Azimuthally anisotropic elastic impedance inversion for fluid indicator driven by rock physics

Geophysics ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. C211-C227 ◽  
Author(s):  
Xinpeng Pan ◽  
Guangzhi Zhang ◽  
Xingyao Yin
Keyword(s):  
Fractured Reservoirs ◽  
Low Frequency ◽  
Rock Physics ◽  
Real Data ◽  
Inversion Method ◽  
Anisotropic Rock ◽  
Weak Anisotropy ◽  
Fluid Identification ◽  
Anisotropic Elastic ◽  
Elastic Impedance

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.

Reservoir Prediction Under Control of Sedimentary Facies

2017 ◽  
Vol 25 (03) ◽  
pp. 1750022
Author(s):  
Xiuwei Yang ◽  
Peimin Zhu
Keyword(s):  
Seismic Data ◽  
Low Frequency ◽  
Prediction Method ◽  
Rock Physics ◽  
Real Data ◽  
Sedimentary Facies ◽  
Seismic Inversion ◽  
Rock Properties ◽  
Reservoir Prediction ◽  
Frequency Model

Acoustic impedance (AI) from seismic inversion can indicate rock properties and can be used, when combined with rock physics, to predict reservoir parameters, such as porosity. Solutions to seismic inversion problem are almost nonunique due to the limited bandwidth of seismic data. Additional constraints from well log data and geology are needed to arrive at a reasonable solution. In this paper, sedimentary facies is used to reduce the uncertainty in inversion and rock physics modeling; the results not only agree with seismic data, but also conform to geology. A reservoir prediction method, which incorporates seismic data, well logs, rock physics and sedimentary facies, is proposed. AI was first derived by constrained sparse spike inversion (CSSI) using a sedimentary facies dependent low-frequency model, and then was transformed to reservoir parameters by sequential simulation, statistical rock physics and [Formula: see text]-model. Two numerical experiments using synthetic model and real data indicated that the sedimentary facies information may help to obtain a more reasonable prediction.

Impacts of kerogen content and fracture properties on the anisotropic seismic reflectivity of shales with orthorhombic symmetry

2015 ◽  
Vol 3 (3) ◽  
pp. ST1-ST7 ◽  
Author(s):  
Li Yang ◽  
Xiaoyang Wu ◽  
Mark Chapman
Keyword(s):  
Transverse Isotropy ◽  
Rock Physics ◽  
Vertical Axis ◽  
Orthorhombic Symmetry ◽  
Anisotropic Rock ◽  
Weak Anisotropy ◽  
Fracture Properties ◽  
Rock Physics Modeling ◽  
Axis Of Symmetry ◽  
Physics Modeling

Shale often has strong intrinsic anisotropy, which can be described by transverse isotropy with a vertical axis of symmetry. When vertical fractures are present, shale is likely to exhibit orthorhombic symmetry. We used anisotropic rock-physics models to describe the orthorhombic properties of fractured shale, and we determined that composition and fracture properties had an impact on the azimuthal amplitude variations. Interpretation of azimuthal reflectivity variations was often performed under simplified assumptions. Although the Rüger equation was derived for weak anisotropy and for transverse isotropy with a horizontal axis of symmetry, our results indicated that the orthorhombic response can be well described by the Rüger equation. However, ambiguities could be introduced into the interpretation of parameters. We suggested that careful rock-physics modeling was important for interpreting the anisotropic seismic response of fractured shale.

scholarly journals Azimuthal Attenuation Elastic Impedance Inversion for Fluid and Fracture Characterization Based on Modified Linear-Slip Theory

Geofluids ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-18
Author(s):  
Xinpeng Pan ◽  
Guangzhi Zhang ◽  
Yian Cui
Keyword(s):  
Porous Medium ◽  
Wave Attenuation ◽  
Real Data ◽  
Seismic Attenuation ◽  
P Wave ◽  
Inversion Method ◽  
S Wave ◽  
Fracture Characterization ◽  
Fractured Porous Medium ◽  
Elastic Impedance

The seismic attenuation should be considered while accounting for the effect of anisotropy on the seismic wave propagating through a saturated fractured porous medium. Based on the modified linear-slip theory and anisotropic Gassmann’s equation, we derive an analytical expression for a linearized PP-wave reflection coefficient and an azimuthal attenuation elastic impedance (AAEI) equation in terms of fluid/porosity term, shear modulus, density, dry normal and tangential fracture weaknesses, and compressional (P-wave) and shear (S-wave) attenuation parameters in a weak-attenuation isotropic background rock containing one single set of vertical aligned fractures. We then propose an AAEI inversion method to characterize the characteristics of fluids and fractures using two kinds of constrained regularizations in such a fractured porous medium. The proposed approach is finally confirmed by both the synthetic and real data sets acquired over a saturated fractured porous reservoir.

