Xingyao Yin

AVAZ inversion for fracture weakness parameters based on the rock physics model

Subsurface fractures within many carbonates and unconventional resources play an important role in the storage and movement of fluid. The more reliably the detection of fractures could be performed, the more finely the reservoir description could be made. In this paper, we aim to propose a method which uses two important tools, a fractured anisotropic rock physics effective model and AVAZ (amplitude versus incident and azimuthal angle) inversion, to predict fractures from azimuthal seismic data. We assume that the rock, which contains one or more sets of vertical or sub-vertical fractures, shows transverse isotropy with a horizontal axis of symmetry (HTI). Firstly, we develop one improved fractured anisotropic rock physics effective model. Using this model, we estimate P-wave velocity, S-wave velocity and fracture weaknesses from well-logging data. Then the method is proposed to predict fractures from azimuthal seismic data based on AVAZ inversion, and well A is used to verify the reliability of the improved rock physics effective model. Results show that the estimated results are consistent with the real log value, and the variation of fracture weaknesses may detect the locations of fractures. The damped least squares method, which uses the estimated results as initial constraints during the inversion, is more stable. Tests on synthetic data show that fracture weaknesses parameters are still estimated reasonably with moderate noise. A test on real data shows that the estimated results are in good agreement with the drilling.

Improving seismic interpretation: a high-contrast approximation to the reflection coefficient of a plane longitudinal wave

Linearized approximations of reflection and transmission coefficients set a foundation for amplitude versus offset (AVO) analysis and inversion in exploration geophysics. However, the weak properties contrast hypothesis of those linearized approximate equations leads to big errors when the two media across the interface vary dramatically. To extend the application of AVO analysis and inversion to high contrast between the properties of the two layers, we derive a novel nonlinearized high-contrast approximation of the PP-wave reflection coefficient, which establishes the direct relationship between PP-wave reflection coefficient and P-wave velocities, S-wave velocities and densities across the interface. (A PP wave is a reflected compressional wave from an incident compressional wave (P-wave).) This novel approximation is derived from the exact reflection coefficient equation with Taylor expansion for the incident angle. Model tests demonstrate that, compared with the reflection coefficients of the linearized approximations, the reflection coefficients of the novel nonlinearized approximate equation agree with those of the exact PP equation better for a high contrast interface with a moderate incident angle. Furthermore, we introduce a nonlinear direct inversion method utilizing the novel reflection coefficient equation as forward solver, to implement the direct inversion for the six parameters including P-wave velocities, S-wave velocities, and densities in the upper and lower layers across the interface. This nonlinear inversion algorithm is able to estimate the inverse of the nonlinear function in terms of model parameters directly rather than in a conventional optimization way. Three examples verified the feasibility and suitability of this novel approximation for a high contrast interface, and we still could estimate the six parameters across the interface reasonably when the parameters in both media across the interface vary about 50%.

A Novel Prestack AVO Inversion And Its Application

Prestack AVO inversion is multidimensional and ill posed, and is often strongly affected by noise and measurement uncertainty, so it is necessary to performing constraints in order to obtain steady and rational inversion results. A novel prestack AVO inversion method is developed based on linearized approximation of the Zoeppritz equation and Bayesian parameter estimation theory. Covariance matrix is used to describe the correlation degree between the parameters, Gaussian distribution is used for likelihood function and modified Cauchy distribution is used for prior distribution; P-wave impedance, S-wave impedance, density and rock physics relation are applied to constrain the inversion results, thus it is reliable to make the result more accurate and steady. Tests on synthetic and real data show that all inverted parameters are almost perfectly retrieved even the SNR is low.

Azimuthal Seismic Amplitude Difference Inversion for Fracture Weakness

Fracture weakness prediction is an important task in fractured reservoir analysis. We propose a new method to use seismic amplitude differences between azimuths to estimate the normal and tangential fracture weaknesses under the assumption that the anisotropic perturbation of the reflection coefficient is mainly induced by fractures. We first derive an expression of the reflection coefficient in terms of the normal and tangential fracture weaknesses for the case of an interface separating two fractured media. Then we use the linear fitting method to get the relationship between the two fracture weaknesses, and change the variables to precondition the inversion problem. The Bayesian framework, under the hypothesis of a Cauchy distribution prior information and a Gaussian distribution likelihood function, is employed to construct the objective function, and an initial low-frequency constraint is introduced to the objective function to make the inversion more stable. The conjugate gradient algorithm is adopted to solve the inverse problem. Tests on both synthetic and real data demonstrate that the normal and tangential fracture weaknesses can be estimated reasonably in the case of seismic data containing a moderate noise, and our inversion approach appears to be a stable method for predicting the fracture weaknesses.

