CN114283254A - Core digital pore network model construction method based on nuclear magnetic resonance data - Google Patents
Core digital pore network model construction method based on nuclear magnetic resonance data Download PDFInfo
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Abstract
The invention discloses a core digital pore network model construction method based on nuclear magnetic resonance data, which comprises the steps of selecting a core sample, drying the core sample, measuring sample parameters, vacuumizing the sample to saturation to simulate formation water or simulate formation crude oil; performing nuclear magnetic resonance scanning on a sample to obtain a two-dimensional image; carrying out interpolation on the two-dimensional image to obtain a rock core three-dimensional data volume; establishing a three-dimensional unordered pore network model, and assigning a three-dimensional data body to a node of the model; calculating the pore throat radius of each adjacent node in the model through the conversion coefficient and simulating the permeability of the model; and adjusting the conversion coefficient to ensure that the permeability is close to the actually measured permeability of the rock core, and establishing a digital pore network model of the rock core. The method has the advantages of high accuracy and modeling efficiency of the established model, capability of really reducing the real core characteristics of the reservoir, wide application range, low physical experiment cost and short period, and remarkably reduces the difference between the simulation result and the actual experiment result in the model.
Description
Technical Field
The invention relates to the field of oil and gas field development, in particular to a core digital pore network model construction method based on nuclear magnetic resonance data, which is suitable for conventional sandstone oil and gas reservoirs, unconventional oil and gas reservoirs such as compact oil and gas, shale oil and gas, natural gas hydrate and the like, and is also suitable for CO2 geological storage technology.
Background
Petroleum and natural gas are one of important energy sources for maintaining the high-speed development of national economy, and how to reasonably exploit the petroleum and the natural gas and improve the recovery ratio of the petroleum and the natural gas is always an important problem in the development process of oil and gas fields. The internal pore throat structure of actual underground reservoir rock is complex, and the seepage rule of fluid in the rock is difficult to clear through experimental means. Many inventors have used porous media models to simulate the flow of different types of fluids within rock to find methods useful for enhanced oil recovery. The digital core technology is used as a branch of a porous medium model and can be used in various fields of geology, earthquake, well logging and development, enhanced recovery ratio and the like in the petroleum and natural gas industry. The digital core can effectively retain microcosmic physical characteristics of the core, can ensure that the core can be used for unlimited times, is an important platform for numerical simulation of rock physical experiments, can quantitatively invent the influence of various microcosmic factors (such as pore connectivity, wettability and the like) in the core on the reservoir seepage process, and can calculate physical properties which cannot be directly measured by the traditional physical experiments, such as three-phase relative permeability of oil, gas and water. In view of the wide applicability, the development of the invention of the digital core has important significance for improving the recovery ratio of petroleum and natural gas.
The most fundamental work when the digital core is applied to various rock physical experiments is to establish an accurate three-dimensional digital core model which is consistent with actual rocks. In the past 15 years, with the innovation of experimental instruments and the breakthrough of new theories, new methods for constructing digital core models are continuously proposed by invention teams at home and abroad. The invention for years divides the method for constructing the digital rock core into three major categories, namely a numerical reconstruction method, a physical experiment method and a mixing method. The numerical reconstruction method is a method for reconstructing a three-dimensional digital core by a random simulation method or a sedimentary rock process simulation method by using information contained in a two-dimensional picture on the basis of a small number of two-dimensional slice images. The accuracy and the modeling efficiency of the model built by the method are low, and the selection of the constraint conditions in the modeling method can cause that the simulation result has contingency and the real core characteristics of the reservoir are difficult to restore. The physical experiment method is that a core sample is shot or scanned by using an experimental instrument to obtain a large number of two-dimensional pictures of the core, and then the two-dimensional pictures are overlapped and reconstructed into a three-dimensional digital core through a modeling program or software. However, the method is limited by the resolution and precision of experimental instruments (such as a CT scanner), the scale of the established model is small (generally millimeter scale), the representativeness and engineering application of the model are greatly limited, extraction and analysis of the micro parameters of the rock core with the characteristic of the karst cave fractures are difficult, and the physical experiment cost is high and the period is long. The hybrid method can establish a more accurate three-dimensional model by combining a plurality of modeling methods and taking the length of each model, but the scale of the established model is still different from that of a real rock core. Meanwhile, due to the imperfection of a pore-scale seepage theory system and a mathematical model, the simulation result in the model established by the method is different from the actual experiment result in different degrees.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a core digital pore network model construction method based on nuclear magnetic resonance data, the core digital pore network model established by the method can apply a micro seepage mechanism to a core scale pore network for numerical simulation, can be directly compared with a macroscopic experiment result obtained by indoor core experiment analysis for verification, can also perform larger scale-up analysis on the basis of indoor core analysis, is an important supplement of indoor core analysis and macroscopic scale oil and gas reservoir numerical simulation, and builds a bridge between the indoor core analysis and the macroscopic oil and gas reservoir numerical simulation.
