Fluid saturation inversion method and apparatus

Abstract

The application provides a fluid saturation inversion method and device, and relates to the technical field of geophysics. The method comprises the following steps: acquiring an electromagnetic field parameter based on a spatial rectangular coordinate system; generating resistivity tensor data by using the electromagnetic field parameter; determining a target parameter value in Archie formula by using the resistivity tensor data; and generating a fluid saturation inversion result by using the target parameter value and the Archie formula. The target parameter value in the Archie formula is corrected by calculating the resistivity tensor data, so that the accuracy of fluid saturation prediction is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of geophysical technology, and in particular to a fluid saturation inversion method and device. BACKGROUND

[0002] In the electromagnetic wave detection process for shale oil and gas, the electrical properties of shale have obvious anisotropy. The anisotropy refers to the fact that the electrical parameters of shale present different values in different directions, mainly in the form of shale resistivity and dielectric constant. In anisotropic media (for example, media with large fractures), with the change of fracture morphology, the equivalent electrical parameters will change greatly, while the resistivity in Archie's Law is a scalar, which cannot characterize the anisotropy, thereby causing a large error in the calculated water saturation. In classical electromagnetic theory, the constitutive form of electrical conductivity and resistivity is a second-order tensor, which contains nine components in different directions. For anisotropic media, the change information of electrical parameters is reflected in the expression of these nine components. If only scalar electrical conductivity or resistivity is used to describe, the information in other direction components will be lost, resulting in unsatisfactory effect of water saturation and other physical parameter inversion. SUMMARY

[0003] The present application provides a fluid saturation inversion method and device, which can correct Archie's formula by calculating the resistivity tensor, and improve the accuracy of water saturation prediction.

[0004] In a first aspect, the present application provides a fluid saturation inversion method, which comprises: acquiring electromagnetic field parameters based on a spatial rectangular coordinate system; generating resistivity tensor data by using the electromagnetic field parameters; determining a target parameter value in Archie's formula by using the resistivity tensor data; and generating a fluid saturation inversion result by using the target parameter value and the Archie's formula.

[0005] In a second aspect, the present application also provides a fluid saturation inversion device, which comprises: an acquisition module configured to acquire electromagnetic field parameters based on a spatial rectangular coordinate system; a tensor module configured to generate resistivity tensor data by using the electromagnetic field parameters; a parameter module configured to determine a target parameter value in Archie's formula by using the resistivity tensor data; and an inversion module configured to generate a fluid saturation inversion result by using the target parameter value and the Archie's formula.

[0006] In a third aspect, the present application also provides a computer device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the above fluid saturation inversion method when executing the computer program.

[0007] In a fourth aspect, the embodiments of the present application further provide a computer readable storage medium, which stores a computer program for implementing the fluid saturation inversion method.

[0008] The embodiments of the present application have the following beneficial effects: The embodiments of the present application provide a fluid saturation inversion scheme, which first acquires electromagnetic field parameters based on a spatial rectangular coordinate system; then generates resistivity tensor data by using the electromagnetic field parameters; determines the target parameter value in Archie's formula by using the resistivity tensor data; and finally generates a fluid saturation inversion result by using the target parameter value and Archie's formula. The embodiments of the present application correct the target parameter value in Archie's formula by calculating the resistivity tensor data, thereby improving the accuracy of fluid saturation prediction.

[0009] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art upon examination of the following or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and attained by the structure particularly pointed out in the description, claims and drawings.

[0010] In order to make the above objectives, characteristics and advantages of the present application more apparent and easy to understand, the following preferred embodiments are specifically described below, and the accompanying drawings are referred to, and the detailed description is as follows. BRIEF DESCRIPTION OF DRAWINGS

[0011] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings needed to be used in the specific embodiments or the prior art description. Obviously, the drawings described below are some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0012] Figure 1 The fluid saturation inversion method flowchart provided by the embodiments of the present application is shown in the following figure:

[0013] Figure 2 The water saturation inversion method implementation step schematic diagram provided by the embodiments of the present application is shown in the following figure:

[0014] Figure 3 The two idealized fracture schematic diagrams provided by the embodiments of the present application are shown in the following figures:

[0015] Figure 4 The fracture resistivity tensor calculation flowchart provided by the embodiments of the present application is shown in the following figure:

[0016] Figure 5 The fracture resistivity tensor dispersion curve provided by the embodiments of the present application is shown in the following figure:

[0017] Figure 6A comparison chart of scalar formula and tensor formula of circular inclusions provided for the embodiment of the present application is shown in FIG. 1.

