Unconventional oil and gas exploration and development has gradually become a hot spot in oil and gas industry, and production prediction has much uncertainty in early development stage. In this paper, a new prediction method combi-ning decline analysis with probability statistics was proposed to quantify the uncertainty and thus make the early production forecast more reasonable. By taking the tight oil projects in North America as the research object, according to the typical feature of unconventional oil and gas statistically, using statistics that did not change with time to describe single well pro-duction performance, combining traditional decline analysis and probability statistics, a classification method building type curve under different probability was put forward. The method focuses on the uncertainty on tight oil production prediction in early development stage, using a predicted range to describe possible type curve. A practical method was provided for tight oil projects yield prediction and undeveloped reserves evaluation. Because it only makes probability statistics analysis on in-itial production and initial decline rate, it can not fully reflect the uncertainty of production prediction, Therefore, as the project continues and production data rise, next work should be aim at expanding the range of parameters of probability a-nalysis and making prediction more rational. The method has been applied to actual operation of the project, and the fore-cast result consists with the actual production data, which proves that it has better applicability.%非常规油气开发早期的产量预测存在诸多不确定性. 以北美地区的致密油项目为研究对象, 依据非常规油气在统计学上的典型特征, 使用几乎不随时间变化的统计数据来描述非常规区带单井的生产动态, 将传统递减分析与概率统计相结合, 提出一种建立不同概率下典型生产曲线的方法. 用一个预测范围描述可能的典型生产曲线, 较好地解决了非常规油气开发早期产量预测过程中的不确定性问题, 为非常规油气产量分级预测及未开发储量评估提供了一种实用方法. 由于本方法只对初始产量和初始递减率两个最主要的参数进行了概率统计分析, 不能完全反映产量预测过程中的不确定性, 因此随着项目生产数据的增多, 应扩大概率分析的参数范围, 增加预测的合理性. 实际生产验证, 该方法预测结果和生产数据吻合较好.
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