Geofluid Discrimination Incorporating Poroelasticity and Seismic Reflection Inversion

Geofluid discrimination plays an important role in the fields of hydrogeology, geothermics, and exploration geophysics. A geofluid discrimination approach incorporating linearized poroelasticity theory and pre-stack seismic reflection inversion with Bayesian inference is proposed in this study to identify the types of geofluid underground. Upon the review of the development of different geofluid indicators, the fluid modulus is defined as the geofluid indicator mainly affected by the fluid contained in reservoirs. A novel linearized P-wave reflectivity equation coupling the fluid modulus is derived to avoid the complicated nonlinear relationship between the fluid modulus and seismic data. Model examples illustrate the accuracy of the proposed linearized P-wave reflectivity equation comparing to the exact P-wave reflectivity equation even at moderate incident angle, which satisfies the requirements of the parameter estimations with P-wave pre-stack seismic data. Convoluting this linearized P-wave reflectivity equation with seismic wavelets as the forward solver, a pragmatic pre-stack Bayesian seismic inversion method is presented to estimate the fluid modulus directly. Cauchy and Gaussian probability distributions are utilized for prior information of the model parameters and the likelihood function, respectively, to enhance the inversion resolution. The preconditioned conjugate gradient method is coupled in the optimization of the objective function to weaken the strong degree of correlation among the four model parameters and enhance the stability of those parameter estimations simultaneously. The synthetic examples demonstrate the feasibility and stability of the proposed novel seismic coefficient equation and inversion approach. The real data set illustrates the efficiency and success of the proposed approach in differentiating the geofluid filled reservoirs.

Fluid discrimination study from Fluid Elastic Impedance (FEI)

Summary We propose a method, named Fluid elastic impedance (FEI) which is derived by the extending the concept of Elastic Impedance (Connolly, 1999) to make the fluid discrimination more stable and reliable. The fluid component of the in-situ reservoir rock here is proposed based on the poroelasticity theory of Boit and Gassmann, and rock physics analysis and forward modeling result based on the well-logging measurement indicate that the fluid component ( f ) is an effective tool for fluid discrimination. Our study shows that the FEI inversion can extract the fluid component more valuable and easier to carry out research on the fluid discrimination. A real data example illustrates the applicability of the proposed method.

Direct inversion for a fluid factor and its application in heterogeneous reservoirs

ABSTRACT Prestack seismic inversion plays an important role in estimating elastic parameters that are sensitive to reservoirs and fluid underground. In this paper, a simultaneous inversion method named FMR‐AVA (Fluid Factor, Mu (Shear modulus), Rho (Density)‐Amplitude Variation with Angle) is proposed based on partial angle stack seismic gathers. This method can be used for direct inversion for the fluid factor, shear modulus and density of heterogeneous reservoirs. Firstly, an FMR approximation equation of a reflection coefficient is derived based on poroelasticity with P‐ and S‐wave moduli. Secondly, a stable simultaneous AVA inversion approach is presented in a Bayesian scheme. This approach has little dependence on initial models. Furthermore, it can be applied in heterogeneous reservoirs whose initial models for inversion are not easy to establish. Finally, a model test shows the superiority of this FMR‐AVA inversion method in stability and independence of initial models. We obtain a reasonable fluid factor, shear modulus and density even with smooth initial models and moderate Gaussian noise. A real data case example shows that the inverted fluid factor, shear modulus and density fit nicely with well log interpretation results, which verifies the effectiveness of the proposed method.

Simultaneous inversion of petrophysical parameters based on geostatistical a priori information

The high-resolution nonlinear simultaneous inversion of petrophysical parameters is based on Bayesian statistics and combines petrophysics with geostatistical a priori information. We used the fast Fourier transform-moving average (FFT-MA) and gradual deformation method (GDM) to obtain a reasonable variogram by using structural analysis and geostatistical a priori information of petrophysical parameters. Subsequently, we constructed the likelihood function according to the statistical petrophysical model. Finally, we used the Metropolis algorithm to sample the posteriori probability density and complete the inversion of the petrophysical parameters. We used the proposed method to process data from an oil field in China and found good match between inversion and real data with high-resolution. In addition, the direct inversion of petrophysical parameters avoids the error accumulation and decreases the uncertainty, and increases the computational efficiency.

Joint Inversion of 3D Seismic, VSP And Crosswell Seismic Data

Inversion of 3D seismic data is a strongly ill-posed problem. The inversion resolution is limited by the bandwidth of the seismic data used. A good choice to get accurate result is the joint inversion with all the available information. Based on the Bayesian theorem, the VSP and crosswell seismic data is injected into the inversion process according to the joint probability distribution. The joint inversion theory is built and the inversion stage is complete. Model test shows that the joint inversion method possessed the different frequency bandwidth information of VSP and crosswell data, the inversion result is more accurate and the resolution is higher. The joint inversion method of 3D seismic data, VSP and crosswell seismic data is feasible with different field data. The impedance inversion result is more reasonable and can match better with the logging data.

Pre-stack basis pursuit seismic inversion for brittleness of shale

Brittleness of rock plays a significant role in exploration and development of shale gas reservoirs. Young’s modulus and Poisson’s ratio are the key parameters for evaluating the rock brittleness in shale gas exploration because their combination relationship can quantitatively characterize the rock brittleness. The high-value anomaly of Young’s modulus and the low-value anomaly of Poisson’s ratio represent high brittleness of shale. The technique of pre-stack amplitude variation with angle inversion allows geoscientists to estimate Young’s modulus and Poisson’s ratio from seismic data. A model constrained basis pursuit inversion method is proposed for stably estimating Young’s modulus and Poisson’s ratio. Test results of synthetic gather data show that Young’s modulus and Poisson’s ratio can be estimated reasonably. With the novel method, the inverted Young’s modulus and Poisson’s ratio of real field data focus the layer boundaries better, which is helpful for us to evaluate the brittleness of shale gas reservoirs. The results of brittleness evaluation show a good agreement with the results of well interpretation.