试油层非线性产量预测模型研究

Study on The Prediction Model of Oil Testing Formation Non-linear Productivity

准确的产量预测是油田勘探开发的重要研究任务,而常规的预测方法无法应用于开发初期。同一勘探区块,试油层产量与各影响因素存在一定的相关性。首先建立了产量与各静、动态参数的一元非线性回归模型,然后将其作为新的自变量,进行多元线性回归,最后获得了预测试油层产量的非线性回归模型。现场实际应用表明,建立的多元非线性模型比线性模型预测精度更高,适用性更好。为该勘探区块试油层措施改造决策提供了科学的指导,提高了试油经济效益。

The accurate productivity prediction is an important research task in the process of exploration and development of oil filed.However,conventional prediction methods are inapplicable for the early stage of oil development.There is a certain correlation between oil-test formation production and all related factors in the same exploration blocks.A nonlinear regression model between the production and all static or dynamic parameters is established,which is used as a new independent variable to start multiple linear regression.Finally a non-linear regression model used for the prediction of oil-test formation production is obtained.Nonlinear model is more accurate in prediction and more applicable compared with multivariate linear models.It provides scientific guidance for deciding the oil-test formation reconstruct method in the exploration block and increases the economic benefits of oil testing.