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News Article | May 10, 2017
Site: marketersmedia.com

Wiseguyreports.Com Adds “Automotive Coolant -Market Demand, Growth, Opportunities and Analysis of Top Key Player Forecast To 2022” To Its Research Database This report studies Automotive Coolant in Global market, especially in North America, Europe, China and Asia, focuses on top manufacturers in global market, with production, price, revenue and market share for each manufacturer, covering Market Segment by Regions, this report splits Global into several key Regions, with production, consumption, revenue, market share and growth rate of Automotive Coolant in these regions, from 2012 to 2022 (forecast), like Split by Product Type, with production, revenue, price, market share and growth rate of each type, can be divided into Ethylene Glycol Coolant Propylene Glycol Coolant Other Split by Application, this report focuses on consumption, market share and growth rate of Automotive Coolant in each application, can be divided into Passenger Vehicle Commercial Vehicle 1 Industry Overview of Automotive Coolant 1 1.1 Definition of Automotive Coolant 1 1.2 Classification of Automotive Coolant 1 1.2.1 Ethylene Glycol Coolant 2 1.2.2 Propylene Glycol Coolant 3 1.2.3 Type Three 3 1.3 Applications of Automotive Coolant 3 1.3.1 Passenger Vehicles 4 1.3.2 Commercial Vehicles 5 1.4 Industry Chain Structure of Automotive Coolant 6 1.5 Industry Overview and Major Regions Status of Automotive Coolant 7 1.5.1 Industry Overview of Automotive Coolant (Companies Segment) 7 1.5.2 Global Major Regions Status of Automotive Coolant 8 1.6 Industry Policy Analysis of Automotive Coolant 8 1.7 Industry News Analysis of Automotive Coolant 9 8 Major Manufacturers Analysis of Automotive Coolant 66 8.1 Prestone 66 8.1.1 Company Profile 66 8.1.2 Product Introduction 67 8.1.3 Production, Price, Gross Margin and Revenue 67 8.1.4 Contact Information 68 8.2 Shell 69 8.2.1 Company Profile 69 8.2.2 Product Introduction 69 8.2.3 Production, Price, Gross Margin and Revenue 70 8.2.4 Contact Information 72 8.3 ExxonMobil 72 8.3.1 Company Profile 72 8.3.2 Product Introduction 73 8.3.3 Production, Price, Gross Margin and Revenue 74 8.3.4 Contact Information 75 8.4 Castrol 75 8.4.1 Company Profile 76 8.4.2 Product Introduction 77 8.4.3 Production, Price, Gross Margin and Revenue 77 8.4.4 Contact Information 78 8.5 Total 79 8.5.1 Company Profile 79 8.5.2 Product Introduction 79 8.5.3 Production, Price, Gross Margin and Revenue 80 8.5.4 Contact Information 81 8.6 CCI 82 8.6.1 Company Profile 82 8.6.2 Product Introduction 83 8.6.3 Production, Price, Gross Margin and Revenue 83 8.6.4 Contact Information 84 8.7 BASF 85 8.7.1 Company Profile 85 8.7.2 Product Introduction 86 8.7.3 Production, Price, Gross Margin and Revenue 86 8.7.4 Contact Information 87 8.8 Valvoline 88 8.8.1 Company Profile 88 8.8.2 Product Introduction 89 8.8.3 Production, Price, Gross Margin and Revenue 89 8.8.4 Contact Information 90 8.9 Old World Industries 91 8.9.1 Company Profile 91 8.9.2 Product Introduction 92 8.9.3 Production, Price, Gross Margin and Revenue 93 8.9.4 Contact Information 94 8.10 KMCO 95 8.10.1 Company Profile 95 8.10.2 Product Introduction 95 8.10.3 Production, Price, Gross Margin and Revenue 96 8.10.4 Contact Information 97 8.11 Chevron 98 8.11.1 Company Profile 98 8.11.2 Product Introduction 98 8.11.3 Production, Price, Gross Margin and Revenue 99 8.11.4 Contact Information 