为精准描述低对比度油气层与其他类型储层之间的数学差异,引入特征选择和分类归纳等数学分析模型.所提方法并不要求储层计算参数与储层实际特征完全吻合,只要能准确刻画不同类型流体之间的数值差异即可.以鄂尔多斯盆地陇东地区超低渗透油层改造后的产能预测为例,阐述整个实施过程.结果表明:利用所建产能模型预测77口新井压裂后的产能,平均绝对误差为0 95 t/d,平均相对误差为9.49％,可以满足实际生产需求；在开展或完善储层表征参数理论模型研究的同时,各种数学分析方法的适用性、逻辑性也应被重视;传统方法和数学模型的有效结合能避免方法的单一化或模式化,有助于解决地层评价领域中的各种疑难问题.%In order to accurately identify the mathematical difference between the low contrast hydrocarbon reservoir and other reservoirs and precisely discover the low contrast hydrocarbon reservoir, the feature selection and classification models were introduced. They were applied 1o exploring the particularity of low contrast hydrocarbon reservoir. This method doesn't require the calculated reservoir parameters to be fully equivalent to the practical reservoir characteristics. It will be workable as long as the numerical differences among different types of fluids can be depicted- Taking the productivity forecast of ultra-low permeability oil layer in the Longdong region of Ordos Basin as an example, its whole process was elaborated. The productivity model was utilized to predict the fracturing productivities of 77 new wells. The mean absolute error is 0. 95 t/d and the mean relative error is 9. 49%. And the accuracy rale is satisfactory. The theoretical model of reservoir characterizatiun parameters should be' improved, while the applicability and logicality of the mathematical analysis method should also be given enough attention. Moreover, the effeclive combination of the traditional methods and mathematical models can avoid the simplification and modeling of method, and be conducive to the solution of difficult problems in the area of formation evaluation.
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