The purpose of the invention is realized by the following technical scheme:
a core digital pore network model construction method based on nuclear magnetic resonance data comprises the following steps:
the method comprises the following steps: measuring the pore throat length, porosity and permeability of the core after the core sample is selected and dried, and vacuumizing the core sample to simulate formation water or simulate formation crude oil;
step two: performing nuclear magnetic resonance MRI/T on core sample2Scanning and measuring to obtain two-dimensional images of the rock core on different sections;
step three: interpolating the two-dimensional image to obtain core MRI/T2A three-dimensional data volume;
step four: establishing a three-dimensional disordered pore network model, and carrying out MRI/T2Assigning the three-dimensional data volume to a node of the three-dimensional disordered pore network model;
step five: calculating the pore throat radius of each adjacent node in the three-dimensional disordered pore network model through the conversion coefficient alpha, and simulating and calculating the permeability of the core digital pore network model; and adjusting the size of the conversion coefficient alpha to ensure that the permeability of the pore network is similar to the actually measured permeability of the rock core, and establishing a digital rock core pore network model.
Specifically, the second step specifically comprises: performing nuclear magnetic resonance scanning on the core sample after vacuum saturation simulation by using a nuclear magnetic resonance instrument, and generating T by using a SIRT inversion algorithm2Distributing; the method comprises the steps of slicing different parts of a rock core, selecting proper slice positions and section numbers within the processing range of a nuclear magnetic resonance instrument to carry out nuclear magnetic resonance imaging scanning on the rock core according to the scanning precision of the nuclear magnetic resonance instrument, obtaining nuclear magnetic resonance MRI two-dimensional images of the rock core at different slice positions of the rock core, and storing slice position coordinates and pixel data of the two-dimensional images in a TXT text of the two-dimensional images.
Further, the mri scanning process specifically includes: measuring by using a low-field nuclear magnetic resonance core analysis system with the magnetic field intensity of 0.5t, wherein the test parameters comprise dominant frequency, echo spacing, polarization time and echo number; in the process of scanning the core, a standard core with the length of 5cm and the diameter of 2.5cm is placed in a constant magnetic field, and gradient fields are applied in the x direction, the y direction and the z direction; when a sample is collected, initially, the resonance in the layer is consistent, a phase encoding gradient is applied to a magnetic field, the phase encoding gradient is removed, then a frequency encoding gradient is applied, and each voxel is marked with a mark; applying radio frequency pulse to a certain layer, and receiving MR signals of the layer; and decoding to obtain the MR signal of each voxel on the layer, and displaying the MR signal on the corresponding pixel of the fluorescent screen.
Specifically, the third step specifically comprises: utilizing an interpolation algorithm to combine the TXT text of the two-dimensional image obtained in the step two and the pore throat length of the rock core in the step one to carry out interpolation processing on the nuclear magnetic resonance imaging data volume, namely the nuclear magnetic resonance MRI two-dimensional image of the rock core, so that the scale of the data volume meets the requirement of reflecting the microscopic pore throat characteristics of the rock, and obtaining the MRI/T related to the rock core2A three-dimensional tensor data volume.
