Method for establishing fluid saturation prediction model of fractured-vug carbonate rock and method for determining fluid saturation

Abstract

This invention provides a method for establishing a fluid saturation prediction model for fractured-vuggy carbonate rocks and a method for determining fluid saturation. The method for establishing the fluid saturation prediction model includes: based on resistivity data of core samples with different matrix porosities, fracture porosities, and cavern porosities at different water saturations in the study area, a fluid saturation prediction model for the fractured-vuggy carbonate rocks in the study area is determined. This model is a mathematical relationship model of six parameters: core resistivity, water resistivity, water saturation, matrix porosity, fracture porosity, and cavern porosity. The method for determining fluid saturation includes: based on the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity of the target fractured-vuggy carbonate rock, and using the fluid saturation prediction model for fractured-vuggy carbonate rocks in the study area where the target fractured-vuggy carbonate rock is located, the water saturation and / or hydrocarbon saturation of the target fractured-vuggy carbonate rock are determined.

Description

Technical Field

[0001] This specification relates to the field of oil and gas exploration and development technology, and in particular to a technical solution for establishing a prediction model for fluid saturation in fractured-vuggy carbonate rocks and a technical solution for determining fluid saturation in fractured-vuggy carbonate rocks. Background Technology

[0002] The physical properties and logging response mechanisms of deep oil and gas reservoirs, especially deep carbonate reservoirs, differ significantly from those of conventional oil and gas reservoirs. The lithology and pore structure of carbonate rocks in deep carbonate reservoirs are more complex than in conventional reservoirs, exhibiting multiple media such as pores, caverns, and fractures. Rock resistivity experiments show non-Archie phenomena. Resistivity logging curves of deep carbonate reservoirs vary greatly, exhibiting anomalous curves such as high water-resistivity layers and low oil and gas-resistivity layers, making effective reservoir identification and evaluation challenging.

[0003] Currently, digital core modeling and conductivity simulation technologies for fractured-vuggy carbonate rocks with complex pore structures (i.e., fractured-vuggy carbonate rocks) are relatively mature, but quantitative evaluation technologies for oil-bearing potential are still in the initial stages of research. Therefore, it is still necessary to study quantitative evaluation technologies suitable for fractured-vuggy carbonate rocks with complex pore structures (i.e., fractured-vuggy carbonate rocks) to better identify and evaluate effective reservoirs in fractured-vuggy carbonate rocks. Summary of the Invention

[0004] The purpose of this invention is to provide a technical solution for determining the fluid saturation of carbonate rocks with complex porous structures containing fissures and cavities (i.e., fissure-cavity carbonate rocks).

[0005] To achieve the above objectives, the present invention provides the following ten technical solutions.

[0006] In a first aspect, the present invention provides a method for establishing a fluid saturation prediction model for fractured-cavitary carbonate rocks, wherein the method includes:

[0007] Resistivity data of core samples with different matrix porosity, different fracture porosity, and different cave porosity in the fractured-cavity carbonate rock study area were obtained at different water saturation levels.

[0008] Based on resistivity data of core samples with different matrix porosity, fracture porosity, and cavern porosity at different water saturation levels, a fluid saturation prediction model for fracture-cavity carbonate rocks in the study area was determined. The fluid saturation prediction model for fracture-cavity carbonate rocks is a mathematical relationship model of six parameters: core resistivity, water resistivity, water saturation, matrix porosity, fracture porosity, and cavern porosity.

[0009] The pores of fractured-cavity carbonate rocks consist of matrix pores, fractures, and cavities. The porosity of the matrix pores is called matrix porosity, the porosity of the fractures is called fracture porosity, and the porosity of the cavities is called cavity porosity.

[0010] Secondly, the present invention also provides a method for determining the fluid saturation of fractured carbonate rocks, wherein the method includes:

[0011] Obtain the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity of the target fractured carbonate rock.

[0012] The method for establishing a fluid saturation prediction model for fractured carbonate rocks provided in the first aspect of this invention is used to construct a fluid saturation prediction model for fractured carbonate rocks in the study area where the target fractured carbonate rock is located.

[0013] Based on the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity of the target fractured carbonate rock, the water saturation and / or hydrocarbon saturation of the target fractured carbonate rock are determined using a fluid saturation prediction model for fractured carbonate rocks in the study area.

[0014] Thirdly, the present invention provides a device for establishing a fluid saturation prediction model for fractured-cavity carbonate rocks, wherein the device comprises:

[0015] The data acquisition module for model building is used to acquire resistivity data of core samples with different matrix porosity, different fracture porosity, and different cave porosity at different water saturation levels in the fractured-cavity carbonate rock study area.

[0016] Model building module: used to determine the fluid saturation prediction model of fracture-cavity carbonate rocks in the study area based on resistivity data of cores with different matrix porosity, different fracture porosity, and different karst porosity at different water saturation levels; wherein, the fluid saturation prediction model of fracture-cavity carbonate rocks is a mathematical relationship model of six parameters: core resistivity, water resistivity, water saturation, matrix porosity, fracture porosity, and karst porosity.

[0017] The pores of fractured-cavity carbonate rocks consist of matrix pores, fractures, and cavities. The porosity of the matrix pores is called matrix porosity, the porosity of the fractures is called fracture porosity, and the porosity of the cavities is called cavity porosity.

[0018] Fourthly, the present invention also provides a device for determining the fluid saturation of fractured carbonate rocks, wherein the device comprises:

[0019] Target fractured carbonate rock data acquisition module: used to acquire the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity in the target fractured carbonate rock.

[0020] Model for predicting fluid saturation in fractured-cavitary carbonate rocks: This model is used to construct a prediction model for fluid saturation in fractured-cavitary carbonate rocks in the study area where the target fractured-cavitary carbonate rocks are located.

[0021] Fluid saturation determination module: Based on the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity of the target fractured carbonate rock, this module uses a fluid saturation prediction model for fractured carbonate rocks in the study area to determine the water saturation and / or hydrocarbon saturation of the target fractured carbonate rock.

[0022] Fifthly, embodiments of this specification also provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for establishing a fractured-cavity carbonate rock fluid saturation prediction model provided in the first aspect.

[0023] In a sixth aspect, embodiments of this specification also provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for determining fluid saturation in fractured carbonate rocks provided in the second aspect.

[0024] In a seventh aspect, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for establishing a fluid saturation prediction model for fractured-cavity carbonate rocks provided in the first aspect.

[0025] Eighthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for determining fluid saturation in fractured carbonate rocks provided in the second aspect.

[0026] In a ninth aspect, the present invention provides a computer program product comprising a computer program that, when executed by a processor, implements the method for establishing a fractured-cavity carbonate rock fluid saturation prediction model provided in the first aspect.

[0027] In a tenth aspect, the present invention provides a computer program product comprising a computer program that, when executed by a processor, implements the method for determining fluid saturation in fractured carbonate rocks provided in the second aspect.

[0028] The technical solution provided by this invention can determine the fluid saturation of carbonate rocks with complex porous structures containing fractures and cavities (i.e., fractured-cavity carbonate rocks), thereby promoting the identification and evaluation of effective reservoirs in fractured-cavity carbonate rocks. It has high application value in the analysis of factors affecting rock conductivity and the evaluation of reservoir saturation, laying the foundation for guiding the exploration and development of deep oil and gas reservoirs, and has broad application prospects. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. The drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is a flowchart illustrating the method for establishing a fluid saturation prediction model for fractured-cavity carbonate rocks in the embodiments of this specification.

[0031] Figure 2 This is a flowchart illustrating the method for determining fluid saturation in fractured carbonate rocks as described in the embodiments of this specification.

[0032] Figure 3 This is a schematic diagram of a three-dimensional digital core model of the rock skeleton and matrix pores in Example 1 of this specification.

[0033] Figure 4 This is a schematic diagram of the three-dimensional digital B-type core model in Example 1 of this specification.

[0034] Figure 5 This is a schematic diagram of the three-dimensional digital C-type core model in Example 1 of this specification.

[0035] Figure 6 This is a comparison diagram of the potential distribution and current density distribution of the three-dimensional digital A-type core model, three-dimensional digital B-type core model, and three-dimensional digital C-type core model in Example 1 of this specification.

[0036] Figure 7 Example 1 of this specification Fitted plot in double logarithmic coordinates.

[0037] Figure 8 Example 1 of this specification Fitted plot in double logarithmic coordinates.

[0038] Figure 9 IS in Example 1 of this specification w Fitted plot in double logarithmic coordinates.

[0039] Figure 10Example 1 of this specification Fitted graph in coordinate system.

[0040] Figure 11 IS in Example 1 of this specification w Fitted plot in double logarithmic coordinates.

[0041] Figure 12 Example 1 of this specification Fitted plot in double logarithmic coordinates.

[0042] Figure 13 Example 1 of this specification Fitted plot in double logarithmic coordinates.

[0043] Figure 14 This is a graph showing the well logging data and water saturation prediction data from Example 1 of this specification. Detailed Implementation

[0044] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. The specific embodiments described herein are only used to explain this disclosure, and not to limit this disclosure. All other embodiments obtained by those skilled in the art based on the described embodiments of this disclosure are within the scope of protection of this disclosure. In addition, relational terms such as "first" and "second" 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.

[0045] Please see Figure 1 This invention provides a method for establishing a fluid saturation prediction model for fractured-vuggy carbonate rocks, wherein the method includes:

[0046] Step S11: Obtain resistivity data of cores with different matrix porosity, different fracture porosity, and different cave porosity in the fractured carbonate rock study area at different water saturation levels.

[0047] Step S12: Based on the resistivity data of cores with different matrix porosity, different fracture porosity, and different cavern porosity at different water saturation levels, determine the fluid saturation prediction model for fracture-cavity carbonate rocks in the study area; wherein, the fluid saturation prediction model for fracture-cavity carbonate rocks is a mathematical relationship model of six parameters: core resistivity, water resistivity, water saturation, matrix porosity, fracture porosity, and cavern porosity.

[0048] The pores of fractured-cavity carbonate rocks consist of matrix pores, fractures, and cavities. The porosity of the matrix pores is called matrix porosity, the porosity of the fractures is called fracture porosity, and the porosity of the cavities is called cavity porosity.

