Rock physical model generation method and device, storage medium and electronic equipment

Abstract

The invention relates to a rock physical model generation method and device, a storage medium and electronic equipment, and the method comprises the steps: building a density curve corresponding to a to-be-measured oil field, and obtaining the basic parameters of the to-be-measured oil field; according to the density curve and the basic parameters, the density apparent porosity and the sound wave apparent porosity of the oil field to be measured are determined; according to the density apparent porosity and the sound wave apparent porosity, laumonite position information of the oil field to be detected is determined; determining the mineral content of the to-be-detected oil field according to the laumontite position information and the logging curve of the to-be-detected oil field; establishing a model matrix skeleton according to the mineral content; according to the model matrix skeleton, establishing a dry rock equivalent modulus corresponding to the to-be-measured oil field; obtaining a first water saturation corresponding to the to-be-measured oil field, and performing homing prediction on the first water saturation to obtain a fluid equivalent modulus corresponding to the to-be-measured oil field; and establishing a rock physical model according to the model matrix skeleton, the dry rock equivalent modulus and the fluid equivalent modulus.

Description

Technical Field

[0001] The present invention relates to the technical field of oilfield development, and in particular to a method, device, storage medium and electronic equipment for generating a rock physics model. Background Art

[0002] The resources of sandstone and conglomerate reservoirs are very huge and are an important area for oilfield production planning. At present, reservoir identification is carried out through rock physical modeling, but conventional rock physical modeling methods are mainly used for equivalent sandstone and mudstone. Due to the abnormal elastic parameters of lauric zeolite and the electrical resistance caused by lauric zeolite minerals, conventional modeling methods cannot accurately characterize the rock physical properties of this type of reservoir. At the same time, the models created by conventional modeling methods have problems such as low accuracy. Summary of the invention

[0003] In view of this, the present invention provides a method, device, storage medium and electronic device for generating a rock physics model.

[0004] Specifically, the present invention is achieved through the following technical solutions:

[0005] According to a first aspect of the present invention, a method for generating a rock physics model is provided, which is used for an oil field to be tested. The method for generating a rock physics model comprises: establishing a density curve corresponding to the oil field to be tested and obtaining basic parameters of the oil field to be tested; determining the density apparent porosity and the acoustic apparent porosity of the oil field to be tested according to the density curve and the basic parameters; determining the lauric zeolite position information of the oil field to be tested according to the density apparent porosity and the acoustic apparent porosity; performing segmented calculation according to the lauric zeolite position information and the well logging curve of the oil field to be tested to determine the mineral content of the oil field to be tested; establishing a model matrix skeleton according to the mineral content; establishing a dry rock equivalent modulus corresponding to the oil field to be tested according to the model matrix skeleton; obtaining a first water saturation corresponding to the oil field to be tested, performing a homeostasis prediction on the first water saturation to obtain a second water saturation, and determining the fluid equivalent modulus corresponding to the oil field to be tested according to the second water saturation; and establishing a rock physics model according to the model matrix skeleton, the dry rock equivalent modulus and the fluid equivalent modulus.

[0006] The method for generating a rock physics model in the present technical solution obtains basic parameters of the oil field to be tested by establishing a density curve corresponding to the oil field to be tested, establishes a model matrix skeleton corresponding to the oil field to be tested based on the density curve and the basic parameters, creates a dry rock equivalent modulus corresponding to the oil field to be tested based on the model matrix skeleton, and creates a fluid equivalent modulus corresponding to the oil field to be tested, and then combines the model matrix skeleton, dry rock equivalent modulus and fluid equivalent modulus into a rock physics model, enriches the physical properties of the rock physics model, effectively improves the model accuracy of the rock physics model, improves the practicability of the rock physics model, and shortens the creation cycle of the rock physics model.