100 8.12 SONAX 101 8.12.1 Company Profile 101 8.12.2 Product Introduction 102 8.12.3 Production, Price, Gross Margin and Revenue 102 8.12.4 Contact Information 103 8.13 Getz Nordic 104 8.13.1 Company Profile 104 8.13.2 Product Introduction 104 8.13.3 Production, Price, Gross Margin and Revenue 105 8.13.4 Contact Information 106 8.14 Kost USA 107 8.14.1 Company Profile 107 8.14.2 Product Introduction 107 8.14.3 Production, Price, Gross Margin and Revenue 108 8.14.4 Contact Information 109 8.15 Recochem 110 8.15.1 Company Profile 110 8.15.2 Product Introduction 110 8.15.3 Production, Price, Gross Margin and Revenue 111 8.15.4 Contact Information 112 8.16 Amsoil 113 8.16.1 Company Profile 113 8.16.2 Product Introduction 114 8.16.3 Production, Price, Gross Margin and Revenue 115 8.16.4 Contact Information 116 8.17 MITAN 116 8.17.1 Company Profile 116 8.17.2 Product Introduction 117 8.17.3 Production, Price, Gross Margin and Revenue 117 8.17.4 Contact Information 118 8.18 Gulf Oil International 119 8.18.1 Company Profile 119 8.18.2 Product Introduction 119 8.18.3 Production, Price, Gross Margin and Revenue 120 8.18.4 Contact Information 121 8.19 Paras Lubricants 122 8.19.1 Company Profile 122 8.19.2 Product Introduction 123 8.19.3 Production, Price, Gross Margin and Revenue 123 8.19.4 Contact Information 124 8.20 Solar Applied Materials 125 8.20.1 Company Profile 125 8.20.2 Product Introduction 126 8.20.3 Production, Price, Gross Margin and Revenue 126 8.20.4 Contact Information 127 8.21 Pentosin 128 8.21.1 Company Profile 128 8.21.2 Product Introduction 128 8.21.3 Production, Price, Gross Margin and Revenue 129 8.21.4 Contact Information 131 8.22 Millers Oils 131 8.22.1 Company Profile 131 8.22.2 Product Introduction 132 8.22.3 Production, Price, Gross Margin and Revenue 133 8.22.4 Contact Information 134 8.23 Silverhook 134 8.23.1 Company Profile 135 8.23.2 Product Introduction 135 8.23.3 Production, Price, Gross Margin and Revenue 136 8.23.4 Contact Information 137 8.24 Evans 138 8.24.1 Company Profile 138 8.24.2 Product Introduction 139 8.24.3 Production, Price, Gross Margin and Revenue 139 8.24.4 Contact Information 140 8.25 ABRO 141 8.25.1 Company Profile 141 8.25.2 Product Introduction 142 8.25.3 Production, Price, Gross Margin and Revenue 142 8.25.4 Contact Information 143 8.26 Sinopec 144 8.26.1 Company Profile 144 8.26.2 Product Introduction 144 8.26.3 Production, Price, Gross Margin and Revenue 145 8.26.4 Contact Information 146 8.27 CNPC 147 8.27.1 Company Profile 147 8.27.2 Product Introduction 148 8.27.3 Production, Price, Gross Margin and Revenue 148 8.27.4 Contact Information 149 8.28 Lanzhou Blue Star 150 8.28.1 Company Profile 150 8.28.2 Product Introduction 150 8.28.3 Production, Price, Gross Margin and Revenue 151 8.28.4 Contact Information 152 8.29 Zhongkun Petrochemical 153 8.29.1 Company Profile 153 8.29.2 Product Introduction 153 8.29.3 Production, Price, Gross Margin and Revenue 154 8.29.4 Contact Information 155 8.30 China-TEEC 155 8.30.1 Company Profile 155 8.30.2 Product Introduction 156 8.30.3 Production, Price, Gross Margin and Revenue 156 8.30.4 Contact Information 158 8.31 Guangdong Delian 158 8.31.1 Company Profile 158 8.31.2 Product Introduction 158 8.31.3 Production, Price, Gross Margin and Revenue 159 8.31.4 Contact Information 160 For more information, please visit https://www.wiseguyreports.com/sample-request/1270488-global-automotive-coolant-market-2017-industry-trend-and-forecast-2022