Inversion of reservoir fluid mobility from the frequency-dependent seismic data-a case study of gas-bearing reservoirs

2020 ◽  
pp. 1-47
Author(s):  
Yijiang Zhang ◽  
Xiaotao Wen ◽  
Dongyong Zhou ◽  
Wenhua Wang ◽  
Man Lu ◽  
...  
Keyword(s):  
Seismic Data ◽  
Extraction Method ◽  
Low Frequency ◽  
Real Data ◽  
Inversion Method ◽  
Frequency Dependent ◽  
Reservoir Fluid ◽  
Well Data ◽  
Gas Bearing ◽  
Mobility Coefficient

The reservoir fluid mobility is by definition the ratio of rock permeability to fluid viscosity. This attribute can be applied to reservoir physical property and permeability evaluation. So far, the only means of obtaining the reservoir fluid mobility over a large range of exploration areas is based on the extraction method. However, the location of high fluid mobility obtained by the extraction method is close to the reservoir interface. To obtain the fluid mobility in the middle of the reservoir, an approximate inversion method of reservoir fluid mobility from frequency-dependent seismic data is proposed. Firstly, we calculate the reservoir fluid mobility coefficient using well data according to the relationship of fluid parameters. Then, we establish an inversion equation based on the low-frequency reflection coefficient and the reservoir fluid mobility. Taking the reservoir fluid mobility coefficient calculated from well data as a priori constraint, the low-frequency model is subsequently constructed and applied with the inversion equation to obtain an inversion objective function. Next, the inversion equation is solved by the basis pursuit algorithm. Finally, the proposed reservoir fluid mobility inversion method is applied to synthetic and real data of gas-bearing reservoirs. The real data processing results show that the proposed reservoir fluid mobility inversion method can estimate the fluid mobility in the actual position of the reservoir more effectively.

Fracture detection and fluid identification based on anisotropic Gassmann equation and linear-slip model

Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. R85-R98 ◽  
Author(s):  
Xinpeng Pan ◽  
Guangzhi Zhang
Keyword(s):  
Seismic Data ◽  
Order Approximation ◽  
Low Frequency ◽  
Rock Physics ◽  
Transversely Isotropic ◽  
Slip Model ◽  
Fracture Detection ◽  
Fluid Identification ◽  
Pp Wave ◽  
Linear Slip Model

Detection of fracture and fluid properties from subsurface azimuthal seismic data improves our abilities to characterize the saturated porous reservoirs with aligned fractures. Motivated by the fracture detection and fluid identification in a fractured porous medium, we have developed a feasible approach to perform a rock physics model-based amplitude variation with offset and azimuth (AVOAz) inversion for the fracture and fluid parameters in a horizontal transversely isotropic (HTI) medium using the PP-wave angle gathers along different azimuths. Based on the linear-slip model, we first use anisotropic Gassmann’s equation to derive the expressions of saturated stiffness components and their perturbations of first-order approximation in terms of elastic properties of an isotropic porous background and fracture compliances induced by a single set of rotationally invariant fractures. We then derive a linearized PP-wave reflection coefficient in terms of fluid modulus, dry-rock matrix term, porosity, density, and fracture compliances or quasi-compliances for an interface separating two weakly HTI media based on the Born scattering theory. Finally, we solve the AVOAz inverse problems iteratively constrained by the Cauchy-sparse regularization and the low-frequency regularization in a Bayesian framework. The results demonstrate that the fluid modulus and fracture quasi-compliances are reasonably estimated in the case of synthetic and real seismic data containing moderate noise in a gas-filled fractured porous reservoir.