[0018] Figure 7 A comparison chart of scalar formula and tensor formula of ellipsoidal inclusions provided for the embodiment of the present application is shown in FIG. 2.

[0019] Figure 8 A chart of the influence of the change of the crack angle on the minor diagonal component provided for the embodiment of the present application is shown in FIG. 3.

[0020] Figure 9 A chart of the influence of the minor diagonal component on the change of the tortuosity index provided for the embodiment of the present application is shown in FIG. 4.

[0021] Figure 10 A schematic diagram of the correction effect of the Archie formula by using the tensor provided for the embodiment of the present application is shown in FIG. 5.

[0022] Figure 11 A schematic diagram of the step of deducing the resistivity tensor by using the force-electricity relationship provided for the embodiment of the present application is shown in FIG. 6.

[0023] Figure 12 A schematic diagram of the cross-physical relationship between the force and the electricity provided for the embodiment of the present application is shown in FIG. 7.

[0024] Figure 13 A structural block diagram of a fluid saturation inversion device provided for the embodiment of the present application is shown in FIG. 8.

[0025] Figure 14 A structural block diagram of another fluid saturation inversion device provided for the embodiment of the present application is shown in FIG. 9.

[0026] Figure 15 A structural block diagram of a computer device provided for the embodiment of the present application is shown in FIG. 10. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme of the present application will be described clearly and completely below with reference to the drawings. Obviously, the described embodiments are some embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0028] Reservoir water (oil and gas) content identification has always been a hot spot in oil and gas exploration and reservoir evaluation. In engineering applications, resistivity-water saturation function is widely used to calculate reservoir water saturation. The existing method based on the idealized rock model of pore space proposes a theoretical method for calculating the dielectric response of water-saturated rock. However, this theory fails to explain the relationship between complex dielectric constant and salinity content at low frequency. The existing method starts from Archie's Law and theoretically deduces that water saturation, formation factor and other factors will affect the water saturation index. Through experiments, it is found that formation factor and formation water resistivity will affect the water saturation index of sandstone. The existing method calculates the conductivity and dielectric constant of rock samples at low frequency (100Hz-10MHz) using the two-electrode method. According to the rock conduction mechanism, a model for calculating the water saturation of rock is given. The existing method develops a random joint inversion method for processing quantitative rock interpretation of hydrocarbon-bearing shale, which explains the statistical correlation between water saturation, salt concentration, porosity and resistivity. The existing method proposes a new method for calculating the porosity and water saturation of fractured reservoirs using the anisotropy gradient of fractured reservoirs. However, this method cannot be used for fracture porosity inversion. The existing method establishes an equivalent resistivity model based on the parallel circuit principle, which is used to quantify the relationship between resistivity and hydrate saturation. In the method of calculating water saturation, Archie's Law is a common and practical method. Archie's Law can calculate the corresponding water saturation by combining the measured resistivity and porosity parameters. This method has good results in relatively uniform and isotropic media.

[0029] The conventional water saturation calculation scheme is insufficient in describing anisotropy, so it cannot accurately consider the influence of underground fractures or non-continuous feature patterns on water saturation in shale oil and gas development.

[0030] There are also researchers at home and abroad who have carried out the work of using electrical tensor to carry out water saturation inversion of anisotropic formation. In the existing methods for predicting water saturation by using resistivity (conductivity) tensor form, the characteristic equation method for solving water saturation is more prominent. The existing method verifies that the tensor form of electrical parameters can be used to characterize the water saturation in the condition of heterogeneous medium, and analyzes the case of horizontal well penetrating anisotropic medium. However, this method still needs to solve the eigenvalues and eigenvalues of the tensor, and needs to solve the characteristic equation, which cannot be efficiently used in engineering practice. On the other hand, the existing method also proposes to use tensor electrical parameters to infer the water saturation in the heterogeneous shale, which has the advantage of combining resistivity imaging data to directly calculate the horizontal and vertical resistivity, but at the same time, this method needs to add a receiver or a transmission coil on the original logging device, so there are certain difficulties in applying the traditional resistivity logging method or solving based on the existing logging data.

