川中低渗气藏中的储层流动单元划分研究

FLOW UNIT DIVISION OF THE LOW-PERMEABILITY GAS RESERVOIRS IN CENTRAL SICHUAN

针对低渗气藏开发中所面临的难题,以及流动单元划分中存在的问题,提出了一种比较有效的储层流动单元划分新方法。本文以川中低渗气藏为例,结合取心物性资料、测井资料,选用流动层带指数FZI划分方法将取心井储层流动单元划分成Ⅰ、Ⅱ、Ⅲ类,并建立流动单元的识别和划分标准。在此基础上,利用BP神经网络技术对取心井储层流动单元进行学习训练,与测井曲线建立其相关的学习和预测模型,对非取心段储层流动单元进行预测,明显提高了测井解释精度。其中,Ⅰ类流动单元开发效果最好,Ⅱ类流动单元开发效果次之,是挖潜的主要目标,Ⅲ类流动单元开发效果最差。

A new method is proposed to divide the flow unit effectively according to the problems in development of low-permeability gas reservoirs.In the paper, the reservoir flow units of a coring well are divided into 3 kinds ( type Ⅰ, type Ⅱ and type Ⅲ) by choosing the flow zone index FZI based on the physical property data and logging data and the identification and division standards are established.Then BP neural network is used to train the flow units of coring wells and establish correlative learning and predictive model with logs, with which the flow units of non-coring reservoirs can be predict. It improves the well logging interpretation precision greatly.The development effect of typeⅠis best,type II follows by, which are the main goal of tapping the potential, and type Ⅲ is worest.