[0049] In some embodiments, resistivity data of cores with different matrix porosity, different fracture porosity, and different cavern porosity in the fractured-cavity carbonate rock study area at different water saturation levels include:

[0050] Resistivity data of Type A cores with different matrix porosity at 100% water saturation, resistivity data of Type B cores with different fracture porosity at 100% water saturation, resistivity data of Type C cores with different karst cave porosity at 100% water saturation, resistivity data of Type A cores at different water saturation, resistivity data of Type B cores with different fracture porosity at different water saturation, and resistivity data of Type C cores with different karst cave porosity at different water saturation;

[0051] Among them, the pore structure of Class A cores contains only matrix pores and no cracks or cavities; the pore structure of Class B cores contains matrix pores and cracks but no cavities; and the pore structure of Class C cores contains matrix pores, cracks, and cavities.

[0052] In some embodiments, the resistivity data of Class B cores with different fracture porosities at 100% water saturation are the resistivity data of Class B cores with different fracture porosities but the same matrix porosity at 100% water saturation.

[0053] In some embodiments, the resistivity data of Class C cores with different cave porosity at 100% water saturation are resistivity data of Class C cores with different cave porosity at 100% water saturation, where the matrix porosity and fracture porosity are the same.

[0054] In some embodiments, the resistivity data of Class A cores at different water saturation levels are resistivity data of Class A cores with the same matrix porosity at different water saturation levels.

[0055] In some embodiments, the resistivity data of Type B cores with different fracture porosities at different water saturation levels are the resistivity data of Type B cores with the same matrix porosity but different fracture porosities at different water saturation levels.

[0056] In some embodiments, the resistivity data of Class C cores with different cave porosity at different water saturation levels are resistivity data of Class C cores with different cave porosity at different water saturation levels, where the matrix porosity and fracture porosity are the same.

[0057] In some embodiments, step S11 includes:

[0058] Three-dimensional digital core models of fractured-cavity carbonate rocks with different matrix porosity, different fracture porosity, and different cave porosity were constructed in the study area.

[0059] The oil-water distribution or gas-water distribution under different water saturation conditions were simulated for each three-dimensional digital core model, and then the current physical field was simulated for each model. The resistivity data of each three-dimensional digital core model under different water saturation conditions were determined as the resistivity data of cores with different matrix porosity, different fracture porosity, and different karst porosity under different water saturation conditions.

[0060] In these embodiments, resistivity data of core samples with different matrix porosity, different fracture porosity, and different karst porosity under different water saturation levels are obtained by simulating the physical field of the current in three-dimensional digital core models with different matrix porosity, different fracture porosity, and different karst porosity under different water saturation levels.

[0061] In some embodiments, simulating the oil-water distribution or gas-water distribution under different water saturation levels for each three-dimensional digital core model can be performed, but is not limited to, using existing oil-water distribution or gas-water distribution simulation methods, such as mathematical morphology simulation. In one specific embodiment, the following opening operation is used for mathematical morphology simulation:

[0062]

[0063] In the formula, A is the data set of the three-dimensional digital core model; B is the data set of the structural elements of the three-dimensional digital core model. The structural elements are usually spheres with a certain radius or cubes with a certain side length. ! represents the opening operation between A and B; ! represents the erosion operator; For expansion operators; corrosion and expansion are both basic operations in mathematical morphology. The distribution of fluid in pores is simulated by first corroding and then expanding the fluid pores.

[0064] In these embodiments, mathematical morphology is used to simulate the oil and water distribution in a three-dimensional digital core model.

[0065] In some embodiments, current physical field simulation can be performed, but is not limited to, using existing core current physical field simulation methods;

[0066] For example, the generated surface module in Avizo was used to generate meshes for each 3D digital core model after the oil-water distribution or gas-water distribution simulation was completed. The mesh size was then adjusted and optimized in the Meshing module. The mesh was then imported into COMSOL software. Current physics and steady-state study were selected. The two sides of the 3D digital core model along the z-axis were selected as the current inlet and outlet. The potentials of the current inlet and outlet and the conductivity of the pore fluid were set. The potentials and current densities at each node and the resistivity of the entire 3D digital core model were calculated. Optional steps included: visualizing the potentials and current densities of the 3D digital core model and dividing the conductive structure according to the current density.

[0067] In these embodiments, the electric potential, current density, and overall resistivity of the three-dimensional digital core model are calculated using the finite element method, and the conductive structure is divided based on the electric field visualization.

[0068] In some embodiments, the three-dimensional digital core models with different matrix porosity, different fracture porosity, and different karst cave porosity include three-dimensional digital Class A core models with different matrix porosity, three-dimensional digital Class B core models with different fracture porosity, and three-dimensional digital Class C core models with different karst cave porosity.

[0069] Among them, the pore structure of the Type A core model contains only matrix pores and does not contain cracks or cavities; the pore structure of the Type B core model contains matrix pores and cracks but does not contain cavities; and the pore structure of the Type C core model contains matrix pores, cracks, and cavities.

[0070] In some embodiments, the step of constructing a three-dimensional digital core model of the fractured-cavity carbonate rock study area with different matrix porosity, different fracture porosity, and different cavern porosity includes:

[0071] X-CT scans of core samples from the fractured-cavity carbonate rock study area were obtained;

[0072] Based on the X-CT scan images of core samples from the fractured-cavity carbonate rock study area, three-dimensional digital core models of the rock skeleton and matrix pores, three-dimensional digital core models of fractures, and three-dimensional digital core models of caves were constructed for the core samples.

[0073] Based on the three-dimensional digital core models of the rock skeleton and matrix porosity, the three-dimensional digital core models of fractures and karst caves, three-dimensional digital A-type core models with different matrix porosity, three-dimensional digital B-type core models with different fracture porosity, and three-dimensional digital C-type core models with different karst cave porosity were constructed.

[0074] In some embodiments, based on X-CT scans of core samples from fractured-cavity carbonate rock study areas, three-dimensional digital core models of the rock skeleton and matrix pores, three-dimensional digital core models of fractures, and three-dimensional digital core models of caves of the core samples can be constructed, but are not limited to, in the following ways:

[0075] X-CT scans of core samples from the fractured-cavity carbonate rock study area were converted into grayscale images and imported into Avizo software. Thresholding was performed using the interactive thresholding module. By selecting an appropriate threshold range, the segmented images yielded three-dimensional digital core models of the rock skeleton and matrix pores, three-dimensional digital core models of fractures, and three-dimensional digital core models of karst caves. Among these, the parts with uniform and continuous matrix pore distribution were selected as the three-dimensional digital core models of the rock skeleton and matrix pores.

[0076] In some embodiments, based on the three-dimensional digital core model of the rock skeleton and matrix porosity, the three-dimensional digital core model of fractures, and the three-dimensional digital core model of karst caves, three-dimensional digital Class A core models with different matrix porosity, three-dimensional digital Class B core models with different fracture porosity, and three-dimensional digital Class C core models with different karst cave porosity can be constructed, but are not limited to, through the following methods:

[0077] Based on the obtained three-dimensional digital core model of rock skeleton and matrix porosity, three-dimensional digital Class A core models with different matrix porosities were constructed.

[0078] The fractures in the three-dimensional digital core model of the fracture were rotated and scaled to construct three-dimensional digital core models of fractures with different fracture porosities.

[0079] By rotating and scaling the karst caves in the three-dimensional digital core model, three-dimensional digital core models of karst caves with different porosities are constructed.

[0080] By superimposing the three-dimensional digital core models of rock skeleton and matrix porosity and three-dimensional digital core models of fractures with different fracture porosity using the Arithmetic module in Avizo, three-dimensional digital B-type core models with different fracture porosity are constructed.

[0081] By using the Arithmetic module in Avizo, three-dimensional digital core models of rock skeleton and matrix pores, three-dimensional digital core models of fractures, and three-dimensional digital core models of karst caves with different porosities are superimposed with karst caves, fractures, and matrix pores to construct three-dimensional digital C-type core models with different karst cave porosities.

[0082] In these embodiments, digital cores are constructed using CT scanning technology, and the extracted fractures and caverns are varied in size to create three-dimensional digital core models containing fractures and caverns with different fracture porosities and cavern porosities.

[0083] In some embodiments, the fluid saturation prediction model for fractured carbonate rocks is as follows:

[0084]

[0085] In the formula, R t R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. The value represents crack porosity, and the unit is dimensionless. S represents the porosity of the karst cave, with dimensionsless units; w α1 represents water saturation, dimensionless; m2 represents matrix porosity index; m3 represents fracture porosity index; m4 represents cavern porosity index; a1 represents the first lithology coefficient; a2 represents the second lithology coefficient; n1 represents matrix porosity saturation index; n2 represents fracture saturation index; α3 represents the first fracture saturation index coefficient; β3 represents the second fracture saturation index coefficient; α1 represents the first cavern coefficient; β1 represents the second cavern coefficient; α2 represents the third cavern coefficient; β2 represents the fourth cavern coefficient.

[0086] The above-mentioned fluid saturation prediction model for fractured-vuggy carbonate rocks is based on the study of the conductivity response mechanism of micropores in carbonate rocks under the conductivity structure theory. It is established by taking the conductivity structure as the starting point and transforming the conductivity simulation idea of ​​rocks. It has high simulation result accuracy and high conductivity characteristic description ability. It can predict the saturation of fractured-vuggy carbonate rocks and evaluate reservoirs, thus effectively solving the problem of oil-bearing evaluation in carbonate rock reservoir evaluation.

[0087] In some embodiments, step S12 includes:

[0088] Based on the resistivity data of Class A cores with different matrix porosities at 100% water saturation, Equation 1 was fitted to determine the matrix porosity index m1; wherein, the pore structure of Class A cores contains only matrix pores and does not contain cracks or cavities.

[0089] Relation 1 is:

[0090] In the formula, R t R represents the resistivity of the core sample (here, the resistivity of the core sample at 100% water saturation), in Ω·m. w Ω·m is the resistivity of water. denoted as matrix porosity, with dimensionless units; m1 is the matrix porosity index; a′ is a parameter determined during the fitting of Equation 1.

[0091] Based on the resistivity data of Class B cores with different fracture porosity at 100% water saturation, and combined with the matrix porosity index m1, Equation 2 was fitted to determine the fracture porosity index m2; wherein, the pore structure of Class B cores includes matrix porosity and fractures but does not contain karst caves.

[0092] Relation 2 is:

[0093] In the formula, R t R represents the resistivity of the core sample (here, the resistivity of the core sample at 100% water saturation), in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. , where m1 is the matrix porosity, and m2 is the fracture porosity; a″ is a parameter determined during the fitting of Equation 2.