[0031] Based on this, the embodiment of the present application provides a fluid saturation inversion method and device, which modifies the water saturation calculation formula by calculating the second-order resistivity tensor and introducing the tensor into Archie's Law. In practical application, due to the limitation of measuring instruments or methods, only scalar resistivity or the main diagonal resistivity (three-component induced resistivity) in the tensor matrix can be measured. In order to make up for this deficiency in practical logging application, the force-electric cross-physical relationship is established, and the resistivity tensor change is calculated through the mechanical modulus (for example, Young's modulus), to compensate for the incomplete resistivity measurement.

[0032] Combined with acoustic logging data, the resistivity tensor is inversely calculated through the force-electric coupling relationship, and the Archie's Law formula is directly modified by using the tensor component, so as to avoid solving the characteristic equation and simplify the prediction process. The scheme modifies Archie's Law by calculating the resistivity tensor, improves the accuracy of water saturation prediction, and establishes the force-electric cross-physical relationship to inversely calculate the resistivity tensor by using the mechanical modulus without tensor measurement.

[0033] In order to facilitate the understanding of the present embodiment, first, a fluid saturation inversion method disclosed by the present embodiment is introduced in detail.

[0034] The embodiment of the present application is based on classical electromagnetic theory, and an idealized fracture is simulated by numerical modeling, an equivalent resistivity tensor is calculated, and the main and secondary diagonal components of the resistivity tensor are used to correct Archie's Law.

[0035] The embodiment of the present application provides a fluid saturation inversion method, and refers to a fluid saturation inversion method flowchart shown in Figure 1 The method comprises the following steps:

[0036] In step S102, electromagnetic field parameters based on a space rectangular coordinate system are acquired.

[0037] In the embodiment of the present application, the electromagnetic field parameters comprise electric field distribution data and current density data. Figure 3 As shown in two idealized fracture schematic diagrams in

[0038] In step S104, resistivity tensor data is generated by using the electromagnetic field parameters.

[0039] In the embodiment of the present application, a set of equivalent resistivity data is generated by using the electromagnetic field parameters in each direction, and the equivalent resistivity data in three directions are combined, so that the resistivity tensor data can be obtained.

[0040] In step S106, a target parameter value in Archie's formula is determined by using the resistivity tensor data.

[0041] In the embodiment of the present application, after the resistivity tensor data is obtained, the value of the target parameter in Archie's formula is calculated by using the resistivity tensor data, and the target parameter can be selected in Archie's formula according to actual requirements.

[0042] It should be noted that Archie's formula is as follows: Wherein, S w is water saturation, a is tortuosity, m is cementation exponent (or, pore connectivity index), φ is porosity, n is saturation exponent, ρ w is water resistivity, ρ t is measured equivalent resistivity.

[0043] It is also noted that the calibration parameters a and m are determined by simulation of a two-phase mixture. When the mixture is two-phase: The equation was found to be a good representation of the relationship between effective resistivity and porosity for isotropic geometries (circular inclusions).

[0044] In step S108, the fluid saturation inversion result is generated by using the target parameter value and Archie formula.

[0045] In the embodiment of the present application, after the target parameter value is calculated by using the resistivity tensor data, the fluid saturation inversion result is calculated by substituting the target parameter value into the Archie formula.

[0046] The embodiment of the present application provides a fluid saturation inversion scheme. First, the electromagnetic field parameter based on the spatial rectangular coordinate system is acquired. Then, the resistivity tensor data is generated by using the electromagnetic field parameter. The target parameter value in the Archie formula is determined by using the resistivity tensor data. Finally, the fluid saturation inversion result is generated by using the target parameter value and the Archie formula. In the embodiment of the present application, the target parameter value in the Archie formula is corrected by calculating the resistivity tensor data, so that the accuracy of fluid saturation prediction is improved.

[0047] In order to facilitate the calculation of the resistivity tensor data, the resistivity tensor data can be generated by using the electromagnetic field parameter according to the following steps:

[0048] The resistivity values in three directions of the spatial rectangular coordinate system are determined by solving Maxwell equations. The resistivity tensor data is determined according to the resistivity values in three directions.

