Day 1 Wed, October 16, 2019最新文献

{"title":"Digital Transformation in Oil and Gas Industry","authors":"A. Zeynalli, Ruslan Butdayev, V. Salmanov","doi":"10.2118/198337-ms","DOIUrl":"https://doi.org/10.2118/198337-ms","url":null,"abstract":"\u0000 Digital transformation is the large-scale business transformation, which affects the entire set of enterprise functions from the automation of processes to execution and control. It directly affects both the change in the operating model and the infrastructure of the enterprise. This paper explores the industry trends in digital transformation as well as SOCAR AQS initiatives in this field. Digital transformation in the oil and gas industry has gained momentum in the last few years. The use of digital advances and innovation is not new to the oil and gas industry, as early as the 1980s, leading companies began to adopt digital technologies.\u0000 The study explores different approaches to the conceptualization of digital transformation. The result of a successful digital transformation is not the creation of a new organization, but its restructuring of the existing valuable assets in a new way. In other words, digital transformation is not only technological change but also the change in the tasks that management is facing. Practical examples and insights on digital transformation journey are provided.\u0000 The research analyses multiple case studies to understand how the world's leading companies are embracing digital transformation to reshape their operating landscape and achieve greater productivity, higher efficiency, and cost optimization. With digital transformation, businesses in the oil and gas industry no longer only save money, but also make money. How does this work? It's the vernal part of the topic. There's no precise model or approach that has been widely accepted in the industry, contrary to the consumer market, which has successful and mind-blowing cases like Uber and AirBnB where businesses do not own assets and create an ecosystem for customers to find the products and services they need. In the industrial sector, specifically oil and gas, this topic is sensitive to the competitiveness between businesses and others. However, it's clear that whichever industrial companies manage to have a breakthrough in the synthesis of AI, big data and cloud computing for the benefit of comparative advantage will lead and dominate the industry reshaping it for the next generation.\u0000 Alice: Would you tell me, please, which way I ought to go from here?\u0000 The Cheshire Cat: That depends a good deal on where you want to get to.\u0000 Lewis Carroll, Alice in Wonderland","PeriodicalId":169430,"journal":{"name":"Day 1 Wed, October 16, 2019","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116266927","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":"The Role of Pressure Observation and Pressure Transient Analysis in Changing the Geological Concept of Mature Oil Field","authors":"A. Mukanov, Aibek Aldazhar","doi":"10.2118/198333-ms","DOIUrl":"https://doi.org/10.2118/198333-ms","url":null,"abstract":"\u0000 The field of interest was discovered in late eightees. The main productive zone 1 obtained oil. The reservoir 2 is uplift basement located in the center of the field, to which reservoir 1 is pinched out and confined to reservoir 2 from east and west. The reservoir 1 has a gas cap and production is characterized by high GOR with no signs of any decline despite the long production period.\u0000 Therefore, all the available information of geology, production and pressure transient analysis were reviewed. There has been no production from the basement and just one well has been observing reservoir pressures for last ten years. These data were plotted bringing to unexpected result. The plot showed stable declining trend. So, there was a question – how does it happen when pressures are continuously decreasing while there is no production from the reservoir 2? Thus, gas sampling was performed on all three parts, pressure buildup and interference tests were conducted, geological data were reviewed and analyzed.\u0000 After completion of the works, the following results were obtained. PVT analysis indicates similar properties of gas from all three wells. However, the most important fact is that the results of interference test proved obvious pressure communication between wells in the reservoir 1 and 2. In addition, analysis of geological data also does not exclude the possibility of the communication. As the result, a conclusion that the two reservoirs could be one reservoir is drawn up. It is assumed that the main channels for interconnection are fractures, since the formation 2 is metamorphic reservoir with fracture network.