| Title | PROBABILISTIC RESOURCE ASSESSMENT USING EXPERIMENTAL DESIGN AND SECOND ORDER PROXY MODEL: THE ROTORUA GEOTHERMAL SYSTEM |
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| Authors | A.E. Ciriaco, S.J. Zarrouk, G. Zakeri |
| Year | 2018 |
| Conference | New Zealand Geothermal Workshop |
| Keywords | Rotorua, Geothermal resource assessment, probabilistic methods, natural state model, polynomial model, proxy model, response surface, Box-Behnken |
| Abstract | Resource assessment plays an important role in the financing, development and operation of a geothermal power project. There are several simple (volumetric and areal) resource assessment methods used in the industry to quantify the resource potential predominantly of green field projects. On the other hand, a more complicated numerical representation of geothermal reservoirs is used to model dynamic changes in the field and make predictions of future capacity. However, there is a need to develop a more robust approach with a lower level of uncertainty in the predictions compared to the existing techniques. A hybrid approach of response surface methodology and reservoir simulation provides an alternative method for probabilistic resource assessments. A probability distribution of production potential is generated by first determining the significant reservoir model parameters using Experimental Design (ED). A Box-Behnken response surface model design is then applied to determine the number of simulation runs required to run the experiment at three parameter levels (low, medium and high). The power potential calculated from the reservoir model runs is then used to create a polynomial (proxy) model and a Monte Carlo simulation is then applied to the proxy model to generate a probabilistic distribution of the potential power output. The method was tested successfully to the calibrated natural state model of the Rotorua Geothermal Field. At a 95% confidence interval, the model shows that the Rotorua geothermal system has an average potential to produce: P10 between 148 and 153 MWe, P50 between 147 and 153 MWe and P90 between 146 and 151 MWe for at least 30 years. This approach offers a new perspective on geothermal resource assessment, highlights the importance of developing numerical models even for a geothermal prospect at the early due diligence stage and provides a systematic way of handling the uncertain reservoir model parameters. |