— Global Automotive Coolant Market report covers product scope, market overview, opportunities, risk, and driving force. It analyzes the top manufacturers of Automotive Coolant, with sales, revenue, and price in 2016 and 2017. It also display the competitive situation among the top manufacturers, with sales, revenue and market share in 2016 and 2017. Companies profiled in this research report are Prestone, Shell, Exxon Mobil, Castrol, Total, CCI, BASF, Old World Industries, Valvoline, Sinopec, CNPC, Lanzhou BlueStar, Zhongkun Petrochemical, KMCO, Chevron, China-TEEC, Guangdong Delian, SONAX, Getz Nordic, Kost USA, Amsoil, Recochem, MITAN, Gulf Oil International, Paras Lubricants, Solar Applied Materials, Pentosin, Millers Oils, Silverhook, Evans and ABRO. Access this report at https://www.themarketreports.com/report/global-automotive-coolant-market-by-manufacturers-countries-type-and-application-forecast-to-2022 To provide the historical development this report includes global market by regions, with sales, revenue and market share of Automotive Coolant, for each region, from 2012 to 2017 and market analysis by type and application, with sales market share and growth rate by type, application, from 2012 to 2017. This report also analyze the key regions, with sales, revenue and market share by key countries in North America, Europe, Asia-Pacific, South America, and Middle East and Africa. Later, this report provides Automotive Coolant Market forecast, by regions, type and application, with sales and revenue, from 2017 to 2022. In addition to above this report includes Automotive Coolant sales channel, distributors, traders, dealers, and sum up with research findings and conclusion. Purchase this premium report at: https://www.themarketreports.com/report/buy-now/520994 Market Analysis by Regions • North America (USA, Canada and Mexico) • Europe (Germany, France, UK, Russia and Italy) • Asia-Pacific (China, Japan, Korea, India and Southeast Asia) • South America (Brazil, Argentina, Columbia etc.) • Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa) Inquire about this report at: https://www.themarketreports.com/report/ask-your-query/520994 For more information, please visit https://www.themarketreports.com/report/global-automotive-coolant-market-by-manufacturers-countries-type-and-application-forecast-to-2022


Pruessmann J.,TEEC | Bergmann P.,German Research Center for Geosciences | Gierse G.,TEEC | Lippmann A.,TEEC | Lueth S.,German Research Center for Geosciences
74th European Association of Geoscientists and Engineers Conference and Exhibition 2012 Incorporating SPE EUROPEC 2012: Responsibly Securing Natural Resources | Year: 2012

The Common Reflection Surface, or CRS technique offers a comprehensive workflow for improving seismic processing, imaging, and reservoir characterisation in time and depth, which has been demonstrated in a project of geological CO2 storage at the Ketzin site in Eastern Germany. In applications to the 3D seismic baseline data that was acquired before CO2 injection, the results of the CRS time processing chain are compared to a previous conventional processing. The CRS noise suppression and regularization in the prestack data result in the so-called CRS gathers where acquisition related data gaps and fold variation are compensated for using the lateral event continuation of the CRS method. Both, the data reconstruction and the enhanced prestack signal quality lead to an increased resolution of the subsurface image, and strongly improve the tie to the well data. In the mapping of shallow gas at extremely low fold at this time level, CRS-based AVO resolves a well defined outline and inner structure of the gas zone, and clearly discriminates high-amplitude events outside the gas zone. The CRS technique thus proves to be a versatile tool for improved structural assessment and reservoir monitoring in both, storage and exploration projects.


Eisenberg-Klein G.,TEEC | Trappe H.,TEEC | Endres H.,TEEC | Pruessmann J.,TEEC
76th EAGE Conference and Exhibition 2014, Workshops | Year: 2014

The common-reflection-surface (CRS) technique provides an effective workflow for seismic data preparation and imaging in large areas of regional studies. In a case study from the North Sea, the multi-parameter stacking technique is used to combine and homogenize vintage seismic data in time domain, and to accelerate the model building cycle in depth imaging. CRS time processing may directly start from input data acquired at diverse natural binning grids, and provide the regularisation and interpolation to a uniform output grid in one step. The regular CRS gathers show an almost complete CMP-offset coverage and a high signal to-noise ratio, and thus enhance the resolution of prestack migration in time and depth. Depth model building departs from the CRS attributes which provide the initial model via CRS tomography, and benefits in the model update by residual moveout analysis from the enhanced signal-to-noise ratio in the prestack data.


