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Prediction of Coalbed Methane Production Based on BP Neural Network

机译:基于BP神经网络的煤层气产量预测。

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The low average daily gas production per well and the poor economic benefit of exploration and development have become the main problems restricting the exploration and development of coalbed methane in China. Combining multiple coal seam geological parameters to predict the high-yield area of the block can not only provide guidance for the exploitation of coal-bed methane, but also bring enormous economic benefits. Aiming at the difficulty of coalbed methane dessert discrimination and production prediction, a method of coal-bed methane production prediction based on BP neural network is proposed in this paper. Starting from the average daily production of coalbed methane single well, we use the method of grey correlation degree to get the main controlling factors of coalbed methane production. For the main control factors, we use BP neural network with high fitting accuracy and get a good prediction result.
机译:每口井日均天然气产量低,勘探开发的经济效益差已成为制约我国煤层气勘探开发的主要问题。结合多个煤层地质参数预测该区块的高产区,不仅可以为煤层气的开采提供指导,而且可以带来巨大的经济效益。针对煤层气甜点识别及产量预测的难点,提出了一种基于BP神经网络的煤层气产量预测方法。从煤层气单井的日均产量开始,采用灰色关联度法得出煤层气产量的主要控制因素。对于主要控制因素,采用拟合精度高的BP神经网络,取得了良好的预测效果。

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