[0094] Based on the resistivity data of Class C cores with different karst porosity at 100% water saturation, and combined with the matrix porosity index m1 and fracture porosity index m2, Equation 3 was fitted to determine the first lithology coefficient a1, the second lithology coefficient a2, and the karst porosity index m3; wherein, the pore structure of Class C cores includes matrix porosity, fractures, and karst caves.

[0095] Relation 3 is:

[0096] In the formula, R t R represents the resistivity of the core sample (here, the resistivity of the core sample at 100% water saturation), in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. The value represents crack porosity, and the unit is dimensionless. m1 is the porosity of the karst cave, in dimensionless units; m2 is the matrix porosity index; m3 is the fracture porosity index; a1 is the first lithological coefficient; a2 is the second lithological coefficient.

[0097] Based on the resistivity data of Class A cores at different water saturation levels, Equation 4 was fitted to determine the matrix pore saturation index n1.

[0098] Relation 4 is:

[0099] In the formula, R tThe resistivity of the core (here, the resistivity of the core at water saturation S) w Resistivity at 100% water saturation (in Ω·m); R0 is the resistivity of the core at 100% water saturation (in Ω·m); S w is the water saturation, with dimensionless units; n1 is the matrix porosity saturation index; b′ is a parameter, determined during the fitting of relation 4;

[0100] Based on the resistivity data of Class B cores with different fracture porosity at different water saturation levels, and combined with the matrix porosity saturation index n1, Equation 5 was fitted to determine the coefficient α3 of the first fracture saturation index and the coefficient β3 of the second fracture saturation index.

[0101] Relation 5 is: in

[0102] In the formula, R t The resistivity of the core (here, the resistivity of the core at water saturation S) w The resistivity of the core at 100% water saturation is expressed in Ω·m; R0 is the resistivity of the core at 100% water saturation, expressed in Ω·m. S represents crack porosity, with dimensionless units. w α is the water saturation, dimensionless; n1 is the matrix porosity saturation index; n2 is the fracture saturation index; α3 is the coefficient of the first fracture saturation index; β3 is the coefficient of the second fracture saturation index; b″ is a parameter, determined during the fitting of relation 5.

[0103] Based on the resistivity data of Class C cores with different karst porosity at different water saturation levels, and combined with the matrix porosity saturation index n1, the first fracture saturation index coefficient α3, and the second fracture saturation index coefficient β3, Equation 6 was fitted to determine the first karst coefficient α1, the second karst coefficient β1, the third karst coefficient α2, and the fourth karst coefficient β2.

[0104] Relation 6 is:

[0105] in

[0106] In the formula, R t The resistivity of the core (here, the resistivity of the core at water saturation S) w The resistivity of the core at 100% water saturation is expressed in Ω·m; R0 is the resistivity of the core at 100% water saturation, expressed in Ω·m. The value represents crack porosity, and the unit is dimensionless. S represents the porosity of the karst cave, with dimensionsless units; wα1 represents water saturation, dimensionless; n1 represents matrix porosity saturation index; n2 represents fracture saturation index; α3 represents the first fracture saturation index coefficient; β3 represents the second fracture saturation index coefficient; α1 represents the first karst coefficient; β1 represents the second karst coefficient; α2 represents the third karst coefficient; β2 represents the fourth karst coefficient; b1 represents the third lithology coefficient; b2 represents the fourth lithology coefficient.

[0107] Based on the matrix porosity saturation index n1, the first fracture saturation index coefficient α3, the second fracture saturation index coefficient β3, the first cavern coefficient α1, the second cavern coefficient β1, the third cavern coefficient α2, the fourth cavern coefficient β2, the matrix porosity index m1, the fracture porosity index m2, the first lithology coefficient a1, the second lithology coefficient a2, and the cavern porosity index m3, a fluid saturation prediction model for fractured-cavitary carbonate rocks was determined; the fluid saturation prediction model for fractured-cavitary carbonate rocks is as follows:

[0108]

[0109] In the formula, R t R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. The value represents crack porosity, and the unit is dimensionless. S represents the porosity of the karst cave, with dimensionsless units; w α1 represents water saturation, unit is dimensionless; m2 represents matrix porosity index; m3 represents cavern porosity index; a1 represents the first lithological coefficient; a2 represents the second lithological coefficient; n1 represents matrix porosity saturation index; n2 represents fracture saturation index; α3 represents the first fracture saturation index coefficient; β3 represents the second fracture saturation index coefficient; α1 represents the first cavern coefficient; β1 represents the second cavern coefficient; α2 represents the third cavern coefficient; β2 represents the fourth cavern coefficient.

[0110] In some embodiments, the step of fitting Equation 5 based on resistivity data of Type B cores with different fracture porosities at different water saturations, combined with the matrix porosity saturation index n1, to determine the first fracture saturation index coefficient α3 and the second fracture saturation index coefficient β3 includes:

[0111] Based on the resistivity data of Type B cores with varying fracture porosity at different water saturations, and combined with the matrix porosity saturation index n1, the relationships in Equation 5 are respectively... By performing fitting, the crack saturation index n2 corresponding to each crack porosity is determined;

[0112] Based on the crack saturation index n2 corresponding to each crack porosity, the relationship in Equation 5 is... By fitting the data, the coefficients of the first crack saturation index α3 and the second crack saturation index β3 were determined.

[0113] In some embodiments, the step of fitting Equation 6 to determine the first cavern coefficient α1, the second cavern coefficient β1, the third cavern coefficient α2, and the fourth cavern coefficient β2 based on resistivity data of Class C cores with different cavern porosities at different water saturation levels, combined with matrix porosity saturation index n1, first fracture saturation index coefficient α3, and second fracture saturation index coefficient β3, includes:

[0114] Based on the resistivity data of Class C cores with varying porosity at different water saturation levels, and combined with the matrix porosity saturation index n1, the first fracture saturation index coefficient α3, and the second fracture saturation index coefficient β3, the relationships in Equation 6 are respectively... By performing fitting, the third lithological coefficient b1 and the fourth lithological coefficient b2 corresponding to the porosity of each karst cave were determined;

[0115] Based on the third lithology coefficient b1 and the fourth lithology coefficient b2 corresponding to the porosity of each karst cave, the relationship in Equation 6 is... By fitting the data, the first cave coefficient α1, the second cave coefficient β1, the third cave coefficient α2, and the fourth cave coefficient β2 were determined.

[0116] See Figure 2 This invention provides a method for determining the fluid saturation of fractured carbonate rocks, wherein the method includes:

[0117] Step S21: Obtain the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity in the target fractured carbonate rock.

[0118] Step S22: Construct a fluid saturation prediction model for fractured-cavitary carbonate rocks in the study area where the target fractured-cavitary carbonate rock is located using the method for establishing a fluid saturation prediction model for fractured-cavitary carbonate rocks provided in the embodiments of the present invention;

[0119] Step S23: Based on the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity in the target fractured carbonate rock, the water saturation and / or hydrocarbon saturation of the target fractured carbonate rock are determined using the fluid saturation prediction model for fractured carbonate rocks in the study area where the target fractured carbonate rock is located.

[0120] In some embodiments, step S21 includes:

[0121] Obtain resistivity logging data of the target fractured carbonate rock, and then determine the resistivity of the target fractured carbonate rock based on the resistivity logging data of the target fractured carbonate rock;

[0122] Porosity logging data, nuclear magnetic resonance logging data, and electrical imaging logging data of the target fractured carbonate rock are obtained. Then, based on the porosity logging data, nuclear magnetic resonance logging data, and electrical imaging logging data of the target fractured carbonate rock, the matrix porosity, fracture porosity, and cavern porosity of the target fractured carbonate rock are determined.

[0123] Obtain the resistivity of water in the target fractured carbonate rock;

[0124] In determining the matrix porosity, fracture porosity, and cavern porosity of the target fractured carbonate rock based on porosity logging data, nuclear magnetic resonance logging data, and electrical imaging logging data, existing methods for determining matrix porosity, fracture porosity, and cavern porosity based on porosity logging data, nuclear magnetic resonance logging data, and electrical imaging logging data can be used, but are not limited to.

[0125] This specification provides an apparatus for establishing a fluid saturation prediction model for fractured-cavity carbonate rocks, as described in the following embodiments. Since the principle underlying this apparatus is similar to the method for establishing a fluid saturation prediction model for fractured-cavity carbonate rocks, the implementation of this apparatus can refer to the implementation of the method for establishing a fluid saturation prediction model for fractured-cavity carbonate rocks; repeated details will not be elaborated further.

[0126] The apparatus for establishing a fluid saturation prediction model for fractured-cavity carbonate rocks provided in this embodiment of the invention includes:

[0127] The data acquisition module for model building is used to acquire resistivity data of core samples with different matrix porosity, different fracture porosity, and different cave porosity at different water saturation levels in the fractured-cavity carbonate rock study area.

[0128] Model building module: used to determine the fluid saturation prediction model of fracture-cavity carbonate rocks in the study area based on resistivity data of cores with different matrix porosity, different fracture porosity, and different karst porosity at different water saturation levels; wherein, the fluid saturation prediction model of fracture-cavity carbonate rocks is a mathematical relationship model of six parameters: core resistivity, water resistivity, water saturation, matrix porosity, fracture porosity, and karst porosity.

[0129] The pores of fractured-cavity carbonate rocks consist of matrix pores, fractures, and cavities. The porosity of the matrix pores is called matrix porosity, the porosity of the fractures is called fracture porosity, and the porosity of the cavities is called cavity porosity.

[0130] In some embodiments, resistivity data of cores with different matrix porosity, different fracture porosity, and different cavern porosity in the fractured-cavity carbonate rock study area at different water saturation levels include:

[0131] Resistivity data of Type A cores with different matrix porosity at 100% water saturation, resistivity data of Type B cores with different fracture porosity at 100% water saturation, resistivity data of Type C cores with different karst cave porosity at 100% water saturation, resistivity data of Type A cores at different water saturation, resistivity data of Type B cores with different fracture porosity at different water saturation, and resistivity data of Type C cores with different karst cave porosity at different water saturation;

[0132] Among them, the pore structure of Class A cores contains only matrix pores and no cracks or cavities; the pore structure of Class B cores contains matrix pores and cracks but no cavities; and the pore structure of Class C cores contains matrix pores, cracks, and cavities.

[0133] In some embodiments, the resistivity data of Class B cores with different fracture porosities at 100% water saturation are the resistivity data of Class B cores with different fracture porosities but the same matrix porosity at 100% water saturation.

