利用改进组合交叉熵实现煤层气储层地震属性约简

在煤层气储层参数预测中，地震属性数据量的冗余会给预测带来不便。为获得煤层气储层地震属性的最优约简，提出一种利用改进型交叉熵算法优化地震属性的方法。该方法对迭代过程产生的样本进行改进，进而生成优秀的样本集进行迭代，同时将粗糙集属性约简构成的模型作为目标函数进行寻优求解。最后利用某地区煤层气储层的地震属性对算法进行验证，并与其他算法的测试结果对比、分析，结果表明:该算法对煤层气的地震属性约简耗时小、约简精度和约简率高，可以有效的应用于煤层气储层的地震属性约简。 

Seismic attribute reduction of CBM reservoir using improved combined cross entropy

In the prediction of CBM reservoir parameters, the redundancy of seismic attribute data brings inconvenience to the prediction. In order to obtain the optimal reduction of seismic attributes of CBM reservoir, an method using improved cross entropy algorithm to optimize seismic attributes was proposed. This method improved the samples generated by the iterative process, and then generated an excellent set of samples. At the same time, the model of rough set attribute reduction was used as the objective function to solve the optimization. The model of attribute reduction of rough set is solved by using the improved combined cross entropy algorithm. Finally, the seismic attributes in an area were used to verify and compare the algorithm with the other algorithms. The results show that the algorithm is less time-consuming, has high precision and ratio of reduction, and can be effectively used in seismic attribute reduction of CBM reservoir.