Direct inversion of Young's and Poisson impedances for fluid discrimination

Zong, Zhaoyun; Yin, Xingyao

doi:10.1111/gfl.12202

Cited by 14 publications

(4 citation statements)

References 18 publications

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“…In this paper, we solve it with the iterative reweighted least-squares algorithm [47,48]. Meanwhile, considering the correlation between the four inverted parameters, we utilize the preconditioned conjugate gradient method proposed by Zong and Yin [49] in the inversion method to decouple the inverted parameters completely. Subsequent to the reconstruction of the reflectivity of different AVO parameters, the rock properties of K f , Y, μ m , and ρ can be obtained by solving Fx = m, where x represents the logarithm of four inverted parameters and F denotes the first-order difference matrix.…”

Section: Geofluidsmentioning

confidence: 99%

Inversion for Geofluid Discrimination Based on Poroelasticity and AVO Inversion

Wang

Zhou

et al. 2019

Geofluids

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Geofluid discrimination plays an important role in reservoir characterization and prospect identification. Compared with other fluid indicators, the effective pore-fluid bulk modulus is more sensitive to the property of fluid contained in reservoirs. We combine the empirical relations with deterministic models to form a new kind of linearized relationship between the mixed fluid/rock term and the fluid modulus. On the one hand, the linearized relationship can decouple the fluid bulk modulus from the mixed fluid/rock term; on the other hand, the decoupled terms are more stable especially in low-porosity situations compared with previous approaches. In terms of the new linearized equation of the fluid modulus, we derive a novel linearized amplitude variation with offset (AVO) approximation to avoid the complicated nonlinear relationship between the fluid modulus and the reflectivity series. Convoluting this linearized AVO approximation with seismic wavelets, the forward modeling is constructed to combine the prestack seismic records with the fluid modulus. Meanwhile, we introduce the Bayesian inference with multivariable Cauchy prior to the fluid modulus inversion for a stable and high-resolution solution. Model examples demonstrate the accuracy of the proposed linearized AVO approximation compared with the exact Zoeppritz equation and Aki-Richards approximate equation. The synthetic and field data tests illustrate the accuracy and feasibility of the proposed fluid modulus inversion approach for geofluid discrimination.

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Section: Geofluidsmentioning

confidence: 99%

Inversion for Geofluid Discrimination Based on Poroelasticity and AVO Inversion

Wang

Zhou

et al. 2019

Geofluids

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“…Their researches show that the introduction of effective pore-fluid bulk modulus will lead to an increase in the number of target parameters that need to be inverted, which will seriously affect the stability of nonlinear inversion algorithms. Zong and Yin [12] suggested that Young's impedance (YI) and Poisson ratio impedance (PI) have great potential in fluid discrimination and lithology identification of unconventional reservoirs. However, the physical meaning of these two parameters is undefined.…”

Section: Introductionmentioning

confidence: 99%

“…Yin and Zhang [11], Zong et al [16], and Du et al [17] derived the fluid matrix decoupled linear approximation equation and realized the linear inversion of the fluid modulus. Zong and Yin [12] achieved direct inversion of Young's and Poisson impedances for fluid discrimination. It should be noted that the forward operators of above inversion methods are linear approximation equations of the exact Zoeppritz equations.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear AVA Inversion Based on a Novel Quadratic Approximation for Fluid Discrimination

et al. 2020

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Fluid discrimination plays an important role in reservoir exploration and development. At present, the fluid factors used for fluid discrimination are estimated by linear AVA inversion methods based on the linear approximations of the Zoeppritz equations. However, the Zoeppritz equations show that the relationship between prestack AVA reflection coefficients and reservoir parameters is highly nonlinear. Therefore, inversion methods based on linear approximations will seriously influence the nonuniqueness and uncertainty of inversion results. In this paper, a nonlinear inversion based on the quadratic approximation is carried out to reduce the nonuniqueness and uncertainty of fluid factor. Firstly, in order to directly invert the fluid factor, a novel quadratic approximation in terms of the fluid factor ( ρ f ), shear modulus, and density on both sides of the reflection interface is derived based on poroelasticity theory. Then, a nonlinear inversion objective function is constructed using the novel quadratic approximation in a Bayesian framework, and the Gauss-Newton method is adopted to minimize this objective function. The synthetic data example shows that the new method can obtain reasonable fluid factor inversion results even in low SNR (signal-to-noise ratio) case. Finally, the proposed method is also applied to field data which shows that it can effectively discriminate reservoir fluids.

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“…Fluid identification is an important task in the seismic inversion for fractured reservoirs [8][9][10][11][12]. The normal fracture compliance varies with fluid content; however, the tangential fracture compliance exhibits independence on fluid infills.…”

Section: Introductionmentioning

confidence: 99%

Elastic-Impedance-Based Fluid/Porosity Term and Fracture Weaknesses Inversion in Transversely Isotropic Media with a Tilted Axis of Symmetry

Pan

Zhang

et al. 2020

Geofluids

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The rock containing a set of tilted fractures is equivalent to a transversely isotropic (TTI) medium with a tilted axis of symmetry. To implement fluid identification and tilted fracture detection, we propose an inversion approach of utilizing seismic data to simultaneously estimate parameters that are sensitive to fluids and tilted fractures. We first derive a PP-wave reflection coefficient and elastic impedance (EI) in terms of the dip angle, fluid/porosity term, shear modulus, density, and fracture weaknesses, and we present numerical examples to demonstrate how the PP-wave reflection coefficient and EI vary with the dip angle. Based on the information of dip angle of fractures provided by geologic and well data, we propose a two-step inversion approach of utilizing azimuthal seismic data to estimate unknown parameters involving the fluid/porosity term and fracture weaknesses: (1) the constrained sparse spike inversion (CSSI) for azimuthally anisotropic EI data and (2) the estimation of unknown parameters with the low-frequency constrained regularization term. Synthetic and real data demonstrate that fluid and fracture parameters are reasonably estimated, which may help fluid identification and fracture characterization.

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Direct inversion of Young's and Poisson impedances for fluid discrimination

Cited by 14 publications

References 18 publications

Inversion for Geofluid Discrimination Based on Poroelasticity and AVO Inversion

Inversion for Geofluid Discrimination Based on Poroelasticity and AVO Inversion

Nonlinear AVA Inversion Based on a Novel Quadratic Approximation for Fluid Discrimination

Elastic-Impedance-Based Fluid/Porosity Term and Fracture Weaknesses Inversion in Transversely Isotropic Media with a Tilted Axis of Symmetry

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