Shale reservoir fracture and brittleness prediction method based on Bayesian inversion and system thereof

A technology for shale reservoirs and prediction methods, applied in measuring devices, geophysical measurements, seismology, etc., can solve the problem of insufficient characterization of shale brittleness, anisotropy parameters that are easily affected by fluids, and poor indication of reservoirs. The development of layer cracks and other problems can be improved to improve prediction accuracy and avoid cumulative errors

Pending Publication Date: 2022-02-15
CHINA UNIV OF PETROLEUM (EAST CHINA)
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Problems solved by technology

[0004] 1. Due to the influence of factors such as organic carbon content, porosity and fluid in shale reservoirs, in some cases Young's modulus is not enough to characterize shale brittleness
In addition, the elastic parameters (compressional and shear wave velocities and densities) obtained by traditional methods are indir...

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  • Shale reservoir fracture and brittleness prediction method based on Bayesian inversion and system thereof
  • Shale reservoir fracture and brittleness prediction method based on Bayesian inversion and system thereof
  • Shale reservoir fracture and brittleness prediction method based on Bayesian inversion and system thereof

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Embodiment 1

[0043] This embodiment provides a Bayesian inversion-based fracture and brittleness prediction method for shale reservoirs, including:

[0044] Obtain azimuth partial angle stack seismic data, azimuth seismic wavelet and low-frequency model of model parameters;

[0045] According to the acquired azimuthal partial angle superimposed seismic data, azimuthal seismic wavelet and low-frequency model of model parameters, and the preset shale reservoir fracture and brittleness prediction model, the prediction result is obtained;

[0046] Among them, the establishment process of the shale reservoir brittleness prediction model is as follows: deriving the approximate equation of the azimuthal reflection coefficient of the HTI medium containing the new brittleness indicator factor and fracture density; according to the above relationship and the Bayesian AVAZ inversion method, establishing the shale reservoir Crack and brittleness prediction model.

[0047] Specifically, as figure 1 A...

Embodiment 2

[0107] The present embodiment has carried out practical application to the method proposed in the embodiment 1, as follows:

[0108] The validity of the method is verified by using the 2D line seismic data of a work area in the Sichuan Basin passing through Well A. Imaging logging data and core data show that gas-bearing shale reservoirs mainly develop near-vertical high-angle fractures, so they can be equivalent to HTI media. The pre-stack azimuth gathers have been subjected to amplitude preservation and denoising processing in advance, and 12 partial angle stack seismic data are obtained through the azimuth and partial angle stack processing. The divided azimuth angles are 20°, 65°, 110° and 155°. The angles are 10° (small angle), 20° (medium angle) and 30° (large angle), such as Figure 7 , Figure 8 and Figure 9 shown. The Bayesian AVAZ inversion is carried out by using the azimuth and partial angle stacking seismic data. The model parameter profile obtained by the in...

Embodiment 3

[0110] This embodiment provides a Bayesian inversion-based fracture and brittleness prediction system for shale reservoirs, including a data acquisition module and a prediction module;

[0111] The data acquisition module is configured to: acquire azimuth partial angle superimposed seismic data, azimuth seismic wavelets and low-frequency models of model parameters;

[0112] The prediction module is configured to: superimpose seismic data, azimuth seismic wavelet and model parameter low-frequency model according to the acquired azimuth partial angle, and a preset shale reservoir fracture and brittleness prediction model to obtain a prediction result;

[0113] Among them, the establishment process of the shale reservoir brittleness prediction model is as follows: deriving the approximate equation of the azimuthal reflection coefficient of the HTI medium containing the new brittleness indicator factor and fracture density; according to the above relationship and the Bayesian AVAZ ...

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Abstract

The invention provides a shale reservoir fracture and brittleness prediction method based on Bayesian inversion. The method comprises the steps that azimuth part angle superposition seismic data, azimuth seismic wavelets and a model parameter low-frequency model are acquired; a prediction result is obtained according to the obtained azimuth part angle superposition seismic data, azimuth seismic wavelets, a model parameter low-frequency model and a preset shale reservoir fracture and brittleness prediction model; an establishment process of the shale reservoir fracture and brittleness prediction model comprises the following steps: deducing an HTI medium longitudinal wave azimuth reflection coefficient approximate equation containing a new brittleness indication factor and fracture density; and a shale reservoir fracture and brittleness prediction model can be established according to the relationship and a Bayesian AVAZ inversion method. According to the method, accumulative errors in the parameter indirect conversion process are effectively avoided, and the shale reservoir fracture and brittleness prediction precision is improved.

Description

technical field [0001] The present disclosure belongs to the technical field of shale reservoir inversion prediction, and in particular relates to a method and system for predicting fractures and brittleness of shale reservoirs based on Bayesian inversion. Background technique [0002] Shale reservoirs have the characteristics of low porosity, ultra-low permeability and tightness, and require fracturing to form a complex fracture network in order to obtain commercial production capacity. Fractability is defined as the property that shale reservoirs can be effectively fractured to obtain stimulation ability. The main factors affecting fractability include shale brittleness and natural fractures. Generally, the more natural fractures are developed in the reservoir, the better the brittleness, and the better the fractability. The brittleness index of shale is generally expressed by the brittleness index. The brittleness evaluation methods mainly include the mineral composition...

Claims

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Application Information

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IPC IPC(8): G06F30/20G01V1/30G01V1/28G06F119/02
CPCG06F30/20G01V1/282G01V1/30G01V1/301G01V1/306G06F2119/02
Inventor 李林张广智陈康印兴耀张佳佳王保丽周游王腾飞韩钊
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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