Synthetic Evaluation of Oilfield Development Plans Based on a Cloud Model
Zhibin Liu, LU Liu-li, Zhiyong Zhang, Yi-Shen Chen · Energy Technology & Policy · 2014
In the process of evaluating the oilfield development plans, there always exist uncertainties in data, weight assignment, and scheme grading. In this article, an improved evaluation method is introduced to tackle the uncertainties based on a cloud model. The indicators of a development plan are input into this model and a contribution score cloud is obtained for evaluation. The evaluation clouds of all the development plans are sorted by the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), with the weighted hamming distance. Then we can get the optimum development plan according to the order. In this model, the randomness and the fuzziness are both taken into consideration, and the feasibility and validity are verified by an example.