CN109900617B - Method for calculating permeability curve of fractured formation based on acoustoelectric imaging log - Google Patents
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Abstract
The invention discloses a method for calculating a permeability curve of a fractured stratum based on an acoustoelectric imaging log, which comprises the following steps of: s1, converting the color acoustoelectric imaging log map into a gray scale map; s2, dividing the cracks and holes in the gray-scale image to obtain a binary image; s3, cutting the binary image into a plurality of small binary images by selecting proper window length and step length; s4, taking a small block binary image, and constructing a three-dimensional physical model of the crack and the hole of the small block binary image; s5, calculating permeability based on the three-dimensional physical model; s6, repeating the steps S4-S5 to obtain the permeability of all the small binary images; and S7, drawing a permeability curve of the fractured formation by using the permeability of all the small binary maps. The method is based on the color acoustoelectric imaging log map, and can accurately calculate the permeability curve of the fractured formation, so that the evaluation of the fractured oil and gas reservoir is more accurate, and the exploration and development of the fractured oil and gas reservoir are better guided.
Description
Technical Field
The invention relates to the field of petroleum and natural gas exploration and development, in particular to a method for calculating a permeability curve of a fractured stratum based on an acoustoelectric imaging log.
Background
Fractures have a relatively small effect on porosity, but a very large effect on formation permeability. In fractured formations (including fractured formations, fracture-vug formations, etc.), the permeability of the formation is mainly determined by the degree of development of the fractures and vugs. In general, formation permeability may be determined by three broad categories of methods:
(1) well testing and stratum testing: the well testing and stratum testing method is that a well testing instrument or a modular stratum tester is put into an oil-gas well at a specified depth, and the permeability of the depth is calculated through pressure data obtained by testing.
(2) Core permeability experiment: the experimental method of the permeability of the rock core comprises the steps of taking out an underground rock core to the ground, manufacturing the underground rock core into a regular rock core plunger, and measuring the permeability of the rock core plunger by using a pore permeability testing instrument. Compared with well testing and stratum testing methods, the method has lower cost and better effect on a porous stratum, but because the cracks in the fractured stratum are extremely developed and complete rock cores are difficult to obtain, the core permeability experiment is generally difficult to perform.
(3) And (3) well logging data calculation: the well logging data calculation method is to calculate the formation permeability by using the well logging data, the porosity and the permeability formula. The logging information adopted by the method comprises an acoustic curve, a neutron curve and a density curve. Firstly, obtaining the porosity of the stratum through a porosity formula, then combining the porosity with the core permeability for testing to establish a permeability formula, and finally applying the permeability formula to the whole well section to obtain the permeability curve of the stratum. However, the permeability calculated by the method only can reflect the porosity of the matrix and cannot reflect the permeability of cracks and larger holes. However, in fractured formations, formation permeability is primarily determined by fractures and vugs. Therefore, the existing well logging data calculation method cannot be applied to fractured formations.
The acoustoelectric imaging logging has a good crack and hole display function. Cracks and holes often appear as dark stripes, dark blocks, etc. on the sonographic log. At present, a great amount of acoustoelectric imaging well logging is almost measured in fractured hydrocarbon reservoirs, but at present, the acoustoelectric imaging well logging is only used for visually identifying whether fractures and holes exist, judging the development density of the fractures and the holes and calculating the porosity of the fractures and the holes.
On the whole, no method capable of accurately calculating the permeability curve of the fractured stratum exists at present, so that a method for calculating the permeability curve of the fractured stratum based on logging information is developed, and the method has important significance and broad prospects in the fields of exploration and development of fractured oil and gas reservoirs.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the existing problems, the method for calculating the permeability curve of the fractured stratum based on the acoustoelectric imaging log is provided, and the permeability curve of the fractured stratum can be accurately calculated by the method, so that the evaluation of the fractured oil and gas reservoir is more accurate, and the exploration and development of the fractured oil and gas reservoir are better guided.
The technical scheme adopted by the invention is as follows:
a method for calculating a permeability curve of a fractured stratum based on an acoustoelectric imaging log comprises the following steps:
s1, converting the color acoustoelectric imaging log map into a gray scale map;
s2, dividing the cracks and holes in the gray-scale image to obtain a binary image;
s3, cutting the binary image into a plurality of small binary images by selecting proper window length and step length;
s4, taking a small block binary image, and constructing a three-dimensional physical model of the crack and the hole of the small block binary image;
s5, calculating permeability based on the three-dimensional physical model;
s6, repeating the steps S4-S5 to obtain the permeability of all the small binary images;
and S7, drawing a permeability curve of the fractured formation by using the permeability of all the small binary maps.
