基于子波分解与重构的储层预测技术
RESERVOIR PREDICTION TECHNOLOGY BASED ON WAVELET DECOMPOSITION AND RECONSTRUCTION
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摘要: 随着油气勘探程度的不断提高,勘探对象越来越复杂,为了增储上产,开展有效的储层预测成为油气勘探的重点。受分辨率的限制,利用常规地震剖面进行储层预测很难满足油田生产的需求。为此,对子波分解与重构理论进行了深入研究。结合实际资料,建立了能反映储层情况的地质模型,对模型进行正演模拟,明确了特殊地质体的地震响应特征。发现低频端包含了较多的储层信息,对储层空间展布的精细预测具有非常重要的作用。模型试验和实际资料处理表明,该方法能充分挖掘地震资料的有效信息,较好地进行储层预测。将该技术应用到研究工区的储层预测中,获得了与钻井结果相吻合的良好效果。Abstract: In order to increase the oil reserve and production, use of effective methods for reservoir prediction has become the main requirement of oil exploration. Owing to the limitation of resolution, reservoir prediction based on conventional seismic profile is hard to meet the needs of oil field production. This paper devotes itself to the deep study on the wavelet decomposition and reconstruction theory. According the actual data, a reservoir geological model which can reflect the actual situation is created. Forward modeling is done based on the model and the seismic characteristics of specific geological objects are revealed. It is found that the low frequency part of seismic data contains some useful information on the spatial distribution of reservoir. Model tests and practical seismic data interpretation have demonstrated that the method can fully dig out valid information from seismic data and effectively predict the distribution pattern of the reservoir. The result of reservoir prediction using the method coincides well with drilling results.