Abstract

Pore-fluid identification is one of the key technologies in seismic exploration. Fluid indicators play important roles in pore-fluid identification. For sandstone reservoirs, the effective pore-fluid bulk modulus is more susceptible to pore-fluid than other fluid indicators. AVO (amplitude variation with offset) inversion is an effective way to obtain fluid indicators from seismic data directly. Nevertheless, current methods lack a high-order AVO equation for a direct, effective pore-fluid bulk modulus inversion. Therefore, based on the Zoeppritz equations and Biot–Gassmann theory, we derived a high-order P-wave AVO approximation for an effective pore-fluid bulk modulus. Series reversion and Bayesian theory were introduced to establish a direct non-linear P-wave AVO inversion method. By adopting this method, the effective pore-fluid bulk modulus, porosity, and density can be inverted directly from seismic data. Numerical simulation results demonstrate the precision of our proposed method. Model and field data evaluations show that our method is stable and feasible.

Highlights

  • Pore-fluid identification remains a key part of hydrocarbon reservoir exploration

  • Fluid indicators are crucial to distinguishing pore-fluid

  • The first fluid indicator is defined as the weighting difference of

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Summary

Introduction

Pore-fluid identification remains a key part of hydrocarbon reservoir exploration. Fluid indicators are crucial to distinguishing pore-fluid. To improve the accuracy of fluid identification, Yin and Zhang (2014) presented an effective pore-fluid bulk modulus as a fluid indicator. Yin and Zhang (2014) deduced a linear four-term AVO approximation and proposed a Bayesian AVO inversion method for an effective pore-fluid bulk modulus. By using this method, the effective pore-fluid bulk modulus could be inverted from seismic data directly [7]. Neither exact nor nonlinear equations exist for an effective pore-fluid bulk modulus. Based on Zoeppritz equations and the Biot–Gassmann theory, we first deduce a high-order AVO approximation for the effective pore-fluid bulk modulus.

Sensitivity Analysis of the Effective Pore-Fluid Bulk Modulus
The relative variations fluid indicators in sandstone models:
With the increase of of Equation is larger than that of
Weighting
Effective Pore-Fluid Bulk Modulus Nonlinear AVO Inversion Method
Model Data Test
P-wave
11. Cross-plot
Discussion
Conclusions
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