Ultralow-resistance hydrocarbon reservoir identification method, device and equipment based on irreducible water saturation calculation and medium

Abstract

The invention discloses an ultra-low-resistance hydrocarbon reservoir recognition method, device and equipment based on irreducible water saturation calculation and a medium, and relates to the field of geophysical logging, and the method comprises the steps: carrying out the standardization operation of logging information of a to-be-recognized stratum, so as to obtain target logging information, performing a core experiment on a first target stratum in the to-be-identified stratum to obtain core data, and performing core depth homing based on target logging data to obtain target core data; constructing a first function based on a natural potential corresponding to a first target stratum in the target logging information; determining a first empirical coefficient and a second empirical coefficient according to the first function and irreducible water saturation corresponding to a first target stratum in the target core data, and constructing a second function by using the first empirical coefficient and the second empirical coefficient; and aiming at a second target stratum which is not subjected to a core experiment in the stratum to be identified, identifying the ultra-low resistivity hydrocarbon reservoir in the second target stratum based on the porosity, the deep induced resistivity and the irreducible water saturation determined by the second function.

Description

Technical Field

[0001] The present application relates to the field of geophysical logging, and in particular to a method, device, equipment and medium for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation. Background Art

[0002] Low-resistivity oil and gas layers are widely developed in high-porosity and permeability clastic rocks in major oil and gas basins in my country. Since the resistivity of such oil and gas layers shows low or even ultra-low resistivity characteristics, the ratio of the resistivity of the oil and gas layer to the adjacent water layer is defined as the resistivity increase coefficient. Generally, oil and gas layers with a resistivity increase coefficient less than 2 are defined as low-resistivity oil and gas layers, and those with a resistivity increase coefficient less than 1.5 are specifically defined as ultra-low-resistivity oil and gas layers. Existing data show that high formation water mineralization and high bound water saturation are the main reasons for the ultra-low resistivity of oil and gas layers. Under the dual background of high formation water mineralization and high bound water saturation, oil and gas layers show ultra-low resistivity, concave shape, and high invasion characteristics. The identification methods commonly used in existing technologies to identify ultra-low-resistivity oil and gas layers based on "resistivity size, shape, and invasion characteristics" have obvious limitations and are prone to misjudgment of oil and gas layers. Therefore, how to accurately identify ultra-low-resistivity oil and gas layers is a technical problem that needs to be solved urgently. Summary of the invention

[0003] In view of this, the purpose of this application is to provide a method, device, equipment and medium for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation, which can accurately identify ultra-low resistivity oil and gas layers. The specific scheme is as follows:

[0004] In a first aspect, the present application provides a method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation, comprising:

[0005] Performing a standardization operation on the well logging data of the formation to be identified that has been acquired in advance to obtain target well logging data, performing a core experiment on a first target formation in the formation to be identified to obtain core data, and performing a core depth homing operation based on the target well logging data to update the core data to obtain target core data;

[0006] Constructing a first function based on the spontaneous potential corresponding to the first target formation in the target logging data; the first function is used to obtain relative values ​​of the spontaneous potential corresponding to the first target formation at different depths;

[0007] Determine a first empirical coefficient and a second empirical coefficient according to the first function and the irreducible water saturation corresponding to the first target formation in the target core data, and construct a second function using the first empirical coefficient and the second empirical coefficient; the second function is used to obtain the irreducible water saturation corresponding to the second target formation at different depths; the second target formation is a formation in the formation to be identified that has not been subjected to the core experiment;

[0008] The ultra-low resistivity oil and gas layer in the second target formation is identified based on the porosity, deep induction resistivity and irreducible water saturation determined by the second function; wherein the ultra-low resistivity oil and gas layer is an oil and gas layer whose resistivity increase coefficient is less than a preset coefficient threshold.

[0009] Optionally, the step of performing a standardization operation on the pre-acquired well logging data of the formation to be identified to obtain target well logging data includes:

[0010] Acquire well logging data corresponding to the formation to be identified, and determine a standard layer from the formation to be identified;

[0011] Performing a standardization operation on each logging curve corresponding to the formation to be identified in the logging data, and judging whether the standardization operation is completed based on the logging curve corresponding to the standard layer after the standardization operation;

[0012] If not completed, jump to the step of performing a standardization operation on each logging curve corresponding to the formation to be identified in the logging data until the standardization operation is completed to obtain the target logging data.

[0013] Optionally, the step of performing a standardization operation on each logging curve corresponding to the formation to be identified in the logging data includes:

[0014] Obtaining a preset standardized correction amount corresponding to each well logging curve; the well logging curves are well logging curves corresponding to the formations to be identified in the well logging data;

[0015] A normalization operation is performed on each of the logging curves based on the normalization correction amount.

[0016] Optionally, constructing a first function based on the spontaneous potential corresponding to the first target formation in the target well logging data includes:

[0017] Obtaining a natural potential curve corresponding to the first target formation in the target logging data, and determining a natural potential maximum value and a natural potential minimum value corresponding to the natural potential curve;

[0018] Based on the maximum spontaneous potential and the minimum spontaneous potential, a first function is constructed with the spontaneous potential as a variable.

[0019] Optionally, determining a first empirical coefficient and a second empirical coefficient according to the first function and irreducible water saturation corresponding to the first target formation in the target core data, and constructing a second function using the first empirical coefficient and the second empirical coefficient includes:

[0020] For a first target formation at any depth, a relative value of the natural potential corresponding to the first target formation is obtained based on the first function, and a medium induction resistivity corresponding to the first target formation is determined using the target logging data;

[0021] Determining irreducible water saturation corresponding to the first target formation according to the target core data;

[0022] Based on the irreducible water saturation, the medium induction resistivity and the relative value of the natural potential, and using a preset function model, determine a first empirical coefficient and a second empirical coefficient corresponding to the first target formation;

[0023] Based on the first empirical coefficient and the second empirical coefficient, a second function is constructed with the relative value of the induction resistivity and the natural potential as variables.

