Well point fracture porosity prediction method based on dispersion characteristics of logging information

A technology of well logging data and fractures and pores, applied in the field of exploration geophysics, can solve the problems of difficult acquisition of 3D seismic, seldom calculating fractures, expensive acquisition costs, etc.

Inactive Publication Date: 2019-10-15
CHINA PETROLEUM & CHEM CORP +1
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Problems solved by technology

However, compared with P-wave data, S-wave data have a lower signal-to-noise ratio, are expensive to acquire, and are even difficult to obtain in 3D seismic
In addition, co

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  • Well point fracture porosity prediction method based on dispersion characteristics of logging information
  • Well point fracture porosity prediction method based on dispersion characteristics of logging information
  • Well point fracture porosity prediction method based on dispersion characteristics of logging information

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[0045] In order to make the above and other objects, features and advantages of the present invention more comprehensible, the preferred embodiments are listed below and shown in the accompanying drawings in detail as follows.

[0046] Such as figure 1 as shown, figure 1 It is a flow chart of the method for predicting the porosity of well point fractures based on the dispersion characteristics of well logging data of the present invention.

[0047] Step 101: Division of microscopic pore structure systems of reservoir rocks. Based on the rock mineral composition and pore structure of the reservoir rock in the work area, the composition of the pore structure is determined, and the pore microscopic system is divided into hard pores (pore aspect ratio or flatness above 0.01) and soft pores (pore aspect ratio or flatness above 0.01) with different aspect ratios. flatness below 0.01), such as figure 2 As shown, based on the core CT scanning image results, the rock microscopic po...

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Abstract

The invention provides a well point fracture porosity prediction method based on dispersion characteristics of logging information. The well point fracture porosity prediction method based on the dispersion characteristics of the logging information comprises the following steps: Step 1, carrying out reservoir rock microscopic pore structure system division; Step 2, calculating the rock physical modulus of a dispersion medium model; Step 3, calculating the compressional wave velocity and the shear wave velocity of a rock physical model with multi-pore distribution; Step 4, carrying out matching inversion on the compressional wave velocity and the shear wave velocity of logging and the velocities of the theoretical model; and Step 5, when a matching objective function F(alpha<n>) is smallerthan delta Vp, outputting the attributes of reservoir fracture pores at a current point. The well point fracture porosity prediction method based on the dispersion characteristics of the logging information has the advantages that the logging information is utilized for fracture porosity prediction, so that the fracture development situation of a single well can be effectively predicted, and an effective basis can be provided for fracturing evaluation.

Description

technical field [0001] The invention relates to the field of exploration geophysics, in particular to a method for predicting the porosity of well point fractures based on the dispersion characteristics of well logging data. Background technique [0002] For oil and gas exploration and development, fractures are a very important feature of reservoirs. If the fractures in the oil and gas reservoir are well developed, it means that the reservoir has higher commercial value. On the contrary, if fractures are not developed, even if the formation contains oil and gas, considering a series of factors of industrial development costs, it may not even be considered as oil and gas reservoirs. In addition, the relevant physical characteristics of the fracture are also critical. Generally speaking, the larger the fracture size, the larger the fracture opening and closing degree, the larger the fracture space, and the higher the fracture density, it means that the reservoir has better ...

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Application Information

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IPC IPC(8): G01V11/00G06F17/50
CPCG01V11/00G06F30/20
Inventor 刘浩杰魏国华陈雨茂杨宏伟林松辉毕丽飞王蓬
Owner CHINA PETROLEUM & CHEM CORP
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