\u0000 Reservoir pressure monitoring and pressure transient analysis became main factors and source of valuable information for changing the geological model of the field. Once again the importance of the pressure transient analysis is proved to be applicable not only by reservoir engineers but also by geologists. Eventually, the main results of the study influenced on the entire development strategy of the mature field.","PeriodicalId":169430,"journal":{"name":"Day 1 Wed, October 16, 2019","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125005859","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":"Impact of Aquifer Strength on Carbonate Gas Condensate Field Development Strategy, Case Study","authors":"Zhandos Yeshtay, Yerlan Bekenov, Z. Karamergenov","doi":"10.2118/198370-ms","DOIUrl":"https://doi.org/10.2118/198370-ms","url":null,"abstract":"\u0000 Before beginning the development of a carbonate gas condensate field, it is necessary to consider all the technological risks of development, related with pressure dropping below dew point pressure, thus the productivity of the aquifer. The field under consideration is carbonate, where the key words are the conductivity of fracture components, because of advancement of fluids in the pore space and matrix for storage of hydrocarbon reserves with low permeability. The reservoir drive mechanism assumed for this field is gas cycling. There was performed a comparative material balance analysis of aquifer influence with an analog field with similar geology but with differing hydrocarbon saturation, where waterflooding is considered the main drive mechanism. Then sensitivity studies were conducted on a simulation model of the field. It was important to define the strength of the aquifer in the matrix and fracture parts, to determine the aquifer productivity, permeability properties and other parameters. The conclusions were taken into account in the planning the versions of development, and compared with the initial technological indicators. As well as recommendations for improving development strategies.","PeriodicalId":169430,"journal":{"name":"Day 1 Wed, October 16, 2019","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132273259","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":"Future Geosteering and Well Placement Solutions from an Operator Perspective","authors":"K. Hermanrud, F. Antonsen, Maria Emilia Teixeira De Oliveira, S. Petersen, M. V. Constable","doi":"10.2118/198377-ms","DOIUrl":"https://doi.org/10.2118/198377-ms","url":null,"abstract":"\u0000 Innovative interpretation methods based on efficient measurements to map structure and fluids around high angle and horizontal wells while drilling are critical for future success in a marginal, but increasingly strategical, business on the Norwegian Continental Shelf (NCS). A high number of infill wells are expected to prolong the operational life of assets for the coming decades. Success of horizontal infill wells targeting bypassed zones are challenged by uncertainties in the subsurface description and by fluid content variation generated by differences in sweep efficiency over time. Optimizing well placement of such producer wells has a direct impact on cost and recovery. This could also potentially unlock targets not accessible today with currently used methods and technologies.\u0000 Driven by the advanced integration of subsurface information, the capacity of 3D mapping and characterization of the reservoir features has reached an unprecedented understanding level. Through the incorporation of data from real time LWD measurements, 1D and 2D ultra-deep azimuthal resistivity inversions, all the way to 3D and 4D surface seismic, it is now possible to describe in detail not just the structural and stratigraphic components but also the reservoir properties and fluid distribution along horizontal wells.\u0000 The key challenge is to establish more efficient workflows for advanced integration of subsurface information through new digital solutions transforming future geosteering and well placement solutions with 3D mapping and characterization real-time. Key elements of the integrated workflows and potential benefits in all phases of a well placement job will be discussed in this paper with examples from real cases from NCS.","PeriodicalId":169430,"journal":{"name":"Day 1 Wed, October 16, 2019","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126225940","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":"Reservoir Value-Engineering for West Siberian Oil Fields","authors":"M. Naugolnov, R. Murtazin","doi":"10.2118/198374-ms","DOIUrl":"https://doi.org/10.2118/198374-ms","url":null,"abstract":"\u0000 A new reservoir engineering analytic tool is presented that provides express oil residual reserves estimation, classification and following express waterflooding optimization for large West Siberian brownfields. Results are compared with full field 3d simulation models, and field pilot approbations.\u0000 The approach is based on residual reserves estimation and classification. Reserves classification is done with author's approach for reservoir complexity index (RCI) evaluation. The complexity of reservoir depends on three main parameters: permeability (1), fluid and rock properties: wettability, relative permeability, saturation and viscosity (2), and reservoir heterogeneity, calculated as a function of sweep efficiency and pumped pore volumes (3). All reserves are divided by RCI into several classes with the most economical way of development: sidetracks, re' hydraulic fracturing, treatments and flooding optimization. Waterflooding optimization using capacitance and resistivity model (CRM) considered more carefully as the main way to involve the largest scope of remaining reserves.