[0024] Optionally, the constructing of a second function based on the first empirical coefficient and the second empirical coefficient, with the medium induction resistivity and the relative value of the natural potential as variables, comprises:

[0025] Obtaining each correlation coefficient based on a first empirical coefficient and a second empirical coefficient corresponding to a first target formation at each depth;

[0026] Taking the maximum correlation coefficient as the target correlation coefficient, and determining the first empirical coefficient and the second empirical coefficient corresponding to the target correlation coefficient as the first target empirical coefficient and the second target empirical coefficient;

[0027] Based on the first target empirical coefficient and the second target empirical coefficient, a second function is constructed with the relative value of the medium induction resistivity and the natural potential as variables.

[0028] Optionally, the identifying of the ultra-low resistivity oil and gas layer in the second target formation based on the porosity, the deep induction resistivity and the irreducible water saturation determined by the second function includes:

[0029] Calculating irreducible water saturation corresponding to a second target formation based on a second function, and determining porosity and deep induction resistivity corresponding to the second target formation using target logging data;

[0030] The ultra-low-resistivity oil and gas layer in the second target formation is identified according to the irreducible water saturation, the porosity and the deep induction resistivity.

[0031] In a second aspect, the present application provides a device for identifying an ultra-low resistivity oil and gas layer based on irreducible water saturation calculation, comprising:

[0032] A data acquisition module is used to perform a standardization operation on the pre-acquired logging data of the to-be-identified formation to obtain target logging data, perform a core experiment on a first target formation in the to-be-identified formation to obtain core data, and perform a core depth homing operation based on the target logging data to update the core data to obtain target core data;

[0033] A first function construction module is used to construct a first function based on the natural potential corresponding to the first target formation in the target logging data; the first function is used to obtain relative values ​​of the natural potential corresponding to the first target formation at different depths;

[0034] a second function construction module, for determining a first empirical coefficient and a second empirical coefficient according to the first function and the irreducible water saturation corresponding to the first target formation in the target core data, and constructing a second function using the first empirical coefficient and the second empirical coefficient; the second function is used to obtain the irreducible water saturation corresponding to the second target formation at different depths; the second target formation is a formation in the formation to be identified that has not undergone the core experiment;

[0035] The formation identification module is used to identify the ultra-low resistivity oil and gas layer in the second target formation based on the porosity, deep induction resistivity and irreducible water saturation determined by the second function; wherein the ultra-low resistivity oil and gas layer is an oil and gas layer whose resistivity increase coefficient is less than a preset coefficient threshold.

[0036] In a third aspect, the present application provides an electronic device, including:

[0037] Memory, used to store computer programs;

[0038] The processor is used to execute the computer program to implement the aforementioned method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation.

[0039] In a fourth aspect, the present application provides a computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the aforementioned method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation.

[0040] In the present application, the well logging data of the formation to be identified that is acquired in advance is standardized to obtain target well logging data, a core experiment is performed on the first target formation in the formation to be identified to obtain core data, and a core depth homing operation is performed based on the target well logging data to update the core data to obtain target core data; a first function is constructed based on the natural potential corresponding to the first target formation in the target well logging data; the first function is used to obtain the relative value of the natural potential corresponding to the first target formation at different depths; a first empirical coefficient and a second empirical coefficient are determined according to the first function and the irreducible water saturation corresponding to the first target formation in the target core data, and a second function is constructed using the first empirical coefficient and the second empirical coefficient; the second function is used to obtain the irreducible water saturation corresponding to the second target formation at different depths; the second target formation is a formation in the formation to be identified that has not yet undergone the core experiment; an ultra-low resistivity oil and gas layer in the second target formation is identified based on porosity, deep induction resistivity and irreducible water saturation determined by the second function; wherein the ultra-low resistivity oil and gas layer is an oil and gas layer whose resistivity increase coefficient is less than a preset coefficient threshold. As can be seen from the above, the present application first obtains the logging data of the formation to be identified and the core data corresponding to the first target formation, and performs core depth retrieval operation based on the target logging data after standardized operation to obtain the target core data; a second function is constructed based on the natural potential corresponding to the first target formation in the target logging data and the irreducible water saturation corresponding to the first target formation in the target core data, so as to obtain the irreducible water saturation corresponding to the second target formation at different depths; in this way, the ultra-low resistivity oil and gas layer in the second target formation is identified based on the porosity, deep induction resistivity and the irreducible water saturation determined by the second function, which can accurately identify the ultra-low resistivity oil and gas layer, improve the interpretation accuracy of the oil and gas layer, and lay the foundation for the effective identification and evaluation of the ultra-low resistivity oil and gas layer. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0042] Figure 1 This is a flow chart of a method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation disclosed in this application;

[0043] Figure 2 A schematic diagram of a specific well logging curve change before and after a standardized operation disclosed in this application;

[0044] Figure 3A schematic diagram of a specific well logging curve change before and after a standardized operation disclosed in this application;

[0045] Figure 4 A schematic diagram of the corresponding relationship between core data and logging data before and after core depth relocation disclosed in this application;

[0046] Figure 5 A specific schematic diagram of comprehensive well logging evaluation disclosed in this application;

[0047] Figure 6 A specific schematic diagram of comprehensive well logging evaluation disclosed in this application;

[0048] Figure 7 A specific schematic diagram of comprehensive well logging evaluation disclosed in this application;

[0049] Figure 8 This is a schematic diagram of the structure of a device for identifying ultra-low-resistance oil and gas layers based on irreducible water saturation calculation disclosed in this application;