[0134] In some embodiments, the resistivity data of Class C cores with different cave porosity at 100% water saturation are resistivity data of Class C cores with different cave porosity at 100% water saturation, where the matrix porosity and fracture porosity are the same.

[0135] In some embodiments, the resistivity data of Class A cores at different water saturation levels are resistivity data of Class A cores with the same matrix porosity at different water saturation levels.

[0136] In some embodiments, the resistivity data of Type B cores with different fracture porosities at different water saturation levels are the resistivity data of Type B cores with the same matrix porosity but different fracture porosities at different water saturation levels.

[0137] In some embodiments, the resistivity data of Class C cores with different cave porosity at different water saturation levels are resistivity data of Class C cores with different cave porosity at different water saturation levels, where the matrix porosity and fracture porosity are the same.

[0138] In some embodiments, the data acquisition module for model building includes:

[0139] The 3D digital core model construction submodule is used to construct 3D digital core models with different matrix porosity, different fracture porosity, and different cavern porosity in the fractured-cavity carbonate rock research area.

[0140] The model establishment data determination submodule is used to simulate the oil-water distribution or gas-water distribution of each three-dimensional digital core model under different water saturation, and then to simulate the current physical field to determine the resistivity data of each three-dimensional digital core model under different water saturation as the resistivity data of cores with different matrix porosity, different fracture porosity, and different karst porosity under different water saturation.

[0141] In some embodiments, the three-dimensional digital core models with different matrix porosity, different fracture porosity, and different karst porosity include three-dimensional digital Class A core models with different matrix porosity, three-dimensional digital Class B core models with different fracture porosity, and three-dimensional digital Class C core models with different karst porosity; wherein, the pore structure of the Class A core model contains only matrix porosity and does not contain fractures or karst caves; the pore structure of the Class B core model contains matrix porosity and fractures but does not contain karst caves; and the pore structure of the Class C core model contains matrix porosity, fractures, and karst caves.

[0142] In some embodiments, the three-dimensional digital core model construction submodule includes:

[0143] Core sample scanning image acquisition unit: used to acquire X-CT scan images of core samples from the fractured-cavity carbonate rock study area;

[0144] The first core sample model construction unit is used to construct three-dimensional digital core models of the rock skeleton and matrix pores, fractures, and caves based on the X-CT scan images of core samples from the fractured carbonate rock research area.

[0145] The second core sample model construction unit is used to construct three-dimensional digital core models with different matrix porosities, three-dimensional digital core models with different fracture porosities, and three-dimensional digital core models with different karst cave porosities based on the three-dimensional digital core models of the rock skeleton and matrix porosity, the three-dimensional digital core models of fractures, and the three-dimensional digital core models of karst caves.

[0146] In some embodiments, the fluid saturation prediction model for fractured carbonate rocks is as follows:

[0147]

[0148] In the formula, R t R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. The value represents crack porosity, and the unit is dimensionless. S represents the porosity of the karst cave, with dimensionsless units; wα1 represents water saturation, unit is dimensionless; m2 represents matrix porosity index; m3 represents cavern porosity index; a1 represents the first lithological coefficient; a2 represents the second lithological coefficient; n1 represents matrix porosity saturation index; n2 represents fracture saturation index; α3 represents the first fracture saturation index coefficient; β3 represents the second fracture saturation index coefficient; α1 represents the first cavern coefficient; β1 represents the second cavern coefficient; α2 represents the third cavern coefficient; β2 represents the fourth cavern coefficient.

[0149] In some embodiments, the model building module 12 includes:

[0150] The first fitting submodule is used to fit Equation 1 to the resistivity data of Class A cores with different matrix porosities at 100% water saturation, and determine the matrix porosity index m1; wherein, the pore structure of Class A cores contains only matrix pores and does not contain cracks or caves.

[0151] Relation 1 is:

[0152] In the formula, R t R represents the resistivity of the core sample (here, the resistivity of the core sample at 100% water saturation), in Ω·m. w Ω·m is the resistivity of water. denoted as matrix porosity, with dimensionless units; m1 is the matrix porosity index; a′ is a parameter determined during the fitting of Equation 1.

[0153] The second fitting submodule is used to fit the resistivity data of Class B cores with different fracture porosity at 100% water saturation, and combine it with the matrix porosity index m1 to fit Equation 2 to determine the fracture porosity index m2; wherein, the pore structure of Class B cores includes matrix pores and fractures but does not include karst caves.

[0154] Relation 2 is:

[0155] In the formula, R t R represents the resistivity of the core sample (here, the resistivity of the core sample at 100% water saturation), in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. , where m1 is the matrix porosity, and m2 is the fracture porosity; a″ is a parameter determined during the fitting of Equation 2.

[0156] The third fitting submodule is used to fit the resistivity data of Class C cores with different karst porosity at 100% water saturation, and combine the matrix porosity index m1 and the fracture porosity index m2 to the relation 3 to determine the first lithology coefficient a1, the second lithology coefficient a2 and the karst porosity index m3; wherein, the pore structure of Class C cores includes matrix porosity, fractures and karst caves;

[0157] Relation 3 is:

[0158] In the formula, R t R represents the resistivity of the core sample (here, the resistivity of the core sample at 100% water saturation), in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. The value represents crack porosity, and the unit is dimensionless. m1 is the porosity of the karst cave, in dimensionless units; m2 is the matrix porosity index; m3 is the fracture porosity index; a1 is the first lithological coefficient; a2 is the second lithological coefficient.

[0159] The fourth fitting submodule is used to fit Equation 4 based on resistivity data of Class A cores at different water saturation levels, and determine the matrix pore saturation index n1.

[0160] Relation 4 is:

[0161] In the formula, R t The resistivity of the core (here, the resistivity of the core at water saturation S) w Resistivity at 100% water saturation (in Ω·m); R0 is the resistivity of the core at 100% water saturation (in Ω·m); S w is the water saturation, with dimensionless units; n1 is the matrix porosity saturation index; b′ is a parameter, determined during the fitting of relation 4;

[0162] The fifth fitting submodule is used to fit the resistivity data of Class B cores with different fracture porosities at different water saturation levels, and to combine the matrix porosity saturation index n1 to fit Equation 5, thereby determining the first fracture saturation index coefficient α3 and the second fracture saturation index coefficient β3.

[0163] Relation 5 is: in

[0164] In the formula, R t The resistivity of the core (here, the resistivity of the core at water saturation S) wThe resistivity of the core at 100% water saturation is expressed in Ω·m; R0 is the resistivity of the core at 100% water saturation, expressed in Ω·m. S represents crack porosity, with dimensionless units. w α is the water saturation, dimensionless; n1 is the matrix porosity saturation index; n2 is the fracture saturation index; α3 is the coefficient of the first fracture saturation index; β3 is the coefficient of the second fracture saturation index; b″ is a parameter, determined during the fitting of relation 5.

[0165] The sixth fitting submodule is used to fit the resistivity data of Class C cores with different karst porosity at different water saturation levels, and to combine the matrix porosity saturation index n1, the first fracture saturation index coefficient α3, and the second fracture saturation index coefficient β3 to the relation 6, and to determine the first karst coefficient α1, the second karst coefficient β1, the third karst coefficient α2, and the fourth karst coefficient β2.

[0166] Relation 6 is:

[0167] in

[0168] In the formula, R t The resistivity of the core (here, the resistivity of the core at water saturation S) w The resistivity of the core at 100% water saturation is expressed in Ω·m; R0 is the resistivity of the core at 100% water saturation, expressed in Ω·m. The value represents crack porosity, and the unit is dimensionless. S represents the porosity of the karst cave, with dimensionsless units; w α1 represents water saturation, dimensionless; n1 represents matrix porosity saturation index; n2 represents fracture saturation index; α3 represents the first fracture saturation index coefficient; β3 represents the second fracture saturation index coefficient; α1 represents the first karst coefficient; β1 represents the second karst coefficient; α2 represents the third karst coefficient; β2 represents the fourth karst coefficient; b1 represents the third lithology coefficient; b2 represents the fourth lithology coefficient.

[0169] The model determination submodule is used to determine the fluid saturation prediction model for fractured-cavitary carbonate rocks based on the matrix porosity saturation index n1, the first fracture saturation index coefficient α3, the second fracture saturation index coefficient β3, the first cavern coefficient α1, the second cavern coefficient β1, the third cavern coefficient α2, the fourth cavern coefficient β2, the matrix porosity index m1, the fracture porosity index m2, the first lithology coefficient a1, the second lithology coefficient a2, and the cavern porosity index m3. The fluid saturation prediction model for fractured-cavitary carbonate rocks is as follows:

[0170]

[0171] In the formula, Rt R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. The value represents crack porosity, and the unit is dimensionless. S represents the porosity of the karst cave, with dimensionsless units; w α1 represents water saturation, unit is dimensionless; m2 represents matrix porosity index; m3 represents cavern porosity index; a1 represents the first lithological coefficient; a2 represents the second lithological coefficient; n1 represents matrix porosity saturation index; n2 represents fracture saturation index; α3 represents the first fracture saturation index coefficient; β3 represents the second fracture saturation index coefficient; α1 represents the first cavern coefficient; β1 represents the second cavern coefficient; α2 represents the third cavern coefficient; β2 represents the fourth cavern coefficient.

[0172] In some embodiments, the fifth fitting submodule includes:

[0173] Fracture saturation index determination unit: Used to determine the resistivity data of Class B cores at different water saturation levels based on the porosity of each fracture, combined with the matrix porosity saturation index n1, to determine the values ​​in Equation 5. By performing fitting, the crack saturation index n2 corresponding to each crack porosity is determined;

[0174] The crack saturation index coefficient determination unit is used to determine the crack saturation index coefficient n2 in equation 5 based on the crack saturation index n2 corresponding to each crack porosity. By fitting the data, the coefficients of the first crack saturation index α3 and the second crack saturation index β3 were determined.

[0175] In some embodiments, the sixth fitting submodule includes:

[0176] The lithology coefficient determination unit is used to determine the resistivity data of Class C cores at different water saturation levels based on the porosity of each karst cave. It combines the matrix porosity saturation index n1, the first fracture saturation index coefficient α3, and the second fracture saturation index coefficient β3 to determine the coefficients in Equation 6. By performing fitting, the third lithological coefficient b1 and the fourth lithological coefficient b2 corresponding to the porosity of each karst cave were determined;

[0177] The unit for determining the karst cave coefficient is used to determine the coefficients in Equation 6 based on the third lithology coefficient b1 and the fourth lithology coefficient b2 corresponding to the porosity of each karst cave. By fitting the data, the first cave coefficient α1, the second cave coefficient β1, the third cave coefficient α2, and the fourth cave coefficient β2 were determined.

