A nuclear magnetic resonance logging characterization method and system for the dominant seepage layer based on pore structure

Abstract

The present invention provides a method and system for characterizing a dominant seepage layer segment based on pore structure using nuclear magnetic resonance logging. The method comprises the following steps: constructing a microscopic pore structure coefficient; calculating the microscopic pore structure coefficient using nuclear magnetic resonance logging; determining the macroscopic homogeneity coefficient; and calculating a dominant seepage layer segment evaluation index by combining the microscopic pore structure coefficient and the macroscopic homogeneity coefficient. The present invention utilizes the geometric mean value of the nuclear magnetic resonance T2 spectrum to characterize the microscopic pore structure characteristics, while considering the influence of the macroscopic homogeneity of the sand body on the seepage characteristics, and comprehensively establishes a method for characterizing the dominant seepage layer segment by combining the microscopic and macroscopic characteristic parameters of the sandstone reservoir. The technical solution of the present invention is effective and convenient, with high precision, low cost, and strong practicality. It solves the technical problem of poor practicality of existing methods for identifying dominant seepage layers, and provides technical guidance for the next step of reservoir water injection development adjustment and residual oil potential tapping.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas geological exploration, and in particular to a nuclear magnetic resonance logging characterization method and system for a dominant seepage layer segment based on pore structure. Background Art

[0002] Preferential seepage pathways refer to interconnected, highly permeable zones formed during long-term waterflooding in sandstone reservoirs. These zones manifest as vertically dominant flow intervals within a single well. The presence of these pathways can lead to ineffective circulation of injected water, resulting in reduced oilfield recovery, increased production costs, and decreased development efficiency. Therefore, effectively identifying these pathways, providing a basis for subsequent plugging and adjusting waterflooding relationships, is a key foundation for the sustained and effective development of the widespread high-water-cut reservoirs.

[0003] Existing methods for identifying dominant seepage intervals mainly include two aspects: the first is based on dynamic data, such as tracers, well-to-ground potential, interwell microseismicity, well testing, and production logging. These methods mainly rely on production conditions and various monitoring data to identify dominant seepage intervals, which are costly, generally have a small acquisition range, and generally have low applicability. The second is based on a combination of dynamic and static data, such as core experiments and reservoir engineering. These methods are generally based on multiple reservoir theories and algorithms, and are complex and time-consuming due to the numerous factors involved. They are difficult to promote and apply in practice. Given the problems existing in the above research, establishing a simple, highly accurate, low-cost method for identifying dominant seepage intervals in oil fields that can be widely applied is a technical problem that needs to be solved in the industry today. Summary of the Invention

[0004] To address the above issues, the present invention provides a method and system for characterizing the pore structure of the dominant permeable layer using nuclear magnetic resonance logging. To achieve the above objectives, the present invention adopts the following technical solutions:

[0005] A nuclear magnetic resonance logging characterization method for a dominant seepage layer segment based on pore structure comprises the following steps:

[0006] Construct microscopic pore structure coefficient;

[0007] Calculate microscopic pore structure coefficients using nuclear magnetic resonance logging;

[0008] Determine the macroscopic homogeneity coefficient;

[0009] The evaluation index of the dominant seepage layer section is calculated by combining the apparent pore structure coefficient and the macroscopic homogeneity coefficient.

[0010] Preferably, the calculation formula for constructing the microscopic pore structure coefficient ε is:

[0011]

[0012] Where: D M —mean pore throat radius, μm;

[0013] D—relative sorting coefficient;

[0014] P d —Displacement pressure, MPa.

[0015] Preferably, the calculation of the microscopic pore structure coefficient by nuclear magnetic resonance logging is specifically as follows: calculating the geometric mean of the nuclear magnetic resonance T2 spectrum, and calculating the microscopic pore structure coefficient based on the geometric mean.

[0016] Preferably, the macroscopic homogeneity coefficient is determined as follows:

[0017] Calculate reservoir permeability using nuclear magnetic resonance;

[0018] Calculate various permeability heterogeneity parameters;

[0019] The seepage homogeneity coefficient, ie the macroscopic homogeneity coefficient, is constructed based on various permeability heterogeneity parameters.

