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Index Evaluation Methodology of Egs Exploration Constituency
There are many EGS projects in the world, dealing with numerous basic geological data, but there is no detailed report on exploration evaluation methodology. Chinese Academy of Sciences (Pang Zhonghe), Institute of Water And Environment of Geological Survey Bureau (Ma Feng), Sinopec (He Zhiliang) and other institutes have carried out the establishment of exploration systems. Based on the consideration of different factors, the evaluation methodologies built are not the same, but they all consider geological, engineering, economic and etc.. After complete investigation, ENN energy Research Institute established the evaluation index system of EGS exploration constituency based on geological evaluation. The selection of evaluation indexes tries to comprehensively consider possible geological problems as far as possible, which can be divided into two levels: the first level has 4 indexes, namely heat source, heat reservoir, cap layer and fault, and the second level has 22 indexes, including 8 heat source indexes, 8 heat storage indexes, which can be divided into granite and carbonate rocks. There are 3 indicators for both cap layer and fault, which have been specially discussed in another article (Liu Yuying). For quantitative evaluation of various sites, it is necessary to establish an index evaluation methodology, including the determination of the weight coefficients of each secondary index and the expert scoring method. After multiplying the weight coefficients and the corresponding evaluation scores, the comprehensive score of the site can be obtained. The analytic hierarchy process (AHP) is used to determine the weight coefficient, which combines quantitative analysis with qualitative analysis to ensure its scientific nature. According to the established indicator system and its mutual relationship, the total weight of indicators with correlation at all levels is 1. For each level of indicators, the relative importance of each level of indicators is judged by decision-maker's understanding, and the importance is assigned, and the relative weight of each level of indicators is calculated by matrix judgment method. Finally, the comprehensive weight coefficient of the secondary index is obtained by using the single weight score of the secondary index and the corresponding weight of the primary index. Considering the scientific nature of the scoring and the complexity of geological conditions, if the evaluation of each secondary index is "good", the corresponding score is 95 or 85; if the evaluation is "medium", the corresponding score is 75 or 65; if the evaluation is "poor", the corresponding score is 55 or 45.