An Application of Petrophysical Fades Study and Artificial Neural Network in Log Interpretation at High Water - cut Stage

摘要

In this paper, an integrated technique is developed for reservoir parameters interpretation, which involves reservoir petrophysical facies study and the application of artificial neural network. The key points for this technique are as follows:1) Reservoir petrophysical facies study: By taking advantage of core data, based on petrophysical properties analysis and the quantitative indicator FZI(flow zone indicator), together with lithofacies types, the types of petrophysical facies are subdivided, and each of these types is characterized.2)The relationships between FZI and log responses are established based on artificial neural network model and crossplots of FZI vs log responses are also established.3) Establish reservoir parameters prediction models based on petrophysical facies types by using artificial neural network.4)Select the appropriate prediction model for parameters prediction. This method has resulted in an improved prediction of reservoir parameters interpretation, particularly for the low and super low permeability formations which are the major potential targets at high water- cut stage.