[0007] According to a second aspect of the present invention, a device for generating a rock physics model is provided, which is used for an oil field to be tested. The device for generating a rock physics model comprises: a processing module, which is used to establish a density curve corresponding to the oil field to be tested and obtain basic parameters of the oil field to be tested; the processing module is also used to determine the density apparent porosity and the acoustic apparent porosity of the oil field to be tested according to the density apparent porosity and the acoustic apparent porosity; the processing module is also used to determine the location information of the lauricite in the oil field to be tested according to the density apparent porosity and the acoustic apparent porosity; the processing module is also used to perform segmentation according to the lauricite location information and the logging curve of the oil field to be tested. The processing module is used to obtain the mineral content of the oil field to be tested, and the processing module is also used to establish the model matrix skeleton according to the mineral content. The processing module is also used to establish the dry rock equivalent modulus corresponding to the oil field to be tested according to the model matrix skeleton. The processing module is also used to obtain the first water saturation corresponding to the oil field to be tested, perform a return prediction on the first water saturation to obtain the second water saturation, and determine the fluid equivalent modulus corresponding to the oil field to be tested according to the second water saturation. The processing module is also used to establish a rock physics model according to the model matrix skeleton, the dry rock equivalent modulus and the fluid equivalent modulus.

[0008] The rock physics model generation device in the present technical solution obtains the basic parameters of the oil field to be tested by establishing a density curve corresponding to the oil field to be tested, and establishes a model matrix skeleton corresponding to the oil field to be tested according to the density curve and the basic parameters. Based on the model matrix skeleton, a dry rock equivalent modulus corresponding to the oil field to be tested is created, and a fluid equivalent modulus corresponding to the oil field to be tested is created, and then the model matrix skeleton, the dry rock equivalent modulus and the fluid equivalent modulus are combined into a rock physics model, which enriches the physical properties of the rock physics model, effectively improves the model accuracy of the rock physics model, improves the practicability of the rock physics model, and shortens the creation cycle of the rock physics model.

[0009] According to a third aspect of the present invention, there is provided a storage medium having stored thereon a program or instruction, which, when executed by a processor, implements the steps of the method for generating a rock physical model in any possible implementation of the first aspect.

[0010] According to a fourth aspect of the present invention, there is provided an electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for generating a rock physical model in any possible implementation of the first aspect are implemented.

[0011] The technical solution provided by the present invention brings at least the following beneficial effects:

[0012] It enriches the physical properties of the rock physics model, effectively improves the model accuracy of the rock physics model, improves the practicability of the rock physics model, and shortens the creation cycle of the rock physics model. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0014] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0015] Figure 1 One of the flow charts of a method for generating a rock physics model provided in an embodiment of the present invention;

[0016] Figure 2 A second flow chart of a method for generating a rock physics model provided in an embodiment of the present invention;

[0017] Figure 3 A third flow chart of a method for generating a rock physics model provided by an embodiment of the present invention;

[0018] Figure 4 A fourth flow chart of a method for generating a rock physics model provided in an embodiment of the present invention;

[0019] Figure 5 A fifth flow chart of a method for generating a rock physics model provided in an embodiment of the present invention;

[0020] Figure 6 A sixth flow chart of a method for generating a rock physics model provided in an embodiment of the present invention;

[0021] Figure 7 A seventh flow chart of a method for generating a rock physics model provided in an embodiment of the present invention;

[0022] Figure 8 A structural block diagram of a rock physics model generation device provided by an embodiment of the present invention;

[0023] Fig. 9 One of the schematic diagrams of a device for generating a rock physics model provided by an embodiment of the present invention;

[0024] Fig.10 A second schematic diagram of a device for generating a rock physics model provided by an embodiment of the present invention;

[0025] Fig.11 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] The technical solution of the method for generating a rock physics model provided by the present invention may be implemented by a generating device, and may also be determined according to actual use requirements, which is not specifically limited here. In order to more clearly describe the method for generating a rock physics model provided by the present invention, the following description is made with the generating device as the implementing body.