[0020] Preferably, the various permeability heterogeneity parameters include permeability variation coefficient, permeability surge coefficient and permeability difference;

[0021] The permeability variation coefficient V k The calculation formula is:

[0022] The permeability breakthrough coefficient T k The calculation formula is:

[0023] The permeability difference J k The calculation formula is:

[0024] Among them, K max —maximum permeability;

[0025] K min — minimum permeability;

[0026] K i —Permeability at point i;

[0027] —Average permeability of sand layer;

[0028] n—number of sampling points.

[0029] Preferably, the calculation formula for constructing the seepage homogeneity coefficient ρ is as follows:

[0030] Preferably, the calculation of the evaluation index of the dominant seepage layer segment is specifically as follows: determining the weight of the apparent pore structure coefficient as a, the weight of the macroscopic homogeneity coefficient as b, and calculating the evaluation index Sd of the dominant seepage layer segment, and the calculation formula is: Sd = a × ε + b × ρ, where a + b = 1.

[0031] A nuclear magnetic resonance logging characterization system for the dominant seepage layer based on pore structure, including

[0032] Building module for constructing microscopic pore structure coefficients;

[0033] Microscopic pore structure coefficient module, used for calculating microscopic pore structure coefficient by nuclear magnetic resonance logging;

[0034] Macro homogeneity coefficient module, used to determine the macro homogeneity coefficient;

[0035] The module for evaluating the dominant seepage layer segment index is used to calculate the dominant seepage layer segment evaluation index by combining the apparent pore structure coefficient and the macroscopic homogeneity coefficient.

[0036] Preferably, the building block is used to construct a calculation formula for the microscopic pore structure coefficient ε:

[0037]

[0038] Where: D M —mean pore throat radius, μm;

[0039] D—relative sorting coefficient;

[0040] P d —Displacement pressure, MPa.

[0041] Preferably, the microscopic pore structure coefficient module is used for calculating the microscopic pore structure coefficient by nuclear magnetic resonance logging by calculating the geometric mean of the nuclear magnetic resonance T2 spectrum and calculating the microscopic pore structure coefficient based on the geometric mean.

[0042] Preferably, the macroscopic homogeneity coefficient module is used to determine the macroscopic homogeneity coefficient specifically as follows:

[0043] Calculate reservoir permeability using nuclear magnetic resonance;

[0044] Calculate various permeability heterogeneity parameters;

[0045] The seepage homogeneity coefficient, ie the macroscopic homogeneity coefficient, is constructed based on various permeability heterogeneity parameters.

[0046] Preferably, the various permeability heterogeneity parameters include permeability variation coefficient, permeability surge coefficient and permeability difference;

[0047] The permeability variation coefficient V kThe calculation formula is:

[0048] The permeability breakthrough coefficient T k The calculation formula is:

[0049] The permeability difference J k The calculation formula is:

[0050] Among them, K max —maximum permeability;

[0051] K min — minimum permeability;

[0052] K i —Permeability at point i;

[0053] —Average permeability of sand layer;

[0054] n—number of sampling points.

[0055] Preferably, the calculation formula for constructing the seepage homogeneity coefficient ρ is as follows:

[0056] Preferably, the dominant seepage layer segment evaluation index module is used to calculate the dominant seepage layer segment evaluation index by combining the apparent pore structure coefficient and the macroscopic homogeneity coefficient. Specifically, the weight of the apparent pore structure coefficient is determined to be a, and the weight of the macroscopic homogeneity coefficient is determined to be b, and the dominant seepage layer segment evaluation index Sd is calculated using the following formula: Sd = a × ε + b × ρ, where a + b = 1.

