Day 2 Tue, August 06, 2019最新文献

{"title":"Using Reservoir Navigation Service and Formation Pressure Testing to Meet Drilling Objectives in Offshore Niger Delta","authors":"Victor Imomoh, C. Ndokwu, K. Amadi, Oluwaseun Toyobo, I. Nwabueze, Victor Okowi, Oyekunle Ajao, Genevieve Okeke, Y. Dada, Sandison Jumbo, S. Aina","doi":"10.2118/198716-MS","DOIUrl":"https://doi.org/10.2118/198716-MS","url":null,"abstract":"\u0000 Oil and gas drilling has fully embraced the practice of drilling horizontal and extended-reach wells in place of deviated wells to avoid multi-platform drilling and increase hydrocarbon recovery. However, the producer is still faced with multiple challenges that include lateral facies change, lateral variation in reservoir properties and structural uncertainties. Consequently, it is paramount that continuous advancement is achieved in combining fit-for-purpose, real-time logging-while-drilling (LWD) solutions to assist further in the enhancement of hydrocarbon recovery.\u0000 Reservoir navigation services (RNS) involve predicting the geology ahead of the bit to place the wellbore correctly in the zone of interest in a horizontal or near-horizontal path. LWD data, obtained from downhole drilling suites, transmitted in real time through mud pulses to a surface computer where the data are interpreted and used to steer the well in the desired direction. Formation pressure while drilling (FPWD) is a process of acquiring reservoir pressures downhole and this is done with a specialized downhole LWD pressure-testing tool. The use of RNS in Well-MX played a significant role in the drilling project – landing Well-MX in the targeted M reservoir bed and drilling the lateral section. The major geosteering technologies used are the at-bit resistivity and azimuthal propagation resistivity, which provides geostopping capability, reservoir bed boundary mapping and accurate distance to bed boundary calculation. These technologies helped in keeping the wellbore within the hydrocarborn unit of the M reservoir. Performing formation pressure testing in realtime, the team was able to carry out a reservoir gradient analysis which helped with reservoir fluid identification, fluid contact determination, and connectivity of hydrocarbon zones before drilling was concluded.\u0000 Well-MX is a horizontal well located in the Mirum field of the Niger Delta Basin, offshore Nigeria. The well was drilled to target the deep multi-lobed M reservoir to a total hole depth of 11,307ft MD. By using Well-MX as a case study, this paper discusses how the combination of reservoir navigation service and real-time formation pressure sampling helped meet drilling objectives for this well. Some of the challenges encountered includes vertical seismic interpretation uncertainty, poor reservoir quality along the drain hole section, change in depth of oil to water contact and undulating bed boundaries. Other challenges and decisions taken to successfully geosteer the well will be reviewed in this paper.","PeriodicalId":11110,"journal":{"name":"Day 2 Tue, August 06, 2019","volume":"69 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86756764","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}

{"title":"A Computer-Aided Hydrate Management System","authors":"Databa Lawson-Jack, T. Odutola, Ogbonda Douglas Chukwu","doi":"10.2118/198775-MS","DOIUrl":"https://doi.org/10.2118/198775-MS","url":null,"abstract":"\u0000 In this study, a computer-aided system for effective hydrate management is presented. A flowchart was developed to suggest possible intervention approaches to follow in the event that hydrates are restricting flow in flowlines. Using VBA® in Excel, a worksheet was developed to serve as a direct means of proposing an intervention approach to adopt after confirming the cause(s) of hydrate formation in the flowline that is monitored. The worksheet created suggests intervention approaches in a matter of seconds after a series of prompts to input the identified causative agents. The main causative agents considered were hydrate formation temperature (HFT), hydrate formation pressure (HFP) and Sufficient Gas/Water. Six scenarios of causative agent occurrences were considered. Scenario 1 was a combination of HFT, HFP and sufficient gas/water, the proposed intervention was to depressurize, heat flowline, carry out chemical inhibition and dehydrate. Scenario 2 was a combination of HFP and HFT, the intervention proposed was to depressurize, heat flowline and carry out inhibition. Scenario 3 was HFP only, the intervention strategy proposed was to depressurize and carry out chemical inhibition. Scenario 4 was a combination of HFT and sufficient gas/water, the proposed intervention was to heat flowline, carry out chemical inhibition and dehydrate. Scenario 5 was HFT only, the proposed intervention strategy was to heat flowline, carry out chemical inhibition. Scenario 6 was a combination of no HFP, HFT or sufficient gas/water, the proposed intervention was that the causative elements be checked again since hydrate presence in the flowline had been previously confirmed.","PeriodicalId":11110,"journal":{"name":"Day 2 Tue, August 06, 2019","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84752716","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}

