Surfactant-Alternating-Gas (<em>SAG</em>) utilizes foam to reduce gas mobility and improve reservoir sweep efficiency in gas-injection enhanced oil recovery and carbon capture and storage. Although <em>SAG</em> is known to have many benefits that increase hydrocarbon recovery, liquid injectivity is typically very poor during a <em>SAG</em> process. Conventional foam simulators use the Peaceman model to estimate injection-well pressure. However, because they assume uniform saturation in the grid block, they do not account for near-wellbore saturation distribution that improves gas and liquid injectivities during a <em>SAG process</em>. We use a conventional foam simulator to test the impact of grid refinement on injectivity. We compare simulation results to those with fractional-flow theory (<em>FFT</em>) using the a model very widely used in simulations. In addition, we test the effect of complete foam collapse at irreducible water saturation (<em>S</em>_<em>wr</em>), of neglecting the Peaceman model, and of disallowing foam in the injector grid block. We compare the transient behaviors and the average injectivities, calculated during one pore volume of injected fluid. Our results show that in a conventional simulation (including the Peaceman model) grid refinement increases gas and liquid injectivities. However, the results do not match <em>FFT</em> predictions. The assumption of complete foam collapse at <em>S</em>_<em>wr</em> increases gas injectivity (still without matching <em>FFT</em> results); however, it has a smaller impact on liquid injectivity and grid refinement results in an increase in gas and liquid injectivities. Excluding the Peaceman model reduces the error in simulated injectivities at coarse grid refinements but still without matching the <em>FFT</em> prediction. Finally, the procedure of excluding foam in the injection-well grid block gives average injectivities like our <em>FFT</em> calculations without requiring extraordinary grid refinement.</div></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"11 3","pages":"Pages 799-814"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of fracturing fluid rheology on proppant transport and elbow erosion: A comparative CFD-DEM study","authors":"Chun-Rong Wang,&nbsp;Peng Wang,&nbsp;Xing-Yang Guo,&nbsp;Shi-Wei Qiao,&nbsp;Jian-Ping Yuan,&nbsp;Yan-Dong Gu,&nbsp;Fan Meng,&nbsp;Qiao-Rui Si","doi":"10.1016/j.ptlrs.2026.01.006","DOIUrl":"10.1016/j.ptlrs.2026.01.006","url":null,"abstract":"<div><div>To enable the precise prediction and control of erosion in hydraulic fracturing pipelines, this study employs a CFD-DEM method coupled with a wear model to quantitatively analyze the influence of shear-thinning fracturing fluids on proppant transport and elbow erosion. The study reveals a critical, non-monotonic effect of fluid concentration on erosion. Compared to the water baseline, the low-concentration (0.2%) fluid, by enhancing particle impact kinetic energy, counter-intuitively caused the maximum elbow erosion rate to surge by approximately 40%. However, as the concentration was further increased to 0.4%, the fluid's effective viscosity became dominant, causing the maximum erosion rate to plummet relative to the 0.2% case, ultimately falling to a level ∼8% below the water baseline. More importantly, the high-concentration fluid altered particle trajectories, leading to a significant shift of the peak erosion zone from the elbow's midpoint (∼77°) to its outlet (90°). This finding quantifies the complex impact of fracturing fluid rheology on erosion and provides critical data and a new perspective for proactively managing pipeline integrity by optimizing the fluid's non-Newtonian properties.</div></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"11 3","pages":"Pages 880-894"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}