[0057] The present invention has the following beneficial effects: It utilizes the geometric mean of the nuclear magnetic resonance T2 spectrum to characterize microscopic pore structure characteristics, while simultaneously considering the influence of sand body macroscopic homogeneity on seepage characteristics. This method integrates both microscopic and macroscopic characteristic parameters to establish a comprehensive characterization method for the dominant seepage interval in sandstone reservoirs. This effective and convenient technical solution offers high precision, low cost, and strong practicality. It addresses the technical difficulties of existing methods in identifying dominant seepage intervals, providing technical guidance for future adjustments to reservoir waterflooding development and tapping remaining oil potential.

[0058] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0060] Figure 1 A comparison diagram of the core nuclear magnetic resonance T2 spectrum distribution and the mercury injection pore throat radius distribution of the present invention is shown;

[0061] Figure 2 The figure shows the correlation between the geometric mean value of the core nuclear magnetic resonance T2 spectrum and the core pore structure parameters of the present invention;

[0062] Figure 3 The geometric mean value of the core nuclear magnetic resonance T2 spectrum of the present invention and (1-S wi ) / S wi Relationship diagram;

[0063] Figure 4 The figure shows the relationship between the pore structure coefficient ε and the geometric mean value of the core nuclear magnetic resonance T2 spectrum of the present invention;

[0064] Figure 5 The figure shows the distribution diagram of comprehensive evaluation index of the dominant seepage layer sections of 34 wells in the study area according to the embodiment of the present invention. DETAILED DESCRIPTION

[0065] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention. The raw material orlistat and its pharmaceutical excipients of the present invention are all commercially available.

[0066] Internal microscopic pore structure characteristics determine the macroscopic physical properties of sandstone reservoirs. The formation of a dominant pore zone ultimately results from changes in the reservoir's internal micropore structure under water injection conditions. Therefore, effective identification and evaluation of dominant pore zones requires a mechanistic analysis based on microstructure, primarily studying the reservoir's micropore structure. Numerous methods exist for studying reservoir micropore structure, including vapor adsorption, diffusion, mercury intrusion, centrifugation, thin-section microscopy, radiographic imaging, and hybrid methods. Currently, mercury intrusion and nuclear magnetic resonance (NMR) are the most commonly used methods, yielding the most parameters. Mercury intrusion is performed in the laboratory and can accurately determine the microscopic pore structure parameters for individual reservoir samples. Nuclear magnetic resonance logging (NMR) can provide high-precision, longitudinally continuous reservoir micropore structure information independent of the reservoir's pore structure, making it highly applicable to effectively identify and evaluate dominant pore zones based on pore structure using NMR logging data.

[0067] Therefore, the present invention proposes a nuclear magnetic resonance logging method for characterizing the dominant seepage layer segment based on pore structure, comprising the following steps:

[0068] (1) Construct the microscopic pore structure coefficient (ε):

[0069] Pore ​​structure characteristics refer to the geometric shape, size, distribution, and connectivity of the pores and throats in rocks. They are mainly divided into three categories: parameters that characterize pore throat size, such as the maximum pore throat radius, median pore throat radius, average pore throat radius, and mean pore throat radius; parameters that characterize pore throat sorting, such as sorting coefficient, relative sorting coefficient, skewness, and peak state; and parameters that characterize pore throat connectivity and control fluid movement, such as displacement pressure, median pressure, and mercury withdrawal efficiency. In order to analyze the impact of pore structure parameters on the seepage capacity of sandstone reservoirs, core data from three wells in the study area were analyzed, and the above 11 pore structure parameters were respectively related to reservoir permeability. Based on the correlation coefficient, the three parameters of mean pore throat radius, relative sorting coefficient, and displacement pressure were optimized to construct the pore structure coefficient (ε). The calculation formula is:

[0070]

[0071] Where: D M —mean pore throat radius, μm;

[0072] D—relative sorting coefficient;

[0073] P d —Displacement pressure, MPa.