[0178] This specification provides an embodiment of a device for determining the fluid saturation of fractured carbonate rocks, as described in the following embodiments. Since the principle underlying this device is similar to the method for determining the fluid saturation of fractured carbonate rocks, the implementation of this device can refer to the implementation of the method for determining the fluid saturation of fractured carbonate rocks; repeated details will not be elaborated further.

[0179] The device for determining the fluid saturation of fractured carbonate rocks provided in this embodiment of the invention includes:

[0180] Target fractured carbonate rock data acquisition module: used to acquire the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity in the target fractured carbonate rock.

[0181] Model for predicting fluid saturation in fractured-cavitary carbonate rocks: This model is used to construct a prediction model for fluid saturation in fractured-cavitary carbonate rocks in the study area where the target fractured-cavitary carbonate rocks are located.

[0182] Fluid saturation determination module: Based on the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity of the target fractured carbonate rock, this module uses a fluid saturation prediction model for fractured carbonate rocks in the study area to determine the water saturation and / or hydrocarbon saturation of the target fractured carbonate rock.

[0183] In some embodiments, the target fractured carbonate rock data acquisition module includes:

[0184] The first resistivity data acquisition submodule acquires resistivity logging data of the target fractured carbonate rock, and then determines the resistivity of the target fractured carbonate rock based on the resistivity logging data of the target fractured carbonate rock.

[0185] Porosity data acquisition submodule: Acquires porosity logging data, nuclear magnetic resonance logging data, and electrical imaging logging data of the target fractured carbonate rock, and then determines the matrix porosity, fracture porosity, and cavern porosity of the target fractured carbonate rock based on the porosity logging data, nuclear magnetic resonance logging data, and electrical imaging logging data of the target fractured carbonate rock;

[0186] The second resistivity data acquisition submodule acquires the resistivity of water in the target fractured carbonate rock.

[0187] This specification also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for establishing a fluid saturation prediction model for fractured-cavity carbonate rocks provided in this embodiment of the invention.

[0188] This specification also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for determining the fluid saturation of fractured carbonate rocks provided in this embodiment of the invention.

[0189] This specification also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for establishing a fluid saturation prediction model for fractured-cavity carbonate rocks provided in this embodiment of the invention.

[0190] This specification also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for determining fluid saturation in fractured carbonate rocks provided in this embodiment of the invention.

[0191] This specification also provides a computer program product, which includes a computer program that, when executed by a processor, implements the method for establishing a fluid saturation prediction model for fractured-cavity carbonate rocks provided in this embodiment of the invention.

[0192] This specification also provides a computer program product, which includes a computer program that, when executed by a processor, implements the method for determining fluid saturation in fractured carbonate rocks provided in this embodiment of the invention.

[0193] Example 1

[0194] This embodiment provides a method for determining the fluid saturation of fractured carbonate rocks, wherein the method includes:

[0195] 1. Construct a fluid saturation prediction model for fractured carbonate rocks in the study area where the target fractured carbonate rocks are located.

[0196] Specifically, it includes:

[0197] 1.1 Constructing three-dimensional digital core models of fractured-cavitary carbonate rocks in the study area with different matrix porosities, fracture porosities, and cavern porosities. Specifically, this includes:

[0198] 1.1.1 Obtain X-CT scans of multiple core samples from the fractured-cavity carbonate rock study area, and obtain the measured porosity and resistivity of core samples with matrix pores as the main pore structure in the fractured-cavity carbonate rock study area.

[0199] 1.1.2. Convert the X-CT scan images of each core sample into grayscale images and import them into Avizo software. Use the interactive thresholding module to perform threshold segmentation. Select an appropriate threshold range to segment the images to obtain three-dimensional digital core models of the rock skeleton and matrix pores, three-dimensional digital core models of fractures, and three-dimensional digital core models of caves.

[0200] In this model, the portion of grayscale value within the interval [0, 19973] is classified as pores, and the portion within the interval [19974, 655535] is classified as the skeleton. The portion with uniform and continuous pore distribution is selected as the three-dimensional digital core model of the rock skeleton and matrix pores (e.g., ...). Figure 3 (As shown).

[0201] 1.1.3. Based on the acquired three-dimensional digital core models of multiple rock skeletons and matrix porosities, three-dimensional digital A-type core models (400×400×400 voxels) with different matrix porosities were constructed; three-dimensional digital core models of fractures with different porosities (3.12%, 6.25%, 9.35%, 12.47%) were constructed by rotating and scaling the fractures in the three-dimensional digital core model of fractures; three-dimensional digital core models of karst caves with different porosities (3.12%, 6.25%, 9.35%, 12.47%) were constructed by rotating and scaling the karst caves in the three-dimensional digital core model of karst caves. Three-dimensional digital core models of karst caves with different porosities (0.81%, 1.59%, 3.47%, 5.33%, 9.25%, 12.67%) were constructed. Using the Arithmetic module in Avizo, three-dimensional digital core models of a rock skeleton and matrix porosity, and three-dimensional digital core models of fractures with different porosities, were superimposed with matrix porosity to construct three-dimensional digital Class B core models (400×400×400 voxels) with different fracture porosities. The results are as follows: Figure 4 As shown; using the Arithmetic module in Avizo, three-dimensional digital core models of a rock skeleton and matrix pores, a three-dimensional digital core model of a fracture, and three-dimensional digital core models of caves with different porosities were superimposed with the caves, fractures, and matrix pores to construct three-dimensional digital C-type core models (400×400×400 voxels) with different cave porosities. The results are as follows. Figure 5 As shown.

[0202] The pore structure of the Type A core model contains only matrix pores and no cracks or cavities; the pore structure of the Type B core model contains matrix pores and cracks but no cavities; the pore structure of the Type C core model contains matrix pores, cracks, and cavities.

[0203] 1.2. Simulate the oil-water distribution or gas-water distribution at different water saturation levels for each 3D digital core model, and then perform current physical field simulations to determine the resistivity data of each 3D digital core model at different water saturation levels (including resistivity data of 3D digital A-type core models with different matrix porosity at 100% water saturation, resistivity data of 3D digital B-type core models with the same matrix porosity but different fracture porosity at 100% water saturation, resistivity data of 3D digital C-type core models with the same matrix porosity and fracture porosity but different cavern porosity at 100% water saturation, resistivity data of 3D digital A-type core models with a certain porosity at different water saturation levels, resistivity data of 3D digital B-type core models with the same matrix porosity but different fracture porosity at different water saturation levels, and resistivity data of 3D digital C-type core models with the same matrix porosity and fracture porosity but different cavern porosity at different water saturation levels). This data serves as resistivity data for cores with different matrix porosity, fracture porosity, and cavern porosity at different water saturation levels. It includes resistivity data for Type A cores with different matrix porosity at 100% water saturation; resistivity data for Type B cores with the same matrix porosity but different fracture porosity at 100% water saturation; resistivity data for Type C cores with the same matrix and fracture porosity but different cavern porosity at 100% water saturation; and resistivity data for Type A cores with a specific porosity. Resistivity data at different water saturation levels; resistivity data of Type B cores with different fracture porosity but the same matrix porosity at different water saturation levels; resistivity data of Type C cores with different karst porosity but the same matrix porosity and fracture porosity at different karst porosity levels; (Type A core model pore structure contains only matrix porosity and no fractures or karst caves; Type B core model pore structure contains matrix porosity and fractures but no karst caves; Type C core model pore structure contains matrix porosity, fractures, and karst caves). Specifically, this includes:

[0204] 1.2.1 Mathematical morphology simulation was used to simulate oil-water distribution under different water saturation levels for each three-dimensional digital core model; the following opening operation was used for mathematical morphology simulation:

[0205]

[0206] In the formula, A is the data set of the three-dimensional digital core model; B is the data set of the structural elements of the three-dimensional digital core model, and the structural elements are cubes with a certain side length. ! represents the opening operation between A and B; ! represents the erosion operator; For expansion operators; corrosion and expansion are both basic operations in mathematical morphology. The distribution of fluid in pores is simulated by first corroding and then expanding the fluid pores.

[0207] 1.2.2. For each 3D digital core model after the oil-water distribution or gas-water distribution simulation is completed, the generate surface module in Avizo is used to generate a mesh. The mesh size is adjusted and optimized in the Meshing module. The mesh is then imported into COMSOL software. The current physics field and steady-state study are selected. The two sides of the 3D digital core model in the z-axis direction are selected as the current inlet and outlet. The potentials of the current inlet and outlet are set to 1V and 0V, respectively, and the conductivity of the pore fluid is set to 20S / m. The potential and current density at each node and the resistivity of the entire 3D digital core model are calculated.

[0208] 1.2.3. Visualize the potential and current density of the 3D digital core model. Compare the potential and current density distributions of the 3D digital A-type core model with those of the 3D digital B-type and C-type core models. The comparison results are as follows: Figure 6 As shown. By Figure 6 It can be seen that the current density of the cracks is significantly greater than that of other parts, forming a highly efficient conductive channel, which is in parallel with the matrix pores. The current density of the cave is comparable to that of the matrix pores, and is in series with the matrix pores.

[0209] 1.3 Based on resistivity data of core samples with different matrix porosity, fracture porosity, and cavern porosity at different water saturation levels, a fluid saturation prediction model for fracture-cavity carbonate rocks in the study area was determined. This model is a mathematical relationship model of six parameters: core resistivity, water resistivity, water saturation, matrix porosity, fracture porosity, and cavern porosity. Specifically, it includes:

[0210] 1.3.1 Based on the resistivity data of Class A cores with different matrix porosities at 100% water saturation, Equation 1 was fitted. Specifically, in... The matrix porosity index m1 was determined by fitting the data in a double logarithmic coordinate system; among them, the pore structure of the Class A core contained only matrix pores and did not contain cracks or caverns.

[0211] Relation 1 is:

[0212] In the formula, F represents the stratigraphic factor; R t R represents the resistivity of the core sample (here, the resistivity of the core sample at 100% water saturation), in Ω·m. w The resistivity of water is expressed in Ω·m, with a value of 0.05 Ω·m. denoted as matrix porosity, with dimensionless units; m1 is the matrix porosity index; a′ is a parameter determined during the fitting of Equation 1.