\u0000 The implementation of the new approach based on reserves estimation and classification helps to identify the most attractive zones and to select the most suitable way for development. It also shows values of profitable and unprofitable current remaining reserves. Based on simple capacitance resistive analogue and economic models instrument for waterflooding optimization solves the problems of OPEX reduction, NPV or production maximization in express way. Combined capacitance and OPEX optimization models demonstrate good results on some West Siberian fields and find wells with unproductive injection, unprofitable oil production (due to high watercut and low liquid rate), show zones with high production potential, help to reallocate injection volumes and to involve into development additional amount of oil coupled with economic profit. The injection wells work regime optimization is solved using genetic algorithms based on differential evolution. Results of instrument implementation correspond with 3d simulation model and show nice additional oil production on real field. To summarize, the described approach gives an opportunity to minimize operational expenditures and to improve project economic performance without additional capital expenditures or investments in the terms of low oil prices.\u0000 The novelty of the work is in the using of new approach of reservoir complexity index estimation for STOIIP classification and best development methods selection. The novelty is also in integration of RCI, semi analytical physical based waterflooding management methods with hybrid data engineering methods and optimization algorithms. Using of new methods together with economic model provides a responsible tool for solving reservoir cost-engineering problems and increasing of project's value.","PeriodicalId":169430,"journal":{"name":"Day 1 Wed, October 16, 2019","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122310132","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":"Production Sustenance and Offshore Operation Safety Through Facility Optimization and Debottlenecking","authors":"F. Mehran, Ali Didanloo, Tu Le Mai Khanh, Q. HungLe.","doi":"10.2118/198379-ms","DOIUrl":"https://doi.org/10.2118/198379-ms","url":null,"abstract":"\u0000 Hai Su Trang (HST) – Hai Su Den (HSD) fields are located in the Cuu Long Basin, in block 15-2/01 with approximately 60 km away from Ba Ria – Vung Tau, the Southern coast of Vietnam. This field has complex facility infrastructure consisting of one well head platform HSD and one well head separation platform HST. TLJOC recently faced some operational challenges such as instability and even system shutdown and as the operating safety is very critical for this offshore field, they have started the investigation on finding solution for more efficient operational condition.\u0000 In TLJOC system, debottlenecking of the three separates network including oil, water injection and gas lift network were typically needed for entire field life to maximize the production rate and avoid any further system shutting in future. In addition, there were few changes in reservoir system such as increasing perforation zone for some of the wells to enhance production rate which should be simulated in advance to make sure of facility capability and flow assurance. Furthermore, finding root cause of bottlenecking and controlling operational condition to avoid the exceed limitations was very critical for asset team.\u0000 All production units were modelled and analysed for current condition and future operational condition base on reservoir management plan. The several scenarios based on TLJOC- RMP cases has been run and result got evaluated to make sure facility pipelines and equipment have enough capacity and at the same time there will be no integrity in pipeline such as slug issue. Also, additional cases were defined for possible upcoming event such as dropping or increasing facility unit pressure or decreasing water injection pressure to have better view of system health and capacity for entire life of field.