[0074] (2) Calculation of microscopic pore structure coefficient (ε) by nuclear magnetic resonance logging:

[0075] Nuclear magnetic resonance (NMR) core measurements primarily measure the relaxation characteristics of hydrogen-containing fluids in rock pores. After placing the sample in a magnetic field, radio frequency pulses of a certain frequency are emitted, causing hydrogen protons to resonate and absorb the pulse energy. When the pulse ends, the protons release the absorbed energy. This energy release is detected by a dedicated coil, creating the NMR signal. Different samples release energy at different rates, and these signal differences can be used to directly reflect the changing characteristics of the rock's pore structure. Figure 1 This is a comparison of the core NMR T2 spectrum distribution of the coring well and the pore throat radius distribution curve obtained from the mercury injection test. As can be seen from the figure, the two are very similar or close in shape and amplitude, indicating a good correspondence between the two. Therefore, NMR T2 spectrum can also be used to study the microscopic pore structure of the reservoir. The microscopic pore structure coefficient calculated by NMR logging is specifically:

[0076] ① Calculate the geometric mean of the NMR T2 spectrum

[0077] T2 geometric mean (T 2g ) is one of the characterization parameters of the nuclear magnetic resonance T2 spectrum, reflecting the average characteristics of the reservoir nuclear magnetic distribution and containing microscopic pore structure information. The geometric mean value of T2 (T 2g ) and the various microscopic pore structure parameters obtained from core experiments were compared. The results are as follows Figure 2 The results showed that there was generally good correlation, indicating that the T2 geometric mean (T 2g ) can well reflect the microscopic pore structure of the reservoir.

[0078] Figure 3 The geometric mean of T2 and (1-S wi ) / S wi The following conclusions can be drawn from the figure: T2 geometric mean and (1-S wi ) / S wi There is a very good correlation between them; for existing laboratory NMR measuring instruments and NMR logging instruments, when the echo interval is less than or equal to 1.2ms, the diffusion effect on the T2 spectrum of saturated water samples is not obvious, the diffusion term in the T2 spectrum can be ignored, and the T2 spectrum morphology is mainly controlled by the pore distribution morphology of the sample. Figure 3 Can be used S wi The formula for calculating the geometric mean of T2 is:

[0079]

[0080] Where: T 2g —Geometric mean of NMR T2;

[0081] S wi —NMR capillary bound water saturation.

[0082] ②Calculate the microscopic pore structure coefficient (ε) based on the T2 geometric mean value

[0083] There is a good correlation between the pore structure coefficient calculated from the core data of the coring well and the T2 geometric mean value calculated from the nuclear magnetic resonance logging of the well. Based on this, a calculation formula for the microscopic pore structure coefficient based on the T2 geometric mean value is constructed (e.g. Figure 4 ):R=0.98(3).

[0084] (3) Determine the macroscopic homogeneity coefficient:

[0085] Due to the influence of sedimentation, diagenesis, and tectonic processes during their formation, oil and gas reservoirs exhibit uneven variations in their spatial distribution and properties. This variation is known as reservoir heterogeneity. Reservoir heterogeneity is a major factor influencing the movement of underground oil, gas, and water, as well as oil and gas recovery rates. Reservoir homogeneity is relative, while heterogeneity is absolute. In terms of oilfield development, within a development stratum, reservoir heterogeneity includes interlayer, intralayer, planar, and microscopic heterogeneity, which are the manifestations of reservoir heterogeneity in different aspects. For example, this example focuses on a single sand body and is based on well logging data. Therefore, the analysis focuses on intralayer heterogeneity. Intralayer heterogeneity refers to the vertical variation in reservoir properties within a single sand layer, including the degree of vertical permeability differences, the location of the most permeable layer, grain size rhythm, permeability rhythm, permeability heterogeneity, and the distribution of discontinuous thin mud interlayers within the layer. Intra-layer heterogeneity is a key geological factor that directly controls and affects the thickness of the injected agent in a single sand layer reservoir. Its characterization parameters include permeability variation coefficient, permeability breakthrough coefficient, and permeability gradient. Therefore, the parameters for evaluating the homogeneity of intra-layer permeability are: permeability variation coefficient (V k ), permeability breakthrough coefficient (T k ) and permeability difference (J k ) together to construct the seepage homogeneity coefficient as a macroscopic index for comprehensive evaluation of the dominant seepage layer. The macroscopic homogeneity coefficient is determined as follows:

[0086] ① Calculate various permeability heterogeneity parameters

[0087] Permeability variation coefficient (V k ), permeability breakthrough coefficient (T k ) and permeability difference (J k ) The calculation formulas are:

[0088]

[0089]

[0090]

[0091] Where: K max —maximum permeability;

[0092] K min — minimum permeability;

[0093] K i —Permeability at point i;

[0094] —Average permeability of sand layer;

[0095] n—number of sampling points.

[0096] ② Construct the seepage homogeneity coefficient (ρ) based on various permeability heterogeneity parameters

[0097] In order to comprehensively reflect the permeability heterogeneity of the sand body, the seepage homogeneity coefficient (ρ) is constructed based on the above three parameters. The calculation formula is as follows:

[0098]

[0099] ③NMR calculation of reservoir permeability

[0100] Well logging data is currently the only method that can obtain continuous permeability measurement results. In addition to accurately providing the total porosity, effective porosity, and movable fluid porosity of the reservoir, nuclear magnetic resonance logging can also describe the pore structure. This method avoids the influence of lithology, can more accurately provide reservoir physical property data, and perform high-precision permeability evaluation. It is currently the most effective well logging permeability evaluation method.

[0101] In 1991, George R. Coates proposed an explanatory model for calculating absolute permeability (i.e., the calculation formula for layer permeability) by comprehensively utilizing the free flow index, irreducible water volume, and porosity. The calculation formula is as follows:

[0102]

[0103] Where: FFI—free fluid volume, %;

[0104] BVI—bound fluid volume, %.

[0105] This model integrates the common influencing factors of porosity and pore size, and fully utilizes the advantages of nuclear magnetic resonance logging technology in accurately providing total porosity, movable fluid volume, and bound fluid volume; it uses the relationship between the ratio of the bound fluid pore volume and free fluid volume related to pore size and the rock specific surface area, and establishes an empirical formula for reservoir permeability through correlation analysis between nuclear magnetic resonance characteristics and permeability.

[0106] (4) Calculate the evaluation index of the dominant seepage layer section by combining the apparent pore structure coefficient and the macroscopic homogeneity coefficient:

[0107] By determining the two evaluation factors of microscopic pore structure parameters and macroscopic homogeneity coefficient, the weights of the two are set. For example, the weight of the microscopic pore structure coefficient is 0.75 and the weight of the macroscopic homogeneity coefficient is 0.25. The calculation formula of the evaluation index of the dominant seepage layer is comprehensively constructed:

[0108] Sd=0.75×ε+0.25×ρ (9)

[0109] Where: Sd—evaluation index of dominant seepage layer calculated by nuclear magnetic resonance logging;

[0110] ε—microstructure coefficient calculated by nuclear magnetic resonance logging;

[0111] ρ—is the macroscopic homogeneity coefficient of the sand body calculated by nuclear magnetic resonance logging permeability.

[0112] For example, the above method is used to calculate the comprehensive evaluation index of the dominant seepage layer section of the NmIV9-3 sand body of 34 wells in the study area since 2006:

[0113] (1) The continuous T2 geometric mean T is calculated by using formula (2) from the NMR logging data. 2g :

[0114]

[0115] (2) According to the T2 geometric mean T calculated in the previous step 2g , substitute into formula (3) to calculate the microscopic pore structure coefficient:

[0116]

[0117] (3) The continuous reservoir permeability curve is obtained by calculating the NMR logging data using formula (8):

[0118]

[0119] (4) Calculate the seepage homogeneity coefficient (ρ):

[0120] According to the permeability parameters processed by NMR logging data, the maximum permeability of each sand body (K max ), minimum value (K min ),average value and standard deviation (σ), respectively, are substituted into formulas (4) and (6) to obtain the parameters for evaluating the mean permeability of the sand body: the coefficient of variation of permeability within the layer (V k ), permeability surge coefficient within the layer (T k ) and intra-layer permeability difference (J k ):