Pruessmann J.,TEEC | Eisenberg-Klein G.,TEEC
76th EAGE Conference and Exhibition 2014, Workshops | Year: 2014

Wide azimuth (WAZ) marine seismic data commonly provide an enhanced but varying coverage in azimuth-offset domain, which decreases towards crossline azimuths and near-offsets. The variable offset-azimuth illumination of WAZ data is commonly exploited in prestack depth migration in order to resolve complex subsurface structures, but often leads to amplitude footprints due to the variation, that disturb AVO and AVAZ analyses. An interpolation in azimuth-offset domain based on the CRS technique may largely reduce these footprints, and effectively precondition the data for amplitude studies. The CRS, or Common Reflection Surface method is essentially a multi-parameter stacking method that is used here to regularize and interpolate the data in one step. A regular coverage in CMP-offset-azimuth is thus achieved in most part of the data. Subsequent azimuth-dependent prestack time migration provides high resolution images at low migration noise, with strongly reduced footprints and well-preserved amplitude trends as a basis for subsequent amplitude studies.


Eisenberg-Klein G.,TEEC | Trappe H.,TEEC | Gierse G.,TEEC | Pruessmann J.,TEEC | Zehnder M.,TEEC
Saint Petersburg 2012 - Geosciences: Making the Most of the Earth's Resources | Year: 2012

Noise suppression and signal enhancement prior to prestack depth migration (PreSDM) may significantly increase the resolution of the depth image, and the effectiveness of the PreSDM workflow. The Common-Reflection-Surface (CRS) technique was previously used for this enhancement of seismic prestack data, providing so-called CRS gathers with regularized CMP and offset coverage, and with a strong noise suppression. These CRS gathers considerably improved the depth image in Kirchhoff PreSDM but were not suited for shot-based PreSDM algorithms. This case study now presents a straightforward way to produce geometry-preserving CRS gathers that similarly increase the signal-to-noise ratio. In a first implementation, CRS prestack data interpolation is performed at the existing trace locations providing a straightforward and automatic preservation of the original shot geometry. Application to 3D seismic land data demonstrates the improved signal-to-noise ratio and resolution both in the geometry-preserving CRS shot gathers, and in the corresponding QC stack. As in the Kirchhoff migration of regularized CRS gathers, such enhancements are expected for Reverse Time Migration of CRS shot gathers as well.


Gierse G.,TEEC | Pruessmann J.,TEEC | Trappe H.,TEEC | Harms G.,RWE AG | Vosberg H.,RWE AG
Saint Petersburg 2012 - Geosciences: Making the Most of the Earth's Resources | Year: 2012

The Common-Reflection-Surface (CRS) method may improve seismic processing beyond imaging, e.g. in an enhanced Amplitude Versus Offset (AVO) analysis. Various applications have shown that the more realistic subsurface assumptions, and the increased fold of the CRS imaging allow to extend AV O analysis into noise zones and to deep targets with low signal quality. Extreme fluctuations of AVO parameters are removed, and AVO anomalies are enhanced. The CRS method assumes subsurface reflector elements with dip and curvature, which implies large-fold stacking surfaces extending both across offset, and across neighboring CMP locations. The extension across neighboring CMPs defines a CRS gather at the central CMP location, comprising data from a multitude of traces. The CRS moveout correction compensates for the local dip across these neighboring CMPs, thus contrasting to conventional AV O super-gathers based on NMO correction that collect dipping events horizontally at varying phase. The presented case studies show that CRS-AVO attribute stacks are produced with a much higher signalto-noise ratio from CRS gathers than from CMP gathers in conventional AVO. The CRS-AVO attribute sections clearly distinguish anomalies at known or expected gas-bearing reservoirs.


