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新场须四段叠后裂缝综合预测 被引量:6

The integrated poststack fracture prediction of Xusi formation in Xinchang survey
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摘要 叠前裂缝预测方法主要针对垂缝和高角度缝,而川西新场须四下亚段致密砂岩储层裂缝以低角度缝为主,叠前方法在本工区不再适用;而单一叠后属性的裂缝预测方法可靠性差,因此,笔者提出了一套叠后裂缝综合预测新方法:首先基于多属性聚类分析进行裂缝地震相分级,并利用实测资料进行监控,从而实现多属性、多尺度裂缝综合定性预测;然后对滤掉基质相的曲率数据计算蚂蚁体,减小基质相对蚂蚁追踪的影响,从而得到能识别小尺度裂缝且裂缝形态更加清晰的高精度蚂蚁体;最后,基于高精度蚂蚁体建立三维裂缝模型,对裂缝发育特征进行半定量预测。实际应用结果表明:基于叠后资料的新一套裂缝综合预测思路在新场地区应用效果好,有效解决了低角度缝难预测的问题。 Techniques of prestack fracture prediction mainly aim at vertical and high angle fractures. However, low angle fractures of the tight sandstone gas reservoir are dominant in Chuanxi field of Xinchang survey. Therefore prestack methods are not suitable to this survey. Furthermore, the reliability of single poststack attribute to predict fractures has been questioned. To overcome the above prob- lems, the authors propose in this paper a new idea about the integrated fracture prediction. Firstly, fracture classification based on multi-attribute is adopted, and real measured data are used to monitor the result, and then qualitatively integrated fracture prediction of multi-attribute and multi-scale is realized. Secondly, ant attribute body can be obtained from curvature that has filtered the background data. The influences of the background part of curvature on the ant attribute body can be reduced, so that ant attribute body with high precision is obtained, which can recognize smaller fractures clearly. Finally, on the basis of the ant attribute body with high precision, 3D fracture model is established, and then quantitative prediction on the features of fracture development can be realized. The applica- tion of this new idea of integrated fracture prediction to Xinchang survey shows that the new method is effective, and the problem of low angle fractures prediction is effectively solved.
出处 《物探与化探》 CAS CSCD 2014年第5期1038-1044,共7页 Geophysical and Geochemical Exploration
基金 国家重大专项(2011ZX05005-002-003-003) 中石化科技部项目(P12109)
关键词 裂缝预测 叠后 地震相分级 曲率 蚂蚁体 新场 fracture prediction poststack seismic classification curvature ant attribute body Xinchang
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