Further, the method for converting the color acoustoelectric imaging log into the gray scale map in step S1 is as follows: the RGB format color acoustoelectric imaging log graph is decomposed into three gray level graphs of an RED channel, a GREEN channel and a BLUE channel, and one of the three gray level graphs with the most obvious crack and hole characteristics is selected and output as a required gray level graph.
Further, step S2 is: and (4) dividing cracks and holes in the gray-scale image by a threshold value method to obtain a binary image.
Furthermore, after the cracks and holes in the gray-scale image are segmented by a threshold method to obtain a binary image, the width of the cracks and the size of the holes need to be adjusted by adopting a morphological corrosion or expansion algorithm, and pseudo cracks and pseudo holes need to be removed.
Further, the window length and the step length have the following relationship with the three-dimensional physical model:
Range＝D1-D2
Step≤Range
where Range-window length, m;
Step-Step, m;
D1-bottom depth of the three-dimensional physical model, m;
D2-top depth, m, of the three-dimensional physical model.
Further, the method for constructing the three-dimensional physical model of the crack and the hole of the small binary image in the step S4 includes: (1) stretching the small binary image to form a three-dimensional data volume; (2) and extracting cracks and holes in the three-dimensional data body, and constructing a three-dimensional physical model for permeability simulation.
Further, the equation for calculating the permeability in step S5 is:
in the formula, k is the permeability, m2；
m-borehole coverage of the acoustoelectric imaging log, in the range of [0-1 ];
h is the thickness of the three-dimensional physical model, m;
r-borehole radius, m;
q-flow of three-dimensional physical model section, m3·s-1；
P1-a fluid inlet pressure, Pa, of the three-dimensional physical model;
P2-a fluid outlet pressure, Pa, of the three-dimensional physical model;
D1-bottom depth of the three-dimensional physical model, m;
D2-top depth, m, of the three-dimensional physical model.
Further, the flow Q of the section of the three-dimensional physical model is obtained by integrating the fluid velocity of each point in the three-dimensional physical model;
the equation for calculating the fluid velocity at each point in the three-dimensional physical model is:
in the formula, u is the fluid velocity at each point in the three-dimensional physical model, m.s-1；
μ -fluid viscosity, pas;
p-fluid pressure, Pa.
Further, in step S7, the method for drawing the permeability curve of the fractured formation by using the permeability of all the small binary maps is as follows: and drawing the points of the depth and the permeability corresponding to each small binary image into a connecting line graph by taking the permeability and the depth as coordinate axes to obtain a permeability curve of the fractured formation.
Further, the depth corresponding to each small binary image is the depth of the middle point between the bottom depth and the top depth of the three-dimensional physical model corresponding to the small binary image.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
the method is based on the color acoustoelectric imaging log map, and can accurately calculate the permeability curve of the fractured stratum, so that the evaluation of the fractured oil and gas reservoir is more accurate, and the exploration and development of the fractured oil and gas reservoir are better guided.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a block flow diagram of the present invention.
FIG. 2 is a comparison of a color acoustoelectric imaging log and a gray scale map obtained by a three-channel method and a weighting method according to an embodiment of the present invention.
FIG. 3 is a threshold selection histogram of a thresholding gray scale map according to an embodiment of the invention.
FIG. 4 is a comparison graph of a gray scale map and binary maps before and after adjustment according to an embodiment of the present invention.
FIG. 5 is a comparison graph of binary plots for different window lengths and step sizes for the cutting of embodiments of the present invention.
FIG. 6 is a schematic diagram of a three-dimensional physical model and a permeability calculation process according to an embodiment of the present invention.
FIG. 7 is a block flow diagram of an embodiment of the present invention.