[0028] See also Figure 1 The embodiment of the present invention provides a method for generating a rock physics model for an oil field to be tested. The method may include the following steps:

[0029] S101, establishing a density curve corresponding to the oil field to be tested, and obtaining basic parameters of the oil field to be tested;

[0030] S102, determining the density apparent porosity and the acoustic apparent porosity of the oil field to be measured according to the density curve and basic parameters;

[0031] S103, determining the location information of the lauric zeolite in the oil field to be measured according to the density apparent porosity and the acoustic apparent porosity;

[0032] S104, performing segmented calculations based on the lauzenite position information and the well logging curve of the oil field to be tested to determine the mineral content of the oil field to be tested;

[0033] S105, establishing a model matrix skeleton according to the mineral content;

[0034] S106, establishing a dry rock equivalent modulus corresponding to the oil field to be tested according to the model matrix skeleton;

[0035] S107, obtaining a first water saturation corresponding to the oil field to be tested, performing a return prediction on the first water saturation to obtain a second water saturation, and determining a fluid equivalent modulus corresponding to the oil field to be tested according to the second water saturation;

[0036] S108. Establish a rock physics model based on the model matrix skeleton, dry rock equivalent modulus and fluid equivalent modulus.

[0037] In this embodiment, a method for generating a rock physics model is provided for an oil field to be tested, wherein the oil field to be tested is an oil field to be surveyed, and the rock physics model is a physical model corresponding to the rock in the oil field to be tested. A generating device establishes a density curve corresponding to the oil field to be tested, and obtains basic parameters of the oil field to be tested, wherein the density curve is a curve that can represent the density characteristics of the oil field to be tested, and the basic parameters are parameters that can represent the basic characteristics of the oil field to be tested.

[0038] In some embodiments, the area where the oil field to be tested is located can be specifically a set of regional mudstone caprocks. Due to the water absorption and expansion of clay minerals and the horizontal stress of the formation, the well wall collapses, and density logging cannot perform true wall logging, resulting in distortion.

[0039] The generating device determines the density apparent porosity and the acoustic apparent porosity of the oil field to be measured according to the density curve and the basic parameters, wherein the density apparent porosity is the apparent porosity determined by the density curve, and the acoustic apparent porosity is the apparent porosity determined by the acoustic wave.

[0040] The generating device determines the lauric zeolite position information of the oil field to be tested according to the density apparent porosity and the acoustic apparent porosity, wherein the lauric zeolite position information is the position information of the lauric zeolite in the oil field to be tested.

[0041] The generating device obtains the mineral content of the oil field to be tested by segmenting the well logging curve based on the determined location information of the lauzenite, wherein the well logging curve is the characteristic curve of the oil field to be tested, and the mineral content is the content information of each mineral in the oil field to be tested.

[0042] It should be noted that the halogenite minerals in the conglomerate are special, which will cause the reservoir resistivity to be high, affecting the accuracy of well logging interpretation, reservoir evaluation, and rock physics modeling.

[0043] In some embodiments, according to the location information of lauric zeolite, the oil field to be tested is divided into layers containing lauric zeolite and layers not containing lauric zeolite, and the mineral content of the layers containing lauric zeolite and the layers not containing lauric zeolite are determined separately to obtain the mineral content of the oil field to be tested.

[0044] The generating device establishes a model matrix skeleton corresponding to the oil field to be measured according to the model matrix skeleton, wherein the model matrix skeleton is the skeleton of the physical model corresponding to the oil field to be measured.

[0045] In some embodiments, the model matrix skeleton may be specifically equivalent to a complex mineral rock skeleton.

[0046] The generating device creates a dry rock equivalent modulus corresponding to the oil field to be tested based on the model matrix skeleton, obtains a first water saturation corresponding to the oil field to be tested, and performs a return prediction on the first water saturation to obtain a second water saturation, wherein the dry rock equivalent modulus is the equivalent modulus of the dry rock material in the oil field to be tested, the first water saturation is the preset water saturation corresponding to the oil field to be tested, and the second water saturation is the calibrated water saturation.

[0047] In some embodiments, the second water saturation may be specifically a precise water saturation.

[0048] The generating device determines the fluid equivalent modulus corresponding to the oil field to be measured according to the second water saturation, wherein the fluid equivalent modulus is the equivalent modulus of the fluid material in the oil field to be measured.

