Recognition method for simultaneously inverting reservoir fluid and brittleness based on porous medium model

Abstract

The invention discloses a recognition method for simultaneously inverting reservoir fluid and brittleness based on a porous medium model, and provides an AVO parametric equation and an inversion method based on a Bayesian framework to reflect the product of fluid equivalent bulk modulus and Young modulus and density. The fluid equivalent bulk modulus has enough sensitivity for determining the property of the fluid, the fluid equivalent bulk modulus can overcome the influence of porosity through linear change of water saturation, and the fluid recognition multiplicity is reduced. The Young modulus and the density of the brittle reservoir have relatively high values, and the product of the Young modulus and the density can highlight the brittleness of the reservoir; and the two parameters are obtained at the same time by using a new parameterized AVO approximation formula, so that the consistency of inversion results is ensured, and the calculated amount is reduced. According to the method, fluid recognition and brittleness evaluation are comprehensively considered, reliable support is provided for reservoir fluid prediction and subsequent development, and good practical applicationvalue is achieved.

Description

technical field [0001] The invention discloses a recognition method for simultaneous inversion of reservoir fluid and brittleness based on a porous medium model, and belongs to the technical field of oil and gas exploration. Background technique [0002] Artificial seismic exploration methods play a vital role in oil and gas exploration. As oil and gas exploration turns to deep and unconventional oil and gas reservoirs, methods for detection, analysis, and extraction of seismic reservoirs and oil and gas information have been greatly developed. Using seismic data to identify fluid and brittleness characteristics is an important part of reservoir prediction and development, especially unconventional reservoirs, but it is difficult to effectively identify fluids and reservoir brittleness in reservoirs with only a small amount of or single information, which requires We extract more attributes from seismic data for comprehensive analysis. [0003] Currently, seismic fluid iden...

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Problems solved by technology

[0012] Disadvantages of this method: the inherent "ill-conditioned solution" and "multiple solutions" of the seismic inversion problem itself, it is impossible to obtain the exact solution of the elastic parameters of the reservoir only by inversion of seismic data

However, the mineral composition of the actual reservoir is very complex, and it is obviously not enough to characterize the brittleness of the entire tight oil sandstone only by the content of a few highly brittle minerals such as quartz and feldspar

In addition, the level of brittleness requires mechanical experiments in the laboratory, requiring a large amount of core data, which is often accompanied by high costs

At the same time, the change of the underground medium is very complicated, and it is not representative to measure the brittleness only through the laboratory, and it is difficult to use it in practice.

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