A method for evaluating original oil saturation logging based on pore structure classification

Abstract

The application provides a pore structure classification-based original oil saturation logging evaluation method and belongs to the technical field of oil and gas field development. On the basis of conventional logging data and in combination with core experiment analysis data, the reservoir pore structure is divided by using nuclear magnetic resonance, four logging parameter values of AC, CNL, DEN and GR are introduced by using a canonical discriminant function method, the pore structure type is further determined from a high-dimensional space, the non-homogeneity, continuity and separation degree of the logging parameters are described by using a partition function, a mass index, a multifractal spectrum, a singular strength and a multifractal dimension by adopting the concept of a multifractal, and a pore structure classification-based original oil saturation logging interpretation model is established. The method can accurately evaluate the reservoir physical property parameters and oil layer identification, has high oil saturation calculation precision, and has important significance for efficient use and economic development of the area.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development technology, and in particular to a method for evaluating the original oil saturation through logging based on pore structure classification. Background Technology

[0002] Tight sandstone and conglomerate reservoirs have poor physical properties and complex pore structures. Conventional logging responses to these reservoirs have poor resolution capabilities. Furthermore, due to their complex genesis, it is difficult to accurately evaluate the fluid properties and reservoir parameters of these oil and gas reservoirs. Conventional logging evaluation methods are not very suitable for evaluating this type of reservoir, and there are technical bottlenecks in the fine evaluation of oil and gas.

[0003] The main methods for evaluating the original oil saturation logging include: (1) rock physics methods, (2) J function method, and (3) conventional logging combined with nuclear magnetic resonance logging.

[0004] (1) Rock physics methods: The Archie formula, WS model, dual-water model, and argillaceous sandstone model are mainly used for saturation evaluation. Most calculation methods are still based on saturation evaluation techniques for argillaceous sandstone. Due to the complex pore structure and strong heterogeneity of sandstone and conglomerate reservoirs, it is difficult to evaluate the pore structure characteristics of rocks using conventional logging data such as natural gamma logging, shallow and deep resistivity logging, and sonic logging. The pore structure of the same formation varies greatly, making it difficult to evaluate its original oil saturation using conventional sandstone rock electrical models.

[0005] (2) J-function method: First, the capillary pressure curve under reservoir conditions is converted into a J-function. Then, multiple regression is used to obtain the relationship between the J-function and water saturation. Next, the oil column height is calculated from the oil-water interface and reservoir structural depth. Multiple regression is then used to establish the relationship between oil saturation and porosity, permeability, and oil column height, thus realizing the calculation of reservoir saturation. The J-function method is well applicable to low-resistivity oil layers with low amplitude tectonic origin. For strongly heterogeneous reservoirs, the shape of the reservoir J-function curve varies greatly, and the oil saturation fitted by the J-function differs significantly from the actual value.

[0006] (3) The development trend of logging technology for low-saturation reservoirs is mainly to use conventional logging combined with nuclear magnetic resonance and formation cable testing logging technologies to comprehensively identify oil and water layers. The application of electrical imaging technology and array induction logging technology can obtain more formation information of low-saturation reservoirs, increasing the means of accurate reservoir evaluation.

[0007] For reservoirs with strong vertical heterogeneity, containing interlayers and low-permeability layers, resulting in the mutual development of high- and low-saturation oil layers, and exhibiting obvious characteristics of low porosity, low permeability, and low oil saturation, the traditional Archie formula is not applicable due to the complex reservoir-rock-electric relationship, leading to inaccurate evaluation results. Summary of the Invention

[0008] To address the problems of existing technologies, this invention provides a method for evaluating the original oil saturation logging based on pore structure classification. Building upon conventional logging data and core experimental analysis, the method utilizes nuclear magnetic resonance (NMR) to classify the reservoir pore structure and introduces four logging parameters (AC, CNL, DEN, and GR) using the canonical discriminant function method. Starting from a high-dimensional space, the pore structure type is further determined. Employing the concept of multifractals, the method uses partition functions, quality indices, multifractal spectra, singular intensity, and multifractal dimension to characterize the heterogeneity, continuity, and separation of logging parameters. This establishes an original oil saturation logging interpretation model based on pore structure classification, which can accurately evaluate reservoir physical parameters and identify oil layers. This method offers high accuracy in calculating oil saturation, and is of significant importance for efficient utilization and economic development in this area.