[0213] The final matrix porosity index was determined to be m1 = 2.41.

[0214] 1.3.2. Based on the resistivity data of Type B cores with different fracture porosities (9.03% matrix porosity) at 100% water saturation, and combined with the matrix porosity index m1, Equation 2 was fitted. Specifically... Fitting in double logarithmic coordinates (see) Figure 7 The fracture porosity index m2 was determined; among them, the pore structure of the B-type core included matrix pores and fractures but did not contain karst caves;

[0215] Relation 2 is:

[0216] In the formula, F represents the stratigraphic factor; R t R represents the resistivity of the core sample (here, the resistivity of the core sample at 100% water saturation), in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. denoted as crack porosity, with dimensionless units; m1 is the matrix porosity index, with a value of 2.41; m2 is the crack porosity index; a″ is a parameter, determined during the fitting of relation 2.

[0217] The final crack porosity index was determined to be m2 = 0.9974.

[0218] 1.3.3. Based on the resistivity data of Class C cores with different cavern porosities (9.03% matrix porosity and 6.25% fracture porosity) at 100% water saturation, and combined with the matrix porosity index m1 and fracture porosity index m2, Equation 3 was fitted. Specifically... Fitting in double logarithmic coordinates (see) Figure 8 The first lithological coefficient a1, the second lithological coefficient a2, and the karst porosity index m3 were determined; among them, the pore structure of the C-type cores includes matrix pores, fractures, and karst caves;

[0219] Relation 3 is:

[0220] In the formula, F represents the stratigraphic factor; R t R represents the resistivity of the core sample (here, the resistivity of the core sample at 100% water saturation), in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. The value represents crack porosity, and the unit is dimensionless. m1 is the porosity of the karst cave, with a dimensionless unit; m2 is the matrix porosity index, with a value of 2.41; m3 is the fracture porosity index, with a value of 0.9974; m4 is the karst cave porosity index; a1 is the first lithological coefficient; a2 is the second lithological coefficient.

[0221] The final values ​​were determined as follows: first lithology coefficient a1 = 6.105, second lithology coefficient a2 = 0.925, and karst porosity index m3 = 0.4.

[0222] 1.3.4. Based on the resistivity data of Class A cores with a matrix porosity of 9.03% at different water saturation levels, Equation 4 was fitted, specifically in IS... w The matrix porosity saturation index n1 was determined by fitting the data in a double logarithmic coordinate system.

[0223] Relation 4 is:

[0224] In the formula, I is the resistivity increase coefficient; R t The resistivity of the core (here, the resistivity of the core at water saturation S) w Resistivity at 100% water saturation (in Ω·m); R0 is the resistivity of the core at 100% water saturation (in Ω·m); S w is the water saturation, with dimensionless units; n1 is the matrix porosity saturation index; b′ is a parameter determined during the fitting of relation 4.

[0225] The final matrix porosity saturation index was determined to be n1 = 6.18.

[0226] 1.3.5. Based on the resistivity data of Class B cores with various fracture porosities of 9.03% matrix porosity at different water saturation levels, and combined with the matrix porosity saturation index n1, Equation 5.1 was fitted, specifically in IS... w Fitting in a double logarithmic coordinate system (e.g.) Figure 9 As shown), the crack saturation index n2 corresponding to each crack porosity is determined.

[0227] Relation 5.1 is:

[0228] In the formula, I is the resistivity increase coefficient; R t The resistivity of the core (here, the resistivity of the core at water saturation S) w Resistivity at 100% water saturation (in Ω·m); R0 is the resistivity of the core at 100% water saturation (in Ω·m); S w n1 is the water saturation level, with a dimensionless unit; n2 is the matrix porosity saturation index, with a value of 6.18; b” is a parameter, determined during the fitting of relation 5.1.

[0229] Based on the crack saturation index n2 corresponding to each crack porosity, Equation 5.2 is fitted, specifically in... Fitting in coordinate system (e.g.) Figure 10 As shown), the first crack saturation index coefficient α3 and the second crack saturation index coefficient β3 were determined.

[0230] Relation 5.2 is:

[0231] In the formula, α is the crack porosity, dimensionless; n2 is the crack saturation index; α3 is the coefficient of the first crack saturation index; β3 is the coefficient of the second crack saturation index.

[0232] The final values ​​were determined to be the first crack saturation index coefficient α3 = -24.65 and the second crack saturation index coefficient β3 = 6.13.

[0233] 1.3.6. Based on the resistivity data of Class C cores with matrix porosity of 9.03% and fracture porosity of 6.25% at different water saturation levels, and combined with the matrix porosity saturation index n1, the coefficient of the first fracture saturation index α3, and the coefficient of the second fracture saturation index β3, Equation 6.1 was fitted, specifically in IS... w Fitting in a double logarithmic coordinate system (e.g.) Figure 11 As shown), the third lithological coefficient b1 and the fourth lithological coefficient b2 corresponding to the porosity of each karst cave were determined.

[0234] Relation 6.1 is: in

[0235] In the formula, I is the resistivity increase coefficient; R t The resistivity of the core (here, the resistivity of the core at water saturation S) w The resistivity of the core at 100% water saturation is expressed in Ω·m; R0 is the resistivity of the core at 100% water saturation, expressed in Ω·m. S represents crack porosity, with dimensionless units. w α is the water saturation level, dimensionless; n1 is the matrix porosity saturation index, with a value of 6.18; n2 is the matrix porosity saturation index; α3 is the first fracture saturation index coefficient; β3 is the second fracture saturation index coefficient.

[0236] Based on the third lithological coefficient b1 and the fourth lithological coefficient b2 corresponding to the porosity of each karst cave, Equation 6.2 is fitted, specifically in... Fitting in coordinate system (e.g.) Figure 12 As shown), the relationship 6.3 is fitted, specifically in... Fitting in coordinate system (e.g.) Figure 13 As shown, the first cave coefficient α1, the second cave coefficient β1, the third cave coefficient α2, and the fourth cave coefficient β2 were determined.

[0237] Relation 6.2 is:

[0238] Relation 6.3 is:

[0239] In the formula, α1 represents the porosity of the karst cave, with dimensionless units; α1 is the first karst cave coefficient; β1 is the second karst cave coefficient; α2 is the third karst cave coefficient; β2 is the fourth karst cave coefficient; b1 is the third lithology coefficient; b2 is the fourth lithology coefficient.

[0240] The final values ​​were determined as follows: first cave coefficient α1 = 13.45, second cave coefficient β1 = 0.43, third cave coefficient α2 = 1.16, and fourth cave coefficient β2 = 0.74.

[0241] 1.3.7. Based on the matrix porosity saturation index n1, the first fracture saturation index coefficient α3, the second fracture saturation index coefficient β3, the first vault coefficient α1, the second vault coefficient β1, the third vault coefficient α2, the fourth vault coefficient β2, the matrix porosity index m1, the fracture porosity index m2, the first lithology coefficient a1, the second lithology coefficient a2, and the vault porosity index m3, a fluid saturation prediction model for fractured-vuggy carbonate rocks is determined; the fluid saturation prediction model for fractured-vuggy carbonate rocks is as follows:

[0242]

[0243] In the formula, R t R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. The value represents crack porosity, and the unit is dimensionless. S represents the porosity of the karst cave, with dimensionsless units; w α1 represents water saturation, unit is dimensionless; m2 represents matrix porosity index; m3 represents cavern porosity index; a1 represents the first lithological coefficient; a2 represents the second lithological coefficient; n1 represents matrix porosity saturation index; n2 represents fracture saturation index; α3 represents the first coefficient; β3 represents the second fracture saturation index coefficient; α1 represents the first cavern coefficient; β1 represents the second cavern coefficient; α2 represents the third cavern coefficient; β2 represents the fourth cavern coefficient.

[0244] The final determined model for predicting fluid saturation in fractured carbonate rocks is as follows:

[0245]

[0246] 2. Obtain the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity within the target fractured carbonate rock. Specifically, this includes:

[0247] Obtain resistivity logging data of the target fractured carbonate rock, and then determine the resistivity of the target fractured carbonate rock based on the resistivity logging data of the target fractured carbonate rock;

[0248] Porosity logging data, nuclear magnetic resonance logging data, and electrical imaging logging data of the target fractured carbonate rock are obtained. Then, based on the porosity logging data, nuclear magnetic resonance logging data, and electrical imaging logging data of the target fractured carbonate rock, the matrix porosity, fracture porosity, and cavern porosity of the target fractured carbonate rock are determined.

[0249] Obtain the measured resistivity of water in the target fractured carbonate rock.

[0250] like Figure 14 As shown.

[0251] 3. Based on the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity of the target fractured-cavity carbonate rock, the water saturation of the target fractured-cavity carbonate rock was determined using the fluid saturation prediction model for fractured-cavity carbonate rocks in the study area, employing the `solve` function in MATLAB. The results are as follows: Figure 14 As shown, in Figure 14 The label in the middle represents the water saturation of the new model.

[0252] The water saturation of the target fractured carbonate rock will be determined by core experiments, and the results are as follows: Figure 14 As shown, in Figure 14 The values ​​are marked as core saturation; the Archie water saturation of the target fractured carbonate rock was determined, and the results are as follows: Figure 14 As shown. Comparison Figure 14 In the study, the new model's water saturation, core saturation, and Archie water saturation showed good fit with the core saturation and Archie water saturation, indicating that the technical solution provided by this invention can accurately determine the water saturation of fractured-cavity carbonate rocks.

[0253] Those skilled in the art will understand that this specification can be provided as a method, system, or computer program product. Therefore, this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0254] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments thereof. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. The computer may be a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0255] The functional units in the embodiments of this specification can be integrated into one processing unit, or each functional unit can exist physically separately, or two or more functional units can be integrated into one processing unit.

[0256] Those skilled in the art will understand that the descriptions of the various embodiments in this specification have different focuses, and parts not described in detail in a certain embodiment can be referred to in the relevant descriptions of other embodiments. Furthermore, it is understood that those skilled in the art, after reading this specification, can conceive of any combination of some or all of the embodiments listed in this specification without creative effort, and such combinations are also within the scope of disclosure and protection of this specification.

[0257] Although this specification has been described through embodiments, those skilled in the art will understand that the above embodiments are merely illustrative of the core ideas of this specification. Those skilled in the art will appreciate that many variations and modifications are possible with this specification. It is intended that the appended claims encompass these variations and modifications without departing from the spirit of this specification.