[0049] In the embodiment of the present application, referring to the fracture resistivity tensor calculation flowchart shown in Figure 4 The idealized fracture geometry mainly includes two types of needle-shaped and sheet-shaped. The calculation of the resistivity tensor is performed by solving Maxwell equations on the mixed medium model.

[0050]

[0051] where, represents the electric field intensity, represents the magnetic field, and ε0 and μ0 are two constants. ρ represents the charge density, and the unit is charge / volume, represents the current density, and the unit is current / area.

[0052] The electric field intensity and the current density in three directions of the spatial rectangular coordinate system are determined by solving Maxwell equations. After the electric field intensity and the current density are obtained, the resistivity values in three directions can be respectively calculated by using the following formula. The electric field in each direction generates three directions of equivalent resistivity data, so nine equivalent resistivity data need to be extracted for analysis.

[0053]

[0054] For example, the first time, the resistivity value of the first direction is obtained The second time, the resistivity value of the second direction is obtained The third time, the resistivity value of the third direction is obtained The resistivity values of the three directions are combined to obtain the resistivity tensor data

[0055] After obtaining the resistivity tensor data, the target parameter value in Archie formula is corrected, and the target parameter value can be set to at least include an equivalent resistivity value and a tortuosity value; the target parameter value in Archie formula is determined by using the resistivity tensor data, and the following steps can be performed:

[0056] The equivalent resistivity value is calculated by using the resistivity tensor data; and the tortuosity value is calculated by using the resistivity tensor data.

[0057] In the embodiment of the present application, the target parameter value to be corrected in the Archie formula can be selected according to actual needs, and the embodiment of the present application does not make specific limitation, for example, the equivalent resistivity value and the tortuosity value can be selected to be corrected, or the equivalent resistivity value and the saturation index can be selected to be corrected.

[0058] In order to obtain more accurate inversion results, the equivalent resistivity value can be calculated by using the resistivity tensor data according to the following formula:

[0059]

[0060] Wherein, ρ t is the equivalent resistivity, ρ xx ρ yy ρ zz is the main diagonal line component of the resistivity tensor.

[0061] In the embodiment of the present application, when the geometric change is an ellipsoid, the crack angle change will bring a larger error, and the present application introduces the main diagonal line component correction of the tensor, that is, the geometric average of the main diagonal line component. After correction, the formula can capture the change of the crack angle. Next, the rock-water-oil mixed medium is simulated, the matrix of the model is hydrophilic rock, water is the interlayer, and oil is the inclusion.

[0062] In order to obtain more accurate inversion results, the tortuosity value can be calculated by using the resistivity tensor data according to the following formula:

[0063] a = 2.78 x 10 -5 ρ *4 -0.0032 ρ *3 + 0.107 ρ*2 -ρ * +529

[0064]

[0065] Wherein, a is the degree of curvature, ρ xy , ρ yz , ρ xz is the sub-diagonal line of the resistivity tensor.

[0066] In the embodiment of the present application, the rotation fracture angle, the change of the resistivity sub-diagonal component value is observed. This change is due to the influence of the fracture dip angle change on the degree of curvature of the electric field, and therefore, the sub-diagonal correction is introduced into the curvature index a in the embodiment of the present application, and the correction is based on the square average of the sub-diagonal component. After the correction, the new Archie's Law contains each component in the main and sub-diagonal lines of the resistivity tensor. It can be seen that the corrected formula has better effect in the medium with fractures.

[0067] It should be noted that in the embodiment of the present application, the other data in the resistivity tensor data except the main diagonal line is taken as the sub-diagonal data of the resistivity tensor.

[0068] In view of the fact that in actual application, only scalar resistivity is generally measured, the resistivity tensor can be calculated by establishing the force-electric cross-physical relationship, and therefore, the method can further perform the following steps:

[0069] Obtaining a plurality of fluid saturation inversion results corresponding to mechanical parameter values under the condition that the model angles and porosities are the same; determining the mutual relationship between the fluid saturation inversion results and the mechanical parameter values; when the target mechanical parameter value is received, determining the target fluid saturation inversion result corresponding to the target mechanical parameter value according to the mutual relationship.

