학위논문 (석사)-- 서울대학교 대학원 : 에너지시스템공학부, 2016. 8. 최종근.A distance is the degree of model dissimilarity and it is important for effective model selection. This paper suggests a cross spatial pattern to find permeability distribution from an injector to a producer. The distance is defined as one minus correlation coefficient of permeability data obtained by the spatial pattern.
Using multi-dimensional scaling, initial 400 reservoir models are projected on two dimensions based on the distance. By K-medoids clustering, they are classified into 10 groups. One representative medoid is chosen with the least difference in productions from the reference field. Then, 100 models are selected around the medoid for ensemble smoother(ES).
The proposed distance can achieve improved reservoir characterization and history matching combined with ES. Also, this method helps to reduce uncertainty ranges of future oil and water productions, and decreases total simulation time by 75% with proper sampling of good 100 models.1. Introduction 1
2. Methodologies 7
2.1 Defined distance from spatial patterns 7
2.2 Multi-dimensional scaling 10
2.3 K-medoids clustering 14
2.4 Ensemble smoother 17
3. Results and discussions 18
3.1 Field with high permeability at the side corners 19
3.2 Field with high permeability in diagonal direction 43
4. Conclusions 62
References 65
국문 초록 68Maste