[0009] This application provides a method for evaluating the original oil saturation through logging based on pore structure classification, comprising the following steps:

[0010] Using nuclear magnetic resonance logging data, reservoir pore structure types are classified;

[0011] Based on the results of reservoir pore structure type classification using nuclear magnetic resonance logging data, the pore structure type is determined by using conventional logging curves and the canonical discriminant function method.

[0012] Based on the classified pore structure types, a porosity calculation model is established;

[0013] The original oil saturation of the cored data is restored, and the calculation formulas for the original oil saturation and original water saturation of the cored data are obtained.

[0014] Correction of resistivity of planar formations;

[0015] Based on the calculation formulas for the original oil saturation and the original water saturation, as well as the corrected formation plane resistivity, a calculation model for the original oil saturation of different types of pore structures is established.

[0016] The original oil saturation was calculated based on the original oil saturation calculation model for different types of pore structures, and then evaluated.

[0017] Preferably, using nuclear magnetic resonance logging data, based on the T2 spectrum morphology of nuclear magnetic resonance logging, the three-pore method is used to classify the reservoir pore structure type, and the pore structure is divided into three categories: Category I, Category II, and Category III.

[0018] Preferably, based on the pore structure type results classified by nuclear magnetic resonance logging data, logging parameters are introduced using the canonical discriminant function method with conventional logging curves. Starting from high-dimensional space, the pore structure type is determined. High-dimensional space refers to at least two-dimensional space.

[0019] Preferably, the logging parameters introduced by the canonical discriminant function method include four logging parameter values: sonic transit time curve AC, neutron curve CNL, density curve DEN, and natural gamma ray GR.

[0020] Preferably, the discrimination dimension 1 is calculated using the following formula:

[0021] F1=0.380*AC+0.201*CNL+37.846*DEN-0.052*GR-120.1;

[0022] Preferably, the discrimination dimension 2 is calculated using the following formula:

[0023] F2=0.356*AC+0.285*CNL+43.743*DEN-0.04*GR-132.0;

[0024] Preferably, the constructed classification function is as follows:

[0025] Class 1: F1 = 93.18*AC - 13.183*CNL + 10267*DEN - 0.477*GR - 15871.6;

[0026] Category II: F1 = 92.63*AC - 12.494*CNL + 10194*DEN - 0.586*GR - 15657.2;

[0027] Category 3: F1 = 94.29*AC - 12.452*CNL + 10375*DEN - 0.658*GR - 16218.2;

[0028] Preferably, when using conventional logging curves to identify different types of pore structures, the concept of multifractals is introduced, and the heterogeneity, continuity, and separation of logging parameters are characterized by using partition functions, quality indices, multifractal spectra, singularity intensities, and multifractal dimensions.

[0029] Preferably, the well logging parameter value partition function is characterized as follows:

[0030]

[0031] Preferably, the quality index of well logging parameter values ​​is characterized as follows:

[0032]

[0033] Preferably, the multifractal spectrum of the logging parameter values ​​is:

[0034] f(α)=αq-τ(q)

[0035] Preferably, the singularity intensity of the logging parameter values ​​is:

[0036]

[0037] Preferably, the multifractal dimension of the logging parameter values ​​is:

[0038]

[0039] Preferably, the heterogeneity of the logging parameters is characterized by the following formula:

[0040] Δα=α -10 -α 10

[0041] Preferably, the continuity of logging parameters is characterized by the following formula:

[0042] H = (D² + 1) / 2

[0043] Preferably, the separation degree of the logging parameters is characterized by the following formula:

[0044] R d =(α0-α) 10 )-(α -10 -α0)

[0045] Preferably, the original oil saturation of the cored data is restored to obtain the calculation formulas for the original oil saturation and original water saturation of the cored data. Specifically, the oil-water residual rate is obtained by cross-referencing the oil and water saturation, and the calculation formulas for the original oil saturation and original water saturation are obtained.

