Handong Huang

Zoeppritz equation-based prestack inversion and its application in fluid identification

Prestack seismic inversion methods adopt approximations of the Zoeppritz equations to describe the relation between reflection coefficients and P-wave velocity, S-wave velocity, and density. However, the error in these approximations increases with increasing angle of incidence and variation of the elastic parameters, which increases the number of inversion solutions and minimizes the inversion accuracy. In this study, we explore a method for solving the reflection coefficients by using the Zoeppritz equations. To increase the accuracy of prestack inversion, the simultaneous inversion of P-wave velocity, S-wave velocity, and density by using prestack large-angle seismic data is proposed based on generalized linear inversion theory. Moreover, we reduce the ill posedness and increase the convergence of prestack inversion by using the regularization constraint damping factor and the conjugate gradient algorithm. The proposed prestack inversion method uses prestack large-angle seismic data to obtain accurate seismic elastic parameters that conform to prestack seismic data and are consistent with logging data from wells.

Detection of gas hydrate sediments using prestack seismic AVA inversion

Bottom-simulating reflectors (BSRs) in seismic profile always indicate the bottom of gas hydrate stability zone, but is difficult to determine the distribution and features of gas hydrate sediments (GHS). In this study, based on AVA forward modeling and angle-domain common-image gathers we use prestack AVA parameters consistency inversion in predicting gas hydrate sediments in the Shenhu area at northern slope of South China Sea, and obtain the vertical and lateral features and saturation of GHS.

Prestack seismic facies-controlled joint inversion of reservoir elastic and petrophysical parameters for sweet spot prediction

The elastic and petrophysical parameters of a reservoir can be directly applied to lithology prediction and fluid identification. Existing seismic joint inversion methods for estimating the elastic and petrophysical parameters of a reservoir are primarily based on either the Gassmann equation, with which these parameters are inverted from prestack seismic data through stochastic optimization methods, or Wyllie’s modified equation, with which these parameters are inverted from poststack seismic data using deterministic optimization methods. Regardless of the stochastic or deterministic inversion of reservoir parameters, only the microscopic connection between parameters is considered, without considering the constraints of the macroscopic geological background. The purpose of this work is to develop a strategy for estimating the elastic and petrophysical parameters of a reservoir based on the Gassmann equation and seismic facies using deterministic seismic prestack inversion. We employ the Gassmann equation to construct the relationship between the prestack seismic data and petrophysical parameters and use a low-pass filter matrix to obtain the combination of seismic facies and seismic inversion and improve the robustness of the inversion results. We treat the joint posterior probability of elastic and petrophysical parameters as the objective function under a Bayesian framework by expanding the objective function with the Taylor formula; the joint equations composed of elastic and petrophysical parameters are obtained through differentiation. The conjugate gradient method is subsequently used to find the optimal solutions for the P-wave velocity, S-wave velocity, density, porosity, water saturation, and clay content. Theoretical calculations and actual data inversion results prove the feasibility and applicability of the method.