{"title":"Injectivity Monitoring & Evolution for Water Injectors in a Deepwater Turbidite Field","authors":"V. Onwuchekwa, M. Usman, P. Wantong, V. Biu, Jed Oukmal","doi":"10.2118/198749-MS","DOIUrl":"https://doi.org/10.2118/198749-MS","url":null,"abstract":"\u0000 Water injection is one of the key improved recovery techniques used for pressure maintenance and sweeping. Throughout the life of a field, changes in injectivity can have an effect on reservoir pressure management and sweep efficiency which both have a direct impact on production.\u0000 This study aims to present an original methodology to analyse the performance of water injectors in a deepwater turbidite field and evaluate the evolution of their injectivity over time.\u0000 An injectivity monitoring tool was developed by incorporating injection flowrate and pressure data with the following analytical techniques: (i) Instantaneous Injectivity Index, (ii) Hearn Plot or Reciprocal Injectivity Index, (iii) Hall Plot, (iv) Derivative Hall Plot and (v) Pressure Transient Analysis.\u0000 The injectivity monitoring tool was able to capture subtle changes in injectivity and demonstrate the long term trend of stable injectivity in this field, even in situations where only wellhead pressure and injection flowrate were available.\u0000 The resulting analysis showed that there is very good injectivity for all water injectors in this field with little or no degradation over time. One of the key drivers for the good injectivity is the water injection process philosophy in this field. This process consists of injecting deaerated seawater with biocides in order to prevent bacterial growth which causes near wellbore plugging. Another contributing factor to the good injection performance is the presence of injection valves which enable each injector to perform downhole shut-ins to stop migration of fines and curtail any possible water hammer effect when intermittent injection shut-ins required.\u0000 It was furthermore found that there was no significant difference in injectivity that could be associated to deviation angle or completion type (Stand Alone Screens (SAS) or Expandable Sand Screens (ESS)). Injectors completed with SAS however appeared to exhibit increased injectivity with increasing screen length but no such correlation was apparent between screen length and injectivity for injectors with ESS.","PeriodicalId":11110,"journal":{"name":"Day 2 Tue, August 06, 2019","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80724417","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}

{"title":"Evaluating the Potential of Bio-Derived Flow Improver and Its Effect on Nigeria Waxy Crude","authors":"A. Fadairo, T. Ogunkunle, A. Oladepo, A. Adesina","doi":"10.2118/198798-MS","DOIUrl":"https://doi.org/10.2118/198798-MS","url":null,"abstract":"\u0000 A root cause of many oil industry production and flow problem is paraffin wax especially in cold and deep offshore fields which are at low temperatures. About 82 – 89% of the hydrocarbon produced in the world suffers when wax precipitates out and solidifies in the pore spaces and channels of flow, around the wellbore, in the production wells or tubing, perforations, pump strings, and rods, and the whole oil transport flow-lines systems. The flow capacity of waxy crude can be quantified and evaluated using the means of pour point measurement. However, the description of this property during the flow of waxy crude is insufficient because the waxy crude rheological properties depend on the viscosity history. Using gelation theory, viscosity – temperature data can be analyzed and used to characterize the temperature behavior of waxy crude as such crude has the tendency to gel at low temperature. This paper evaluates Nigerian Waxy Crude Oil using biodiesel based material as an additive. Laboratory measurements on rheology were carried out on the sample at low temperatures condition. The obtained data of shear rate and shear stress plotted. The dose of biodiesel derived additive in neat waxy crude oil was varied between 0.1 to 0.5 v/v at the operating low temperature. The experimental investigations furnish that there is significant decrease in rheological properties with the decrease in pour point and temperature upon the addition of biodiesel derived additive hence, significantly enhance the flow of waxy crude in a flow system.","PeriodicalId":11110,"journal":{"name":"Day 2 Tue, August 06, 2019","volume":"71 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78397688","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}