[0046] Preferably, the correction of planar formation resistivity specifically involves: correcting the planar formation water resistivity, characterizing the planar distribution characteristics of formation water salinity in the well area, and determining the formation water resistivity distribution characteristics of the corrected plane using intersection plots.

[0047] Preferably, based on the calculation formulas for the original oil saturation and the original water saturation, and the corrected formation plane resistivity, the calculation model for the original oil saturation of different types of pore structures is established as follows: using a tight sandstone and conglomerate conductivity model based on ineffective conductive pores, the fitting relationship between the reservoir oil content index and the original oil saturation of the formation for different types of pore structures is established respectively, so as to obtain the saturation calculation model corresponding to different types of pore structures.

[0048] Preferably, the original oil saturation calculation models for different types of pore structures include:

[0049] A saturation calculation model for a type of porous reservoir:

[0050] Model for calculating saturation of reservoirs with type II porosity:

[0051] Three types of porous structure reservoir saturation calculation models:

[0052] in,

[0053] S w Water saturation;

[0054] R w : Formation water resistivity;

[0055] R t Formation resistivity;

[0056] Φ: Formation porosity.

[0057] Compared with the prior art, the present invention has at least the following beneficial effects:

[0058] (1) This invention utilizes nuclear magnetic resonance logging data and, based on the T2 spectrum morphology of nuclear magnetic resonance logging, classifies reservoirs into three types of pore structures. By using conventional logging response characteristics, the pore structure type is determined with a resolution of 82.3%, which is highly consistent with the nuclear magnetic resonance spectrum morphology. This solves the technical problem that it is difficult to effectively classify reservoir pore structure types using conventional logging data.

[0059] (2) This invention adopts the original oil saturation logging interpretation model based on pore structure classification, which takes into account the influence of pore structure differences in the logging interpretation of low saturation reservoirs. The saturation calculation accuracy is high, which realizes the fine evaluation of complex sandstone and conglomerate reservoirs and achieves the purpose of accurately evaluating the fluid properties and reservoir parameters of the reservoir. It has strong applicability and broad application prospects. Attached Figure Description

[0060] Figure 1 This is a flowchart of a well logging evaluation method for original oil saturation based on pore structure classification according to an embodiment of the present invention;

[0061] Figure 2 This is a flowchart of a well logging evaluation method for original oil saturation based on pore structure classification, which is another embodiment of the present invention. Detailed Implementation

[0062] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0063] This application provides a method for evaluating the original oil saturation through logging based on pore structure classification, comprising the following steps:

[0064] Using nuclear magnetic resonance logging data, reservoir pore structure types are classified;

[0065] Based on the results of reservoir pore structure type classification using nuclear magnetic resonance logging data, the pore structure type is determined by using conventional logging curves and the canonical discriminant function method.

[0066] Based on the classified pore structure types, a porosity calculation model is established;

[0067] The original oil saturation of the cored data is restored, and the calculation formulas for the original oil saturation and original water saturation of the cored data are obtained.

[0068] Correction of resistivity of planar formations;

[0069] Based on the calculation formulas for the original oil saturation and the original water saturation, as well as the corrected formation plane resistivity, a calculation model for the original oil saturation of different types of pore structures is established.

[0070] The original oil saturation was calculated based on the original oil saturation calculation model for different types of pore structures, and then evaluated.

[0071] According to a specific embodiment of the present invention, using nuclear magnetic resonance logging data, based on the T2 spectrum morphology of nuclear magnetic resonance logging, the three-pore method is used to classify the reservoir pore structure type, and the pore structure is divided into three categories: Category I, Category II and Category III.