Specifically, the step four specifically includes the following substeps:
s401, setting the size of a model, the coordination number and the average pore throat length according to the core dimension;
s402, adopting a computer programming language and a matrix calculation library Eigen to construct a three-dimensional regular cube network structure to generate an X multiplied by Y multiplied by Z three-dimensional regular cube network;
s403, setting the total number of nodes of the cubic network to be (X-1 (Y-1) X (Z-1), wherein each node represents a pore, the nodes are connected through throats, and the rest parts are rock frameworks;
s404, six throats are connected around each node representing pore in the established cubic network model, and the throat length is the average rock pore throat length<l>(ii) a The side lengths in the x, y and z directions of the cubic network model are respectively Lx＝(X-1)<l>，Ly＝(Y-1)<l>，Lz＝(Z-1)<l>(ii) a All grid nodes in the cubic network model are fully connected through circular tubes, and the ratio of the radius of a pore to the radius of a throat is set to be 1; set up LyAnd LzThe diameter of the actual core is determined, and the distance from the central point in the yoz plane of each layer is greater than LyAll the points of (2) are removed, so that the cubic network model becomes the real rockPlunger-like models with consistent heart shapes;
s405, magnetic resonance imaging/magnetic resonance tomography (MRI/T)2The numerical value in the three-dimensional tensor data body is given to each node of the three-dimensional regular cube network model, and the value of a connecting line between 2 nodes is the pore throat radius R; all pore throat radiuses R in the network are MRI/T on adjacent 2 nodes2An average of the values; randomly moving each node coordinate in the model in a spherical space to generate a disordered network space structure and generate random variation of the pore throat length; and randomly removing part of connection from the network structure to obtain pore network models with different connectivity characteristics.
Specifically, the fifth step specifically includes assuming that the initial value of the conversion coefficient is α, calculating the throat radius R by the conversion coefficient α according to the method of the fourth stepiObtaining a core digital pore network model, calculating the permeability of the constructed core digital pore network model by adopting a single-phase stable seepage pore network simulation algorithm, and checking whether the permeability obtained by simulation is consistent with the permeability measured by the core; if not, adjusting the conversion coefficient alpha, and recalculating the pore throat radius R of the pore networkiAnd reestablishing the core digital pore network model and calculating the permeability value of the core digital pore network model until the permeability of the core digital pore network model is basically consistent with the permeability measured value of the real core, and obtaining the core digital pore network model corresponding to the actual core sample.
The detailed implementation process of the method provided by the invention is as follows:
1. based on MRI/T of nuclear magnetic resonance2Data establishment core digital pore network model
Firstly, selecting a core sample, drying, and measuring the length, diameter, porosity and permeability of the core sample; vacuumizing the rock core sample to simulate formation water or simulate formation crude oil, and performing nuclear magnetic resonance scanning to obtain nuclear Magnetic Resonance Imaging (MRI) data and nuclear magnetic resonance T of the corresponding rock core sample2The spectral data and scanning process can be realized by using NMR imaging technology (in ancient Lin, NMR imaging, 2004, advanced education Press). MRI measurement is carried out on different positions of the rock core to obtain corresponding positionsAnd (4) placing a core MRI two-dimensional image. And according to the scanning precision of the instrument, selecting a proper slice position and a proper section number in the processable range of the instrument, and acquiring the two-dimensional nuclear magnetic resonance MRI images of different slice positions of the rock core. The slice position coordinates and pixel data are saved in TXT text.
