| 密度和速度随机分布共网格模型的重力与地震联合反演 |
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| 引用本文： | 于鹏,戴明刚,王家林,吴健生.密度和速度随机分布共网格模型的重力与地震联合反演[J].地球物理学报,2008,51(3):845-852. |
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| 作者姓名： | 于鹏 戴明刚 王家林 吴健生 |
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| 作者单位： | 1.同济大学海洋地质国家重点实验室, 上海 200092;2.中国石油化工股份有限公司石油勘探开发研究院, 北京 100083 |
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| 基金项目： | 国家高技术研究发展计划(863计划) |
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| 摘 要： | 针对重力与地震联合反演存在的问题,结合已有的研究成果,本文研究实现了速度和密度随机分布共网格单元模型的建模技术,以适应密度和速度剧烈变化的复杂模型及联合反演的计算要求.重力正演利用了该网格的二度半体模型,并进一步改进了地震走时的二维射线追踪计算方法,以适用于速度随机分布的网格介质.结合改进的模拟退火算法,实现了这种共网格条件下的重力与地震资料的同步联合反演.模型试验证明了重力与地震联合反演可以准确确定复杂物性界面的密度和速度结构,适用于物性界面不完全一致和物性变化剧烈的复杂模型,并且联合反演结果要优于单独的重力反演.带先验信息约束下的实际资料的联合反演,进一步证明了该方法的适用性和效果,可提高反演精度并减少多解性.
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| 关 键 词： | 重力 地震 联合反演 模拟退火 网格模型 |
| 文章编号： | 0001-5733(2008)03-0845-08 |
| 收稿时间： | 2007-7-27 |
| 修稿时间： | 2007年7月27日 |
Joint inversion of gravity and seismic data based on common gridded model with random density and velocity distributions |
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| YU Peng,DAI Ming-Gang,WANG Jia-Lin,WU Jian-Sheng.Joint inversion of gravity and seismic data based on common gridded model with random density and velocity distributions[J].Chinese Journal of Geophysics,2008,51(3):845-852. |
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| Authors: | YU Peng DAI Ming-Gang WANG Jia-Lin WU Jian-Sheng |
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| Institution: | 1.State Key Laboratory of Marine Geology, Tongji University, Shanghai 200092,China;2.Petroleum Exploration & Production Research Institute of SINOPEC, Beijing 100083, China |
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| Abstract: | In view of the problems existing in joint inversion of gravity & seismic data and the published research results,we study a model construction method based on common gridded model with random density and velocity distributions to meet the needs of joint inversion and the complicated model with large density and velocity variations.2.5 dimensional gravity forward modeling is fulfilled in accordance with this gridded model.By improving the ray-tracing method in 2 dimensional seismic travel-time computing to suit the gridded media with random velocity distribution,we realize the synchronous joint inversion of gravity & seismic data based on this kind of common gridded model in accordance with the improved very fast simulated annealing algorithm.The model test shows that the joint inversion could accurately determine the density and velocity structures of complicated model with uncommon interface and large variations of density and velocity.Moreover,joint inversion method is clearly superior to the single inversion of gravity data.The joint inversion of the observed data with a priori constraining information also gives good effects,which make it clear that this method is effective and practicable in improving inversion accuracy and reducing ambiguity. |
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| Keywords: | Gravity Seismic Joint inversion Simulated annealing algorithm Gridded model |
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