[0072] According to a specific embodiment of the present invention, based on the pore structure type results classified by nuclear magnetic resonance logging data, logging parameters are introduced using the canonical discriminant function method with conventional logging curves. Starting from a high-dimensional space, the pore structure type is determined. The high-dimensional space refers to at least a two-dimensional space.

[0073] According to a specific embodiment of the present invention, the logging parameters introduced by the canonical discriminant function method include four logging parameter values: sonic transit time curve AC, neutron curve CNL, density curve DEN, and natural gamma ray GR.

[0074] According to a specific embodiment of the present invention, the discrimination dimension 1 is calculated using the following formula:

[0075] F1=0.380*AC+0.201*CNL+37.846*DEN-0.052*GR-120.1;

[0076] According to a specific embodiment of the present invention, the discrimination dimension 2 is calculated using the following formula:

[0077] F2=0.356*AC+0.285*CNL+43.743*DEN-0.04*GR-132.0;

[0078] According to a specific embodiment of the present invention, when identifying different types of pore structures using conventional logging curves, the concept of multifractals is introduced, and the heterogeneity, continuity, and separation of logging parameters are characterized by using the partition function, quality index, multifractal spectrum, singular intensity, and multifractal dimension.

[0079] According to a specific embodiment of the present invention, the well logging parameter value partition function is characterized as follows:

[0080]

[0081] According to a specific embodiment of the present invention, the quality index of well logging parameter values ​​is characterized as follows:

[0082]

[0083] According to a specific embodiment of the present invention, the multifractal spectrum of well logging parameter values ​​is as follows:

[0084] f(α)=αq-τ(q)

[0085] According to a specific embodiment of the present invention, the singularity intensity of the logging parameter value is:

[0086]

[0087] According to a specific embodiment of the present invention, the multifractal dimension of the logging parameter value is:

[0088]

[0089] According to a specific embodiment of the present invention, the heterogeneity of logging parameters is characterized by the following formula:

[0090] Δα=α -10 -α 10

[0091] According to a specific embodiment of the present invention, the continuity of logging parameters is characterized by the following formula:

[0092] H = (D² + 1) / 2

[0093] According to a specific embodiment of the present invention, the separation degree of logging parameters is characterized by the following formula:

[0094] R d =(α0-α) 10 )-(α -10 -α0)

[0095] According to a specific embodiment of the present invention, the original oil saturation of the cored data is restored, and the calculation formulas for the original oil saturation and original water saturation of the cored data are obtained. Specifically, the oil-water residual rate is obtained by cross-referencing the oil and water saturation, and the calculation formulas for the original oil saturation and original water saturation are obtained.

[0096] According to a specific embodiment of the present invention, the correction of planar formation resistivity specifically involves: correcting the planar formation water resistivity, characterizing the planar distribution characteristics of formation water salinity in the well area, and determining the formation water resistivity distribution characteristics of the correction plane through intersection plots.

[0097] According to a specific embodiment of the present invention, based on the calculation formulas for the original oil saturation and the original water saturation, and the corrected formation plane resistivity, the original oil saturation calculation model for different types of pore structures is established as follows: using a tight sandstone and conglomerate conductivity model based on ineffective conductive pores, the fitting relationship between the reservoir oil content index and the original oil saturation of the formation for different types of pore structures is established respectively, thereby obtaining the saturation calculation model corresponding to different types of pore structures.

[0098] According to a specific embodiment of the present invention, the original oil saturation calculation model for different types of pore structures includes:

[0099] A saturation calculation model for a type of porous reservoir:

[0100] Model for calculating saturation of reservoirs with type II porosity:

[0101] Three types of porous structure reservoir saturation calculation models:

[0102] in,

[0103] S w Water saturation;

[0104] R w : Formation water resistivity;

[0105] R t Formation resistivity;

[0106] Φ: Formation porosity;

[0107] According to a specific embodiment of the present invention, the classification function is constructed as follows:

[0108] Class 1: F1 = 93.18*AC - 13.183*CNL + 10267*DEN - 0.477*GR - 15871.6;

[0109] Category II: F1 = 92.63*AC - 12.494*CNL + 10194*DEN - 0.586*GR - 15657.2;

[0110] Category 3: F1 = 94.29*AC - 12.452*CNL + 10375*DEN - 0.658*GR - 16218.2;

[0111] Example 1

[0112] According to a specific embodiment of the present invention, the original oil saturation logging evaluation method based on pore structure classification of the present invention will be described in detail below.

