Gravity gradient data joint inversion method

Abstract

The invention provides a gravity gradient data joint inversion method, relates to the technical field of geophysical inversion, and aims to introduce a gradient depth weighting function, physical property constraints based on pair/index transformation and other methods on the basis of focusing inversion in order to solve the problems of insufficient spatial resolution and the like of gravity gradient data inversion at present. Six components are combined in the full-tensor gradient data, and three-dimensional density inversion is achieved by using a nonlinear conjugate gradient method. Meanwhile, in order to improve the visualization effect and operability of inversion, a software platform with a visualization function is developed on the basis of Python language, PyQt, Matplotlib and other toolkits as proposed inversion methods, and the distinguishing capability of near geologic bodies and the longitudinal space imaging capability of target bodies are effectively improved. A softwareplatform and a development method thereof have the advantages of being easy to use, practical and the like.

Description

technical field [0001] The invention relates to the technical field of geophysical inversion, in particular to a method for joint inversion of gravity gradient data. Background technique [0002] Three-dimensional inversion using gravity exploration data can obtain the density distribution of subsurface space, which is a common interpretation method in geological exploration. Compared with the gravity anomaly data, the signal-to-noise ratio of the gravity gradient data is higher, especially the full tensor gradient data contains more geological information, and the joint inversion using multiple gravity gradient data is conducive to improving the current vertical potential field data. The lack of poor spatial resolution will help to further improve the ability to distinguish adjacent geological bodies. [0003] However, due to the multi-solution nature of the inversion, it is necessary to introduce constraints or prior information to improve the uniqueness of the solution i...

AI Technical Summary

Problems solved by technology

But this method destroys the conjugacy in the search process of the solution, that is, each iteration must change the calculated solution

At the same time, due to the nature of gravity gradient data attenuating with distance, the inversion results may have problems such as low vertical resolution

Some scholars have introduced the depth weighting function in the literature [2-4] (the literature [2] is: LiY, Oldenburg D W.3-D inversion of magnetic data [J]. Geophysics, 1996, 61 (2): 394 -408.; Literature [3] is: Li Y, Oldenburg D W.3-D inversion of gravity data[J].Geophysics,1998,63(1):109-119.; Literature [4] is: Portniaguine O ,Zhdanov M S.3-Dmagnetic inversion with data compression and image focusing[J].Geophysics,2002,67(5):1532-1541.), these classic methods provide a reference for follow-up research, but there are still The bottom imaging effect of deep target bodies is poor (mainly refers to the bottom depth in the inversion results is too large, and the density distribution of geological bodies is not focused)

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