重磁联合反演电震界面的统计建模技术 |
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引用本文: | 阎汉杰.重磁联合反演电震界面的统计建模技术[J].油气地球物理,2003,1(1):22-27. |
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作者姓名: | 阎汉杰 |
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摘 要: | 传统反演技术从理论模型出发,建立重震(电)、磁震(电)的单项反演剖面确定地质模型,而重磁联合反演电震界面的统计建模则是从随机模型出发,建立重磁电震联合反演平面统计地质模型。理论上,重力场、磁力场、电场、地震波场的原函数、逆函数及其复合函数,必然在定义域内皆可展成为泰勒(傅立叶)级数的无限连续可微函数,并可进一步将其简化为求解级数最佳逼近式的统计推断问题。本文以此理论为基础,以分布独立的地质(断裂)系统为控制单元,把反演界面深度作为与其对应的极值重磁异常的二元复合逆函数,利用已知电法—地震深度、极值重磁异常剖面等资料,统计推断其级数分布,构建了重磁震联合反演建模技术。该项基于高精度的重磁场论应用技术已成功应用于合肥盆地重磁电震联合地质勘探中。
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关 键 词: | 物理场函数 随机(理论)模型 重磁差值趋势面分析 统计推断 联合反演 |
The statistical establishing model technique for the electric seismic interface of the gravity-magnetic joint inversion |
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Abstract: | To build gravity-seismic (magnetotelluric), magnetic-seismic (magnetotelluric) inversion section using conven-tional inversion technology is starting with theoretical model to determine the geological model, but gravimagneticjoint inversion of magnetotelluric-seismic profile statistically modeling technology is to built gravimagnetic and elec-tric-seismic joint plane inversion statistical geological model from stochastic model. Theoretically the origin function,inverse function and compound function of gravity, magnetic, electric, seismic wave field must be expanded to a Tay-lor (Fourier) series' infinite continuous differentiable function, and further more it can be simplified to a solution seriesof favorable approximation statistic conclusion. Based on the theory, taking inversion interface depth as its extremismgravimagnetic anomalies bivariate compound inverse function, using geological (fault) system distributing indepen-dently as a controlling unit, applying known electrical-seismic depth, extremum gravimagnetic anomaly section to sta-tistically deducing series distribution a gravity-magnetic-seismic joint inversion modeling technique is built. The highprecision gravimagnetic field theory and application technology have been successfully used ingravity-magnetic-electric-seismic joint geological exploration in Hefei basin. |
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Keywords: | physical field function stochastic model gravimagnetic differential trend surface analysis statistical con-clusion joint inversion |
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