Acquiring nuclear magnetic resonance MRI/T of rock core2A three-dimensional tensor data volume. And (4) interpolating the nuclear magnetic resonance imaging data volume according to the TXT text data of the two-dimensional image and the approximate range of the core pore throat length obtained in the step (i), so that the data volume scale meets the requirement of reflecting the microscopic pore throat characteristics of the rock. The interpolation algorithm can adopt algorithms such as trilinear interpolation, kriging interpolation and the like. The basic parameters of interpolation are determined by the actual length and diameter of the core and the space position of a two-dimensional image slice, and MRI/T is obtained by interpolation2A three-dimensional tensor data volume.
And constructing a spatial disordered structure pore network model. And setting parameters such as the size of the model, coordination number, average pore throat length and the like according to the core dimension. Firstly, a regular cube network structure is constructed by adopting C + + language and a matrix calculation library Eigen to generate an X Y Z three-dimensional regular cube network (X, Y and Z values are obtained by the step II)2Determining the scale of a three-dimensional tensor data volume), setting the total number of nodes of the network model to be (X-1 (Y-1) X (Z-1), wherein each node represents a pore, the nodes are connected by throats (circular pipelines), and the rest parts are rock frameworks. Six throats are connected around each node representing pore in the established network model, and the throat length is the average pore throat length of the rock<l>. The side lengths of the model in the x, y and z directions are respectively Lx＝(X-1)<l>，Ly＝(Y-1)<l>，Lz＝(Z-1)<l>. All grid nodes in the model are fully connected through circular tubes (the coordination number z of any node is 6 at this time), and the ratio of the radius of the pore to the radius of the throat is set to be 1. Set up LyAnd LzThe diameter of the actual core is determined, and the distance from the central point in the yoz plane of each layer is greater than LyAll the points of (a) are removed, making the model a plunger-like model that conforms to the shape of the true core. MRI/T using nuclear magnetic resonance2Three-dimensional gauge for assigning numerical values in three-dimensional tensor data volumeThen the value of the connecting line between 2 nodes on the node of the cubic network is the pore throat radius R. All pore throat radiuses R in the network can be MRI/T on adjacent 2 nodes2Average of the values. And (4) randomly moving each node coordinate of the network in the spherical space to generate a disordered network space structure and generate random variation of the pore throat length. Partial connections are randomly removed from the network structure, and a pore network model with different connectivity (coordination number) characteristics can be obtained.
And fourthly, a core digital pore network model. Nuclear magnetic resonance MRI/T of core sample2The data volume reflects the relative size of the pore space within the rock, and does not directly reflect the pore throat radius size of the rock. Thus, a trial and error approach can be used here to estimate the throat radius R of the rockiAnd corresponding MRI/T2Data amplitude AiCoefficient of conversion between alpha (R)i＝αAi) Constructing a core digital pore network model: assuming the initial value of the conversion coefficient, calculating the pore throat radius R according to the method and the conversion coefficientiObtaining a core digital pore network model, calculating the permeability of the constructed core digital pore network model by adopting a single-phase stable seepage pore network simulation algorithm, and checking whether the permeability obtained by simulation is consistent with the permeability measured by the core; if not, adjusting the conversion coefficient, and recalculating pore throat radius R of the pore networkiAnd re-establishing the core digital pore network model and calculating the permeability value of the core digital pore network model until the permeability of the pore network model is basically consistent with the permeability measured value of the real core, and obtaining the core digital pore network model corresponding to the actual core sample.
For a cylindrical core sample with the diameter of 2.5cm and the length of 5cm, the number of nodes of the corresponding core digital pore network model is more than 100 ten thousand. At this time, the conventional CPU sparse matrix equation solving algorithm is difficult to process such problems, and a GPU algorithm should be used for calculation and solution.
The invention has the beneficial effects that:
1. the invention adopts high-precision nuclear Magnetic Resonance Imaging (MRI) and T2 spectral data, and combines an interpolation algorithm with a random disordered pore network model to establish a digital pore network model of an indoor rock sample. The model overcomes the problems that the scale of the early digital core is small and the multiphase seepage analysis is not easy to develop, has the advantages of large scale and high precision, and can be directly corresponding to the size and the characteristics of an actual rock sample, can more comprehensively analyze the influence of the micro pore throat heterogeneity and the macro heterogeneity of the rock on the seepage process, and assists in the scheme research of improving the recovery ratio of petroleum and natural gas;
2. the method has the advantages of high accuracy and modeling efficiency of the established model, capability of really reducing the real core characteristics of the reservoir, wide application range, low physical experiment cost and short period, and remarkably reduces the difference between the simulation result and the actual experiment result in the model.