[0070] In the embodiment of the present application, a plurality of groups of fluid saturation inversion results and mechanical parameter values are calculated under the condition that the model angles and porosities are the same, to obtain a first group of fluid saturation inversion results and mechanical parameter values, a second group of fluid saturation inversion results and mechanical parameter values, and an Nth group of fluid saturation inversion results and mechanical parameter values. Any two groups of fluid saturation inversion results and mechanical parameter values correspond to different model angles and porosities, and therefore, according to the calculation results of the plurality of groups, the mutual relationship between the fluid saturation inversion results and the mechanical parameter values can be determined, for example, the mutual relationship between the electrical parameters and the mechanical parameters can be determined by using a curve, as shown in the force-electric cross-physical relationship diagram. Figure 12

[0071] In one embodiment, the mechanical parameter values at least include one or more of Young's modulus, Poisson's ratio and shear modulus; and the mechanical parameter values are obtained according to the following formula:​

[0072]

[0073] Wherein, χ and γ are strain parameters, η is stress parameter, υ is Poisson's ratio, E is Young's modulus, and G is shear modulus.

[0074] In the embodiment of the present application, χ, γ and η can be set and obtained according to actual requirements, and the values of the mechanical parameters can be obtained according to the above formula. Figure 2 The water saturation inversion method is shown in the implementation step schematic diagram, the method obtains various moduli through mechanical finite element simulation of the same geometry, and simultaneously establishes the relationship between the electrical parameters, and the relationship provides a conversion basis from acoustic wave data to electrical parameters.

[0075] The embodiment of the present application provides a fluid saturation inversion method and device, which uses tensor resistivity to invert water saturation, and can realize evaluation of crack morphology. Compared with water saturation inversion using scalar resistivity, the method is more applicable to models such as fractured shale with strong anisotropy, and can obtain more accurate water saturation and crack morphology prediction. The force-electricity cross-calculation method can realize complementary advantages of different measurement methods and measurement data, and can effectively improve the inversion accuracy in actual application.

[0076] Referring to Figures 5-11 The embodiment of the present application considers the calculation method of the medium resistivity tensor, which can effectively characterize the anisotropy of the medium. Compared with the scalar calculation method, the method deeply excavates the geometric information in the equivalent measurement parameter, so that the calculation of resistivity-water saturation is more accurate. In addition, the establishment of the force-electricity cross-physical relationship makes up for the shortcomings of insufficient information of a single measurement method, makes the characterization of geological information more complete, and provides a basis for engineering practice.

[0077] The embodiment of the present application further provides a fluid saturation inversion device, as described in the following embodiment. Since the principle of solving the problem of the device is similar to that of the fluid saturation inversion method, the implementation of the device can be referred to the implementation of the fluid saturation inversion method, and the repeated parts will not be described herein. Referring to Figure 13 A fluid saturation inversion device structure diagram is shown, and the device comprises:

[0078] The acquisition module 71 is used to acquire electromagnetic field parameters based on a spatial rectangular coordinate system; the tensor module 72 is used to generate resistivity tensor data by using the electromagnetic field parameters; the parameter module 73 is used to determine target parameter values in Archie's formula by using the resistivity tensor data; and the inversion module 74 is used to generate a fluid saturation inversion result by using the target parameter values and the Archie's formula.

[0079] In one embodiment, the tensor module is specifically configured to determine resistivity values in three directions of a spatial rectangular coordinate system by solving Maxwell equations respectively; and determine resistivity tensor data according to the resistivity values in the three directions.

[0080] In one embodiment, the parameter module is specifically configured to determine a target parameter value in Archie formula by using the resistivity tensor data, including: calculating an equivalent resistivity value by using the resistivity tensor data; and calculating a tortuosity value by using the resistivity tensor data.

[0081] In one embodiment, the parameter module is specifically configured to calculate the equivalent resistivity value by using the resistivity tensor data according to the following formula: wherein, ρ t is the equivalent resistivity, ρ xx ρ yy ρ zz is a main diagonal line of the resistivity tensor.

[0082] In one embodiment, the parameter module is specifically configured to calculate the tortuosity value by using the resistivity tensor data according to the following formula: a = 2.78 x 10 -5 ρ *4 -0.0032ρ *3 +0.107ρ *2 -ρ * +529, wherein, a is the tortuosity, ρ xy , ρ yz , ρ xz are minor diagonal lines of the resistivity tensor.