[0113] This application provides a method for evaluating the original oil saturation through logging based on pore structure classification, comprising the following steps:

[0114] Using nuclear magnetic resonance logging data, reservoir pore structure types are classified;

[0115] Based on the results of reservoir pore structure type classification using nuclear magnetic resonance logging data, the pore structure type is determined by using conventional logging curves and the canonical discriminant function method.

[0116] Based on the classified pore structure types, a porosity calculation model is established;

[0117] The original oil saturation of the cored data is restored, and the calculation formulas for the original oil saturation and original water saturation of the cored data are obtained.

[0118] Correction of resistivity of planar formations;

[0119] Based on the calculation formulas for the original oil saturation and the original water saturation, as well as the corrected formation plane resistivity, a calculation model for the original oil saturation of different types of pore structures is established.

[0120] The original oil saturation was calculated based on the original oil saturation calculation model for different types of pore structures, and then evaluated.

[0121] Example 2

[0122] According to a specific embodiment of the present invention, the original oil saturation logging evaluation method based on pore structure classification of the present invention will be described in detail below.

[0123] This application provides a method for evaluating the original oil saturation through logging based on pore structure classification, comprising the following steps:

[0124] Using nuclear magnetic resonance logging data, reservoir pore structure types are classified. Specifically, based on the T2 spectrum morphology of nuclear magnetic resonance logging data, the three-pore method is used to classify reservoir pore structure types, which are divided into three categories: Category I, Category II, and Category III.

[0125] Based on the results of reservoir pore structure type classification using nuclear magnetic resonance logging data, the pore structure type is determined by using conventional logging curves and the canonical discriminant function method.

[0126] Based on the classified pore structure types, a porosity calculation model is established;

[0127] The original oil saturation of the cored data is restored, and the calculation formulas for the original oil saturation and original water saturation of the cored data are obtained. Specifically, the oil and water residual rates are obtained by cross-plotting the oil and water saturation, and the calculation formulas for the original oil saturation and original water saturation are obtained.

[0128] The planar formation resistivity is corrected by: correcting the planar formation water resistivity, characterizing the planar distribution characteristics of formation water salinity in the well area, and determining the formation water resistivity distribution characteristics of the corrected plane through intersection plots.

[0129] Based on the calculation formulas for the original oil saturation and the original water saturation, as well as the corrected formation plane resistivity, a calculation model for the original oil saturation of different types of pore structures is established.

[0130] The original oil saturation was calculated based on the original oil saturation calculation model for different types of pore structures, and then evaluated.

[0131] Example 3

[0132] According to a specific embodiment of the present invention, the original oil saturation logging evaluation method based on pore structure classification of the present invention will be described in detail below.

[0133] This application provides a method for evaluating the original oil saturation through logging based on pore structure classification, comprising the following steps:

[0134] Using nuclear magnetic resonance logging data, reservoir pore structure types are classified. Specifically, based on the T2 spectrum morphology of nuclear magnetic resonance logging data, the three-pore method is used to classify reservoir pore structure types, which are divided into three categories: Category I, Category II, and Category III.

[0135] Based on the results of reservoir pore structure classification from nuclear magnetic resonance logging data, the pore structure type is determined using the canonical discriminant function method with conventional logging curves. Specifically, based on the pore structure type classification from nuclear magnetic resonance logging data, logging parameters are introduced using the canonical discriminant function method with conventional logging curves. Starting from high-dimensional space, the pore structure type is determined. High-dimensional space refers to at least two-dimensional space.