[0050] Fig. 9 This is a schematic diagram of the structure of an electronic device disclosed in this application. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0052] Low-resistivity oil and gas layers are widely developed in high-porosity and permeability clastic rocks in major oil and gas basins in my country. Since the resistivity of such oil and gas layers shows low resistance or even ultra-low resistance, the ratio of the resistivity of the oil and gas layer to the resistivity of the adjacent water layer is defined as the resistivity increase coefficient. Generally, oil and gas layers with a resistivity increase coefficient less than 2 are defined as low-resistivity oil and gas layers, and those with a resistivity increase coefficient less than 1.5 are specifically defined as ultra-low-resistivity oil and gas layers. Existing data show that high formation water mineralization and high bound water saturation are the main reasons for the ultra-low resistance of oil and gas layers. Under the dual background of high formation water mineralization and high bound water saturation, oil and gas layers show ultra-low resistivity, concave shape, and high invasion characteristics. The identification methods commonly used in the prior art to identify ultra-low-resistivity oil and gas layers based on "resistivity size, shape, and invasion characteristics" have obvious limitations and are prone to misjudgment of oil and gas layers. For this reason, the present application provides an ultra-low-resistivity oil and gas layer identification method based on bound water saturation calculation, which can accurately identify ultra-low-resistivity oil and gas layers.

[0053] See also Figure 1 As shown, the embodiment of the present invention discloses a method for identifying an ultra-low resistivity oil and gas layer based on irreducible water saturation calculation, comprising:

[0054] Step S11, standardize the pre-acquired logging data of the to-be-identified formation to obtain target logging data, conduct a core experiment on the first target formation in the to-be-identified formation to obtain core data, and perform a core depth homing operation based on the target logging data to update the core data to obtain target core data.

[0055] In this embodiment, the well logging data of the formation to be identified is first obtained and the well logging data is standardized to obtain the target well logging data. Specifically, it may include: obtaining the well logging data corresponding to the formation to be identified, and determining the standard layer from the formation to be identified; then performing the standardization operation on each well logging curve corresponding to the formation to be identified in the well logging data, and judging whether the standardization operation is completed based on the well logging curve corresponding to the standard layer after the standardization operation; if not completed, jumping to the step of performing the standardization operation on each well logging curve corresponding to the formation to be identified in the well logging data until the standardization operation is completed to obtain the target well logging data; wherein, performing the standardization operation on each well logging curve corresponding to the formation to be identified in the well logging data may include: first obtaining a pre-set standardized correction amount corresponding to each well logging curve; then performing the standardization operation on each well logging curve based on the standardized correction amount; wherein the above-mentioned well logging curves are the well logging curves corresponding to the formation to be identified in the well logging data.

[0056] It is understandable that in the long-term exploration and development process, the logging data comes from different measuring instruments and is measured by different operating methods. These logging data may have systematic errors that do not reflect the changes in geological factors, so the logging data needs to be standardized. The following takes the ultra-low resistivity oil reservoir in a certain layer of the target work area as an example, and uses the histogram method to standardize the logging data of the target work area:

[0057] First, key wells are selected. Through the study of key wells, the geological model, logging interpretation model, interpretation method, logging scale and standardization method, and the conversion relationship between logging information and geological parameters suitable for the study area are determined. Wells with favorable structural positions, good wellbore environment, complete coring data, and rich logging series can be selected as key wells; then key layers are selected from the above key wells. According to the logging and geological characteristics of the study area and the selection requirements of standard layers, such as a certain lithological stratum in the same layer, with the same sedimentary environment and similar geophysical characteristics, 1-2 strata with stable sedimentation, moderate thickness and small changes, wide distribution range, and easy-to-identify lithology and logging characteristics are selected as standard layers. The mudstone at the top of the Triassic in the target work area can be selected as the standard layer; further, the standard values ​​and histograms of each logging curve corresponding to the standard layer are determined. For example, Table 1 shows the standard values ​​set for each logging curve corresponding to the Triassic mudstone in the work area, among which A C is the acoustic time difference curve, CNL is the compensated neutron curve, DEN is the compensated density curve, RILD is the deep induction resistivity curve, RILM is the medium induction resistivity curve, and RLL8 is the eight-lateral resistivity curve; then, the standardized correction amount of each logging curve corresponding to the standard layer is determined, based on the standardized correction amount, and the frequency cross-plot method is used to perform a standardized operation on each logging curve in the logging data of the target work area, and the actual standard value of each logging curve corresponding to the standard layer is obtained. If the actual standard value of each logging curve is significantly different from the set standard value, the standardized operation of each logging curve is continued until the actual standard value of each logging curve approaches the set standard value, and the standardized operation of the logging data is completed; among them, the standardized correction amount of the acoustic time difference curve, the compensated neutron curve, and the compensated density curve can be an additive factor, and the standardized correction amount of the deep induction resistivity curve, the medium induction resistivity curve, and the eight-lateral resistivity curve can be a multiplicative factor.

[0058] Table 1

[0059]

[0060] After the standardization operation, the corresponding logging curves of the standard layer can be used to judge whether the standardization operation is reasonable. For example, for the reservoir, the acoustic time difference curve, the compensated neutron curve, and the compensated density curve are convergent under the mutual capacity scale; for large sections of mudstone, the deep induction resistivity curve, the medium induction resistivity curve, and the eight lateral resistivity curves are basically overlapped. Therefore, the rationality of the porosity logging curve standardization can be intuitively tested by comparing the convergence of the three porosity curves before and after standardization at the reservoir. Figure 2 The curve in the middle rectangular box is shown; similarly, the rationality of resistivity logging curve standardization can be visually verified by comparing the overlap of the three resistivity curves before and after standardization in the large section of mudstone, as shown in Figure 2. Figure 3 As shown in the curve in the rectangular box. Figure 2 , Figure 3 As shown, it can be seen that the standardization operation is reasonable and the target logging data is obtained.