[0083] In one embodiment, referring to a structural block diagram of a fluid saturation inversion device shown in Figure 14 The device further comprises a relationship module 75 configured to: acquire corresponding mechanical parameter values of a plurality of fluid saturation inversion results under the same model angle and porosity; determine a mutual relationship between the fluid saturation inversion results and the mechanical parameter values; and when a target mechanical parameter value is received, determine a target fluid saturation inversion result corresponding to the target mechanical parameter value according to the mutual relationship.

[0084] In one embodiment, the mechanical parameter values at least include one or more of Young's modulus, Poisson's ratio and shear modulus; and the relationship module is specifically configured to acquire the mechanical parameter values according to the following formula:

[0085]

[0086] wherein, χ and γ are strain parameters, η is a stress parameter, υ is Poisson's ratio, E is Young's modulus, and G is shear modulus.

[0087] The embodiment of the present application further provides a computer device, referring toFigure 15 The computer device structure schematic block diagram is shown, the computer device includes memory 81, processor 82 and computer program stored on the memory and can run on the processor, the processor implements the step of any one of the above-mentioned fluid saturation inversion method when the computer program is executed.

[0088] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working process of the computer device described above can refer to the corresponding process in the foregoing method embodiment, which will not be repeated here.

[0089] The embodiment of the application also provides a computer readable storage medium, the computer readable storage medium stores the computer program for executing any one of the above-mentioned fluid saturation inversion method.

[0090] Those skilled in the art should understand that the embodiments of the application can be provided as a method, a system or a computer program product. Therefore, the application can adopt a completely hardware embodiment, a completely software embodiment or an embodiment combining software and hardware aspects. Moreover, the application can adopt the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program codes.

[0091] The application is described with reference to flowcharts and / or block diagrams of the method, device (system) and computer program product according to the embodiments of the application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 The function specified in one flow or multiple flows and / or blocks. Figure 1 The function specified in one flow or multiple flows and / or blocks.

[0092] These computer program instructions can also be stored in a computer readable storage medium, which can guide the computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer readable storage medium produce a product including instruction devices, which implement the functions specified in the flowcharts and / or block diagrams. Figure 1 The function specified in one flow or multiple flows and / or blocks. Figure 1 The function specified in one flow or multiple flows and / or blocks.

[0093] These computer program instructions can also be loaded into a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The flowchart blocks Figure 1 The flowchart blocks

[0094] Finally, it should be noted that the above-described embodiments are merely exemplary of the application and should not be used to limit its scope, and that the scope of the application is defined by the appended claims. Although the application has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. Accordingly, it is intended to embrace all such alternatives, modifications and variations as fall within the scope of the claims appended hereto.

Claims

1. A fluid saturation inversion method characterized by, The method comprises the following steps: obtaining electromagnetic field parameters based on a spatial rectangular coordinate system; generating resistivity tensor data by using the electromagnetic field parameters; determining target parameter values in Archie formula by using the resistivity tensor data; generating fluid saturation inversion results by using the target parameter values and the Archie formula; generating resistivity tensor data by using the electromagnetic field parameters, comprising: determining the electric field intensity and the current density in three directions of the spatial rectangular coordinate system by solving Maxwell equations respectively, and then calculating the resistivity values in three directions of the spatial rectangular coordinate system by using the following formula respectively, so that the electric field in each direction generates equivalent resistivity data in three directions: wherein E x , E y , E z are the electric field strengths in the three directions of a spatial rectangular coordinate system, J x , J y , J z are the current densities in the three directions of a spatial rectangular coordinate system, p xx , p xy , p xz , p yx , p yy , p yz , p zx , p xy , p zz are the equivalent resistivity data in the three directions of a spatial rectangular coordinate system, respectively, generated by the electric field in the three directions. First pass to obtain resistivity values in a first direction Second pass to obtain resistivity values in a second direction Third pass to obtain resistivity values in a third direction Combining the resistivity values in the three directions to obtain resistivity tensor data 2. The method of claim 1, wherein, the target parameter values at least include equivalent resistivity values and tortuosity values; determining the target parameter values in Archie formula by using the resistivity tensor data, comprising: calculating the equivalent resistivity values by using the resistivity tensor data; calculating the tortuosity values by using the resistivity tensor data.