FIG. 8 is a graphical representation of permeability of a fractured formation plotted according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the detailed description and specific examples, while indicating the preferred embodiment of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
A method for calculating a permeability curve of a fractured formation based on an acoustoelectric imaging log is disclosed, and as shown in FIG. 1, the method comprises the following steps:
step S1, converting the color acoustoelectric imaging log map into a gray scale map;
the original acoustoelectric imaging log is generally a color acoustoelectric imaging log gradually transited from black to dark red to white, and the format of the color acoustoelectric imaging log is an RGB format. In the original sono-electric imaging log, the black areas are characterized by low sonic velocity and low resistivity, respectively, and thus are typically cracks and holes (percolation space). The color acoustoelectric imaging log map is converted into a gray scale map, and then the cracks and the holes can be segmented. The conversion of the color acoustoelectric imaging log map into a gray scale map mainly comprises two methods:
(1) a three-way method:
the color acoustoelectric imaging log map in the RGB format is decomposed into three gray-scale maps of a RED (RED) channel, a GREEN (GREEN) channel and a BLUE (BLUE) channel by using image processing software such as ImageJ or calculation software such as matlab. The expressions of the three gray-scale maps are respectively:
GRAY＝R；
GRAY＝G；
GRAY＝B；
in the formula, GRAY is the value of a pixel point in a GRAY level image;
r-the value of the RED (RED) channel of a pixel point in the original acoustoelectric imaging log;
g is the value of the GREEN channel of a pixel point in the original acoustoelectric imaging log;
B-BLUE (BLUE) channel values of pixel points in the original sono-electric imaging log;
and selecting one of the three decomposed gray-scale images with the most obvious characteristics of the cracks and the holes as a required gray-scale image, and carrying out next step of splitting the cracks and the holes.
(2) A weighting method:
utilizing computing software such as matlab and the like to weight three-channel values of the RGB-format color acoustoelectric imaging log map to obtain a gray scale map, wherein the expression is as follows:
GRAY＝a*R+b*G+c*B；
a+b+c＝1；
in the formula, a, b and c are weighting coefficients, and the value range is [0-1 ].
Step S2, dividing the cracks and holes in the gray-scale image to obtain a binary image;
the invention preferably segments the cracks and holes in the gray-scale image by a threshold value method to obtain a binary image, and selects a proper segmentation threshold value Tv, then:
let BINARY equal to 0, if 0 ≦ GRAY ≦ Tv;
let BINARY equal to 1 if Tv < GRAY ≦ GRAYmax;
in the formula, BINARY is the value of a pixel point in a BINARY image; the pixel point of BINARY 0 represents the crack and the hole; the pixel point of BINARY 1 represents the stroma rock;
GRAYmax is the maximum gray level of a pixel in the gray-level image.
After the cracks and holes in the gray-scale image are segmented by the threshold method to obtain a binary image, the obtained binary image may have a certain deviation with the actual stratum: (1) the width of the crack and the size of the hole are larger or smaller, and the width of the crack and the size of the hole need to be adjusted by adopting a morphological corrosion or expansion algorithm; (2) the invention removes the false cracks and the false holes by adopting a manual identification method. And using the adjusted binary image for subsequent cutting and constructing a three-dimensional physical model.
Step S3, cutting the binary image into a plurality of small binary images by selecting proper window length and step length;
the window length, the step length and the three-dimensional physical model have the following relations:
Range＝D1-D2；
Step≤Range；
where Range-window length, m;
Step-Step, m;
D1-bottom depth of the three-dimensional physical model, m;
D2-top depth of the three-dimensional physical model, m.
Step S4, a small block binary image is taken, and a three-dimensional physical model of the crack and the hole of the small block binary image is constructed:
(1) stretching the small binary image to form a three-dimensional data volume; stretching may be accomplished using image processing software such as AUTOCAD, etc.
(2) And (3) extracting cracks and holes in the three-dimensional data body, namely extracting the three-dimensional data body formed by the parts with BINARY (0) in the small BINARY image, and constructing a three-dimensional physical model for permeability simulation.
Step S5, calculating permeability based on the three-dimensional physical model:
(1) applying fluid inlet pressure P to two end faces (stretching faces) of the three-dimensional physical model1And fluid outlet pressure P2In which P is1＞P2；
(2) Calculating the flow Q of the section of the three-dimensional physical model:
the flow Q of the section of the three-dimensional physical model is obtained by integrating the fluid velocity of each point in the three-dimensional physical model; the equation for calculating the fluid velocity at each point in the three-dimensional physical model is:
in the formula, u is the fluid velocity at each point in the three-dimensional physical model, m.s-1；
μ -fluid viscosity, pas;
p-fluid pressure, Pa.