[0049] In some embodiments, the dry rock equivalent modulus may specifically be the equivalent modulus of the rock in the oil field to be tested, and the fluid equivalent modulus may specifically be the equivalent modulus of the fluid material in the oil field to be tested.

[0050] The generating device combines the model matrix skeleton, dry rock equivalent modulus and fluid equivalent modulus into a rock physics model.

[0051] In some embodiments, the rock physics model may specifically be a rock physics model corresponding to the lauric zeolite conglomerate in the oil field to be tested.

[0052] In some embodiments, in the first step, the density curve of the collapsed section of the oil field to be measured is corrected.

[0053] In the second step, basic parameters such as mud content and dry clay point are obtained.

[0054] The third step is to use the density and sonic wave curves to obtain the density apparent porosity and sonic wave apparent porosity.

[0055] The fourth step is to determine the location information of the lauzenite in the oil field to be tested based on the core analysis and the relative relationship between the density apparent porosity and the acoustic apparent porosity.

[0056] The fifth step is to determine the location information of the lauric zeolite and use the logging curve to obtain the mineral content and pore structure of the oil field to be tested in sections.

[0057] Step 6: Establish the model matrix skeleton based on the mineral content.

[0058] The seventh step is to use the matrix skeleton to establish the dry rock equivalent modulus corresponding to the oil field to be tested.

[0059] The eighth step is to obtain the first water saturation corresponding to the oil field to be tested, perform a regression prediction on the first water saturation, and obtain a water saturation curve close to the actual underground situation.

[0060] The ninth step is to establish the fluid equivalent modulus based on the water saturation curve and reservoir temperature, pressure, salinity and other parameters.

[0061] The tenth step is to replace the calculated fluid into the dry rock using the fluid replacement method based on the calculation results of the model matrix skeleton, dry rock equivalent modulus and fluid equivalent modulus, thereby establishing a rock physics model.

[0062] The method for generating a rock physics model in this embodiment obtains basic parameters of the oil field to be tested by establishing a density curve corresponding to the oil field to be tested, and establishes a model matrix skeleton corresponding to the oil field to be tested based on the density curve and the basic parameters. Based on the model matrix skeleton, a dry rock equivalent modulus corresponding to the oil field to be tested is created, and a fluid equivalent modulus corresponding to the oil field to be tested is created. Then, the model matrix skeleton, the dry rock equivalent modulus and the fluid equivalent modulus are combined into a rock physics model, which enriches the physical properties of the rock physics model, effectively improves the model accuracy of the rock physics model, improves the practicability of the rock physics model, and shortens the creation cycle of the rock physics model.

[0063] See also Figure 2 The embodiment of the present invention provides a method for generating a rock physics model, which may include the following steps:

[0064] S201, obtaining an acoustic time difference curve corresponding to the oil field to be measured, and determining the acoustic wave velocity in the acoustic time difference curve;

[0065] S202, reconstructing a curve according to the acoustic wave velocity to obtain a density curve;

[0066] S203, obtaining basic parameters of the oil field to be tested, and determining the density apparent porosity and acoustic apparent porosity of the oil field to be tested according to the density curve and the basic parameters;

[0067] S204, determining the location information of the lauzenite in the oil field to be measured according to the density apparent porosity and the acoustic apparent porosity;

[0068] S205, performing segmented calculations based on the lauric zeolite position information and the well logging curve of the oil field to be tested to determine the mineral content of the oil field to be tested;

[0069] S206, establishing a model matrix skeleton according to the mineral content;

[0070] S207, establishing the dry rock equivalent modulus corresponding to the oil field to be tested according to the model matrix skeleton;

[0071] S208, obtaining a first water saturation corresponding to the oil field to be tested, performing a return prediction on the first water saturation to obtain a second water saturation, and determining a fluid equivalent modulus corresponding to the oil field to be tested according to the second water saturation;

[0072] S209. Establish a rock physics model based on the model matrix skeleton, dry rock equivalent modulus and fluid equivalent modulus.

