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Methods Study and Appliance of Forecast Acid Fracturing Production in Fractured and Cavernous Carbonatite Reservoir

机译:裂缝性和孔状碳酸盐岩储层酸压裂生产预测方法研究与应用

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Acid fracture treatment is one of the most effective way of stimulation in fractured and cavernous carbonatite reservoir. Because there are too many factors that influence the acid fracture effect, such as geologic factor, technic factor, material's factor, it is difficult to forecast the effect of acid fracture before the treatment has been done. The relationship between these factors and result of acid fracture is very complex, and it is different from hydraulic fracture in clastic reservoir . Although much more experience has been gathered from exercise, the relationship between affect factors and effect is also very difficult to be found. This paper designs two ways to solve this problem. One way is based on experts' experience and statistical method, and, another way is artificial neural network. By using practical data, and compared these two ways, we find that the precision ratio of the first way is 66 percent and another is 86 percent. Both of these two ways are suitable to forecast the effect of acid fracture in fractured and cavernous carbonatite reservoir. Furtherly, the artificial neural network is better.
机译:酸化压裂处理是压裂和海绵状碳酸盐岩储层最有效的增产方法之一。由于影响酸破裂效果的因素太多,例如地质因素,工艺因素,材料因素,因此在处理之前很难预测酸破裂的影响。这些因素与酸破裂结果之间的关系非常复杂,不同于碎屑岩储层的水力破裂。尽管从运动中获得了更多的经验,但是很难找到影响因素与效果之间的关系。本文设计了两种解决此问题的方法。一种方法是基于专家的经验和统计方法,另一种方法是人工神经网络。通过使用实际数据,并比较这两种方法,我们发现第一种方法的精度比率为66%,另一种为86%。这两种方式都适合预测裂缝性和海绵状碳酸盐岩储层中的酸性裂缝影响。此外,人工神经网络更好。

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