(3) And (3) calculating the permeability:
the equation for calculating permeability is:
in the formula, k is the permeability, m2；
m-borehole coverage of the acoustoelectric imaging log, in the range of [0-1 ];
h is the thickness of the three-dimensional physical model, m;
r-borehole radius, m;
q-flow of three-dimensional physical model section, m3·s-1；
P1-a fluid inlet pressure, Pa, of the three-dimensional physical model;
P2-a fluid outlet pressure, Pa, of the three-dimensional physical model;
D1-bottom depth of the three-dimensional physical model, m;
D2-top depth, m, of the three-dimensional physical model.
Step S6, repeatedly executing the steps S4-S5 to obtain the permeability of all the small block binary images;
step S7, the permeability of all the small blocks of binary images is utilized to draw a permeability curve of the fractured formation:
and drawing the points of the depth and the permeability corresponding to each small binary image into a connecting line graph by taking the permeability and the depth as coordinate axes to obtain a permeability curve of the fractured formation. Wherein, the depth D corresponding to each small block binary image is the bottom depth D of the corresponding three-dimensional physical model1And a top depth D2Is located at a depth of the middle point of (c),i.e., the depth center, can be expressed as: d ═ D (D)1+D2)/2。
The features and properties of the present invention are described in further detail below with reference to XX well fractured formation intervals 5426 m-5432 m as examples.
S1, converting the color acoustoelectric imaging log map into a gray scale map;
and respectively carrying out image processing on the original color acoustoelectric imaging log by adopting a three-channel method and a weighting method, and obtaining a gray-scale image, wherein in the weighting method, processing parameters a are b, c are 1/3. As shown in fig. 2, the original color acoustoelectric imaging log is compared with the gray-scale images obtained by the three-channel method and the weighting method, so that the RED (RED) channel gray-scale image obtained by the three-channel method can best reflect the crack characteristics, and therefore, the RED (RED) channel gray-scale image obtained by the three-channel method is used for next-step crack and hole segmentation.
S2, dividing the cracks and holes in the gray-scale image to obtain a binary image;
as shown in fig. 3, an appropriate segmentation threshold Tv is selected as 61, and cracks and holes are distinguished from the matrix rock by a thresholding method, so as to obtain a binary map. The adjusted binary image has a certain deviation from the actual formation, so that the width of the fracture and the size of the hole are reduced by adopting a corrosion algorithm, and the gray-scale image and the binary image pair before and after adjustment are shown in fig. 4.
S3, cutting the binary image into a plurality of small binary images by selecting proper window length and step length;
selecting an appropriate window length Range and Step size, and matching four different window lengths Range and Step sizes shown in fig. 5, which are:
(1)Range＝0.25m，Step＝0.125m；
(2)Range＝0.25m，Step＝0.25m；
(3)Range＝0.5m，Step＝0.25m；
(4)Range＝0.5m，Step＝0.5m。
different window lengths Range and Step lengths Step are matched, permeability data points with different densities in the depth Range can be obtained, and selection can be carried out according to actual requirements. In this embodiment, (2) Range is 0.25m and Step is 0.25m, and the adjusted binary image is divided into 24 small binary images.
S4, taking a small block binary image, and constructing a three-dimensional physical model of the crack and the hole of the small block binary image: taking the small block binary map of 5428m to 5428.25m as an example, as shown in fig. 6, the following steps are performed: (1) stretching the small binary image to form a three-dimensional data volume; (2) and extracting cracks and holes in the three-dimensional data body, and constructing a three-dimensional physical model for permeability simulation.
S5, calculating permeability based on the three-dimensional physical model: setting processing parameters, m is 1, mu is 0.001 Pa.s, r is 0.2159m, D1＝5428.25m，D2＝5428m，P1＝130000Pa，P2＝100000Pa，H＝0.4m。
Calculating by using the permeability equation to obtain a small binary image with depth range of 5428-5428.25 m, corresponding to permeability of 15036.343d and depth center of the small binary image
S6, repeating the steps S4-S5, and obtaining the permeability of all the small blocks of binary images:
for the convenience of calculation, the present embodiment calculates the small block binary image in the order from the lowest bottom depth to the highest bottom depth, as shown in fig. 7. The calculated depth and permeability of the 24 small block binary image are shown in table one.
Table one:
and S7, drawing a permeability curve of the fractured formation by using the permeability of all the small binary maps.