Claims

1. A method for establishing a fluid saturation prediction model for fractured-vuggy carbonate rocks, wherein, The method includes: Resistivity data of core samples with different matrix porosity, different fracture porosity, and different cave porosity in the fractured-cavity carbonate rock study area were obtained at different water saturation levels. Based on resistivity data of core samples with different matrix porosity, fracture porosity, and cavern porosity at different water saturation levels, a fluid saturation prediction model for fracture-cavity carbonate rocks in the study area was determined. The fluid saturation prediction model for fracture-cavity carbonate rocks is a mathematical relationship model of six parameters: core resistivity, water resistivity, water saturation, matrix porosity, fracture porosity, and cavern porosity.

2. The method according to claim 1, wherein, The fluid saturation prediction model for fractured carbonate rocks is as follows: In the formula, R t R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. The value represents crack porosity, and the unit is dimensionless. S represents the porosity of the karst cave, with dimensionsless units; w α1 represents water saturation, unit is dimensionless; m2 represents matrix porosity index; m3 represents cavern porosity index; a1 represents the first lithological coefficient; a2 represents the second lithological coefficient; n1 represents matrix porosity saturation index; n2 represents fracture saturation index; α3 represents the first fracture saturation index coefficient; β3 represents the second fracture saturation index coefficient; α1 represents the first cavern coefficient; β1 represents the second cavern coefficient; α2 represents the third cavern coefficient; β2 represents the fourth cavern coefficient.

3. The method according to claim 1, wherein, Resistivity data of core samples from fractured-cavitary carbonate rocks in the study area at different matrix porosities, fracture porosities, and cavern porosities under different water saturation levels include: Resistivity data of Type A cores with different matrix porosity at 100% water saturation, resistivity data of Type B cores with different fracture porosity at 100% water saturation, resistivity data of Type C cores with different karst cave porosity at 100% water saturation, resistivity data of Type A cores at different water saturation, resistivity data of Type B cores with different fracture porosity at different water saturation, and resistivity data of Type C cores with different karst cave porosity at different water saturation; Type A cores have a pore structure containing only matrix pores and no cracks or cavities; Type B cores have a pore structure containing matrix pores and cracks but no cavities; Type C cores have a pore structure containing matrix pores, cracks, and cavities.

4. The method according to claim 3, wherein, The resistivity data of Class B cores with different fracture porosity at 100% water saturation are the resistivity data of Class B cores with different fracture porosity but the same matrix porosity at 100% water saturation. The resistivity data of Class C cores with different cave porosity at 100% water saturation are as follows: The resistivity data of Class C cores with different cave porosity at 100% water saturation are as follows: The matrix porosity and fracture porosity are the same. The resistivity data of Class A cores at different water saturation levels are resistivity data of Class A cores with the same matrix porosity at different water saturation levels. The resistivity data of Class B cores with different fracture porosity at different water saturation levels are the resistivity data of Class B cores with different fracture porosity but the same matrix porosity at different water saturation levels. The resistivity data of Class C cores with different cave porosity at different water saturation levels are resistivity data of Class C cores with different cave porosity at different water saturation levels, where the matrix porosity and fracture porosity are the same.

5. The method according to claim 3 or 4, wherein, Based on resistivity data from core samples with different matrix porosity, fracture porosity, and cavern porosity at different water saturation levels, the fluid saturation prediction model for fracture-cavity carbonate rocks in the study area is determined as follows: Based on the resistivity data of Class A cores with different matrix porosities at 100% water saturation, Equation 1 was fitted to determine the matrix porosity index m1. Relation 1 is: In the formula, R t R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. m1 is the matrix porosity, dimensionless; a′ is the matrix porosity index; Based on the resistivity data of Class B cores with different fracture porosity at 100% water saturation, and combined with the matrix porosity index m1, Equation 2 was fitted to determine the fracture porosity index m2. Relation 2 is: In the formula, R t R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. , where m1 is the matrix porosity, dimensionless; m2 is the fracture porosity; a″ is a parameter. Based on the resistivity data of Class C cores with different karst porosity at 100% water saturation, combined with matrix porosity index m1 and fracture porosity index m2, Equation 3 was fitted to determine the first lithology coefficient a1, the second lithology coefficient a2 and the karst porosity index m3. Relation 3 is: In the formula, R t R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. The value represents crack porosity, and the unit is dimensionless. m1 is the porosity of the karst cave, in dimensionless units; m2 is the matrix porosity index; m3 is the fracture porosity index; a1 is the first lithological coefficient; a2 is the second lithological coefficient. Based on the resistivity data of Class A cores at different water saturation levels, Equation 4 was fitted to determine the matrix pore saturation index n1. Relation 4 is: In the formula, R t R0 is the resistivity of the core sample, in Ω·m; R0 is the resistivity of the core sample at 100% water saturation, in Ω·m; S w n is the water saturation level, dimensionless; n1 is the matrix porosity saturation index; b′ is a parameter. Based on the resistivity data of Class B cores with different fracture porosity at different water saturation levels, and combined with the matrix porosity saturation index n1, Equation 5 was fitted to determine the coefficient α3 of the first fracture saturation index and the coefficient β3 of the second fracture saturation index. Relation 5 is: in In the formula, R t R0 is the resistivity of the core, in Ω·m; R0 is the resistivity of the core at 100% water saturation, in Ω·m. S represents crack porosity, with dimensionless units. w α is the water saturation level, dimensionless; n1 is the matrix porosity saturation index; n2 is the fracture saturation index; α3 is the first fracture saturation index coefficient; β3 is the second fracture saturation index coefficient; b″ is a parameter. Based on the resistivity data of Class C cores with different karst porosity at different water saturation levels, and combined with the matrix porosity saturation index n1, the first fracture saturation index coefficient α3, and the second fracture saturation index coefficient β3, Equation 6 was fitted to determine the first karst coefficient α1, the second karst coefficient β1, the third karst coefficient α2, and the fourth karst coefficient β2. Relation 6 is: in In the formula, R t R0 is the resistivity of the core, in Ω·m; R0 is the resistivity of the core at 100% water saturation, in Ω·m. The value represents crack porosity, and the unit is dimensionless. S represents the porosity of the karst cave, with dimensionsless units; w α1 represents water saturation, dimensionless; n1 represents matrix porosity saturation index; n2 represents fracture saturation index; α3 represents the first fracture saturation index coefficient; β3 represents the second fracture saturation index coefficient; α1 represents the first karst coefficient; β1 represents the second karst coefficient; α2 represents the third karst coefficient; β2 represents the fourth karst coefficient; b1 represents the third lithology coefficient; b2 represents the fourth lithology coefficient. Based on the matrix porosity saturation index n1, the first fracture saturation index coefficient α3, the second fracture saturation index coefficient β3, the first cavern coefficient α1, the second cavern coefficient β1, the third cavern coefficient α2, the fourth cavern coefficient β2, the matrix porosity index m1, the fracture porosity index m2, the first lithology coefficient a1, the second lithology coefficient a2, and the cavern porosity index m3, a fluid saturation prediction model for fractured-cavitary carbonate rocks was determined; the fluid saturation prediction model for fractured-cavitary carbonate rocks is as follows: In the formula, R t R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. The value represents crack porosity, and the unit is dimensionless. S represents the porosity of the karst cave, with dimensionsless units; w α1 represents water saturation, unit is dimensionless; m1 is matrix porosity index; m2 is fracture porosity index; m3 is cavern porosity index; α1 is the first lithological coefficient; a2 is the second lithological coefficient; n1 is matrix porosity saturation index; n2 is fracture saturation index; α3 is the first fracture saturation index coefficient; β3 is the second fracture saturation index coefficient; α1 is the first cavern coefficient; β1 is the second cavern coefficient; α2 is the third cavern coefficient; β2 is the fourth cavern coefficient.

6. The method according to claim 5, wherein, Based on resistivity data of Type B cores with different fracture porosities at different water saturations, and combined with the matrix porosity saturation index n1, Equation 5 was fitted to determine the first fracture saturation index coefficient α3 and the second fracture saturation index coefficient β3, including: Based on the resistivity data of Type B cores with varying fracture porosity at different water saturations, and combined with the matrix porosity saturation index n1, the relationships in Equation 5 are respectively... By performing fitting, the crack saturation index n2 corresponding to each crack porosity is determined; Based on the crack saturation index n2 corresponding to each crack porosity, the relationship in Equation 5 is... By fitting the data, the coefficients of the first crack saturation index α3 and the second crack saturation index β3 were determined.

7. The method according to claim 5, wherein, Based on resistivity data of Class C cores with different karst porosity at different water saturation levels, and combined with the matrix porosity saturation index n1, the first fracture saturation index coefficient α3, and the second fracture saturation index coefficient β3, Equation 6 was fitted to determine the first karst coefficient α1, the second karst coefficient β1, the third karst coefficient α2, and the fourth karst coefficient β2, which include: Based on the resistivity data of Class C cores with varying porosity at different water saturation levels, and combined with the matrix porosity saturation index n1, the first fracture saturation index coefficient α3, and the second fracture saturation index coefficient β3, the relationships in Equation 6 are respectively... By performing fitting, the third lithological coefficient b1 and the fourth lithological coefficient b2 corresponding to the porosity of each karst cave were determined; Based on the third lithology coefficient b1 and the fourth lithology coefficient b2 corresponding to the porosity of each karst cave, the relationship in Equation 6 is... By fitting the data, the first cave coefficient α1, the second cave coefficient β1, the third cave coefficient α2, and the fourth cave coefficient β2 were determined.

8. A method for determining fluid saturation in fractured carbonate rocks, wherein the method includes: Obtain the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity of the target fractured carbonate rock. A prediction model for fluid saturation of fractured carbonate rocks in the study area where the target fractured carbonate rocks are located is constructed using the method for establishing a prediction model for fluid saturation of fractured carbonate rocks as described in any one of claims 1-7. Based on the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity of the target fractured carbonate rock, the water saturation and / or hydrocarbon saturation of the target fractured carbonate rock are determined using a fluid saturation prediction model for fractured carbonate rocks in the study area.

9. A device for establishing a predictive model for fluid saturation in fractured carbonate rocks, wherein, The model includes: The data acquisition module for model building is used to acquire resistivity data of core samples with different matrix porosity, different fracture porosity, and different cave porosity at different water saturation levels in the fractured-cavity carbonate rock study area. Model building module: used to determine the fluid saturation prediction model of fracture-cavity carbonate rocks in the study area based on resistivity data of cores with different matrix porosity, different fracture porosity, and different karst porosity at different water saturation levels; wherein, the fluid saturation prediction model of fracture-cavity carbonate rocks is a mathematical relationship model of six parameters: core resistivity, water resistivity, water saturation, matrix porosity, fracture porosity, and karst porosity.