[0061] After obtaining the target logging data, select some strata from the strata to be identified as the first target strata, conduct core experiments on the first target strata to obtain core data, and perform core depth retrieval operations based on the above target logging data to update the core data and obtain target core data. The core data includes but is not limited to porosity and irreducible water saturation; relative permeability method, nuclear magnetic resonance method, semi-permeable partition capillary pressure method, etc. can be used to determine irreducible water saturation.

[0062] Specifically, the correlation comparison method is used to determine the movement of the core analysis homing depth, and the core data is compared with the target logging data. The logging depth in the target logging data is used as a benchmark to determine the value of the core depth increase or decrease to ensure the consistency of the core data and the target logging data. Figure 4 As shown, by performing core depth homing operations on 48 coring wells in the Triassic system of a certain oil field, it was found that the core analysis depth corresponding to the core data is generally shallower than the logging depth corresponding to the target logging data, and the core analysis depth of some wells is deeper than the logging depth. The movement amount of the core depth homing of the coring wells is determined by comparison, and the core analysis data is depth adjusted based on the above movement amount. It can be understood that when performing the core depth homing operation, a curve that reflects similar properties in the target logging data can be selected from the core data for comparative analysis to determine the matching point or matching interval between the two; for example, the porosity curve can be selected in this embodiment for core depth homing operation, and a physical property curve can also be selected, such as Figure 4 The acoustic time difference curve, compensated neutron curve, and compensated density curve.

[0063] Step S12: constructing a first function based on the spontaneous potential corresponding to the first target formation in the target logging data; the first function is used to obtain relative values ​​of the spontaneous potential corresponding to the first target formation at different depths.

[0064] In this embodiment, constructing a first function based on the spontaneous potential corresponding to the first target formation in the target logging data may include: obtaining a spontaneous potential curve corresponding to the first target formation in the target logging data, and determining a maximum spontaneous potential and a minimum spontaneous potential corresponding to the spontaneous potential curve; constructing a first function based on the maximum spontaneous potential and the minimum spontaneous potential with the spontaneous potential as a variable; the constructed first function expression is:

[0065] ;

[0066] in, is the relative value of the natural potential, decimal; is the natural potential; is the minimum value of the natural potential corresponding to the natural potential curve; is the maximum value of the natural potential corresponding to the natural potential curve; the first function expression can obtain the relative value of the natural potential corresponding to the first target formation at any depth.

[0067] Step S13, determining a first empirical coefficient and a second empirical coefficient according to the first function and the irreducible water saturation corresponding to the first target formation in the target core data, and constructing a second function using the first empirical coefficient and the second empirical coefficient; the second function is used to obtain the irreducible water saturation corresponding to the second target formation at different depths; the second target formation is a formation in the formation to be identified that has not yet undergone the core experiment.

[0068] In this embodiment, since the logging curves that are sensitive to the irreducible water saturation in the study layer section of the work area are the medium induction resistivity curve and the natural potential curve, a second function can be constructed based on the data fitting method of the sensitive curve to obtain the irreducible water saturation corresponding to the second target formation at different depths. Specifically, for the first target formation at any depth, the relative value of the natural potential corresponding to the first target formation is obtained based on the first function, and the medium induction resistivity corresponding to the first target formation is determined using the target logging data; then the irreducible water saturation corresponding to the first target formation is determined based on the target core data; in this way, for the first target formation at any depth, the corresponding relative value of the natural potential, the medium induction resistivity and the irreducible water saturation can be obtained; based on a combination of multiple irreducible water saturations, medium induction resistivities and relative values ​​of natural potential, the first empirical coefficient and the second empirical coefficient corresponding to the first target formation are determined using a pre-set function model; then, based on the first empirical coefficient and the second empirical coefficient, the second function is constructed with the medium induction resistivity and the relative value of natural potential as variables. Among them, the pre-set function model is:

[0069] ;

[0070] in, is the bound water saturation, a decimal; is the medium induction resistivity, ; A is the first empirical coefficient; B is the second empirical coefficient.

[0071] It should be noted that the above-mentioned construction of the second function based on the first empirical coefficient and the second empirical coefficient, with the medium induction resistivity and the relative value of the natural potential as variables, may include: first, obtaining each correlation coefficient based on the first empirical coefficient and the second empirical coefficient corresponding to the first target formation at each depth; then taking the maximum correlation coefficient as the target correlation coefficient, and determining the first empirical coefficient and the second empirical coefficient corresponding to the target correlation coefficient as the first target empirical coefficient and the second target empirical coefficient; constructing the second function based on the first target empirical coefficient and the second target empirical coefficient, with the medium induction resistivity and the relative value of the natural potential as variables; wherein, the closer the correlation coefficient R is to 1, the more accurate the bound water saturation obtained based on the second function. In this way, based on the bound water saturation obtained from the core experiment, the target core data and the target logging data are fitted to obtain the second function. For example, based on the target work area selected in step S11, the maximum value of the correlation coefficient R is 0.939, at this time A is 9.22, B is 60.675, then the second function at this time is:

[0072] ;

[0073] Step S14, identifying the ultra-low resistivity oil and gas layer in the second target formation based on the porosity, deep induction resistivity and irreducible water saturation determined by the second function; wherein the ultra-low resistivity oil and gas layer is an oil and gas layer whose resistivity increase coefficient is less than a preset coefficient threshold.

[0074] In this embodiment, based on the deep induction resistivity after standardized operation, combined with irreducible water saturation and porosity, a comprehensive interpretation standard of resistivity-restricted water saturation-porosity can be established to identify the ultra-low resistivity oil and gas layer in the second target formation where core experiments have not been conducted.

