基于局部层析的
  <strong>TTI</strong>各向异性参数初始建模方法研究

doi:10.11867/j.issn.1001-8166.2019.10.1060

地球科学进展 ›› 2019, Vol. 34 ›› Issue (10): 1060 -1068. doi: 10.11867/j.issn.1001-8166.2019.10.1060

基于局部层析的 TTI各向异性参数初始建模方法研究

郭恺(

)

中国石油化工股份有限公司石油物探技术研究院，江苏南京 211103

收稿日期:2018-12-24 修回日期:2019-08-20 出版日期:2019-10-10
基金资助:
国家重点研发计划项目“面向E级计算的能源勘探高性能应用软件系统与示范”(2017YFB0202904)

Research on Initial Modeling Method for TTI Anisotropic Parameters Based on Local Tomography

Kai Guo( )

Sinopec Geophysical Research Institute, Nanjing 211103，China

Received:2018-12-24 Revised:2019-08-20 Online:2019-10-10 Published:2019-12-09
About author:Guo Kai （1985-）， male， Weifang City, Shandong Province， Senior engineer. Research areas include velocity modeling technology of anisotropic media. E-mail： guokai_leon@163.com
Supported by:
the National Key R & D Program of China “High performance application software system and demonstration for energy exploration of E-Level computing”(2017YFB0202904)

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TTI各向异性参数初始建模为层析反演精细建模提供初始模型，初始模型的优劣直接影响层析反演的效率和精度，研究精确的TTI各向异性参数初始建模方法非常必要。基于常规TTI各向异性参数初始建模方法流程，优化了各向异性参数提取公式，引入了局部层析方法，完善了TTI各向异性参数初始建模方法流程，进一步提高了TTI各向异性参数初始模型的精度，与实际地质情况更加吻合，有利于后期的层析反演精细建模。模型试算和实际资料处理结果表明基于局部层析的TTI各向异性参数初始建模方法有效且实用。

关键词: TTI介质, 初始建模, 局部层析, 参数提取, 层析反演

The initial modeling method based on TTI anisotropy can provide an initial model for the fine modeling of tomographic inversion, and the quality of the initial model directly affects the efficiency and accuracy of tomographic inversion. It is necessary to study the accurate initial modeling method of TTI anisotropy. Based on the conventional flow of the initial modeling method of TTI anisotropic, in this paper the anisotropic parameter extraction formula was perfected, a local tomography method to optimize the flow of the initial modeling method of TTI anisotropy was introduced, and the accuracy of the initial model was further improved, which is more consistent with the actual geological conditions and conducive to the fine modeling of the later tomographic inversion. The processing results of model and filed data show that the initial modeling method of TTI anisotropy based on local tomography is effective and practical.

Key words: TTI medium, Initial modeling, Local tomography, Parameter extraction, Tomographic inversion.

中图分类号:

P315.3+1

图1 真实模型

Fig.1 The real models
(a)

V P 0

；(b)

ε

；(c)

δ

图1 真实模型

Fig.1 The real models
(a)

V P 0

；(b)

ε

；(c)

δ

图2 初始模型

Fig.2 The initial models
(a)

V P 0

；(b)

ε

；(c)

δ

图2 初始模型

Fig.2 The initial models
(a)

V P 0

；(b)

ε

；(c)

δ

图3 参数提取结果

Fig.3 Parameters extraction results
(a)

V P 0

；(b)

ε

；(c)

δ

图3 参数提取结果

Fig.3 Parameters extraction results
(a)

V P 0

；(b)

ε

；(c)

δ

图4 局部层析结果

Fig.4 Local tomography results
(a)

V P 0

；(b)

ε

；(c)

δ

图4 局部层析结果

Fig.4 Local tomography results
(a)

V P 0

；(b)

ε

；(c)

δ

图5 数值曲线分析

Fig.5 Numerical curves analysis
(a)

V P 0

；(b)

ε

；(c)

δ

图5 数值曲线分析

Fig.5 Numerical curves analysis
(a)

V P 0

；(b)

ε

；(c)

δ

图6 TTI各向异性参数初始模型
(a)，(d)，(g)基于最优拟合表达式提取的

V P 0

，

ε

和

δ

模型；(b)，(e)，(h）局部层析后的

V P 0

，

ε

和

δ

模型；(c)，(f)，(i）局部层析更新量

Fig.6 Initial model of TTI anisotropic parameters
(a)，(d)，(g)

V P 0

，

ε

and

δ

models extracted based on optimal fitting expressions；(b)，(e)，(h）

V P 0

，

ε

and

δ

models after local chromatography；(c)，(f)，(i）Update of local chromatography

图6 TTI各向异性参数初始模型
(a)，(d)，(g)基于最优拟合表达式提取的

V P 0

，

ε

和

δ

模型；(b)，(e)，(h）局部层析后的

V P 0

，

ε

和

δ

模型；(c)，(f)，(i）局部层析更新量

Fig.6 Initial model of TTI anisotropic parameters
(a)，(d)，(g)

V P 0

，

ε

and

δ

models extracted based on optimal fitting expressions；(b)，(e)，(h）

V P 0

，

ε

and

δ

models after local chromatography；(c)，(f)，(i）Update of local chromatography

图7 过井1成像剖面
(a)参数更新前剖面；(b)参数更新后剖面

Fig.7 Imaging profile crossed well 1
(a)Imaging profile before parameters update；(b)Imaging profile after parameters update

图8 过井2成像剖面
(a)参数更新前剖面；(b)参数更新后剖面

Fig.8 Imaging profile crossed well 2
(a)Imaging profile before parameters update；(b)Imaging profile after parameters update

图9 过井3成像剖面
(a)参数更新前剖面；(b)参数更新后剖面

Fig.9 Imaging profile crossed well 3
(a)Imaging profile before parameters update；(b)Imaging profile after parameters update

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