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首页> 外文会议>IEEE International Geoscience and Remote Sensing Symposium >The Quantity Analysis Method Research of Oil and Gas Geo-Anomaly Information Mining - Take Oil and Gas Exploration Application in East China as an Example
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The Quantity Analysis Method Research of Oil and Gas Geo-Anomaly Information Mining - Take Oil and Gas Exploration Application in East China as an Example

机译：石油和天然气地球异常信息采矿量分析方法研究 - 以华东地区为例

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During the oil-gas exploration, there collects much information concerning geo-physical exploration, geo-chemical exploration, remote -sensing and geology exploration. Depending on the traditional exploration methods, it is difficult to make a further progress with the deep step in oil exploration, so new theories and methods are urgently needed. Geo-Anomaly theory was first put forward by Zhao Pengda, a Chinese math geologist, in 1991. It has been widely applied in solid mineral exploration. In this research, it is promoted in oil and gas exploration. How to mine valuable oil and gas geo-anomaly information and knowledge from all collected data is a big problem. From the point of this view, taking Oil and Gas Exploration Application in one Basin in east China as an Example, research has been done on mining oil and gas geo-anomaly information using data mining technology. During the research, some new mining methods such as block convulsion filtering, BP neural network and grey prediction are applied besides entropy, complex methods. Research shows that block convulsion filtering method is beneficial to remove noise from data, and grey prediction methods are better ways to extract geo-anomaly information from drilling and seismic data, BP network method is used well in predicting reserve and cover layer parameters with high accuracy, complex and entropy method does great effect in predicting the oil and gas preferable area. Through the above research on oil and gas geo-anomaly information mining, good results have been achieved in quantity methods for oil and gas geo-anomaly information extraction. The research contributes a lot to get effective exploration knowledge and predict preferable objects for oil and gas exploration.
机译：在石油天然气勘探期间，收集有关地球物理勘探，地理化学探索，远程敏感和地质勘探的许多信息。根据传统的探索方法，难以通过石油勘探的深步进行进一步进展，因此迫切需要新的理论和方法。 1991年，中国数学地质学家赵鹏达首次提出了地理异常理论。它已广泛应用于固体矿产勘探。在这项研究中，它促进了石油和天然气勘探。如何挖掘宝贵的石油和天然气地理异常信息和知识来自所有收集的数据是一个大问题。从这种观点来看，以华东地区的一个盆地申请石油和天然气勘探应用，以挖掘石油和天然气地球异常信息进行了研究。在研究期间，除了熵，复杂的方法之外，还应用了一些新的采矿方法，如块痉挛滤波，BP神经网络和灰度预测。研究表明，块痉挛滤波方法有利于从数据中消除噪声，灰色预测方法是从钻井和地震数据中提取地理异常信息的更好方法，BP网络方法在预测储备和覆盖层参数中使用高精度。 ，复杂和熵方法在预测油气优选的区域方面具有很大的效果。通过上述石油和天然气地球异常信息挖掘研究，石油和天然气地球异常信息提取的数量方法取得了良好的效果。该研究有很多导致有效的探索知识，并预测石油和天然气勘探的优选对象。

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