[0121]

[0122]

[0123]

[0124] Substituting the above three parameters into the calculation formula of the seepage homogeneity coefficient (ρ) (Formula 7), the seepage homogeneity coefficient can be obtained:

[0125]

[0126] (5) Calculate the comprehensive evaluation index of the dominant seepage layer (Sd):

[0127] The calculation formula of the comprehensive evaluation index of the dominant seepage layer section (Formula 9) is used to solve the calculation:

[0128] Sd=0.75×ε+0.25×ρ

[0129] Substitute the pore structure coefficient (ε) calculated in step (2) and the seepage homogeneity coefficient (ρ) calculated in step (4) into the above formula to obtain the comprehensive evaluation index of the sand body's dominant seepage layer. Figure 5 As shown in the figure, the calculated results show that the distribution range of the high permeability index Sd in the early stage of scouring is 0-15; the distribution range of the high permeability index Sd in the middle stage of scouring is 15-20; and the high permeability index Sd in the late stage of scouring is ≥20. Overall, the high permeability index in the highly scouring sand bodies with high water content is significantly higher than that in sand bodies at other stages, indicating that this evaluation index is highly applicable to identifying the dominant seepage zone in the study area.

[0130] (6) Determine the comprehensive evaluation criteria for the dominant seepage layer:

[0131] By comparing wells representing different development periods and different water injection flushing degrees in the study area, the development status of the dominant seepage layer is divided into three categories, corresponding to different quantitative evaluation criteria:

[0132] In the early stage of scouring, the permeability index is 0<Sd≤15; in the middle stage of scouring, the permeability index is 15<Sd<20; and in the late stage of scouring, the permeability index is Sd≥20. Sd≥20 is determined as the evaluation standard for the dominant seepage layer of the target sand body in the study area.

[0133] Based on the above logging characterization method, a nuclear magnetic resonance logging characterization system for the dominant seepage layer based on pore structure is proposed, which includes:

[0134] Building module for constructing microscopic pore structure coefficients;

[0135] The micro-pore structure coefficient module is used to calculate the micro-pore structure coefficient by nuclear magnetic resonance logging. Specifically, the geometric mean of the nuclear magnetic resonance T2 spectrum is calculated, and the micro-pore structure coefficient is calculated based on the geometric mean.

[0136] The macroscopic homogeneity coefficient module is used to determine the macroscopic homogeneity coefficient, specifically: calculating the reservoir permeability by nuclear magnetic resonance; calculating various permeability heterogeneity parameters; and constructing the seepage homogeneity coefficient based on the various permeability heterogeneity parameters, namely the macroscopic homogeneity coefficient;

[0137] The module for evaluating the dominant seepage layer segment is used to calculate the evaluation index of the dominant seepage layer segment by combining the apparent pore structure coefficient and the macroscopic homogeneity coefficient. Specifically, the weight of the apparent pore structure coefficient is determined to be a, and the weight of the macroscopic homogeneity coefficient is determined to be b, and the evaluation index Sd of the dominant seepage layer segment is calculated using the following formula: Sd = a × ε + b × ρ, where a + b = 1.

[0138] In summary, this invention utilizes the geometric mean of the nuclear magnetic resonance T2 spectrum to characterize microscopic pore structure characteristics, while also considering the influence of sand body macroscopic homogeneity on seepage characteristics. This method integrates both microscopic and macroscopic characteristic parameters to develop a comprehensive characterization method for the dominant seepage interval in sandstone reservoirs. This technical solution is effective and convenient, offering high precision, low cost, and strong practicality. It addresses the technical challenges of existing methods for identifying dominant seepage intervals, providing technical guidance for future adjustments to reservoir waterflooding development and tapping remaining oil potential.