3. The method of claim 2, wherein, calculating the equivalent resistivity values by using the resistivity tensor data according to the following formula: where p t is the equivalent resistivity, p xx p yy p zz is the principal diagonal of the resistivity tensor.

4. The method of claim 2, wherein, calculating the tortuosity values by using the resistivity tensor data according to the following formula: a = 2.78 x 10 -5 p *4 -0.0032 p *3 +0.107 p *2 - p * + 529 where a is the degree of curvature, p xy , p yz , p xz are the off-diagonals of the resistivity tensor.

5. The method of claim 1, wherein, further comprising the following steps: obtaining mechanical parameter values corresponding to the fluid saturation inversion results under the condition that the model angles and the porosities are the same; determining the mutual relationship between the fluid saturation inversion results and the mechanical parameter values; when the target mechanical parameter value is received, determining the target fluid saturation inversion result corresponding to the target mechanical parameter value according to the mutual relationship.

6. The method of claim 5, wherein, the mechanical parameter values at least include one or more of Young's modulus, Poisson's ratio and shear modulus; the mechanical parameter values are obtained according to the following formula: wherein χ and γ are strain parameters, η is a stress parameter, υ is Poisson's ratio, E is Young's modulus, and G is shear modulus.

7. A fluid saturation inversion apparatus characterized by, The method comprises the following steps: an obtaining module, configured to obtain electromagnetic field parameters based on a spatial rectangular coordinate system; a tensor module, configured to generate resistivity tensor data by using the electromagnetic field parameters; a parameter module, configured to determine target parameter values in Archie formula by using the resistivity tensor data; an inversion module, configured to generate fluid saturation inversion results by using the target parameter values and the Archie formula; the tensor module is specifically configured to: determine the electric field intensity and the current density in three directions of the spatial rectangular coordinate system by solving Maxwell equations respectively, and then calculate the resistivity values in three directions of the spatial rectangular coordinate system by using the following formula respectively, so that the electric field in each direction generates equivalent resistivity data in three directions: wherein E x , E y , E z are the electric field strengths in the three directions of a spatial rectangular coordinate system, J x , J y , J z are the current densities in the three directions of a spatial rectangular coordinate system, and p xx , p xy , p xz , p yx , p yy , p yz , p zx , p zy , p zz are the equivalent resistivity data in the three directions of a spatial rectangular coordinate system, respectively, generated by the electric field in the three directions. First pass to obtain resistivity values in a first direction Second pass to obtain resistivity values in a second direction Third pass to obtain resistivity values in a third direction Combining the resistivity values in the three directions to obtain resistivity tensor data 8. The apparatus of claim 7, wherein, the parameter module is specifically configured to: determine the target parameter values in Archie formula by using the resistivity tensor data, comprising: calculate the equivalent resistivity values by using the resistivity tensor data; calculate the tortuosity values by using the resistivity tensor data.

9. The apparatus of claim 8, wherein, the parameter module is specifically configured to calculate the equivalent resistivity values by using the resistivity tensor data according to the following formula: where p t is the equivalent resistivity, p xx p yy p zz is the principal diagonal of the resistivity tensor.

10. The apparatus of claim 8, wherein, the parameter module is specifically configured to calculate the tortuosity values by using the resistivity tensor data according to the following formula: a = 2.78 x 10 -5 p *4 -0.0032 p *3 +0.107 p *2 - p * +529 where a is the degree of curvature, p xy , p yz , p xz are the off-diagonals of the resistivity tensor.

11. The apparatus of claim 7, wherein, further comprising a relationship module, configured to: Obtaining a plurality of fluid saturation inversion results corresponding to mechanical parameter values under the condition of same model angle and porosity; Determining the mutual relationship between the fluid saturation inversion results and the mechanical parameter values; When a target mechanical parameter value is received, determining a target fluid saturation inversion result corresponding to the target mechanical parameter value according to the mutual relationship.

12. The apparatus of claim 11, wherein, The mechanical parameter values at least include one or more of Young's modulus, Poisson's ratio and shear modulus; and the relationship module is specifically configured to obtain the mechanical parameter values according to the following formula: Wherein, χ and γ are strain parameters, η is a stress parameter, υ is Poisson's ratio, E is Young's modulus, and G is shear modulus.

13. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the method of any one of claims 1 to 6.

14. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the method of any one of claims 1 to 6.

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