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The extensive application of pre-stack depth migration has produced huge volumes of seismic data, which allows for the possibility of developing seismic inversions of reservoir properties from seismic data in the depth domain. It is difficult to estimate seismic wavelets directly from seismic data due to the nonstationarity of the data in the depth domain. We conduct a velocity transformation of seismic data to make the seismic data stationary and then apply the ridge regression method to estimate a constant seismic wavelet. The estimated constant seismic wavelet is constructed as a set of space-variant seismic wavelets dominated by velocities at different spatial locations. Incorporating the weighted superposition principle, a synthetic seismogram is generated by directly employing the space-variant seismic wavelets in the depth domain. An inversion workflow based on the model-driven method is developed in the depth domain by incorporating the nonlinear conjugate gradient algorithm, which avoids additional data conversions between the time and depth domains. The impedance inversions of the synthetic and field seismic data in the depth domain show good results, which demonstrates that seismic inversion in the depth domain is feasible. The approach provides an alternative for forward numerical analyses and elastic property inversions of depth-domain seismic data. It is advantageous for further studies concerning the stability, accuracy, and efficiency of seismic inversions in the depth domain.

Simultaneous prestack inversion is based on the modified Fatti equation and uses the ratio of the P- and S-wave velocity as constraints. We use the relation of P-wave impedance and density (PID) and S-wave impedance and density (SID) to replace the constant Vp/Vs constraint, and we propose the improved constrained Fatti equation to overcome the effect of P-wave impedance on density. We compare the sensitivity of both methods using numerical simulations and conclude that the density inversion sensitivity improves when using the proposed method. In addition, the random conjugate-gradient method is used in the inversion because it is fast and produces global solutions. The use of synthetic and field data suggests that the proposed inversion method is effective in conventional and nonconventional lithologies.

Currently, the deghosting of towed streamer seismic data assumes a flat sea level and a sea-surface reflection coefficient of −1; this decreases the precision of deghosting. A new method that considers the rough sea surface is proposed to suppress ghost reflections. The proposed deghosting method obtains the rough sea surface reflection coefficient using Gaussian statistics, and calculates the optimized deghosting operator in the τ/p domain. The proposed method is closer to the actual sea conditions, offers an improved deghosting operator, removes the ghost reflections from marine towed seismic data, widens the bandwidth and restores the low-frequency information, and finally improves the signal-tonoise ratio and resolution of the seismic data.

The precision of seismic reflection data does not fulfil to explore private and complex structure oil-gas pools. So we need to improve the resolution of seismic data. To achieve this, we used the inverse Q filter methods to improve the resolution for the seismic data. The results for processing the pre-stack seismic data indicated that the inverse Q filter method can improve peak frequency and frequency bandwidth. Low and middle-high frequency components in those results are reasonable, and its signal/noise ratios are obviously larger than that for other methods in middle-high frequency. Moreover, the results using various Q values indicated that the peak frequency is little added and the frequency bandwidth is expanded when Q value is reducing, but the signal/noise ratio is reducing. Moreover, the improving of the signal/noise ratio is very small when Q value is larger than 200.0, namely addition for Q value only gains reducing of the peak frequency and the bandwidth.