[0136] Based on the classified pore structure types, a porosity calculation model is established;

[0137] The original oil saturation of the cored data is restored, and the calculation formulas for the original oil saturation and original water saturation of the cored data are obtained. Specifically, the oil and water residual rates are obtained by cross-plotting the oil and water saturation, and the calculation formulas for the original oil saturation and original water saturation are obtained.

[0138] The planar formation resistivity is corrected by: correcting the planar formation water resistivity, characterizing the planar distribution characteristics of formation water salinity in the well area, and determining the formation water resistivity distribution characteristics of the corrected plane through intersection plots.

[0139] Based on the calculation formulas for the original oil saturation and the original water saturation, as well as the corrected formation plane resistivity, a calculation model for the original oil saturation of different types of pore structures is established.

[0140] The original oil saturation was calculated based on the original oil saturation calculation model for different types of pore structures, and then evaluated.

[0141] Among them, the logging parameters introduced by the canonical discriminant function method include four logging parameter values: sonic transit time curve AC, neutron curve CNL, density curve DEN, and natural gamma ray GR.

[0142] Example 4

[0143] According to a specific embodiment of the present invention, the original oil saturation logging evaluation method based on pore structure classification of the present invention will be described in detail below.

[0144] This application provides a method for evaluating the original oil saturation through logging based on pore structure classification, comprising the following steps:

[0145] Using nuclear magnetic resonance logging data, reservoir pore structure types are classified. Specifically, based on the T2 spectrum morphology of nuclear magnetic resonance logging data, the three-pore method is used to classify reservoir pore structure types, which are divided into three categories: Category I, Category II, and Category III.

[0146] Based on the results of reservoir pore structure classification from nuclear magnetic resonance logging data, the pore structure type is determined using the canonical discriminant function method with conventional logging curves. Specifically, based on the pore structure type classification from nuclear magnetic resonance logging data, logging parameters are introduced using the canonical discriminant function method with conventional logging curves. Starting from high-dimensional space, the pore structure type is determined. High-dimensional space refers to at least two-dimensional space.

[0147] Based on the classified pore structure types, a porosity calculation model is established;

[0148] The original oil saturation of the cored data is restored, and the calculation formulas for the original oil saturation and original water saturation of the cored data are obtained. Specifically, the oil and water residual rates are obtained by cross-plotting the oil and water saturation, and the calculation formulas for the original oil saturation and original water saturation are obtained.

[0149] The planar formation resistivity is corrected by: correcting the planar formation water resistivity, characterizing the planar distribution characteristics of formation water salinity in the well area, and determining the formation water resistivity distribution characteristics of the corrected plane through intersection plots.

[0150] Based on the calculation formulas for the original oil saturation and the original water saturation, as well as the corrected formation plane resistivity, a calculation model for the original oil saturation of different types of pore structures is established.

[0151] The original oil saturation was calculated based on the original oil saturation calculation model for different types of pore structures, and then evaluated.

[0152] Among them, the logging parameters introduced by the canonical discriminant function method include four logging parameter values: sonic transit time curve AC, neutron curve CNL, density curve DEN, and natural gamma ray GR.

[0153] Among them, when using conventional logging curves to identify different types of pore structures, the concept of multifractals is introduced, and the heterogeneity, continuity and separation of logging parameters are characterized by using partition function, quality index, multifractal spectrum, singularity intensity and multifractal dimension.

[0154] Specifically, based on the calculation formulas for the original oil saturation and original water saturation, and the corrected formation plane resistivity, the calculation models for the original oil saturation of different types of pore structures are established as follows: A tight sandstone-conglomerate conductivity model based on ineffective conductive pores is adopted to establish the fitting relationship between the reservoir oil-bearing index and the original oil saturation of different types of pore structures, thereby obtaining the saturation calculation models corresponding to different types of pore structures. These saturation calculation models include:

[0155] A saturation calculation model for a type of porous reservoir:

[0156] Model for calculating saturation of reservoirs with type II porosity:

[0157] Three types of porous structure reservoir saturation calculation models:

[0158] in,

[0159] S w Water saturation;

[0160] R w : Formation water resistivity;

[0161] R t Formation resistivity;

[0162] Φ: Formation porosity.

