R/S分析估算储层参数分维研究新进展

New development in fractal dimension estimation for reservoir parameters using R/S analysis

成都理工学院,成都610059

Chengdu College of Technology, Chengdu 610059

R/S分析是估算储层参数和测井数据分维的重要方法。R/S分析要求数据满足分数布朗运动(FBM),而许多测井数据和储层参数满足分数高斯噪音 (FGN),R/S分析前必须对数据进行分级处理(Gradedsequence)。迄今为止,没有人对此做出明确解释。本文研究发现,储层参数或测井数据可以看成是典型的灰色系统,分级处理就是对数据进行灰色累加生成 (AGO),AGO处理能削弱数据的随机性。文中还提出了一种识别FBM和FGN的灰色判别新方法。

R/S analysis is an important method in fractal dimension estimation for reservoir parameters and well logs. R/S analysis requires that the data in question must have a fractal character called fractional Brown motion (FBM). However, some reservoir parameters and well logs only have fractal character called fractional Gaussian noise (FGN). So the data should be preconditioned via graded sequence processing before R/S analysis could be carried out. But so far there is no convincing explanation available for such conversion. This paper unveils that reservoir parameters and well logs could be viewed as a typical gray system and graded sequence processing is actually gray accumulated generating operation (AGO) to data. A new method for distinguishing FBM from FGN is also presented in the paper.