{"title":"A Novel Approach for Predicting Sand Stringers: A Case Study of the Baka Field Offshore Nigeria","authors":"O. Chudi, M. Kanu, Austin Anaevune, I. Yamusa, J. Iwegbu, Oloniboko Sesan, Joel Musa","doi":"10.2118/198766-MS","DOIUrl":"https://doi.org/10.2118/198766-MS","url":null,"abstract":"\u0000 This paper details the seismic reservoir characterization study, aimed at predicting isolated sand lenses or stringers. Sand stringers or lenses are laterally discontinuous bodies that are encased in a different lithological body, they appear isolated and variable in lateral extent and thickness but mostly occur as thin beds. The thickness of these stringers makes it difficult for pre-drill predictions. One complicating factor of sand stringer is its potential of being isolated overpressured ramps which if unexpectedly encountered during drilling can cause kicks and if severe a blow-out is inevitable.\u0000 The Baka field is located some 120km off the coast of Nigeria in water depths of 2600ft (800m) to 3900ft (1200 m) with several wells drilled to date. Two of these wells have encountered unpredicted sand bodies that range in thickness from 15-25ft. These sand bodies were encountered within the Baka reservoir play interval of 5000 to 10000ft and were not predicted from conventional seismic reflectivity data, inverted seismic and offset well correlation. To obtain a better prediction of this stringers, alternative solutions are required. For this reason, a novel methodology - Geo-body constrained inversion approach was developed in 2017 to enable accurate prediction of stringer sands. Using this technique, a high-resolution acoustic impedance volume was built. Result of this study allowed the identification of gas bearing sand stringers encountered in previously drilled wells, thereby calibrating the model. The Geo-body inversion model proved a reliable tool for safe drilling of wells in 2018, ensuring that sand stingers were predicted at pre-drill phase in the Baka field.","PeriodicalId":11110,"journal":{"name":"Day 2 Tue, August 06, 2019","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76641704","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}

{"title":"Mathematical Modelling of Oil Viscosity at Bubble point Pressure and Dead Oil Viscosity of Nigerian Crude","authors":"Y. Adeeyo","doi":"10.2118/198770-MS","DOIUrl":"https://doi.org/10.2118/198770-MS","url":null,"abstract":"\u0000 Traditionally, reservoir engineering fluid flow calculations use viscosity data. However, in the absence of lab/experimental data other available derived correlations are used to predict the PVT property. Limit on the number of available data, regional peculiarity of the fluid, several viscosity correlations in the literature have limited accuracy and applicability. This study has developed predictive models using more than 2020 unpublished PVT data sets from different locations in Nigeria in rigorous nonlinear regression modelling. Different nonlinear algorithms, modified Newton-Raphson nonlinear least-square data fitting approach; Levenberg-Marquardt algorithm were used to develop new models for the estimation of the viscosity at the bubblepoint pressure and dead oil viscosity. The results of the performance of the model for viscosity at the bubblepoint show that the model provides better prediction with average absolute relative error of 21.06 and coefficient of correlation of 0.98 and the dead oil viscosity model shows a substantial improvement with average absolute relative error of 30.06 and coefficient of correlation of 0.90 over published correlations.","PeriodicalId":11110,"journal":{"name":"Day 2 Tue, August 06, 2019","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83739398","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}