\u0000 The results of analysis prove that in oil pipeline the slug flow pattern exist in most of cases, as one of key reasons for recent operation issues. Recommendations are either control the operation condition of riser to mitigate slug or to control separator pressure in order to reduce slug. Another recommendation was to maintain the liquid level in separator based on certain level to avoid slugging. Based on back pressure effect analysis this system has capacity to increase production up to 20 %, however 15% increase is more efficient operationally. The water injection and gas lift network can handle all possible event and have no problem with capacity only need to keep monitoring the junction pressure to not fall or exceed the operational and integrity limit.","PeriodicalId":169430,"journal":{"name":"Day 1 Wed, October 16, 2019","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125485399","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":"Digital Twin of a Research Organization: Approaches and Methods","authors":"M. Khasanov, F. Krasnov","doi":"10.2118/198372-ms","DOIUrl":"https://doi.org/10.2118/198372-ms","url":null,"abstract":"\u0000 Competition urges business to adopt the concept of digital twins. In some industry sectors, digital twins are already firmly in place: there are digital twins of plants and cities. However, in the industries where the core product is knowledge, digital twins are not yet in great demand. There is no doubt that research organizations have a backbone, corporate culture, values which help them carry out their unique work. By modeling these internal hidden features of an organization, we can get unique tools for forecasting and managing the technology strategy. A digital twin of a science and technology center may be viewed as a special system model type, which uncovers such hidden phenomena as creation of new branches and schools of thought and the extent of creative burnout and fatigue of the team.\u0000 Prototyping, as an engineering discipline, has been in existence for over 30 years and, at first glance, is doing the same thing. However, unlike the prototype, the digital twin does not aim to quickly implement basic functionality to analyze the operation of the system as a whole.\u0000 Therefore, in order to understand the advantages of digital twins, it is necessary to understand the new opportunities they offer. Going from general to specific, the authors chose a science and technology center as a focus for their analysis, considered the approaches to building a digital twin, and then summed up those approaches. As a result, they have current research hypotheses that have to be checked before creating the digital twin of an organization or its part aiming to produce new knowledge.\u0000 Finally, we provide the results of the simulation of the digital twin model.","PeriodicalId":169430,"journal":{"name":"Day 1 Wed, October 16, 2019","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127156992","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":"Gas/Condensate Fields Development : Subsea to Shore Cost Effective Solution","authors":"L. Rivière, C. Boireau, R. Mackenzie","doi":"10.2118/198343-ms","DOIUrl":"https://doi.org/10.2118/198343-ms","url":null,"abstract":"\u0000 In remote offshore locations or in harsh environment, the development costs of gas/condensate fields must be reduced, in order to keep them economically viable.\u0000 For these offshore gas/condensate fields, the best economic solution is often a Subsea to Shore scenario, as the cost of a stand-alone development is very high and as the operations in these locations are quite complicated.\u0000 The Subsea to Shore scheme for gas/condensate fields can either be a conventional one (as already implemented in North Sea, mainly in Norway), or an innovative one - installing new subsea technologies, using subsea processing and implementing alternative production strategies that reconsider the distribution of facilities between subsea and onshore.\u0000 Through an existing gas/condensate field example, operated by TOTAL in the North Sea, in harsh environment and in a remote location, this paper examines the impact on development costs of the following innovations : –an innovative hydrate management strategy (continuous injection of LDHI Anti-Agglomerate instead of MEG continuous injection),–an innovative production strategy (such as subsea pigging instead of having two production lines allowing the pigging),–an innovative subsea technologies (such as all electrical technology for subsea production systems instead of hydraulic systems),–and innovative subsea processing (such as subsea chemical storage and injection instead of complicated and costly umbilical).\u0000 This paper shows that a combination of alternative production strategies and new subsea technologies can significantly improve the economics of gas/condensate fields, for remote offshore fields or for fields in harsh environment, without jeopardizing HSE performance or production availability.","PeriodicalId":169430,"journal":{"name":"Day 1 Wed, October 16, 2019","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128827625","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":"Implementation of Data Driven Machine Learning Methods and Physics Driven Concepts for Real-Time Well Performance Estimation in Kashagan Field","authors":"Adilbek Mursaliyev, A. Kushekov, Ruslan Sultangaliyev","doi":"10.2118/198338-ms","DOIUrl":"https://doi.org/10.2118/198338-ms","url":null,"abstract":"\u0000 This paper presents the implementation and value of Data Driven Machine Learning methods and Physics driven Concepts for real-time well performance estimation in Kashagan Field. The models are expected to be used to detect fluid properties changes, restrictions in the well tubing and instrumentation malfunctioning.