Drawings
FIG. 1 is a flow chart of the method steps of the present invention;
FIG. 2 is a flow chart of a magnetic resonance MRI scan;
FIG. 3 is an exemplary illustration of MRI two-dimensional images of different locations of a core;
FIG. 4 is MRI/T based on nuclear magnetic resonance2The three-dimensional tensor data visualization image schematic diagram;
FIG. 5 is a schematic diagram of a construction method of a spatially disordered network structure;
fig. 6 is a schematic diagram of a digitized pore network model of a core.
Detailed Description
The following detailed description will be selected to more clearly understand the technical features, objects and advantages of the present invention. It should be understood that the embodiments described are illustrative of some, but not all embodiments of the invention, and are not to be construed as limiting the scope of the invention. All other embodiments that can be obtained by a person skilled in the art based on the embodiments of the present invention without any inventive step are within the scope of the present invention.
The first embodiment is as follows:
in this embodiment, as shown in fig. 1, a core digitized pore network model construction method based on nuclear magnetic resonance data includes the following technical processes: measuring the pore throat length, porosity and permeability of the core after the core sample is selected and dried, and vacuumizing the core sample to simulate formation water or simulate formation crude oil; performing nuclear magnetic resonance MRI/T2 scanning measurement on the core sample to obtain two-dimensional images of the core on different cross sections; interpolating the two-dimensional image to obtain a core MRI/T2 three-dimensional data volume; establishing a three-dimensional disordered pore network model, and assigning an MRI/T2 three-dimensional data volume to nodes of the three-dimensional disordered pore network model; calculating the pore throat radius of each adjacent node in the three-dimensional disordered pore network model through the conversion coefficient alpha, and simulating and calculating the permeability of the core digital pore network model; and adjusting the size of the conversion coefficient alpha to ensure that the permeability of the pore network is similar to the actually measured permeability of the rock core, and establishing a digital rock core pore network model.
In this embodiment, the method is specifically implemented as follows:
1. based on MRI/T of nuclear magnetic resonance2Core digital pore network model
According to nuclear magnetic resonance MRI/T2Data acquisition core two-dimensional slice image
The nuclear magnetic resonance measurement adopts a MesoMR23-60H-I type nuclear magnetic resonance instrument, and adopts an inverted pulse sequence and a Carr-Purcell-Meiboom-Gill pulse sequence to measure nuclear magnetic resonance signals. Generation of T using SIRT (simultaneous iterative reconstruction technique) inversion algorithm2And (4) distribution. The measurement was carried out using a low-field nuclear magnetic resonance core analysis system (MesoMR-060H-HTHP-I) with a magnetic field strength of 0.5t, and the main test parameters included the dominant frequency (21.326MHz), the echo spacing (TE ═ 0.2ms), the polarization time (TW ═ 3000ms), and the number of echoes (NECH ═ 8000). In the process of scanning the core, a standard core with the length of 5cm and the diameter of 2.5cm is placed in a constant magnetic field, a gradient field is applied in the x direction, the y direction and the z direction, and the gradient field strength is equal to the magnetic field strength difference value at two ends of the gradient field/the length of the gradient field. When the sample is acquired, initially the in-plane resonances are aligned, the phase encoding gradient is applied to the magnetic field, the phase encoding gradient is removed, then the frequency encoding gradient is applied, and a marker is marked for each voxel, a process known as encoding or spatial localization. After applying radio frequency pulse to a certain layer, receiving MR signals of the layer.And decoding to obtain the MR signal size of each voxel in the slice, and displaying the volume signal size on the corresponding pixel of the fluorescent screen according to the corresponding relation with each voxel code in the slice. The specific magnetic resonance imaging scanning flow is shown in fig. 2. The signal size is represented by different gray scales, the signal is large, the pixel brightness is large, the signal is small, and the pixel brightness is small. And slicing different parts of the rock core to obtain MRI two-dimensional images of the rock core at different positions. According to the scanning precision of the instrument, the nuclear magnetic resonance MRI images of different positions of the core as shown in FIG. 4 are obtained by selecting proper positions and section numbers (for example, the section number is 6, FIG. 3) within the processing range of the instrument. The slice position coordinates and pixel volume data are saved in TXT text. The pixel point interval within a single two-dimensional picture and the interval between two-dimensional pictures depend on the resolution of the scanning device.