[0163] Example 5

[0164] According to a specific embodiment of the present invention, the original oil saturation logging evaluation method based on pore structure classification of the present invention will be described in detail below.

[0165] This application provides a method for evaluating the original oil saturation through logging based on pore structure classification, comprising the following steps:

[0166] Using nuclear magnetic resonance logging data, reservoir pore structure types are classified. Specifically, based on the T2 spectrum morphology of nuclear magnetic resonance logging data, the three-pore method is used to classify reservoir pore structure types, which are divided into three categories: Category I, Category II, and Category III.

[0167] Based on the results of reservoir pore structure classification from nuclear magnetic resonance logging data, the pore structure type is determined using the canonical discriminant function method with conventional logging curves. Specifically, based on the pore structure type classification from nuclear magnetic resonance logging data, logging parameters are introduced using the canonical discriminant function method with conventional logging curves. Starting from high-dimensional space, the pore structure type is determined. High-dimensional space refers to at least two-dimensional space.

[0168] Based on the classified pore structure types, a porosity calculation model is established;

[0169] The original oil saturation of the cored data is restored, and the calculation formulas for the original oil saturation and original water saturation of the cored data are obtained. Specifically, the oil and water residual rates are obtained by cross-plotting the oil and water saturation, and the calculation formulas for the original oil saturation and original water saturation are obtained.

[0170] The planar formation resistivity is corrected by: correcting the planar formation water resistivity, characterizing the planar distribution characteristics of formation water salinity in the well area, and determining the formation water resistivity distribution characteristics of the corrected plane through intersection plots.

[0171] Based on the calculation formulas for the original oil saturation and the original water saturation, as well as the corrected formation plane resistivity, a calculation model for the original oil saturation of different types of pore structures is established.

[0172] The original oil saturation was calculated based on the original oil saturation calculation model for different types of pore structures, and then evaluated.

[0173] Among them, the logging parameters introduced by the canonical discriminant function method include four logging parameter values: sonic transit time curve AC, neutron curve CNL, density curve DEN, and natural gamma ray GR.

[0174] Specifically, based on the calculation formulas for the original oil saturation and original water saturation, and the corrected formation plane resistivity, the calculation models for the original oil saturation of different types of pore structures are established as follows: A tight sandstone-conglomerate conductivity model based on ineffective conductive pores is adopted to establish the fitting relationship between the reservoir oil-bearing index and the original oil saturation of different types of pore structures, thereby obtaining the saturation calculation models corresponding to different types of pore structures. These saturation calculation models include:

[0175] A saturation calculation model for a type of porous reservoir:

[0176] Model for calculating saturation of reservoirs with type II porosity:

[0177] Three types of porous structure reservoir saturation calculation models:

[0178] in,

[0179] S w Water saturation;

[0180] R w : Formation water resistivity;

[0181] R t Formation resistivity;

[0182] Φ: Formation porosity.

[0183] Among them, when using conventional logging curves to identify different types of pore structures, the concept of multifractals is introduced, and the heterogeneity, continuity and separation of logging parameters are characterized by using partition function, quality index, multifractal spectrum, singularity intensity and multifractal dimension.

[0184] The well logging parameter value partition function is characterized as follows:

[0185]

[0186] The quality index of well logging parameter values ​​is characterized as follows:

[0187]

[0188] The multifractal spectrum of the logging parameter values ​​is as follows:

[0189] f(α)=αq-τ(q)

[0190] The singularity intensity of the logging parameter values ​​is as follows:

[0191]

[0192] The multifractal dimension of the logging parameter values ​​is:

[0193]

[0194] The heterogeneity of the logging parameters is characterized by the following formula:

[0195] Δα=α -10 -α 10

[0196] The continuity of the logging parameters is characterized by the following formula:

[0197] H = (D² + 1) / 2

[0198] The separation degree of the logging parameters is characterized by the following formula:

[0199] R d =(α0-α) 10 )-(α -10 -α0).

