The normal-to-tangential fracture compliance ratio is usually used as a fracture fluid indicator (FFI) for fluid identification in fractured reservoirs. With a new parameterization for fracture weaknesses, we have defined a new FFI based on azimuthally anisotropic elastic impedance (EI) inversion and fractured anisotropic rock-physics models. First, we derived a new azimuthally anisotropic EI equation with a similar expression for the isotropic and anisotropic EI parts to remove the exponential correction of EI that is attributable to weak anisotropy. Then, we built a fractured anisotropic rock-physics model used for the estimation of well-log parameters for the normal and tangential fracture weaknesses, which built the initial background low-frequency trend of fracture weaknesses. Finally, based on the azimuthally anisotropic EI inversion method with the Cauchy-sparse and low-frequency information regularization, we estimated an FFI applied to fluid identification in fractured reservoirs. Tests on the synthetic and real data demonstrate that the anisotropic parameters related to fracture weaknesses can be estimated reasonably and stably and that our method appears to provide an alternative available for fluid identification in fractured reservoirs.

Seismic amplitude variation with offset (AVO) inversion is well-known as a popular and pragmatic tool used for the prediction of elastic parameters in the geosciences. Low frequencies missing from conventional seismic data are conventionally recovered from other geophysical information, such as well-log data, for estimating the absolute rock properties, which results in biased inversion results in cases of complex heterogeneous geologic targets or plays with sparse well-log data, such as marine or deep stratum. Broadband seismic data bring new opportunities to estimate the low-frequency components of the elastic parameters without well-log data. We have developed a novel AVO inversion approach with the Bayesian inference for broadband seismic data. The low-frequency components of the elastic parameters are initially estimated with the proposed broadband AVO inversion approach with the Bayesian inference in the complex frequency domain because seismic inversion in the complex frequency domain is helpful to recover the long-wavelength structures of the elastic models. Gaussian and Cauchy probability distribution density functions are used for the likelihood function and the prior information of model parameters, respectively. The maximum a posteriori probability solution is resolved to estimate the low-frequency components of the elastic parameters in the complex frequency domain. Furthermore, with those low-frequency components as initial models and constraints, the conventional AVO inversion method with the Bayesian inference in the time domain is further implemented to estimate the final absolute elastic parameters. Synthetic and field data examples demonstrate that the proposed AVO inversion in the complex frequency domain is able to predict the low-frequency components of elastic parameters well, and that those low-frequency components set a good foundation for the final estimation of the absolute elastic parameters.

Fluid identification and fracture discrimination play an important role in the exploration and development of an oil-bearing fractured reservoir. The most common fluid indicator in fractured reservoirs, the normal-to-shear fracture compliance ratio, is influenced by the fluid content and the fracture intensity. To reduce the ambiguities in the discrimination of the fluid and fracture parameters, we have aimed to extend the scattering theory to implement the fluid identification and fracture detection by incorporating the azimuthal data in an oil-bearing fractured reservoir via the proposed Bayesian amplitude variation with offset and azimuth (AVOAz) inversion approach. The background medium is, as far as the scattering theory is concerned, an isotropic medium without fractures, and the fractured medium is corresponding to a perturbed medium. The elastic parameters of a saturated anisotropic medium can be parameterized as a perturbation over a homogeneous isotropic background medium. We used the scattering theory to derive a generalized AVOAz approximation that provided the iterative estimates of hydrocarbon fluid indicator, shear modulus, density, and fracture weaknesses in a Bayesian scheme. The inversion algorithm is based on a convolutional model and a weak-contrast and small-weakness PP-wave reflection coefficient. The approach is applied to an oil-bearing field data set from a fractured marlstone reservoir. We observe that reasonable estimates of fluid indicator and fracture weaknesses are inverted, which can be used to perform the discrimination of fluid and fracture parameters. We conclude that the proposed approach provides us a potentially powerful tool to estimate the reservoir fluid and fracture properties in a more straightforward and efficient manner than those previous methods.

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.