Abstract
Currently, the classification criterion of reserves were determined by the scope of the values of criteria such as geological attributes, reservoir phydical parameters and etc., which required all attribute values of one block were just right in the existing range of criteria, otherwise it would be difficult to divide the hard-to-recover reserves into different categories. To solve this problem, this paper combined with Fuzzy -Means clustering algorithm(FCM) and combination weighting approach to classify hard-to-recover reserves. First we use FCM to automatically search for the optimal category number of reserves based on effect indexes, then establish a combination weighting model aiming at the minimal error-sum of deviation of subjective weights and deviation of objective weights, to decide the weights of attributes and the values of effect indexes, and judge which category each block belonge to, according to the result of FCM. To verify the validity of model, this paper applies it to the classification problem of hard-to-recover reserves from an oil field in the 10th Oil Production Plant of PetroChina Daqing Oilfield LLC, which conducts the rolling development of hard-to-recover reserves.
Recommended Citation
Zhi, Li; Juan, Yang; and Kejun, Zhu, "Classification of Hard-to-Recover Reserves Based on FCM and Combination weighting approach" (2013). WHICEB 2013 Proceedings. 70.
https://aisel.aisnet.org/whiceb2013/70