[0200] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A method for evaluating the original oil saturation logging based on pore structure classification, characterized in that, Includes the following steps: Using nuclear magnetic resonance logging data, reservoir pore structure types are classified; Based on the results of reservoir pore structure type classification using nuclear magnetic resonance logging data, the pore structure type is determined by using conventional logging curves and the canonical discriminant function method. Based on the classified pore structure types, a porosity calculation model is established; The original oil saturation of the cored data is restored, and the calculation formulas for the original oil saturation and original water saturation of the cored data are obtained. Correction of resistivity of planar formations; Based on the calculation formulas for the original oil saturation and the original water saturation, as well as the corrected formation plane resistivity, a calculation model for the original oil saturation of different types of pore structures is established. The original oil saturation was calculated based on the original oil saturation calculation model for different types of pore structures, and then evaluated.

2. The method for evaluating the original oil saturation logging based on pore structure classification according to claim 1, characterized in that, Using nuclear magnetic resonance logging data and based on the T2 spectrum morphology of nuclear magnetic resonance logging, the three-pore method was used to classify the reservoir pore structure type, which was divided into three categories: Category I, Category II, and Category III.

3. The method for evaluating the original oil saturation logging based on pore structure classification according to claim 2, characterized in that, Based on the pore structure types identified by nuclear magnetic resonance logging data, logging parameters are introduced using the canonical discriminant function method with conventional logging curves. Starting from a high-dimensional space, the pore structure type is determined. A high-dimensional space refers to at least a two-dimensional space.

4. The method for evaluating the original oil saturation logging based on pore structure classification according to claim 3, characterized in that, The logging parameters introduced by the canonical discriminant function method include four logging parameter values: sonic transit time curve AC, neutron curve CNL, density curve DEN, and natural gamma ray GR.

5. The method for evaluating the original oil saturation logging based on pore structure classification according to claim 3, characterized in that, When using conventional logging curves to identify different types of pore structures, the concept of multifractals is introduced. The partition function, quality index, multifractal spectrum, singular intensity, and multifractal dimension are used to characterize the heterogeneity, continuity, and separation of logging parameters.

6. The method for evaluating the original oil saturation logging based on pore structure classification according to claim 1, characterized in that, The original oil saturation of the cored data is restored, and the calculation formulas for the original oil saturation and original water saturation of the cored data are obtained. Specifically, the oil-water residual rate is obtained by cross-plotting the oil and water saturation, and the calculation formulas for the original oil saturation and original water saturation are obtained.

7. The method for evaluating the original oil saturation logging based on pore structure classification according to claim 1, characterized in that, The specific steps for correcting the resistivity of the formation in the plane are as follows: correct the resistivity of the formation water in the plane, characterize the plane distribution characteristics of the formation water salinity in the well area, and determine the distribution characteristics of the formation water resistivity in the corrected plane through intersection plots.

8. The method for evaluating the original oil saturation logging based on pore structure classification according to any one of claims 1-7, characterized in that, Based on the calculation formulas for the original oil saturation and the original water saturation, and the corrected formation plane resistivity, the calculation models for the original oil saturation of different types of pore structures are established as follows: using the conductivity model of tight sandstone and conglomerate based on ineffective conductive pores, the fitting relationship between the reservoir oil-bearing index and the original oil saturation of the formation is established for different types of pore structures, and the saturation calculation models corresponding to different types of pore structures are obtained.

9. The method for evaluating the original oil saturation logging based on pore structure classification according to claim 8, characterized in that, The original oil saturation calculation models for different types of pore structures include: A saturation calculation model for a type of porous reservoir: Model for calculating saturation of reservoirs with type II porosity: Three types of porous structure reservoir saturation calculation models: in, S w Water saturation; R w : Formation water resistivity; R t Formation resistivity; Φ: Formation porosity.

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