[0075] Specifically, the irreducible water saturation corresponding to the second target formation is first calculated using the second function obtained in step S13, and the porosity and deep induction resistivity corresponding to the second target formation are determined using the target logging data; then, the ultra-low resistivity oil and gas layer in the second target formation is identified based on the irreducible water saturation, porosity and deep induction resistivity.

[0076] It should be noted that the acoustic wave-density intersection method can be used to calculate porosity. For example, for muddy sandstone formations, the rock physics model shows that the logging response equations of acoustic waves and density are:

[0077] ;

[0078] ;

[0079] Change to matrix form:

[0080] ;

[0081] Solving the equation gives:

[0082] ;

[0083] ;

[0084] ;

[0085] in, is the acoustic time difference, microseconds / foot; is the mud content, decimal; is the porosity, a decimal; is the acoustic time difference of the rock skeleton, microseconds / foot; is the mud acoustic time difference, microseconds / foot; is the drilling fluid acoustic wave time difference, microseconds / foot; To compensate for density, ; Compensating density for the rock skeleton, ; is the mud compensation density, ; is the drilling fluid compensation density, .

[0086] Taking the target work area in step S11 as an example, based on the deep induction resistivity after the standardized operation ( ), combined with bound water saturation ( ) and porosity, establish the comprehensive interpretation standard of resistivity-bound water saturation-porosity, determine the interpretation conclusion of reservoir, and identify the strata that have not been tested with cores. As shown in Table 2, when the porosity is not less than 15%, it is interpreted as a reservoir, and when the porosity is less than 15%, it is interpreted as a dry layer; in the reservoir, when the deep induction resistivity is greater than 0.8 At this time, the bound water saturation is generally lower than 40%, which is interpreted as a normal oil and gas layer; when the deep induction resistivity is between 0.4 to 0.8 When the deep induction resistivity is between 0.4 and 0.5, and the irreducible water saturation is higher than 50% (generally between 50% and 70%), it is interpreted as a low-resistivity oil and gas layer; when the deep induction resistivity is between 0.4 and 0.5, to 0.8 When the bound water saturation is less than 50%, it is interpreted as oil and water in the same layer; when the deep induction resistivity is less than 0.4 , at this time, the bound water saturation is generally lower than 50%, which is interpreted as a water layer.

[0087] Table 2

[0088]

[0089] As can be seen from the above, this embodiment first obtains the logging data of the formation to be identified and the core data corresponding to the first target formation, and performs a core depth homing operation based on the target logging data after the standardized operation to obtain the target core data; the target core data is fitted with the target logging data to construct a second function based on the natural potential corresponding to the first target formation in the target logging data and the irreducible water saturation corresponding to the first target formation in the target core data, so as to obtain the irreducible water saturation corresponding to the second target formation at different depths; in this way, the ultra-low resistivity oil and gas layer in the second target formation is identified based on the porosity, deep induction resistivity and the irreducible water saturation determined by the second function, which can accurately identify the ultra-low resistivity oil and gas layer, improve the interpretation accuracy of the oil and gas layer, and lay a foundation for the effective identification and evaluation of the ultra-low resistivity oil and gas layer.

[0090] The technical solution in this application is described below with reference to specific embodiments.

[0091] Embodiment 1:

[0092] The accuracy of this application is verified by referring to the test and production results of K1 well. Figure 5 The comprehensive evaluation diagram of K1 well logging shown in the figure shows that the natural gamma is low and the natural potential is negatively abnormal in the 4187-4225 meter well section, which is a sandstone reservoir. Combined with the mutual capacity convergence of the three porosities and the non-mean change characteristics of the three resistivity curves, a comprehensive analysis shows that it is a suspected oil and gas layer.

[0093] The top mudstone of the Triassic is used as the standard layer to standardize the logging data. Track 4 in the figure is the standardized resistivity curve. It can be seen that the deep, medium and shallow detection resistivity curves of the pure mudstone section from 4182.0 to 4184.0 meters basically coincide, indicating that the standardization effect is credible.

[0094] According to the curve characteristics of the natural potential curve in the pure mudstone and pure sandstone sections in the figure, the maximum value of the natural potential is 85mv and the minimum value is 5mv, thereby determining the relative value DSP of the natural potential of this section of the formation; according to the standardized medium induction resistivity curve value, the second function expression established above is used to calculate the bound water saturation of this section of the formation (Track 5); the porosity of this section of the formation is obtained by the acoustic wave-density intersection method (Track 6).

[0095] According to the established comprehensive interpretation standard of resistivity-bound water saturation-porosity, the deep induction resistivity of layer 1-2 is as low as 0.45 The calculated bound water saturation is 52-57.4%, the average porosity is 21.3%, and the comprehensive interpretation is that it is an ultra-low resistivity oil and gas layer; the deep induction resistivity of layer 3 is 2.58 The calculated bound water saturation is 31.9%, the average porosity is 22%, and the comprehensive interpretation is a normal oil and gas layer; the deep induction resistivity of layer 4 is 0.68 The calculated bound water saturation is 38.5% on average, the porosity is 22.9% on average, and the comprehensive interpretation is that the oil and water are in the same layer; the deep induction resistivity of layer 5-6 is 0.26-0.31 The calculated bound water saturation is 36-48%, and the average porosity is 23.2%, which is comprehensively interpreted as a water layer. The 4187-4196.5m ultra-low resistivity oil and gas layer was tested, with a daily production of 20.3 tons of crude oil, 4,800 cubic meters of gas, and no water. The test conclusion is that it is an oil and gas layer.

[0096] Embodiment 2:

[0097] The accuracy of the present invention is verified by referring to the test and production results of the G4 well. Figure 6 The G4 well logging comprehensive evaluation diagram shown in the figure shows that the 4166-4183m well section has low natural gamma values ​​and negative natural potential anomalies, indicating a sandstone reservoir. Combined with the convergence of the three porosity mutual capacity and the non-mean variation characteristics of the three resistivity curves, a comprehensive analysis shows that it is a suspected oil and gas layer section.

