Carbon fiber is expected to increase its importance as a lightweight substitute material. The significant market potential in the automotive industry is strongly dependent on carbon fiber cost. A decrease of about 50% from the present cost level of polyacrylonitrile (PAN)-based carbon fibers is needed. This ambitious target is only achievable with high-cost transparency in the production chain. This paper reviews published cost models and identifies the need for a consistent methodology and transparency over input parameters. A new cost model with a modular structure covering all process steps by cost type and disclosing all process parameter assumptions is introduced. The most cost-intense steps are polymerization, including raw material (25%), carbonization (22%) and fiber washing after coagulation (19%). Most important cost types are energy (34%), raw material (19%) and capital costs for equipment (18%). The high-cost share of 54% for carbon fiber PAN precursor is consistent with most reviewed models.
The article contains sections titled: 1. Textile Glass Fibers 1.1. Chemical Composition and Properties 1.1.1. Chemical Composition 1.1.2. Properties 1.2. Production 1.2.1. Raw Materials 1.2.2. Melting process 1.2.3. Fiber Forming 1.2.4. Glass Staple Fibers 1.3. Textile Glass Products: Processing and Application 1.3.1. Product Designation 1.3.2. Correlation Between Processing and Application 1.3.3. Description of Textile Glass Products 1.3.4. Applications 1.4. Product Standards 1.5. Economic Aspects 1.5.1. Textile Glass Fiber Market 1.5.2. Producers 1.5.3. New Products 1.6. Toxicology and Occupational Health 2. Glass Fibers for Insulation 2.1. Chemical Composition and Properties 2.1.1. Chemical Composition 2.1.2. Physical Properties 2.1.3. Chemical Properties 2.2. Production 2.2.1. Raw Materials 2.2.2. Melting 2.2.3. Fiber Forming 2.2.4. Product Forming 2.2.5. Environmental Protection 2.3. Applications 2.4. Product Standards 2.5. Economic Aspects 2.6. Toxicology and Occupational Health
TX 75083-3836, U.S.A., fax +1-972-952-9435. AbstractQatargas 3 and Qatargas 4 ventures are jointly developing their assigned project area of the North Field offshore Qatar, the world's largest non-associated natural gas field. The area allocated to the joint development is a 15km by 20.5 km block and consists of 3 15-slot platforms, each with 11 wells drilled into the Khuff carbonate reservoir. Currently the Qatargas 3&4 block is in its late development phase where over 75% of its wells have been drilled, evaluated and completed. The formation evaluation is generally carried out using data acquired by wireline conveyed tools and a standard log acquisition program consist of two runs configured to record mainly resistivity, porosity, sonic and formation pressure data.This extensive data acquisition program entails substantial operational challenges. Because of this, a clear understanding and management of human related factors such as communication, logistics and experience of personnel as well as technical challenges such as hole conditions (clean up), well trajectory, tool configuration, deployment methods and overbalance and risk management are critical to success. This paper provides an overview of these challenges and the involved processes that drive continuous improvement. Improvement was achieved on multiple aspects of the logging program, such as efficiency increase and time optimization of over 65%, and data quality improvements. Practices commonly adhered to include pre-job planning or Log the Well On Paper exercises (LWOP), thorough follow up during execution, mandatory close out by all parties involved in regular service quality meetings, job debriefing with engineers and continuous review of standard operating procedures and best practices. Significant efforts were placed on logging tool conveyance and configuration selection which ultimately led to a decision tree being developed to accommodate the various options.The processes developed by QG3&4 over the last three years could offer a 'running start' for new operators who target similar formations in the region.
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