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.

Prestack inversion based on anisotropic Markov random field-maximum posterior probability inversion and its application to identify shale gas sweet spots

Economic shale gas production requires hydraulic fracture stimulation to increase the formation permeability. Hydraulic fracturing strongly depends on geomechanical parameters such as Young＇s modulus and Poisson＇s ratio. Fracture-prone sweet spots can be predicted by prestack inversion, which is an ill-posed problem; thus, regularization is needed to obtain unique and stable solutions. To characterize gas-bearing shale sedimentary bodies, elastic parameter variations are regarded as an anisotropic Markov random field. Bayesian statistics are adopted for transforming prestack inversion to the maximum posterior probability. Two energy functions for the lateral and vertical directions are used to describe the distribution, and the expectation-maximization algorithm is used to estimate the hyperparameters of the prior probability of elastic parameters. Finally, the inversion yields clear geological boundaries, high vertical resolution, and reasonable lateral continuity using the conjugate gradient method to minimize the objective function. Antinoise and imaging ability of the method were tested using synthetic and real data.

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.

Effect of inaccurate wavelet phase on prestack waveform inversion

Wavelets are critical to inversion methods. Incorrect phase estimation will affect the objective function and cause convergence to local minima, and thus produce biased or incorrect results. Based on two simple models and ignoring all other factors, we studied the variation of the wavelet phase as a function of frequency and its effect on the prestack waveform inversion. Numerical experiments show that an incorrect phase may result in large deviations from the real solution, even if there is a high similarity between the model and real wavelets. The precision of the inversion slightly improves by using the constant-phase rotation; however, the effect of phase inaccuracy is not eliminated, which limits the precision of prestack inversion.

Bayesian prestack seismic inversion with a self-adaptive Huber-Markov random-field edge protection scheme

Seismic inversion is a highly ill-posed problem, due to many factors such as the limited seismic frequency bandwidth and inappropriate forward modeling. To obtain a unique solution, some smoothing constraints, e.g., the Tikhonov regularization are usually applied. The Tikhonov method can maintain a global smooth solution, but cause a fuzzy structure edge. In this paper we use Huber-Markov random-field edge protection method in the procedure of inverting three parameters, P-velocity, S-velocity and density. The method can avoid blurring the structure edge and resist noise. For the parameter to be inverted, the Huber- Markov random-field constructs a neighborhood system, which further acts as the vertical and lateral constraints. We use a quadratic Huber edge penalty function within the layer to suppress noise and a linear one on the edges to avoid a fuzzy result. The effectiveness of our method is proved by inverting the synthetic data without and with noises. The relationship between the adopted constraints and the inversion results is analyzed as well.

Study of prestack elastic parameter consistency inversion methods

The three parameters of P-wave velocity, S-wave velocity, and density have remarkable differences in conventional prestack inversion accuracy, so study of the consistency inversion of the ＂three parameters＂ is very important. In this paper, we present a new inversion algorithm and approach based on the in-depth analysis of the causes in their accuracy differences. With this new method, the inversion accuracy of the three parameters is improved synchronously by reasonable approximations and mutual constraint among the parameters. Theoretical model calculations and actual data applications with this method indicate that the three elastic parameters all have high inversion accuracy and maintain consistency, which also coincides with the theoretical model and actual data. This method has good application prospects.

Inversion of shear wave interval velocity on prestack converted wave data

Seismic velocity is important to migration of seismic data, interpretation of lithology and lithofacies as well as prediction of reservoir. The information of shear wave velocity is required to reduce the uncertainty for discriminating lithology, identifying fluid type in porous material and calculating gas saturation in reservoir prediction. Based on Zoeppritz equations, a numeral and scanning method was proposed in this paper. Shear wave velocity can be calculated with prestack converted wave data. The effects were demonstrated by inversion of theoretical and real seismic data.

Application of joint elastic impedance inversion in the GD Oilfield

For the complicated reservoir description of the GD oilfield, P-wave and S-wave elastic impedance inversion was carried out using pre-stack seismic data to accurately identify the lithology of the reservoir. The joint inversion was performed using three or more partial stacks to overcome the singularity of post-stack seismic inversion that can not satisfy the requirements of complex reservoir description and to avoid the instability of the inversion result caused by low signal-noise ratio in the pre-stack gather. The basic theory of prestack elastic impedance inversion is briefly described in this paper and, using real data of the GD oilfield, the key steps of angle gather wavelet extraction, horizon calibration, S-wave velocity prediction, and elastic parameter extraction were analyzed and studied. The comprehensive interpretation of multiple elastic parameters determined from log analysis is a key to improving the effect ofprestack seismic inversion.

Interval attenuation estimation from prestack seismic data:A case study from the Arabian Peninsula

Accurately estimated interval attenuation(1/Q)values have several applications,such as in quantitative interpretation and seismic resolution enhancement.Although Q values can be estimated by measuring the spectral ratio between seismic reflections from a target and a reference reflector,the results are influenced by factors such as overburden inhomogeneities.Here,we quantitatively analyze the overburden influence on interval Q estimations using the spectral ratio method,time-space domain prestack Q inversion(PSQI),andτ-p domain PSQI.We compare these three methods using a synthetic dataset and a field dataset acquired onshore the Arabian Peninsula.Synthetic seismic gathers are generated from a three-layer model with a low-Q inclusion in the first layer to mimic overburden inhomogeneity.The fi eld data are preconditioned image gathers from a producing oil fi eld.The synthetic data test shows that the small low-Q body produces a considerable error in estimated Q values.The smallest error(i.e.,13.3%)is in theτ-p domain PSQI result.Theoretically,τ-p domain PSQI could obtain more accurate Q values when there are overburden infl uences because of the simultaneous inversion scheme and the application in theτ-p domain.The fi eld data application also illustrates that theτ-p domain PSQI produces reasonable interval Q values.Our measured Q values are also comparable with the Q values estimated from hydrocarbon saturated carbonate reservoirs.

Facies-constrained prestack seismic probabilistic inversion driven by rock physics

Seismic Rock physics plays a bridge role between the rock moduli and physical properties of the hydrocarbon reservoirs.Prestack seismic inversion is an important method for the quantitative characterization of elasticity,physical properties,lithology and fluid properties of subsurface reservoirs.In this paper,a high order approximation of rock physics model for clastic rocks is established and one seismic AVO reflection equation characterized by the high order approximation(Jacobian and Hessian matrix)of rock moduli is derived.Besides,the contribution of porosity,shale content and fluid saturation to AVO reflectivity is analyzed.The feasibility of the proposed AVO equation is discussed in the direct estimation of rock physical properties.On the basis of this,one probabilistic AVO inversion based on differential evolution-Markov chain Monte Carlo stochastic model is proposed on the premise that the model parameters obey Gaussian mixture probability prior model.The stochastic model has both the global optimization characteristics of the differential evolution algorithm and the uncertainty analysis ability of Markov chain Monte Carlo model.Through the cross parallel of multiple Markov chains,multiple stochastic solutions of the model parameters can be obtained simultaneously,and the posterior probability density distribution of the model parameters can be simulated effectively.The posterior mean is treated as the optimal solution of the model to be inverted.Besides,the variance and confidence interval are utilized to evaluate the uncertainties of the estimated results,so as to realize the simultaneous estimation of reservoir elasticity,physical properties,discrete lithofacies and dry rock skeleton.The validity of the proposed approach is verified by theoretical tests and one real application case in eastern China.