[0098] The top mudstone of the Triassic is used as the standard layer to standardize the logging data. Track 4 in the figure is the standardized resistivity curve. It can be seen that the deep, medium and shallow detection resistivity curves of the pure mudstone section from 4182.2 to 4184.5 meters basically coincide, indicating that the standardization effect is credible.

[0099] According to the curve characteristics of the natural potential curve in the pure mudstone and pure sandstone sections in the figure, the maximum value of the natural potential is 95mv and the minimum value is -5mv, thereby determining the relative value DSP of the natural potential of this section of the formation; based on the standardized medium induction resistivity curve value, the irreducible water saturation of this section of the formation is calculated using the irreducible water saturation function expression established above (Track 5); the porosity of this section of the formation is obtained using the acoustic wave-density intersection method (Track 6).

[0100] According to the established comprehensive interpretation standard of resistivity-imposed water saturation-porosity, the deep induction resistivity of layer 1 is 2.6 The calculated irreducible water saturation is 35.8% on average, and the porosity is 24.0% on average, which is interpreted as a normal oil and gas layer. The deep induction resistivity of the upper part of the No. 3 layer is 2.7 The calculated irreducible water saturation is 32.7% on average, and the porosity is 22.8% on average, which are normal oil and gas layer characteristics; the deep induction resistivity of the lower part of layer 3 is reduced to 0.7 The calculated bound water saturation is 53.5% on average, and the porosity is 18.8% on average, which are the characteristics of (extra) low-resistivity oil and gas layers. Layer 3 is comprehensively interpreted as an oil and gas layer. The 4166-4169m oil and gas layer is tested, with a daily production of 35.2 tons of crude oil, 6,380 cubic meters of gas, and no water. The test conclusion is that it is an oil and gas layer.

[0101] Embodiment three:

[0102] The accuracy of the present invention is verified by referring to the test and production results of the K2 well. Figure 7 The comprehensive evaluation diagram of K2 well logging shown in the figure shows that the natural gamma is low and the natural potential is negatively abnormal in the 4172-4199 meter well section, which is a sandstone reservoir. Combined with the convergence of the three porosity mutual capacity and the non-mean change characteristics of the three resistivity curves, a comprehensive analysis shows that it is a suspected oil and gas layer section.

[0103] The top mudstone of the Triassic is used as the standard layer to standardize the logging data. Track 4 in the figure is the standardized resistivity curve. It can be seen that the deep, medium and shallow detection resistivity curves of the pure mudstone section from 4165 to 4175 meters basically coincide, indicating that the standardization effect is credible.

[0104] According to the curve characteristics of the natural potential curve in the pure mudstone and pure sandstone sections in the figure, the maximum value of the natural potential is 65mv and the minimum value is 30mv, thereby determining the relative value DSP of the natural potential of this section of the formation; based on the standardized medium induction resistivity curve value, the irreducible water saturation of this section of the formation is calculated using the irreducible water saturation function expression established above (Track 5); the porosity of this section of the formation is obtained using the acoustic wave-density intersection method (Track 6).

[0105] According to the established comprehensive interpretation standard of resistivity-imposed water saturation-porosity, the deep induction resistivity of layer 1 is 1.05 The calculated bound water saturation is 52.5% on average, and the porosity is 19.2% on average, which is interpreted as a low-resistivity oil and gas layer. The deep induction resistivity of the upper part of the No. 2 layer is reduced to 0.43 The calculated bound water saturation is 58.9% on average, and the porosity is 16% on average, which is a characteristic of an ultra-low resistivity oil and gas layer; the deep induction resistivity in the lower part is 3.6 The calculated bound water saturation is 33.2% on average, and the porosity is 20% on average, which are normal oil and gas layer characteristics; the No. 2 layer is comprehensively interpreted as an oil and gas layer; the deep induction resistivity of the No. 3 layer is 0.26 The calculated bound water saturation is 46.8% on average, and the porosity is 22.2% on average, which is comprehensively interpreted as a water layer. The oil and gas layer at 4171-4183m was tested, with a daily output of 56.3 tons of crude oil, 8910 cubic meters of gas, and no water. The test conclusion is that it is an oil and gas layer.

[0106] Based on the above three specific embodiments, Table 3 can be obtained:

[0107] Table 3

[0108]

[0109] As can be seen from the above, this embodiment uses three specific examples to illustrate the ultra-low resistivity oil and gas layer identification method based on irreducible water saturation calculation described in this application. Based on the comprehensive interpretation of resistivity-reduced water saturation-porosity, ultra-low resistivity oil and gas layers can be accurately identified, thereby improving the interpretation accuracy of oil and gas layers and laying the foundation for the effective identification and evaluation of ultra-low resistivity oil and gas layers.

[0110] See also Figure 8 As shown, the embodiment of the present application also discloses a device for identifying an ultra-low resistivity oil and gas layer based on irreducible water saturation calculation, comprising:

[0111] The data acquisition module 11 is used to perform a standardization operation on the pre-acquired logging data of the to-be-identified formation to obtain target logging data, perform a core experiment on the first target formation in the to-be-identified formation to obtain core data, and perform a core depth homing operation based on the target logging data to update the core data to obtain target core data;

[0112] A first function construction module 12 is used to construct a first function based on the natural potential corresponding to the first target formation in the target logging data; the first function is used to obtain relative values ​​of the natural potential corresponding to the first target formation at different depths;

[0113] A second function construction module 13 is used to determine a first empirical coefficient and a second empirical coefficient according to the first function and the irreducible water saturation corresponding to the first target formation in the target core data, and to construct a second function using the first empirical coefficient and the second empirical coefficient; the second function is used to obtain the irreducible water saturation corresponding to the second target formation at different depths; the second target formation is a formation in the formation to be identified that has not undergone the core experiment;

[0114] The formation identification module 14 is used to identify the ultra-low resistivity oil and gas layer in the second target formation based on the porosity, deep induction resistivity and irreducible water saturation determined by the second function; wherein the ultra-low resistivity oil and gas layer is an oil and gas layer whose resistivity increase coefficient is less than a preset coefficient threshold.

