Simulation Conditions j We set up three users (uA, uB, and uC) for the sim- ulation experiments. Their initial requirements are shown in Table 3. These values were set to be rela- tively strict so that an agreement is less likely to be reached in the first round. Among the three users, uA has the strictest requirements and uC has the least strict requirements. All weights (w(uk)) used to calcu- ior, we define a parameter to decrease the thresh- old after each time the system presents a recom- mended item. late the utility values were set to 1. A user is supposed to accept a recommended item if the utility value of the item for the user equals or Attribute price Table 1: Defined attributes for describing items. Description amount of money expected to be needed distance distance from the nearby airport access how easy to access landscape how beautiful its landscape is crowdedness how not crowded it is barrier free how easy it is for people with disabilities to visit Value range 1000 – 10000 1 – 5 1 – 5 1 – 5 1 – 5 review score Table 2: User personality type and parameters. Personality type Cooperativeness Assertiveness Initial threshold Threshold decay Concession factor price distance review ratio collaborating high high 0.8 0.01 250 10 0.5 0.5 accommodating high low 0.7 0.01 100 10 0.25 1.0 avoiding low low 0 0 – – – – Attribute User uA uB uC price 000 000 0000 distance 10 20 20 access 4 4 4 landscape 5 4 4 crowdedness 5 5 5 barrier free 5 5 4 Table 3: Initial requirements of users in the simulation. review score exceeds the user’s threshold. To reflect the personal- ity types in the simulation model, the initial threshold was set according to the personality types as shown in Table 2. In addition, the threshold is decreased each time the item is presented by the amount speci- fied as threshold decay, which is set to 0.01 for types whose cooperativeness is high (Table 2). For other personality types, this value is set to 0, meaning that the threshold does not change.
Simulation Conditions. Table 6: Initial and boundary conditions for the production test in the RN-15 well. Parameter Value Bottom hole pressure 13.06 MPa Bottom hole enthalpy 1211 kJ/kg Bottom hole temperature 275.5°C Mass flow rate 72 kg/s Simulation time 12 h The RN-15 well completion at the logging date, the thermo-physical parameters and the rock properties are taken from Table 1, Table 3 and Table 4 respectively. The assumed formation temperature is taken from the exponential regression of the given SFT profile, as explained in Subsection 3.1.5 “A priori formation temperature profile down to 2500 m”. Hence, the SFT is 287.7°C at 2500 m depth and remains near constant up to 1500 m (see Figure 4, red curve). In this production test, the boundary conditions are set at the bottom of the well. Table 6 gives the specific parameters used. The chosen bottom-hole temperature corresponds to the average of the measured temperature over the last 200 m of the log. Finally, a simulation period of 12 hours is taken to allow reaching a steady state in the well.
Simulation Conditions. For the general parameters, see Table 1, Table 3 and Table 4. In this test, the boundary conditions are set at the top of the well. Table 7 gives the specific parameters used. In addition, the SFT is taken from the exponential fit as explained in Subsection 3.1.5 “A priori formation temperature profile down to 2500 m”. These data were provided by ISOR, but the water injection duration before measuring was not given. This explains why we will test here three different injection periods. Table 7: Initial and boundary conditions for the injection test in the RN-15 well. Parameter Value Injected water temperature 14°C Mass flow rate 29.5 kg/s Injection period 0.1, 0.5 and 2 years
Simulation Conditions. In this case, only pressure propagation along the borehole is investigated. Xxxxxx et al. (1999) provide a numerical calculation of the pressure profile along the geothermal well M-