Gierse G.,TEEC | Schuenemann E.,TEEC | Tessmer E.,University of Hamburg | Ballesteros R.,Geoprocesados
SEG Technical Program Expanded Abstracts | Year: 2011

Depth migration based on wave-equation algorithms have been established as standard tools in the processing of reflection seismic data. Reverse time migration (RTM) provides depth images of high accuracy but may be hampered by low data quality, and noise contamination. In such cases the combination of RTM with prestack data preconditioning by the Common-Reflection-Surface (CRS) technique can improve the imaging result. While previous CRS strategies for prestack data mapping regularized CMP and offset coverage for an improved Kirchhoff migration, a new CRS strategy provides so-called CRS shot gathers that preserve the original shot geometry while providing a strong noise suppression. These CRS shot gathers are well suited as input of shot based depth migration algorithms like one-way wave equation and reverse time migration (RTM). These state-of-the-art migration techniques benefit from the strong signal-to-noise ratio of CRS shot gathers. The reverse time migrated shot gathers in offset and angle domain offer new possibilities for velocity analysis in complex geologic structures. © 2011 Society of Exploration Geophysicists.


Pruessmann J.,TEEC | Gierse G.,TEEC | Harms G.,RWE AG | Vosberg H.,RWE AG
SEG Technical Program Expanded Abstracts | Year: 2011

The Common-Reflection-Surface (CRS) method may improve seismic processing beyond imaging, e.g. in an enhanced Amplitude Versus Offset (AVO) analysis. Various applications have shown that the more realistic subsurface assumptions, and the increased fold of the CRS imaging allow to extend AVO analysis into noise zones and to deep targets with low signal quality. Extreme fluctuations of AVO parameters are removed, and AVO anomalies are enhanced. The CRS method assumes subsurface reflector elements with dip and curvature, which implies large-fold stacking surfaces extending both across offset, and across neighboring CMP locations. The extension across neighboring CMPs defines a CRS gather at the central CMP location, comprising data from a multitude of traces. The CRS moveout correction compensates for the local dip across these neighboring CMPs, thus contrasting to conventional AVO super-gathers based on NMO correction that collect dipping events horizontally at varying phase. The presented case studies show that CRS-AVO attribute stacks are produced with a much higher signal-to-noise ratio from CRS gathers than from CMP gathers in conventional AVO. The CRS-AVO attribute sections clearly distinguish anomalies at known or expected gas-bearing reservoirs. Cross-plots of CRS-AVO attributes show a better separation of anomalous zones which may be classified in order to identify top and base of hydrocarbon deposits. © 2011 Society of Exploration Geophysicists.


Endres H.,TEEC | Gierse G.,TEEC | Eisenberg-Klein G.,TEEC | Pruessmann J.,TEEC
73rd European Association of Geoscientists and Engineers Conference and Exhibition 2011: Unconventional Resources and the Role of Technology. Incorporating SPE EUROPEC 2011 | Year: 2011

The structural resolution of complex subsurface geology generally requires advanced prestack depth migration based on wave-equation algorithms. The full benefit of these costly algorithms, however, may be missed in case of irregular spatial data sampling, and high noise contamination. A new data regularisation strategy is proposed including both, a careful regularisation of the shot data, and an enhancement of the signal-to-noise ratio, making use of the Common-Reflection-Surface (CRS) method. In contrast to previous CRS regularization strategies in the CDP-offset domain, the new strategy defines the target traces of the CRS prestack data mapping within so-called CRS shot gathers. This data mapping may preserve the existing shot geometry supplying CRS-based noise suppression only, or may build CRS shot gathers at new geometries with a desired regularity. The effectiveness of the approach is demonstrated at a 3D seismic dataset. In a first CRS processing using all prestack data, the existing shot records are reconstructed as CRS shot gathers with preserved geometry. In a second CRS processing, some shot data is omitted in the input, and then rebuilt as CRS shot gathers. Both applications show a strong increase of the signal-to-noise ratio with a good preservation, or reconstruction, respectively, of the original events.

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