CN-121994674-A - Method and process for characterizing heterogeneity of dense sandstone pore-throat structure by fractal analysis

CN121994674ACN 121994674 ACN121994674 ACN 121994674ACN-121994674-A

Abstract

The invention relates to a method and a process for characterizing heterogeneity of a dense sandstone pore-throat structure by fractal analysis, which are characterized in that the method is used for comprehensively considering pore-throat radius and pore-throat form factors of a reservoir according to the characteristics of small and complex pore-throat of the dense sandstone reservoir, comprehensively utilizing the two aspects of pore-throat shape heterogeneity and pore-throat radius distribution fractal dimension weighted average result of mercury-pressing test data to characterize pore-throat radius data distribution heterogeneity, utilizing multi-fractal spectrum width of a slice image to characterize pore-throat shape heterogeneity, and establishing two heterogeneous parameter plates to characterize the heterogeneity of the pore-throat structure of the reservoir.

Inventors

ZHANG XIANGUO
LI XIAO
CUI XINFENG
Gao Xiuhao
LIU HUAFENG

Assignees

中国石油大学(华东)

Dates

Publication Date: 20260508
Application Date: 20260302

Claims (6)

1. A method and a process for characterizing heterogeneity of a dense sandstone pore throat structure by fractal analysis, wherein the identification method comprises the following steps: S1, screening and numbering core analysis samples; S2, randomly selecting an analysis sample, dividing a pore-throat radius frequency distribution curve of a mercury-pressing test into three sections of a large pore section, a middle pore section and a micro pore section, respectively solving the percentage of the area between the three pore-throat radius frequency distribution curve sections and a coordinate transverse axis to the total area of the three sections, and sequentially marking the percentage as Jl, jm and Js; S3, mercury pressing test is carried out on the sample selected in the step S2, pore throat radius distribution fractal dimensions of the macropores, the mesopores and the micropores are respectively calculated, jl, jm and Js obtained in the step S1 are taken as weights, and pore throat radius fractal dimensions of the macropores, the mesopores and the micropores are weighted and averaged to obtain a sample pore throat radius distribution heterogeneity index Hr; s4, carrying out multi-fractal analysis on pore throat of the slice image on the sample selected in the S2, and enabling the spectrum width of the multi-fractal As an index of the shape heterogeneity of the pore throat; S5, analyzing the samples numbered in the step S1 one by one according to the methods and the processes from the step S2 to the step S4 to obtain Hr and Hr of all the samples Parameters; S6: hr- And (5) drawing all the sample calculation results obtained in the step (S5) into the drawing plate to obtain a heterogeneous distribution map of the pore-throat structure of the tight sandstone reservoir in the research area.
2. The method according to claim 1, wherein the step S1 comprises carding analysis test data of the core of the objective interval of the research area, selecting core samples with conventional mercury intrusion analysis test and rock slice analysis test, setting the number of samples meeting the above conditions as n, wherein n is a natural number larger than zero, and numbering the n rock samples in sequence according to the sample depth.
3. The method according to claim 1, wherein step S2 of the method comprises the steps of: (1) Dividing a pore-throat radius distribution interval into three intervals of macropores, mesopores and micropores, sequentially marking as intervals A, B, C, dividing the pore-throat radius frequency distribution curve into three sections according to A, B, C on a pore-throat radius frequency distribution curve obtained by conventional mercury-pressing test of a sample, sequentially marking as curves a, b and c, and respectively corresponding to pore-throat radius frequency distribution curves of macropores, mesopores and micropores; (2) Calculating the fixed integral of curves a, b and c on the radius of the pore throat by adopting a trapezoid method, wherein the integral intervals are A, B, C respectively, the calculation result is sequentially marked as S l 、S m 、S s , and the sum of the three is marked as S t ; (3) The ratio of S l 、S m 、S s to S t is calculated respectively and is sequentially marked as Jl, jm and Js, and the percentages of the three are all; preferably, the division standard of the pore throat radius distribution interval in the step (1) is that macropores are larger than 0.5 μm, mesopores are 0.025-0.5 μm, and micropores are smaller than 0.025 μm.
4. A method according to claims 1 and 3, characterized in that step S3 comprises the following steps: (1) Dividing mercury inlet curve data of sample mercury-pressing analysis into three groups according to A, B, C pore-throat radius intervals, and respectively representing mercury inlet curve data of macropores, mesopores and micropores; (2) Selecting any one of the three groups of data divided in the step (1), calculating the values of lg (1-S Hg ) and lgP c of each test data point in the group, wherein S Hg is the mercury saturation of the test data point, P c is the displacement pressure of the test data point, lg (1-S Hg ) is taken as an ordinate, lgP c is taken as an abscissa, and in a plane rectangular coordinate system, throwing points to all the data points in the group, drawing a scatter diagram, and the type of coordinate axis is taken as a linear coordinate; (3) Performing linear fitting on the scatter diagram obtained in the step (2), wherein the slope of a fitting relation is D, and the fractal dimension of the pore-throat structure is recorded as D, so that the slope of the fitting relation is the slope of D lg(1-S Hg )=(D-3)lgP c + (3-D)P cmin Wherein P cmin is capillary pressure corresponding to the maximum pore throat of the sample, the mercury-pressing test starting pressure is directly read from the mercury-feeding curve of the mercury-pressing curve as P cmin , According to the above, the fractal dimension D of the pore-throat structure is obtained, wherein d=d+3 (4) Respectively solving pore throat radius fractal dimensions of the three groups of data in the step (1) by using the methods of the steps (2) and (3), wherein the pore throat radius fractal dimensions of the macropores, the mesopores and the micropores are sequentially marked as Dl, dm and Ds; (5) A weighted average method is adopted to calculate the pore-throat radius distribution non-uniformity index Hr of the sample, Hr=Jl·Dl+Jm·Dm+Js·Ds。
5. The method according to claim 1, wherein step S4 comprises the steps of: (1) Performing binarization processing on a sheet analysis image of a sample, and dividing information in the image into two parts, namely pore throat and non-pore throat; (2) Performing multi-fractal analysis on the picture subjected to binarization treatment in the step (1), and solving multi-fractal spectrum width As an index of the pore throat shape non-uniformity.
6. The method according to claim 1 or 3 or 4 or 5, wherein step S6 comprises the steps of: (1) Plane orthogonal using linear coordinate axes Hr- A plate, wherein the ordinate and abscissa of the plate represent Hr and Hr, respectively, of the sample Parameters; (2) Hr sum of n samples of study region obtained in S5 The parameter values are cast into the image plate established in the step (1) one by one according to the data of the sample points, and a heterogeneous distribution map of the pore-throat structure of the compact sandstone reservoir in the research area is obtained; (3) For Hr- Sample data points in the plate show that the farther the sample data points are from the vertical axis, the more complex the pore throat morphology of the reservoir layer, the stronger the pore throat shape heterogeneity, and the farther the sample data points are from the horizontal axis, the worse the pore throat size sorting, and the stronger the heterogeneity of the pore diameter distribution.