Bayesian time-lapse inversion

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. R43-R48 ◽  
Author(s):  
Arild Buland ◽  
Youness El Ouair
Keyword(s):  
Water Injection ◽  
Rock Physics ◽  
Real Data ◽  
Time Lapse ◽  
Baseline Survey ◽  
Inversion Method ◽  
Data Set ◽  
Uncertainty Calculation ◽  
The Difference ◽  
Fast Inversion

A new, fast inversion approach for time-lapse seismic data is developed where the uncertainty of the inversion results is an integral part of the solution. The inversion method estimates changes in the elastic material properties of a reservoir because of production of hydrocarbons, including uncertainty bounds on these estimates. The changes in elastic properties then can be related to changes in hydrocarbon saturation and reservoir pressure by using rock-physics relations. The inversion operates directly on the difference between a repeat survey and a baseline survey. This is advantageous with respect to the uncertainty calculation, because an estimate of the seismic uncertainty can be obtained directly from the difference data in zones not affected by production. The method is formulated in a Bayesian setting, and the solution is represented by explicit expressions for the posterior expectation and the covariance of the elastic parameter changes. The explicit analytical form of the posterior distribution provides a computationally fast inversion method. Results of the applied approach to a real data set from the Norne field are consistent with the expected effects of water flushing because of water injection.

scholarly journals Viscoelastic Fluid Factor Inversion and Application in Luojia Oilfield Based on Broadband Impedance

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Ruyi Zhang ◽  
Huazhong Wang
Keyword(s):  
Viscoelastic Fluid ◽  
Rock Physics ◽  
Impedance Method ◽  
Frequency Dependent ◽  
Fluid Identification ◽  
Fluid Factor ◽  
Impedance Inversion ◽  
Elastic Impedance ◽  
Sensitive Parameters ◽  
The Relationship

Based on the physical quantity of log data, the accurate identification of oil- and gas-bearing properties may be caused by the prestack inversion of fluid prediction, which will affect the success rate of exploration and development. Prestack data contain more information of amplitude and frequency. Using the frequency-dependent viscoelastic impedance equation and Bayesian inversion framework, the objective function of frequency-dependent elastic impedance inversion can be established to realize the frequency-dependent impedance inversion at different angles. According to the elastic impedance equation of the frequency-varying viscoelastic fluid factor, the relationship between elastic impedance and the frequency-dependent viscoelastic fluid factor is established, and the prestack seismic inversion method of the frequency-dependent viscoelastic fluid factor is studied. However, one of the important factors easily neglected is that we have been using logging data to establish fluid-sensitive parameters and the lithophysical version for fluid identification, so there are differences between logging and seismic frequency bands for fluid identification. The indicator factors with higher sensitivity to fluid can be selected by laboratory measurements. This article applies this method on Luojia oilfield data and verifies this method with log interpretation results, based on the sample of rock physics obtained in a low-frequency rock physics experiment; the technique of dispersion and fluid-sensitive parameters is studied, and the fluid prediction technology of a multifrequency band rock physics template is adopted, which can build the relationship between rock physical elastic parameters and fluid properties by the multifrequency broadband impedance method.

Statistical rock physics inversion of elastic and electrical properties for CO2 sequestration studies

2020 ◽  
Vol 223 (1) ◽  
pp. 707-724
Author(s):  
Mohit Ayani ◽  
Dario Grana
Keyword(s):  
Electrical Properties ◽  
Co2 Sequestration ◽  
Rock Physics ◽  
Real Data ◽  
Inversion Method ◽  
Model Parameters ◽  
The North ◽  
Physics Model ◽  
Rock Physics Model ◽  
Statistical Rock Physics

SUMMARY We present a statistical rock physics inversion of the elastic and electrical properties to estimate the petrophysical properties and quantify the associated uncertainty. The inversion method combines statistical rock physics modeling with Bayesian inverse theory. The model variables of interest are porosity and fluid saturations. The rock physics model includes the elastic and electrical components and can be applied to the results of seismic and electromagnetic inversion. To describe the non-Gaussian behaviour of the model properties, we adopt non-parametric probability density functions to sample multimodal and skewed distributions of the model variables. Different from machine learning approach, the proposed method is not completely data-driven but is based on a statistical rock physics model to link the model parameters to the data. The proposed method provides pointwise posterior distributions of the porosity and CO2 saturation along with the most-likely models and the associated uncertainty. The method is validated using synthetic and real data acquired for CO2 sequestration studies in different formations: the Rock Springs Uplift in Southwestern Wyoming and the Johansen formation in the North Sea, offshore Norway. The proposed approach is validated under different noise conditions and compared to traditional parametric approaches based on Gaussian assumptions. The results show that the proposed method provides an accurate inversion framework where instead of fitting the relationship between the model and the data, we account for the uncertainty in the rock physics model.

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