Based on a theoretical background [1,2], a lab scale cylindrical SAGD (steam assisted gravity drainage) model was designed, constructed and operated. There are six different parts in the apparatus: (1) water supplier, (2) steam generator, (3) SAGD cylindrical model, (4) cooling system, (5) constant pressure maintaining system and (6) production system. Temperature, pressure and steam injection rate were controlled by computer, and product (mixture of oil and water) was collected/separated manually. Extra heavy oil (<10 cp at 200 o C) and glass bead (diameter 1.5 mm) were mixed homogeneously for making porosity of 0.3 and applied for simulating oil sand. For obtaining optimum operation conditions of SAGD apparatus, several attempts were made. When the steam at high temperature (160-180 o C), high pressure (8-9 atm) was injected with 20-25 cc/min, cSOR (cumulative steam to oil ratio) of about 5 was obtained with oil recovery of 78.8%.
Measuring resilience to natural hazards is a central issue in the hazard mitigation sciences. This paper applied a confirmatory factor methodology to operationalize the biophysical, built-environment, and socioeconomic resilience dimensions for local jurisdictions in large urban metropolitan areas in South Korea. Mapping the factor scores of the dimensions revealed great spatial variations. The factor covariances showed a trade-off relationship between natural infrastructure and human activities. A hierarchical cluster analysis was used to classify the localities into heterogeneous groups with respect to the identified resilience dimensions. Densely developed and affluent urban areas tend to lack biophysical resilience. Some local governments, sorted into the same groups, turn out to be located in different metropolitan areas. The spatial variation and inequality in the resilience dimensions suggest the necessity of integrated and flexible governance for sustainable hazard mitigation.
This paper classifies cities in the metropolitan area based on natural hazard vulnerability. The procedure of our empirical analysis is divided into three parts as follows: First, it summarizes variables related to natural hazard vulnerability to significant factors, carrying out principal component analysis. Second, it classifies cities in the metropolitan area, conducting cluster analysis using factor scores. Lastly, it proposes differential measures for natural hazard mitigation for classified cities in the metropolitan area, based on natural hazard vulnerability.
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