{"title":"Key Success Factors and Challenges of Gas Injection in a Deep Offshore Turbidite Environment – Deepwater Akpo Field Example","authors":"Jed Oukmal, V. Biu, M. Usman","doi":"10.2118/198837-MS","DOIUrl":"https://doi.org/10.2118/198837-MS","url":null,"abstract":"\u0000 Gas injection is used as an improved recovery mechanism to provide reservoir pressure maintenance, oil swelling and sweeping. This mechanism offers a high microscopic recovery comparing to water injection thanks to a lower residual oil saturation to gas. However, its macroscopic recovery tends in general to be smaller due to a lower sweep efficiency - a direct consequence of high gas to oil mobility ratio. The case of Akpo Z represents a success story where gas injection led to a significant increase in the condensate ultimate recovery higher than 70%, as a result of the combination of both high microscopic and macroscopic recoveries. Akpo Z is a light condensate-bearing turbidite reservoir deep offshore Nigeria and has been developed using two gas injectors located at the crest of the structure with four oil producers at the flanks. The key success factors of gas injection in Akpo Z are linked both to a favorable subsurface environment, in particular, a large structure, good horizontal connectivity and a near critical light fluid, but also to appropriate reservoir development choices. These elements are detailed in this paper. This paper also shows the challenges linked to daily reservoir management and monitoring from an operator point of view, in particular, the impact of gas injection availability on condensate production shortfalls and the uncertainties linked to gas production and injection metering. Throughout the field life, several monitoring tools such as Intelligent Well Completion (IWC) and 4D seismic have been leveraged to take appropriate reservoir management decisions that led to a delay in gas and water breakthrough and sustain field condensate potential.","PeriodicalId":11110,"journal":{"name":"Day 2 Tue, August 06, 2019","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83500355","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}

{"title":"Application of Geographically Weighted Regression to Model the Effect of Completion Parameters on Oil Production – Case Study on Unconventional Wells","authors":"M. Wigwe, M. Watson, A. Giussani, E. Nasir, S. Dambani","doi":"10.2118/198847-MS","DOIUrl":"https://doi.org/10.2118/198847-MS","url":null,"abstract":"\u0000 Spatial data exists practically everywhere, including the oil and gas industry. Several factors drive the distribution of the location of oil and gas wells: performance of existing wells, available acreage, need for operators to maintain a certain amount of production and to stay competitive. Some of the important parameters to consider in the design of a completion job for an unconventional oil and gas well are the length of lateral (and by extension perforated interval), number of stages, total pounds of proppants, total volume of fluid pumped, injection pressure and injection rate.\u0000 In big data analytics and building of a regression model to capture the effects of these parameters on oil production, the practice has been to analyze wells in similar formations or similar basins, even when these wells are miles apart. Due to the presence of spatial autocorrelation and non-stationarity in such data, the recommended practice should be to take these spatial dependencies into account by using geographically weighted regression (GWR).\u0000 In this paper, we present an application of GWR in location-based regression modeling to capture the effect of these completion parameters on the first six months of oil production in 5700 wells in the Bakken and Three Forks formation in North Dakota. GWR builds different models for every location, leading to a spatial distribution of variable coefficients. This model is well suited to capture both local and global variations in our dependent variable. We also compare the results obtained with that of three other models: multiple regression model, artificial neural network model and universal kriging. Just like the use of kriging, GWR model resulted in a much-improved prediction of oil production as captured by the goodness-of-fit diagnostics (R squared, AIC, and RMSPE), compared to the other two non-location-based models. We recommend the use of the GWR model in the prediction of oil or gas production when spatial non-stationarity exists.","PeriodicalId":11110,"journal":{"name":"Day 2 Tue, August 06, 2019","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76763795","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}