Acquiring nuclear magnetic resonance MRI/T of rock core2Three-dimensional tensor data volume
Typically, the actual reservoir rock pore throat length l varies from 50 to 300 microns, with an average pore throat length l of about 100 to 150 microns (Tang, Y.B., Li, M., Bernabe, Y.,&zhao, J.Z, (2020), Viscous sizing and presentation flow paths in heterologous moisture locations medium, journal of geographic Research: Solid Earth,125(3), e2019JB 019306). And (3) interpolating the nuclear magnetic resonance imaging data volume according to the approximate range of the core pore throat length, so that the data volume scale meets the requirement of the microscopic pore throat characteristics of the reaction rock. The interpolation algorithm can adopt algorithms such as trilinear interpolation, kriging interpolation and the like. The basic parameters of interpolation are determined according to the actual length of the core and the space position of a two-dimensional image slice, and MRI/T obtained after interpolation2The three-dimensional tensor data volume substantially satisfies the data scale for building a digitized pore network model of rock, as shown in fig. 4.
Construction of spatial disordered structure pore network model
And setting parameters such as the size of the model, coordination number, average pore throat length and the like according to the core dimension. Firstly, a rule cube network structure is constructed by adopting C + + language and a matrix calculation library Eigen to generate an X Y X Z three-dimensional rule cube network, and a network model is setThe total number of nodes is (X-1X (Y-1) X (Z-1), each node represents a pore, the nodes are connected by throats (uniform circular pipelines) (the two-dimensional section of the model is shown in figure 6), the rest parts are filled with solid particle substances, six throats are connected around each node representing the pore in the network built by the nodes, the length of each throat is set to be a constant L which is 150 mu m, the radius of each throat is set to be a unit 1, and the side lengths in the X, Y and Z directions of the model are respectively Lx＝(X-1)×l，Ly＝(Y-1)×l，Lz(Z-1) × l. And recording the coordinates of each node in the network model. All grid nodes in the model are fully connected through circular tubes (the coordination number z of any node is 6 at this time), and the ratio of the radius of the pore to the radius of the throat is set to be 1. Set up LyAnd LzAnd the distance from the central point in the yoz plane of each layer is more than 0.5LyAll of the points of (a) are removed, thereby setting the model as a plunger-like model that conforms to the shape of the true core. MRI/T using nuclear magnetic resonance2And the numerical value in the three-dimensional tensor data body is given to the node of the three-dimensional regular cube network, and the value of the connecting line between 2 nodes is the pore throat radius. The values of all pore throat radii in the network can be taken as the average of the values at two adjacent nodes. And then, randomly moving each node coordinate of the network in a spherical space, thereby generating a disordered network space structure. As shown in fig. 5, random removal of some of the links from the network results in a pore network model with different connectivity (coordination number) characteristics.