[0073] In this embodiment, the generating device obtains the acoustic time difference curve corresponding to the oil field to be measured, and determines the acoustic wave velocity according to the acoustic time difference curve, wherein the acoustic wave time difference curve is a characteristic curve of the oil field to be measured, and the acoustic wave velocity is the velocity characteristic in the acoustic wave time difference curve.

[0074] After determining the acoustic wave velocity, the generating device reconstructs a curve according to the acoustic wave velocity to obtain a density curve.

[0075] In some embodiments, the acoustic time difference curve is mainly used for logging acquisition in a dual-transmit and dual-receive manner, which is less sensitive to the wellbore environment. Therefore, the acoustic time difference curve is used to reconstruct the density curve using the Gardener formula. The specific formula is as follows:

[0076] ρ=kv m ;

[0077] Where ρ represents density in g / cm 3 , v represents the speed of sound waves, the unit is m / s, k represents the proportionality coefficient, which is generally 0.31, and m is a constant, which is generally 0.25.

[0078] The method for generating the rock physics model in this embodiment obtains the acoustic time difference curve corresponding to the oil field to be tested, determines the acoustic wave velocity based on the acoustic time difference curve, and reconstructs the curve based on the acoustic wave velocity to obtain a density curve, thereby ensuring the data accuracy of the density curve of the oil field to be tested, and further ensuring the data accuracy of the rock physics model.

[0079] See also Figure 3 The embodiment of the present invention provides a method for generating a rock physics model, which may include the following steps:

[0080] S301, establishing a density curve corresponding to the oil field to be tested, obtaining a natural gamma curve corresponding to the oil field to be tested, and determining the gamma logging value of the oil field to be tested according to the natural gamma curve;

[0081] S302, determining the shale content according to the gamma logging value;

[0082] S303, obtaining a dry clay point analysis method corresponding to the oil field to be tested;

[0083] S304, determining the dry clay point according to the dry clay point analysis method;

[0084] S305, determining the density apparent porosity and the acoustic apparent porosity of the oil field to be measured according to the density curve and basic parameters;

[0085] S306, determining the location information of the lauric zeolite in the oil field to be measured according to the density apparent porosity and the acoustic apparent porosity;

[0086] S307, performing segmented calculations based on the lauric zeolite position information and the well logging curve of the oil field to be tested to determine the mineral content of the oil field to be tested;

[0087] S308, establishing a model matrix skeleton according to the mineral content;

[0088] S309, establishing the dry rock equivalent modulus corresponding to the oil field to be tested according to the model matrix skeleton;

[0089] S310, obtaining a first water saturation corresponding to the oil field to be tested, performing a return prediction on the first water saturation to obtain a second water saturation, and determining a fluid equivalent modulus corresponding to the oil field to be tested according to the second water saturation;

[0090] S311. Establish a rock physics model based on the model matrix skeleton, dry rock equivalent modulus and fluid equivalent modulus.

[0091] In this embodiment, the basic parameters of the oil field to be tested include mud content and dry clay point, wherein the mud content is a parameter indicating the content of muddy materials in the oil field to be tested, and the dry clay point is a characteristic parameter of dry clay in the oil field to be tested.

[0092] The generating device obtains the natural gamma curve corresponding to the oil field to be tested, and obtains the gamma logging value of the oil field to be tested according to the natural gamma curve, wherein the natural gamma curve is a characteristic curve of the oil field to be tested, and the gamma logging value is a logging value determined according to the natural gamma curve.

[0093] In some embodiments, the natural gamma curve can better reflect the overall lithology changes of the oil field to be tested.

[0094] The generating device calculates the mud content of the oil field to be tested based on the gamma logging value.

[0095] In some embodiments, the calculation formula for the mud content is as follows:

[0096]

[0097]

[0098] Among them, X is the relative value of natural gamma, GR is the natural gamma logging value, GR min is the natural gamma logging value of pure sandstone formation, GR max is the natural gamma logging value of pure mudstone formation, V CLAR is the mud content and a is the empirical coefficient.

[0099] The generating device obtains the dry clay point analysis method corresponding to the oil field to be tested, and then determines the dry clay point according to the dry clay point analysis method, wherein the dry clay point analysis method is a method for analyzing dry clay points.