[0139] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A nuclear magnetic resonance logging method for characterizing the dominant seepage layer based on pore structure, characterized in that: The following steps are involved: Construct microscopic pore structure coefficient; The calculation formula for constructing the microscopic pore structure coefficient ε is: , where: D M —mean pore throat radius, μm; D—relative sorting coefficient; P d —Displacement pressure, MPa; Calculate the microscopic pore structure coefficient by using nuclear magnetic resonance logging; specifically, calculate the geometric mean of the nuclear magnetic resonance T2 spectrum and calculate the microscopic pore structure coefficient based on the geometric mean; Determine the macroscopic homogeneity coefficient; specifically, calculate the reservoir permeability by nuclear magnetic resonance; calculate various permeability heterogeneity parameters; construct the seepage homogeneity coefficient based on the various permeability heterogeneity parameters, that is, the macroscopic homogeneity coefficient; the calculation formula for the constructed seepage homogeneity coefficient ρ is as follows: , where V k represents the permeability variation coefficient, T k represents the permeability breakthrough coefficient, J k represents the permeability difference; The evaluation index of the dominant seepage layer section is calculated by combining the microscopic pore structure coefficient and the macroscopic homogeneity coefficient. Specifically, the weight of the microscopic pore structure coefficient is determined to be a, and the weight of the macroscopic homogeneity coefficient is determined to be b. The evaluation index Sd of the dominant seepage layer section is calculated using the following formula: Sd=a×ε+b×ρ, where a+b=1.

2. The method for characterizing the dominant seepage layer section based on pore structure by nuclear magnetic resonance logging according to claim 1, characterized in that: The various permeability heterogeneity parameters include permeability variation coefficient, permeability breakthrough coefficient and permeability difference; The permeability variation coefficient V k The calculation formula is: , The permeability breakthrough coefficient T k The calculation formula is: , The permeability difference J k The calculation formula is: , Among them, K max —maximum permeability; K min — minimum permeability; K i —Permeability at point i; —average permeability of sand layer; n—number of sampling points.

3. A nuclear magnetic resonance logging characterization system for the dominant seepage layer based on pore structure, characterized in that: include The construction module is used to construct the microscopic pore structure coefficient; the calculation formula for constructing the microscopic pore structure coefficient ε is: , where: D M —mean pore throat radius, μm; D—relative sorting coefficient; P d —Displacement pressure, MPa; The micro-pore structure coefficient module is used to calculate the micro-pore structure coefficient by nuclear magnetic resonance logging. Specifically, it calculates the geometric mean of the nuclear magnetic resonance T2 spectrum and calculates the micro-pore structure coefficient based on the geometric mean. The macroscopic homogeneity coefficient module is used to determine the macroscopic homogeneity coefficient. Specifically, the module calculates the reservoir permeability by nuclear magnetic resonance; calculates various permeability heterogeneity parameters; and constructs the seepage homogeneity coefficient based on the various permeability heterogeneity parameters, i.e., the macroscopic homogeneity coefficient. The calculation formula for constructing the seepage homogeneity coefficient ρ is as follows: , where V k represents the permeability variation coefficient, T k represents the permeability breakthrough coefficient, J k represents the permeability difference; The module for evaluating the dominant seepage layer segment index is used to calculate the dominant seepage layer segment evaluation index by combining the microscopic pore structure coefficient and the macroscopic homogeneity coefficient. Specifically, the weight of the microscopic pore structure coefficient is determined as a, and the weight of the macroscopic homogeneity coefficient is determined as b, and the dominant seepage layer segment evaluation index Sd is calculated using the following formula: Sd = a × ε + b × ρ, where a + b = 1.

4. The nuclear magnetic resonance logging characterization system for the dominant seepage layer based on pore structure according to claim 3 is characterized in that: The various permeability heterogeneity parameters include permeability variation coefficient, permeability breakthrough coefficient and permeability difference; The permeability variation coefficient V k The calculation formula is: , The permeability breakthrough coefficient T k The calculation formula is: , The permeability difference J k The calculation formula is: , Among them, K max —maximum permeability; K min — minimum permeability; K i —Permeability at point i; —average permeability of sand layer; n—number of sampling points.

Images