Core digital pore network model
MRI/T based on nuclear magnetic resonance can be obtained by the method2The core of (a) is a digitized pore network model, as shown in fig. 6. The MRI data volume of the core sample reflects the relative size of the pore space within the rock, and does not directly reflect the pore throat radius size of the rock. Therefore, the conversion coefficient between the actual pore throat radius of the rock and the MRI data volume can be obtained by adopting a trial-and-error method, and the pore throat radius value of the rock is estimated and used for constructing a pore network model: calculating the throat radius R by the conversion coefficient, assuming the initial value of the conversion coefficientiObtaining a core digital pore network model, and adopting a single-phase stable seepage pore network simulation algorithm meterCalculating the permeability of the constructed core digital pore network model, and checking whether the permeability obtained by simulation is consistent with the permeability measured by the core; if not, adjusting the conversion coefficient, and recalculating pore throat radius R of the pore networkiAnd re-establishing the core digital pore network model and calculating the permeability value of the core digital pore network model until the permeability of the pore network model is basically consistent with the permeability measured value of the real core, and obtaining the core digital pore network model corresponding to the actual core sample.
Permeability calculation methods for pore network models (bernbe, y., Li, m., Tang, y.b.,&Evans,B.(2016).Pore space connectivity and the transport properties ofrocks.Oil&gas Science and Technology-Revue d' IFP Energies novaleles, 71(4), 50.): according to kirchhoff's law, the sum of the flow rates of the inflow fluid and the outflow fluid in the node is zero. The fluid flow in the pore network satisfies the laplace equation:
g is the hydraulic conductivity and p is the pressure. Applying the Laplace equation to the pore network model to obtain the equation which satisfies the mass conservation law when the fluid in the pore network model is in steady state seepage: sigmajqij0. According to the relation, a linear equation set or a sparse matrix equation [ A ] can be constructed by traversing all nodes in the pore network][X]＝[B]. The invention solves the matrix equation by adopting conjugate gradient, thus obtaining the fluid pressure field of the fluid flowing in the network model, and then calculates the inflow and outflow flow of the fluid in the model and the permeability of the model by the pressure difference of the inlet end and the outlet end.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. The method for constructing the core digital pore network model based on the nuclear magnetic resonance data is characterized by comprising the following steps of:
the method comprises the following steps: measuring the pore throat length, porosity and permeability of the core after the core sample is selected and dried, and vacuumizing the core sample to simulate formation water or simulate formation crude oil;
step two: performing nuclear magnetic resonance MRI/T on core sample2Scanning and measuring to obtain two-dimensional images of the rock core on different sections;
step three: interpolating the two-dimensional image to obtain core MRI/T2A three-dimensional data volume;
step four: establishing a three-dimensional disordered pore network model, and carrying out MRI/T2Assigning the three-dimensional data volume to a node of the three-dimensional disordered pore network model;
step five: calculating the pore throat radius of each adjacent node in the three-dimensional disordered pore network model through the conversion coefficient alpha, and simulating and calculating the permeability of the core digital pore network model; and adjusting the size of the conversion coefficient alpha to ensure that the permeability of the pore network is similar to the actually measured permeability of the rock core, and establishing a digital rock core pore network model.
2. The method for constructing the core digitized pore network model based on the nuclear magnetic resonance data according to claim 1, wherein the second step specifically comprises: performing nuclear magnetic resonance scanning on the core sample after vacuum saturation simulation by using a nuclear magnetic resonance instrument, and generating T by using a SIRT inversion algorithm2Distributing; the method comprises the steps of slicing different parts of a rock core, selecting proper slice positions and section numbers within the processing range of a nuclear magnetic resonance instrument to carry out nuclear magnetic resonance imaging scanning on the rock core according to the scanning precision of the nuclear magnetic resonance instrument, obtaining nuclear magnetic resonance MRI two-dimensional images of the rock core at different slice positions of the rock core, and storing slice position coordinates and pixel data of the two-dimensional images in a TXT text of the two-dimensional images.