{"title":"Prediction of Oil Reservoir Performance And Original-Oil-in-Place Applying Schilthuis And Hurst-Van Everdingen Modified Water Influx Models","authors":"Amarachi Uche Onuka, F. Okoro","doi":"10.2118/198714-MS","DOIUrl":"https://doi.org/10.2118/198714-MS","url":null,"abstract":"\u0000 This paper predicts the future performance of an oil reservoir with no initial gas cap, being produced by a strong underlying aquifer using the Schilthuis steady state and Hurst-Van Everdingen modified water influx models. The aim of this analysis is to highlight the discrepancies in the capabilities of the Schilthuis steady state water influx model and the Hurst-Van Everdingen modified model to effectively give the reservoir engineer a thorough understanding of the effects of aquifer influx into a reservoir on the cumulative oil production and estimation of oil-in-place. This was achieved by carrying out a simulation analysis using the Schilthius steady state and the Hurst-Van Everdingen unsteady state models in the MBAL package to predict changes in the following reservoir parameters for a 20-year period. For the production period being analysed, the oil recovery factor was given as 26.76%. The difference in recoverable reserves estimated using the Schilthuis steady state and Hurst-Van Everdingen modified water influx models was 0.406738 MMSTB. This implies that in the year 2020, using the Schilthuis steady state model to estimate the water influx into the reservoir, would not be able to account for 0.406738 million stock tank barrels of oil that had been recovered from the reservoir. This is attributed to the unrealistic assumptions of the Schilthuis steady state model that the pressure of the aquifer is constant as the dynamic nature of the reservoir-aquifer system will suggest a change in pressure with time as production of oil continues in an oil reservoir. Therefore, the Hurst-Van Everdingen modified model has been proven to be a more effective tool for the reservoir engineer because it takes into consideration the dependence of pressure changes in a reservoir-aquifer system with time.","PeriodicalId":11110,"journal":{"name":"Day 2 Tue, August 06, 2019","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87285200","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}

{"title":"Using the new FRAC4Well Models for Predicting Fracture Gradient in Depleted Formations; a Key Driver for Borehole Stability Management in Brown Fields","authors":"A. Bassey, A. Dosunmu, F. Otutu, A. Pedro","doi":"10.2118/198723-MS","DOIUrl":"https://doi.org/10.2118/198723-MS","url":null,"abstract":"\u0000 Optimal and consistent prediction of fracture gradient and stress path in depleted formation are of vital importance for well design and well integrity management. A modified and innovative concept for predicting stress path and fracture gradient for depleted intervals was formulated to ease well design and delivery in mostly conventional brown fields. It is imperative to further constrain the impact of poisons ratio as the major rock property affecting the stress path and fracture gradient evaluation considering the uniaxial scaling and variation of horizontal stresses generated by the strength interface of the drained poisons ratio scales in depleted formations. However, in addition to the modeling strategy, a rock property base stress path models (FRAC4Well model) was developed to account for the lateral stress variations at depletions for the change in minimum horizontal stress to pore pressure changes (pore-stress coupling). However, the study also considered the modeling strategy referencing linear elastic – constrained stress changes at different late time production periods within the reservoir, and the representative fracture gradient window. A stepwise validation strategy was formulated for stress arching hysteresis and it impact on thin/soft and thick/hard formations considering the sideburden and overburden impact for the different layers of the reservoirs as the horizontal stresses varies. A fast running semi-analytical model was also proposed to predict fracture sealing potentials after plugging and LCM selection during stress caging as a basis for fracture aperture closure mechanism. However, it is very important to have an accurate prediction of the boundaries of fracture gradients as the pore pressure depletes for optimal wellbore stability prediction to further mitigate challenges such as well control perturbations, borehole instability related NPT's and well integrity challenges that may arise as a result of erroneous fracture gradients predictions due to pore pressure depletion.","PeriodicalId":11110,"journal":{"name":"Day 2 Tue, August 06, 2019","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82513284","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}