And (3) drawing the points of the depth and the permeability corresponding to each small binary image into a connecting line diagram by taking the permeability and the depth as coordinate axes to obtain a permeability curve of the fractured formation, wherein the permeability curve is shown in fig. 8.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (8)
1. A method for calculating a permeability curve of a fractured stratum based on an acoustoelectric imaging log is characterized by comprising the following steps:
s1, converting the color acoustoelectric imaging log map into a gray scale map;
s2, dividing the cracks and holes in the gray-scale image to obtain a binary image;
s3, cutting the binary image into a plurality of small binary images by selecting proper window length and step length, adjusting the crack width and the hole size of the binary image by adopting a morphological corrosion or expansion algorithm, and removing pseudo cracks and pseudo holes;
s4, taking a small block binary image, and constructing a three-dimensional physical model of the crack and the hole of the small block binary image;
s5, calculating permeability based on the three-dimensional physical model;
s6, repeating the steps S4-S5 to obtain the permeability of all the small binary images;
s7, drawing a permeability curve of the fractured formation by using the permeability of all the small binary maps;
the equation for calculating the permeability in step S5 is:
in the formula, k is the permeability, m2；
m-borehole coverage of the acoustoelectric imaging log, in the range of [0-1 ];
h is the thickness of the three-dimensional physical model, m;
r-borehole radius, m;
q-flow of three-dimensional physical model section, m3·s-1；
P1-a fluid inlet pressure, Pa, of the three-dimensional physical model;
P2-a fluid outlet pressure, Pa, of the three-dimensional physical model;
D1-bottom depth of the three-dimensional physical model, m;
D2-top depth of the three-dimensional physical model, m;
μ -fluid viscosity, pas.
2. The method for calculating a permeability curve of a fractured formation based on an acoustoelectric imaging log as claimed in claim 1, wherein the step S1 of converting the color acoustoelectric imaging log into a gray scale map comprises the following steps: the RGB format color acoustoelectric imaging log graph is decomposed into three gray level graphs of an RED channel, a GREEN channel and a BLUE channel, and one of the three gray level graphs with the most obvious crack and hole characteristics is selected and output as a required gray level graph.
3. A method of calculating a permeability curve for a fractured formation based on an acoustoelectric imaging log as claimed in claim 1, wherein the step S2 is: and (4) dividing cracks and holes in the gray-scale image by a threshold value method to obtain a binary image.
4. The method of calculating a permeability curve for a fractured formation based on an acoustoelectric imaging log of claim 1, wherein the window length and the step size have the following relationship with the three-dimensional physical model:
Range＝D1-D2
Step≤Range
where Range-window length, m;
Step-Step, m;
D1-bottom depth of the three-dimensional physical model, m;
D2-top depth, m, of the three-dimensional physical model.
5. The method for calculating a permeability curve of a fractured formation based on an acoustoelectric imaging log of claim 1, wherein the method for constructing the three-dimensional physical model of the fractures and the holes of the small binary image in the step S4 comprises the following steps: (1) stretching the small binary image to form a three-dimensional data volume; (2) and extracting cracks and holes in the three-dimensional data body, and constructing a three-dimensional physical model for permeability simulation.
6. The method for calculating a permeability curve of a fractured formation based on an acoustoelectric imaging log as recited in claim 1, wherein the flow Q of the cross section of the three-dimensional physical model is obtained by integrating fluid velocities of various points in the three-dimensional physical model;
the equation for calculating the fluid velocity at each point in the three-dimensional physical model is:
in the formula, u is the fluid velocity at each point in the three-dimensional physical model, m.s-1；
μ -fluid viscosity, pas;
p-fluid pressure, Pa.
7. The method for calculating a permeability curve of a fractured formation based on an acoustoelectric imaging log as claimed in claim 1, wherein the step S7 uses the permeability of all small binary images and the method for drawing the permeability curve of the fractured formation is as follows: and drawing the points of the depth and the permeability corresponding to each small binary image into a connecting line graph by taking the permeability and the depth as coordinate axes to obtain a permeability curve of the fractured formation.
8. A method of calculating a permeability curve for a fractured formation based on an acoustoelectric imaging log according to claim 7, wherein the depth corresponding to each patch of the binary image is a depth at a point intermediate a bottom depth and a top depth of the three-dimensional physical model corresponding to the patch of the binary image.
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| CN113029899B (en) * | 2021-02-24 | 2022-07-01 | 西南石油大学 | Sandstone permeability calculation method based on microscopic image processing |
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