Description

Method and process for characterizing heterogeneity of dense sandstone pore-throat structure by fractal analysis Technical Field The invention relates to the technical field of oil and gas exploration and development, in particular to a method and a process for characterizing heterogeneity of a pore-throat structure of a tight sandstone reservoir by fractal analysis, which are based on mercury intrusion test data and sheet images. Technical Field Compact sandstone reservoirs are important types in unconventional reservoirs, are also the most important deep reservoirs, and are reservoirs which need to be overcome in a key way from oil and gas exploration and development to the new fields of deep layer, deep sea and unconventional. The knowledge of reservoir pore throat structure is one of the core contents in tight sandstone oil and gas reservoir evaluation and high-quality reservoir prediction. For tight sandstone reservoirs, general micropore development, and in the case of small average pore-throat radius differences, the effect of pore-throat structure heterogeneity on reservoir physical properties is particularly critical. In the last decade, research methods for pore-throat structure of tight sandstone reservoirs have been actively developed, and these methods can be summarized into the following categories: (1) Experimental test method For a core sample, quantitative analysis of pore throat size, distribution and fluid occurrence characteristics is carried out by physical/chemical means, common methods comprise a conventional mercury injection method, a constant-speed mercury injection method, a nitrogen adsorption method, core nuclear magnetic resonance, a centrifugal experiment and the like, microscopic pore throat structure parameters reflected by different testing methods are different, the mercury injection method mainly reflects throat radius distribution, pore throat sorting property and connectivity, the nitrogen adsorption method can carry out quantitative analysis on nanoscale pore throats in a tight sandstone reservoir, and the centrifugal experiment and the nuclear magnetic resonance experiment can analyze the corresponding relation between the irreducible water saturation and pore throat size. (2) Microcosmic imaging technique And directly observing the morphology, the type and the three-dimensional spatial distribution of the pore throat through high-resolution imaging. Common methods include scanning electron microscopy, transmission electron microscopy, micro/nano CT, focused ion beam scanning electron microscopy, and the like. The scanning electron microscope can qualitatively observe pore throat types (inter-particle pores, intra-particle pores, erosion pores and clay mineral pores), morphology and microscopic heterogeneity, the transmission electron microscope can characterize the microstructure of nano pore throats such as inter-particle pores and inter-crystal pores of the clay mineral, the micro/nano CT utilizes X-ray scanning to reconstruct a three-dimensional pore throat network, the pore throat volume, connectivity, pore diameter distribution and spatial spread are quantitatively analyzed, and the nano CT can identify sub-micro pore throats to realize three-dimensional nondestructive characterization. Focused Ion Beam (FIB) -Scanning Electron Microscope (SEM) uses FIB layer-by-layer cutting and SEM imaging to reconstruct nano pore throat network, and accurately analyze connectivity and morphology of micro pore throats. (3) Numerical simulation method Based on experimental/imaging data, the effect of pore throat structure on fluid flow is quantified by a mathematical model, and quantitative characterization is associated with seepage. Common methods include pore-throat network model (PNM), direct Numerical Simulation (DNS), fractal theory, percolation theory, and the like. The pore-throat network model (PNM) abstracts a pore-throat system into a pore-throat network, simulates fluid flow, correlates pore-throat structure parameters (throat radius, pore-throat volume) and seepage characteristics (permeability and relative permeability), directly simulates the fluid flow by a finite element/volume method based on the real pore-throat geometry of a CT image by Direct Numerical Simulation (DNS), accurately reflects the seepage rule of a complex pore-throat, describes the self-similarity of the pore-throat structure by a fractal dimension, quantifies the non-uniformity and complexity of the pore-throat structure by the fractal theory, analyzes pore-throat connectivity threshold by the percolation theory, and evaluates the formation condition of an effective reservoir space. (4) Well logging evaluation technology And the longitudinal continuous pore throat structure evaluation of the reservoir is realized, and the core experiment and the stratum reality are associated. Common techniques include nuclear magnetic resonance logging, elastic wave logging, imaging logging, resistivity logg