一种含水率预测模型的建立及应用

Establishment and application of a water cut prediction model

刘彦成 张亚飞 韩学婷 刘峰 周鹏 韩春硕 刘进

中联煤层气有限责任公司，北京 100015 西安石油大学石油工程学院，陕西 西安 710065 上海石油天然气有限公司，上海 200041 中国石油长庆油田分公司第八采油厂，陕西 西安 751500

China United Coalbed Methane Corporation Ltd., Beijing 100015, China College of Petroleum Engineering, Xi′an Shiyou University, Xi′an 710065, China Shanghai Petroleum Co., Ltd., Shanghai 200041, China No.8 Oil Production Plant, Changqing Oilfield Company, PetroChina, Xi′an 751500, China

含水率是反映水驱油田开发生产动态的一个重要指标，准确预测水驱油田含水上升规律对油田开发具有重要意义，可为油田开发动态分析、开发规划及开发方案调整提供合理依据。鉴于传统含水率预测方法具有一定局限性且与油田开发时间无关，文中依据水驱油田含水上升规律和广义Weibull分布的特征，建立了一种含水率随开发时间变化的预测模型（广义Weibull模型），克服了传统方法在预测水驱油田含水率中的不足。从含水率变化特征分析认为，特定条件下，新模型涵盖了几种特定的含水率预测模型，可以描述凸形、S形和凹形的含水上升规律，适用范围相对单一模型更为广泛。3个油田的实例应用表明，新模型预测精度较高，误差较小，平均相对误差分别为2.01%，6.29%和10.65%，与实际含水上升规律吻合程度较好，适用于整个开发阶段的含水率预测。

Water cut is an important index which can reflect production performance of water flooding fields. Accurate prediction of water cut in water flooding field is of great significance for the development of oilfield, which can provide a reasonable basis for the production performance analysis, development planning and adjustment of development program. Considering that traditional water cut prediction methods have certain limitations and have nothing to do with oilfield development time, based on the rising law of water cut in water flooding oilfields and the characteristics of generalized Weibull distribution, a prediction model of water cut changes with development time was established. This model overcomes the shortcomings of traditional methods in predicting water cut in water flooding oilfields. From the characteristics of water cut change, it is believed that the new model covers several specific water cut prediction models under specific conditions, which can describe the rising law of water cut in convex, S and concave shapes, and the scope of application is wider than that of a single model. The application of examples show that the new model has high prediction accuracy and small errors. The average relative errors of new model are 2.01%, 6.29%, 10.65% respectively, which are in good agreement with the actual water cut rising law. The new model is suitable for the water cut prediction at the entire development stage.

10.6056/dkyqt202302017