10. The apparatus according to claim 9, wherein, The fluid saturation prediction model for fractured carbonate rocks is as follows: In the formula, R t R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. The value represents crack porosity, and the unit is dimensionless. S represents the porosity of the karst cave, with dimensionsless units; w α1 represents water saturation, unit is dimensionless; m2 represents matrix porosity index; m3 represents cavern porosity index; a1 represents the first lithological coefficient; a2 represents the second lithological coefficient; n1 represents matrix porosity saturation index; n2 represents fracture saturation index; α3 represents the first fracture saturation index coefficient; β3 represents the second fracture saturation index coefficient; α1 represents the first cavern coefficient; β1 represents the second cavern coefficient; α2 represents the third cavern coefficient; β2 represents the fourth cavern coefficient.

11. The apparatus according to claim 9, wherein, Resistivity data of core samples from fractured-cavitary carbonate rocks in the study area at different matrix porosities, fracture porosities, and cavern porosities under different water saturation levels include: Resistivity data of Type A cores with different matrix porosity at 100% water saturation, resistivity data of Type B cores with different fracture porosity at 100% water saturation, resistivity data of Type C cores with different karst cave porosity at 100% water saturation, resistivity data of Type A cores at different water saturation, resistivity data of Type B cores with different fracture porosity at different water saturation, and resistivity data of Type C cores with different karst cave porosity at different water saturation; Among them, the pore structure of Class A cores contains only matrix pores and no cracks or cavities; the pore structure of Class B cores contains matrix pores and cracks but no cavities; and the pore structure of Class C cores contains matrix pores, cracks, and cavities.

12. The apparatus according to claim 9, wherein, The resistivity data of Class B cores with different fracture porosity at 100% water saturation are the resistivity data of Class B cores with different fracture porosity but the same matrix porosity at 100% water saturation. The resistivity data of Class C cores with different cave porosity at 100% water saturation are as follows: The resistivity data of Class C cores with different cave porosity at 100% water saturation are as follows: The matrix porosity and fracture porosity are the same. The resistivity data of Class A cores at different water saturation levels are resistivity data of Class A cores with the same matrix porosity at different water saturation levels. The resistivity data of Class B cores with different fracture porosity at different water saturation levels are the resistivity data of Class B cores with different fracture porosity but the same matrix porosity at different water saturation levels. The resistivity data of Class C cores with different cave porosity at different water saturation levels are resistivity data of Class C cores with different cave porosity at different water saturation levels, where the matrix porosity and fracture porosity are the same.

13. The apparatus according to claim 11 or 12, wherein, The model building module includes: The first fitting submodule is used to fit the resistivity data of Class A cores with different matrix porosities at 100% water saturation to Equation 1 and determine the matrix porosity index m1. Relation 1 is: In the formula, R t R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. denoted as matrix porosity, with dimensionless units; m1 is the matrix porosity index; a′ is a parameter determined during the fitting of Equation 1. The second fitting submodule is used to fit the resistivity data of Class B cores with different fracture porosity at 100% water saturation, and combine it with the matrix porosity index m1 to fit Equation 2 to determine the fracture porosity index m2. Relation 2 is: In the formula, R t R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. , where m1 is the matrix porosity, and m2 is the fracture porosity; a” is a parameter determined during the fitting of Equation 2. The third fitting submodule is used to fit the resistivity data of Class C cores with different karst porosity at 100% water saturation, and combine the matrix porosity index m1 and fracture porosity index m2 to fit Equation 3 to determine the first lithology coefficient a1, the second lithology coefficient a2 and the karst porosity index m3. Relation 3 is: In the formula, R t R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. The value represents crack porosity, and the unit is dimensionless. m1 is the porosity of the karst cave, in dimensionless units; m2 is the matrix porosity index; m3 is the fracture porosity index; a1 is the first lithological coefficient; a2 is the second lithological coefficient. The fourth fitting submodule is used to fit Equation 4 based on resistivity data of Class A cores at different water saturation levels, and determine the matrix pore saturation index n1. Relation 4 is: In the formula, R t R0 is the resistivity of the core sample, in Ω·m; R0 is the resistivity of the core sample at 100% water saturation, in Ω·m; S w is the water saturation, with dimensionless units; n1 is the matrix porosity saturation index; b′ is a parameter, determined during the fitting of relation 4; The fifth fitting submodule is used to fit the resistivity data of Class B cores with different fracture porosities at different water saturation levels, and to combine the matrix porosity saturation index n1 to fit Equation 5, thereby determining the first fracture saturation index coefficient α3 and the second fracture saturation index coefficient β3. Relation 5 is: in In the formula, R t R0 is the resistivity of the core, in Ω·m; R0 is the resistivity of the core at 100% water saturation, in Ω·m. S represents crack porosity, with dimensionless units. w α is the water saturation, with dimensionless units; n1 is the matrix porosity saturation index; n2 is the crack saturation index; α3 is the coefficient of the first crack saturation index; β3 is the coefficient of the second crack saturation index; b” is a parameter, determined during the fitting of relation 5; The sixth fitting submodule is used to fit the resistivity data of Class C cores with different karst porosity at different water saturation levels, and to combine the matrix porosity saturation index n1, the first fracture saturation index coefficient α3, and the second fracture saturation index coefficient β3 to the relation 6, and to determine the first karst coefficient α1, the second karst coefficient β1, the third karst coefficient α2, and the fourth karst coefficient β2. Relation 6 is: in In the formula, R t R0 is the resistivity of the core, in Ω·m; R0 is the resistivity of the core at 100% water saturation, in Ω·m. The value represents crack porosity, and the unit is dimensionless. S represents the porosity of the karst cave, with dimensionsless units; w α1 represents water saturation, dimensionless; n1 represents matrix porosity saturation index; n2 represents fracture saturation index; α3 represents the first fracture saturation index coefficient; β3 represents the second fracture saturation index coefficient; α1 represents the first karst coefficient; β1 represents the second karst coefficient; α2 represents the third karst coefficient; β2 represents the fourth karst coefficient; b1 represents the third lithology coefficient; b2 represents the fourth lithology coefficient. The model determination submodule is used to determine the fluid saturation prediction model for fractured-cavitary carbonate rocks based on the matrix porosity saturation index n1, the first fracture saturation index coefficient α3, the second fracture saturation index coefficient β3, the first vault coefficient α1, the second vault coefficient β1, the third vault coefficient α2, the fourth vault coefficient β2, the matrix porosity index m1, the fracture porosity index m2, the first lithology coefficient a1, the second lithology coefficient α2, and the vault porosity index m3. The fluid saturation prediction model for fractured-cavitary carbonate rocks is as follows: In the formula, R t R is the resistivity of the rock core, in Ω·m. w Ω·m is the resistivity of water. The value represents matrix porosity, and the unit is dimensionless. The value represents crack porosity, and the unit is dimensionless. S represents the porosity of the karst cave, with dimensionsless units; w α1 represents water saturation, unit is dimensionless; m2 represents matrix porosity index; m3 represents cavern porosity index; a1 represents the first lithological coefficient; a2 represents the second lithological coefficient; n1 represents matrix porosity saturation index; n2 represents fracture saturation index; α3 represents the first fracture saturation index coefficient; β3 represents the second fracture saturation index coefficient; α1 represents the first cavern coefficient; β1 represents the second cavern coefficient; α2 represents the third cavern coefficient; β2 represents the fourth cavern coefficient.

14. The apparatus according to claim 13, wherein, The fifth fitting submodule includes: Fracture saturation index determination unit: Used to determine the resistivity data of Class B cores at different water saturation levels based on the porosity of each fracture, combined with the matrix porosity saturation index n1, to determine the values ​​in Equation 5. By performing fitting, the crack saturation index n2 corresponding to each crack porosity is determined; The crack saturation index coefficient determination unit is used to determine the crack saturation index coefficient n2 in equation 5 based on the crack saturation index n2 corresponding to each crack porosity. By fitting the data, the coefficients of the first crack saturation index α3 and the second crack saturation index β3 were determined.

15. The apparatus according to claim 13, wherein, The sixth fitting submodule includes: The lithology coefficient determination unit is used to determine the resistivity data of Class C cores at different water saturation levels based on the porosity of each karst cave. It combines the matrix porosity saturation index n1, the first fracture saturation index coefficient α3, and the second fracture saturation index coefficient β3 to determine the coefficients in Equation 6. By performing fitting, the third lithological coefficient b1 and the fourth lithological coefficient b2 corresponding to the porosity of each karst cave were determined; The unit for determining the karst cave coefficient is used to determine the coefficients in Equation 6 based on the third lithology coefficient b1 and the fourth lithology coefficient b2 corresponding to the porosity of each karst cave. By fitting the data, the first cave coefficient α1, the second cave coefficient β1, the third cave coefficient α2, and the fourth cave coefficient β2 were determined.

16. A device for determining the fluid saturation of fractured carbonate rocks, wherein, The device includes: Target fractured carbonate rock data acquisition module: used to acquire the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity in the target fractured carbonate rock. Model for predicting fluid saturation in fractured-cavitary carbonate rocks: This model is used to construct a prediction model for fluid saturation in fractured-cavitary carbonate rocks in the study area where the target fractured-cavitary carbonate rocks are located. Fluid saturation determination module: Based on the resistivity, matrix porosity, fracture porosity, cavern porosity, and water resistivity of the target fractured carbonate rock, this module uses a fluid saturation prediction model for fractured carbonate rocks in the study area to determine the water saturation and / or hydrocarbon saturation of the target fractured carbonate rock.

17. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for establishing a fluid saturation prediction model for fractured-cavity carbonate rocks according to any one of claims 1-7 or the method for determining fluid saturation in fractured-cavity carbonate rocks according to claim 8.

18. A computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for establishing a fluid saturation prediction model for fractured-cavity carbonate rocks according to any one of claims 1-7 or the method for determining fluid saturation in fractured-cavity carbonate rocks according to claim 8.

19. A computer program product comprising a computer program, wherein when executed by a processor, the computer program implements the method for establishing a fluid saturation prediction model for fractured-cavity carbonate rocks according to any one of claims 1-7 or the method for determining fluid saturation in fractured-cavity carbonate rocks according to claim 8.

Images