Research Of Gravity And Seismic Joint Inversion Method For Interface

Deep exploration target, the hill and glutenite oil and gas reservoirs are one of the main directions of exploration. However, due to poor geological conditions of deep seismic, tectonic complex, led to deep seismic data on the quality of the overall relatively poor, it is difficult to understand the underlying characteristics of the structure and traps, thus affecting the hill looks to identify and implement the structure. In order to implement accurately the implementation of local seismic construction, necessary to give full play of other important geophysical data supporting the role of multidisciplinary, comprehensive study of the whole information. Practice has proved that the seismic and gravity joint identify deep-buried hill is a more effective technical mean. This article will be gravity-seismic joint inversion interface of the main contents of the study.Aiming at the absent of interface inversion, the probability model of density, velocity and interface depth is set up, an objective function of seismic-gravity jointing interface inversion based on the Bayesian theory is proposed, from the proposed objective function seismic-gravity jointing inversion interface depth, seismic-gravity jointing inversion velocity and density, seismic-gravity jointing inversion of velocity, density and interface depth formula are derived to form a complete set of stochastic seismic-gravity joint inversion scheme. In order to achieve the stochastic inversion scheme, the stochastic approximation expectation maximum (SAEM) algorithm is introduced, the inversion at each iteration, the automatic modification of the statistical parameters to speed up the computing speed, improves accuracy and stability of the inversion.The core problem of seismic-gravity joint inversion is how to determine the speed and density of the relationship between velocity and density which is the contact link gravity and seismic data, determining a reasonable velocity-density relationship; we assume there is a unknown linear relationship between velocity and density which may vary with depth, e.g. due to temperature variations. In this paper, SAEM algorithm modifies the B coefficient of velocity and density relationship and its covariance, according to the amendments of velocity and density at each iteration. that is, the relationship a priori between velocity and density can be used, but also to overcome the defect of the traditional joint inversion in fixed velocity - density relationship that is not a reasonable reflection of the truth of the different regions, which can achieve the traditional sequential inversion and striped layers inversion, more than their superiority, that is able to interface inversion while inversion property, in order to achieve the true sense of the simultaneous joint inversion of seismic data and gravity data.Finally, through model tests to verify the correctness and effectiveness, and give the the principle to choose parameters. The actual data of southern Jiyang depression are used to verify the practicality of the method.