\u0000 The paper also describes how the data driven and physics driven models are built, tuned and maintained. The comparison of the methods will also be attempted in terms of redundancy.\u0000 The data driven machine learning method (DDML) used in the paper is artificial neural networks model. The model consists of several inputs, layers of artificial neurons and output parameter(s). The built DDML model is trained by feeding labeled input test data and trained. Then the trained DDML model is validated and tested against separate labeled data which the model did not \"see\" before.\u0000 Physics driven model (PDM) is built on Vertical Lift Performance (VLP) equation. The PDM is also \"trained\" with input data by tuning the model in order to fit to test data. The tuning parameter is friction coefficient.\u0000 The trained DDML and PDM models are then tested on same set of data in order to compare the performance. Both methods showed similar degree of accuracy. The reference data comes from MPFM, Test separator and downhole gauges. Downhole pressure gauge signal is used by both of the methods. However, if the downhole gauge is broken, the PDM will not function for estimation of the rate. On the other hand, DDML model can be re-trained with available signals (tubing head pressure, temperature, choke size, flowline pressure and temperature, etc.) by excluding the downhole gauge signal from the training data. It is clear that the DDML model trained without downhole pressure signal is not as accurate fully trained DDML model. However, it is still possible to have reasonable estimate of the parameter with even partially trained model. Both models can be used to estimate downhole pressure in cases where the gauges are broken.\u0000 The proposed methods can be used by practicing engineer to estimate well performance parameters. The methods are mostly suitable for so called smart fields where the data is readily available and makes it possible to extract useful insights from the archived data. With hands on experience with such simple implementation of data driven machine learning techniques an engineer can try to implement ML methods for other applications, e.g. well interference, history match, anomaly detection, etc.","PeriodicalId":169430,"journal":{"name":"Day 1 Wed, October 16, 2019","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127763409","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":"Evaluation of Vertical Fracture Propagation Using Combined Spectral Noise Logging and High Precision Temperature Logging Data in a Low Permeability Sandstone Reservoir, Western Kaz","authors":"Doszhan Yeleussinov, Dinmukhammed Bekmagambetov, I. Crabb, A. Berdimuratov, V. Nagimov, A. Zhumekeshov, A. Makashev, D. Makarov","doi":"10.2118/198339-ms","DOIUrl":"https://doi.org/10.2118/198339-ms","url":null,"abstract":"\u0000 Hydrocarbon production from low permeability heterogeneous clastic reservoirs consisting of a sequence of thin, interbedded sand and shale laminations is challenging. Hydraulic fracturing is essential to achieve good production rates. An understanding of fracture geometry is very important for optimal reservoir management and development. This paper describes the application of an advanced logging system to evaluate near-wellbore vertical fracture properties.\u0000 Conventional production logging focusing primarily on wellbore flow geometry such as perforation and behind casing flow through poor cement may not adequately evaluate fracture properties due to a limited radius of investigation. To overcome this, a campaign using an advanced logging system containing spectral acoustic and high precision temperature measurements to evaluate near-wellbore fracture flow distribution was implemented. The main feature of this logging technique is the ability to scan the active flow behind the casing a few meters from the wellbore. The reservoir flow profile is assessed by temperature modelling enabling differentiation of the different flow regimes and inflow contributions.\u0000 Two vertical water injection wells hydraulically fractured into the low permeability clastic reservoir were logged. Vertical fracture geometry was precisely determined for each case and reservoir injection profile determined based on temperature modelling. Detailed pre-job modelling was necessary to define the logging program including optimal flowing and shut-in regimes. This enabled improved efficiency and accuracy when interpreting the results. The results enabled the determination of any out of zone injected volumes. This study revealed new insights in evaluating fracture geometry that can then be applied to reconcile post-job fracture modelling and improve reservoir management and water flood optimization.","PeriodicalId":169430,"journal":{"name":"Day 1 Wed, October 16, 2019","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115387790","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}