[0115] As can be seen from the above, the present application first obtains the logging data of the formation to be identified and the core data corresponding to the first target formation, and performs core depth retrieval operation based on the target logging data after standardized operation to obtain the target core data; a second function is constructed based on the natural potential corresponding to the first target formation in the target logging data and the irreducible water saturation corresponding to the first target formation in the target core data, so as to obtain the irreducible water saturation corresponding to the second target formation at different depths; in this way, the ultra-low resistivity oil and gas layer in the second target formation is identified based on the porosity, deep induction resistivity and the irreducible water saturation determined by the second function, which can accurately identify the ultra-low resistivity oil and gas layer, improve the interpretation accuracy of the oil and gas layer, and lay the foundation for the effective identification and evaluation of the ultra-low resistivity oil and gas layer.

[0116] In some specific implementations, the data acquisition module 11 includes:

[0117] A standard layer determination unit, used to obtain well logging data corresponding to the formation to be identified, and determine the standard layer from the formation to be identified;

[0118] A standardization operation submodule, used to perform a standardization operation on each logging curve corresponding to the to-be-identified formation in the logging data, and to determine whether the standardization operation is completed based on the logging curve corresponding to the standard layer after the standardization operation;

[0119] The data acquisition unit is used to jump to the step of performing a standardization operation on each logging curve corresponding to the formation to be identified in the logging data if the standardization operation is not completed, until the standardization operation is completed to obtain the target logging data.

[0120] In some specific embodiments, the standardization operation submodule includes:

[0121] A correction amount determination unit is used to obtain a preset standardized correction amount corresponding to each well logging curve; each well logging curve is a well logging curve corresponding to the formation to be identified in the well logging data;

[0122] A standardization operation unit is used to perform a standardization operation on each logging curve based on the standardized correction amount.

[0123] In some specific implementations, the first function building module 12 includes:

[0124] A first information acquisition unit is used to acquire a natural potential curve corresponding to the first target formation in the target logging data, and determine a natural potential maximum value and a natural potential minimum value corresponding to the natural potential curve;

[0125] The first function determination unit is used to construct a first function based on the maximum spontaneous potential and the minimum spontaneous potential and taking the spontaneous potential as a variable.

[0126] In some specific implementations, the second function construction module 13 includes:

[0127] A second information acquisition unit is used to obtain, for a first target formation at any depth, a relative value of the natural potential corresponding to the first target formation based on the first function, and determine the medium induction resistivity corresponding to the first target formation using the target logging data;

[0128] an irreducible water saturation determination unit, configured to determine the irreducible water saturation corresponding to the first target formation according to the target core data;

[0129] an empirical coefficient determination unit, configured to determine a first empirical coefficient and a second empirical coefficient corresponding to the first target formation based on the irreducible water saturation, the medium induction resistivity and the relative value of the spontaneous potential and using a preset function model;

[0130] The second function determination submodule is used to construct a second function based on the first empirical coefficient and the second empirical coefficient, with the medium induction resistivity and the relative value of the natural potential as variables.

[0131] In some specific implementations, the second function determination submodule includes:

[0132] A correlation coefficient determination unit, configured to obtain each correlation coefficient based on a first empirical coefficient and a second empirical coefficient corresponding to a first target formation at each depth;

[0133] a target empirical coefficient determination unit, configured to take the maximum correlation coefficient as the target correlation coefficient, and determine the first empirical coefficient and the second empirical coefficient corresponding to the target correlation coefficient as the first target empirical coefficient and the second target empirical coefficient;

[0134] The second function construction unit is used to construct a second function based on the first target empirical coefficient and the second target empirical coefficient, with the medium induction resistivity and the relative value of the natural potential as variables.

[0135] In some specific implementations, the formation identification module 14 includes:

[0136] a third information acquisition unit, configured to calculate irreducible water saturation corresponding to a second target formation based on the second function, and determine porosity and deep induction resistivity corresponding to the second target formation using target logging data;

[0137] The oil and gas layer identification unit is used to identify the ultra-low resistivity oil and gas layer in the second target formation according to the irreducible water saturation, the porosity and the deep induction resistivity.

[0138] Furthermore, the present application also discloses an electronic device. Fig. 9 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram cannot be regarded as any limitation on the scope of use of the present application.

[0139] Fig. 9 A schematic diagram of the structure of an electronic device 20 provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation disclosed in any of the aforementioned embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0140] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0141] In addition, the memory 22, as a carrier for storing resources, can be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0142] The operating system 221 is used to manage and control the hardware devices and computer program 222 on the electronic device 20, and can be Windows Server, Netware, Unix, Linux, etc. In addition to the computer program that can be used to complete the ultra-low resistivity oil and gas layer identification method based on irreducible water saturation calculation performed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 can further include computer programs that can be used to complete other specific tasks.

[0143] Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the aforementioned disclosed method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation is implemented. The specific steps of the method can be referred to the corresponding contents disclosed in the aforementioned embodiments, and will not be repeated here.

