Joint Inversion Of Constraining And Matching Gravity And Seismic Data

Inversion by only one kind of geophysical data might cause a wrong answer of density underground because of the complex construction and the deviation while collecting the data.Joint inversion aims to consisting different sorts of geophysical data to inverse a better answer than only by one sort of data.Using different sorts of data can apparently improve the quality of inversion.After investigating many theories of joint inversion,I put forward a kind of joint inversion theory by constraining and matching gravity and seismic data.The theory uses the thought of vector matching,by using this we attach the density and seismic data directly.Although using deep weight function,the result of gravity inversion is not realistic.The value of the density after inversing is not pretty same as the model,as well as the position information,especially the edge.But the joint inversion which I raise fits well,not only on the edge,but also the density value.Several different models were built to verify the algorithm,and we find that the result is better than many other algorithms.It can also deal with the inversion problem when the seismic data was not very good,such as when lower event was lost.The result showed that the theory could truly improve the quality of inversion.We also built 3-d model to verify the result of inversion algorithm in the space.The answer showed that the theory could get a pretty answer of density no matter in 2-d or 3-d space.