3. The method for constructing the core digitized pore network model based on the nuclear magnetic resonance data according to claim 1, wherein the nuclear magnetic resonance imaging scanning process specifically comprises: measuring by using a low-field nuclear magnetic resonance core analysis system with the magnetic field intensity of 0.5t, wherein the test parameters comprise dominant frequency, echo spacing, polarization time and echo number; in the process of scanning the core, a standard core with the length of 5cm and the diameter of 2.5cm is placed in a constant magnetic field, and gradient fields are applied in the x direction, the y direction and the z direction; when a sample is collected, initially, the resonance in the layer is consistent, a phase encoding gradient is applied to a magnetic field, the phase encoding gradient is removed, then a frequency encoding gradient is applied, and each voxel is marked with a mark; applying radio frequency pulse to a certain layer, and receiving MR signals of the layer; and decoding to obtain the MR signal of each voxel on the layer, and displaying the MR signal on the corresponding pixel of the fluorescent screen.
4. The method for constructing the digital pore network model of the core based on the nuclear magnetic resonance data as claimed in claim 1, wherein the third step specifically comprises: utilizing an interpolation algorithm to combine the TXT text of the two-dimensional image obtained in the step two and the pore throat length of the rock core in the step one to carry out interpolation processing on the nuclear magnetic resonance imaging data volume, namely the nuclear magnetic resonance MRI two-dimensional image of the rock core, so that the scale of the data volume meets the requirement of reflecting the microscopic pore throat characteristics of the rock, and obtaining the MRI/T related to the rock core2A three-dimensional tensor data volume.
5. The method for constructing the digitized pore network model of the core based on the nuclear magnetic resonance data as claimed in claim 1, wherein the fourth step specifically comprises the following substeps:
s401, setting the size of a model, the coordination number and the average pore throat length according to the core dimension;
s402, adopting a computer programming language and a matrix calculation library Eigen to construct a three-dimensional regular cube network structure to generate an X multiplied by Y multiplied by Z three-dimensional regular cube network;
s403, setting the total number of nodes of the cubic network to be (X-1 (Y-1) X (Z-1), wherein each node represents a pore, the nodes are connected through throats, and the rest parts are rock frameworks;
s404, six throats are connected around each node representing pore in the established cubic network model, and the throat length is the average rock pore throat length<l>(ii) a The side lengths in the x, y and z directions of the cubic network model are respectively Lx＝(X-1)<l>，Ly＝(Y-1)<l>，Lz＝(Z-1)<l>(ii) a All grid nodes in the cubic network model are fully connected through circular tubes, and the ratio of the radius of a pore to the radius of a throat is set to be 1; set up LyAnd LzThe diameter of the actual core is determined, and the distance from the central point in the yoz plane of each layer is greater than LyRemoving all the points to enable the cubic network model to become a plunger-shaped model consistent with the shape of the real rock core;
s405, magnetic resonance imaging/magnetic resonance tomography (MRI/T)2The numerical value in the three-dimensional tensor data body is given to each node of the three-dimensional regular cube network model, and the value of a connecting line between 2 nodes is the pore throat radius R; all pore throat radiuses R in the network are MRI/T on adjacent 2 nodes2An average of the values; randomly moving each node coordinate in the model in a spherical space to generate a disordered network space structure and generate random variation of the pore throat length; and randomly removing part of connection from the network structure to obtain pore network models with different connectivity characteristics.
6. The method for constructing the nuclear magnetic resonance data-based core digitized pore network model according to claim 1, wherein the fifth step specifically comprises assuming that the initial value of the conversion coefficient is α, and calculating the pore throat radius R according to the method of the fourth step and by the conversion coefficient αiObtaining a core digital pore network model, calculating the permeability of the constructed core digital pore network model by adopting a single-phase stable seepage pore network simulation algorithm, and checking whether the permeability obtained by simulation is consistent with the permeability measured by the core; if not, adjusting the conversion coefficient alpha, and recalculating the pore throat radius R of the pore networkiReestablishing the core digital pore networkAnd calculating the permeability value of the model until the permeability of the core digital pore network model is basically consistent with the permeability measurement value of the real core, and obtaining the core digital pore network model corresponding to the actual core sample.
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