[0144] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0145] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0146] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0147] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0148] The technical solution provided by the present application is introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for general technicians in this field, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation, characterized in that: include: Performing a standardization operation on the well logging data of the formation to be identified that has been acquired in advance to obtain target well logging data, performing a core experiment on a first target formation in the formation to be identified to obtain core data, and performing a core depth homing operation based on the target well logging data to update the core data to obtain target core data; Constructing a first function based on the spontaneous potential corresponding to the first target formation in the target logging data; the first function is used to obtain relative values ​​of the spontaneous potential corresponding to the first target formation at different depths; Determine a first empirical coefficient and a second empirical coefficient according to the first function and the irreducible water saturation corresponding to the first target formation in the target core data, and construct a second function using the first empirical coefficient and the second empirical coefficient; the second function is used to obtain the irreducible water saturation corresponding to the second target formation at different depths; the second target formation is a formation in the formation to be identified that has not been subjected to the core experiment; The ultra-low resistivity oil and gas layer in the second target formation is identified based on the porosity, deep induction resistivity and irreducible water saturation determined by the second function; wherein the ultra-low resistivity oil and gas layer is an oil and gas layer whose resistivity increase coefficient is less than a preset coefficient threshold.

2. The method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation according to claim 1, characterized in that: The step of performing a standardization operation on the pre-acquired well logging data of the formation to be identified to obtain target well logging data includes: Acquire well logging data corresponding to the formation to be identified, and determine a standard layer from the formation to be identified; Performing a standardization operation on each logging curve corresponding to the formation to be identified in the logging data, and judging whether the standardization operation is completed based on the logging curve corresponding to the standard layer after the standardization operation; If not completed, jump to the step of performing a standardization operation on each logging curve corresponding to the formation to be identified in the logging data until the standardization operation is completed to obtain the target logging data.

3. The method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation according to claim 2, characterized in that: The standardization operation of each logging curve corresponding to the formation to be identified in the logging data includes: Obtaining a preset standardized correction amount corresponding to each well logging curve; the well logging curves are well logging curves corresponding to the formations to be identified in the well logging data; A normalization operation is performed on each of the logging curves based on the normalization correction amount.

4. The method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation according to claim 1, characterized in that: The constructing a first function based on the spontaneous potential corresponding to the first target formation in the target logging data includes: Obtaining a natural potential curve corresponding to the first target formation in the target logging data, and determining a natural potential maximum value and a natural potential minimum value corresponding to the natural potential curve; Based on the maximum spontaneous potential and the minimum spontaneous potential, a first function is constructed with the spontaneous potential as a variable.

5. The method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation according to claim 1, characterized in that: The step of determining a first empirical coefficient and a second empirical coefficient according to the first function and irreducible water saturation corresponding to the first target formation in the target core data, and constructing a second function using the first empirical coefficient and the second empirical coefficient includes: For a first target formation at any depth, a relative value of the natural potential corresponding to the first target formation is obtained based on the first function, and a medium induction resistivity corresponding to the first target formation is determined using the target logging data; Determining irreducible water saturation corresponding to the first target formation according to the target core data; Based on the irreducible water saturation, the medium induction resistivity and the relative value of the natural potential, and using a preset function model, determine a first empirical coefficient and a second empirical coefficient corresponding to the first target formation; Based on the first empirical coefficient and the second empirical coefficient, a second function is constructed with the relative value of the induction resistivity and the natural potential as variables.

6. The method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation according to claim 5, characterized in that: The method of constructing a second function based on the first empirical coefficient and the second empirical coefficient and taking the relative value of the medium induction resistivity and the natural potential as variables comprises: Obtaining each correlation coefficient based on a first empirical coefficient and a second empirical coefficient corresponding to a first target formation at each depth; Taking the maximum correlation coefficient as the target correlation coefficient, and determining the first empirical coefficient and the second empirical coefficient corresponding to the target correlation coefficient as the first target empirical coefficient and the second target empirical coefficient; Based on the first target empirical coefficient and the second target empirical coefficient, a second function is constructed with the relative value of the medium induction resistivity and the natural potential as variables.

7. The method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation according to any one of claims 1 to 6, characterized in that: The identifying of the ultra-low resistivity oil and gas layer in the second target formation based on the porosity, the deep induction resistivity and the irreducible water saturation determined by the second function comprises: Calculating irreducible water saturation corresponding to a second target formation based on a second function, and determining porosity and deep induction resistivity corresponding to the second target formation using target logging data; The ultra-low-resistivity oil and gas layer in the second target formation is identified according to the irreducible water saturation, the porosity and the deep induction resistivity.

8. A device for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation, characterized in that: include: A data acquisition module is used to perform a standardization operation on the pre-acquired logging data of the to-be-identified formation to obtain target logging data, perform a core experiment on a first target formation in the to-be-identified formation to obtain core data, and perform a core depth homing operation based on the target logging data to update the core data to obtain target core data; A first function construction module is used to construct a first function based on the natural potential corresponding to the first target formation in the target logging data; the first function is used to obtain relative values ​​of the natural potential corresponding to the first target formation at different depths; a second function construction module, for determining a first empirical coefficient and a second empirical coefficient according to the first function and the irreducible water saturation corresponding to the first target formation in the target core data, and constructing a second function using the first empirical coefficient and the second empirical coefficient; the second function is used to obtain the irreducible water saturation corresponding to the second target formation at different depths; the second target formation is a formation in the formation to be identified that has not undergone the core experiment; The formation identification module is used to identify the ultra-low resistivity oil and gas layer in the second target formation based on the porosity, deep induction resistivity and irreducible water saturation determined by the second function; wherein the ultra-low resistivity oil and gas layer is an oil and gas layer whose resistivity increase coefficient is less than a preset coefficient threshold.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor is used to execute the computer program to implement the method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Used to store a computer program, which, when executed by a processor, implements the method for identifying ultra-low resistivity oil and gas layers based on irreducible water saturation calculation as claimed in any one of claims 1 to 7.

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