And extracting a quantitative characterization rock core heterogeneity method based on the pore information of the rock core CT image

Abstract

The invention discloses a method for extracting and quantitatively characterizing core heterogeneity based on core CT image pore information, comprising the following steps: carrying out CT scanning experiment on a carbonate rock core to obtain a two-dimensional gray scale slice; carrying out binarization segmentation, filtering, denoising, optimization processing, superposition reconstruction forming and core peer-to-peer digital core on the obtained two-dimensional gray scale slice; processing the data of the digital rock core; establishing a contribution relation equation of the rock core dissolved pore parameters to the rock core heterogeneity by utilizing the calculation parameters according to the relation that the heterogeneity of the rock core and the ratio of the dissolved pore volume to the total volume of the rock core are in positive correlation and are in inverse correlation with the number of the dissolved pores; and establishing a standard variance of rock core dissolvedpore scale distribution according to the rock core dissolved pore scale and the heterogeneity of the rock core, and quantitatively obtaining the heterogeneity of the rock core. The heterogeneity of the rock is evaluated based on quantitative calculation of the pore attribute of the rock, and the result is accurate and reliable; and guidance is provided for oil and gas reservoir reserve calculation and development schemes.

Description

technical field [0001] The invention relates to a digital rock core analysis method, in particular to a method for quantitatively characterizing rock core heterogeneity based on the extraction of pore information of rock core CT images. Background technique [0002] With the advancement of oil and gas exploration technology, various complex reservoirs have gradually become exploration target layers, such as conglomerate layers, tight layers, and dissolved pore-fracture reservoirs. Among them, carbonate fracture-cavity reservoirs are widely distributed; there are both fractures and dissolution pores in carbonate fracture-cavity reservoirs, which are mainly formed by the comprehensive effect of original lithology, structure and karst. The main storage space of fracture-cavity reservoirs is composed of dissolved caves, fractures and dissolved pores of different sizes. Dissolved pores are the most important storage space, while matrix pores are generally underdeveloped, and frac...

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Problems solved by technology

[0004] For carbonate reservoirs with different storage spaces of pores, fractures and caves, Wang Lien et al. proposed that for reservoirs with double pore structure and pore-cavity reservoirs, various porosities and total porosity of the reservoir can be used. The ratio of matrix permeability, fracture permeability and total permeability can be used to quantitatively describe the degree of heterogeneity of the reservoir. The application of this method has achieved good application results, but it has two disadvantages: (1) It is very difficult to calculate the porosity and permeability of dual porosity separately by conventional methods, and there is no clear division boundary; (2) The porosity ratio and permeability ratio are not necessarily consistent in complex carbonate reservoirs. , thus restricting the universality of its application

[0005] In recent years, with the wide application of CT scanning computer tomography technology in the petroleum industry, a method of establishing digital cores based on CT images to study the pore structure of cores has been formed; Gao Jian et al. used CT scanning imaging technology to select 7 parameters to characterize cores The central tendency, dispersion degree and distribution form of pore distribution characterize the non-uniformity of pore space in the core macroscopically, but the microscopic scale and number of pores of pore space have not been studied from the microscopic perspective of pore space to finely characterize the different Contribution of scale pores and pore number to heterogeneity

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