煤层含气量测井解释方法探讨

基金项目:

国家自然科学基金项目(49474235)

详细信息

DISCUSSION ON THE LOG INTERPRETATION METHOD OF COALBED GAS CONTENT

摘要: 用多元线性回归建立煤层气含量与煤质参数、测井曲线值之间的回归方程,经F检验回归方程有效,但回归方程估算的煤层含气量与煤样解吸测定的含气量之间仍然存在较大的误差,为此利用BP神经网络进一步探讨它们之间的关系,实例表明预测精度较高。
- 测井曲线 /
- BP神经网络 /
- 煤层气 /
- 预测
Abstract: Using multivariate linear regression,the relationships between coalbed gas content with coal quality parameters and log curve values are established.The regression equation is valid according to the F test,but there still a larger error between the coalbed gas content estimated by the regression equation and the gas content determined by the desorption of coal sample.Thus,their relationships are discussed further by using the BP neural network.The examples show that the prediction accuracy is higher.
- log presentation /
- BP neural network /
- coalbed gas /
- prediction