[0100] In some embodiments, the dry clay point analysis method can be specifically to use neutron-density intersection analysis and acoustic wave transit time-density intersection analysis methods to pick up quartz skeleton points (density: 2.65 g / cm 3 ; Neutron porosity: -0.01%; Acoustic time difference: 55μs / ft), free water point (density: 1g / cm 3 ; Neutron porosity: 1%; Acoustic time difference: 189μs / ft), bound water point (density: 1.15g / cm 3 ; Neutron porosity: 1.05%; Acoustic time difference: 189μs / ft) The dry clay skeleton points of the three porosity curves were determined by triangle analysis to optimize logging interpretation and rock physics modeling parameters.

[0101] The method for generating the rock physics model in this embodiment obtains the dry clay point analysis method corresponding to the oil field to be tested, and then determines the dry clay point according to the dry clay point analysis method, thereby ensuring the data accuracy of the mud content and dry clay points of the oil field to be tested, and further ensuring the data accuracy of the rock physics model.

[0102] See also Figure 4 The embodiment of the present invention provides a method for generating a rock physics model, which may include the following steps:

[0103] S401, establishing a density curve corresponding to the oil field to be tested, and obtaining basic parameters of the oil field to be tested;

[0104] S402, determining the density apparent porosity and the acoustic apparent porosity of the oil field to be measured according to the density curve and basic parameters;

[0105] S403, determining the location information of the lauric zeolite in the oil field to be measured according to the density apparent porosity and the acoustic apparent porosity;

[0106] S404, determining first content information of a first layer section and second content information of a second layer section in the oil field to be tested according to the lauzenite position information and the well logging curve;

[0107] S405, determining the mineral content according to the first content information and the second content information;

[0108] S406, establishing a model matrix skeleton according to the mineral content;

[0109] S407, establishing the dry rock equivalent modulus corresponding to the oil field to be tested according to the model matrix skeleton;

[0110] S408, obtaining a first water saturation corresponding to the oil field to be tested, performing a return prediction on the first water saturation to obtain a second water saturation, and determining a fluid equivalent modulus corresponding to the oil field to be tested according to the second water saturation;

[0111] S409. Establish a rock physics model based on the model matrix skeleton, dry rock equivalent modulus and fluid equivalent modulus.

[0112] In this embodiment, the generating device determines the first layer section and the second layer section in the oil field to be tested according to the lauric zeolite location information and the logging curve, wherein the first layer section is the layer section containing lauric zeolite and the second layer section is the layer section not containing lauric zeolite.

[0113] In some embodiments, the halogenite interval and the halogenite-free interval vertically identified by the apparent porosity difference method are subjected to segmented optimized logging interpretation. For the halogenite-free interval, the sandstone-shale optimized logging interpretation is carried out, and for the halogenite-containing reservoir interval, the multi-mineral component optimized logging interpretation is carried out. The optimized logging interpretation results of the halogenite-containing interval are used to replace the corresponding conventional sandstone-shale optimized logging interpretation interval, so as to obtain the mineral component content close to the actual underground situation.

[0114] The generating device determines the first content information of the first layer segment and determines the second content information of the second layer segment, and then determines the mineral content according to the first content information and the second content information, wherein the first content information is the ore content information corresponding to the first layer segment, and the second content information is the ore content information corresponding to the second layer segment.

[0115] In some embodiments, in the process of optimizing logging interpretation of multiple mineral components, not only the influence of lauzenite content on the results should be considered, but also calcite should be added as an output item. This is because albite will generate a large amount of calcite, which is easy to generate a large amount of calcite after contact with water environment, and the elastic parameters of calcite are quite different from those of quartz, so the two cannot be combined. The specific chemical reaction equation is as follows:

[0116] 2CaAl2Si2O8+2Na + +4H2O+6SiO2=CaAl2Si4O 12 ·4H2O+2NaAlSi3O8+Ca 2+ ;

[0117] The quartz, lauzenite, calcite, and clay minerals obtained from the optimized logging interpretation based on the lauzenite reservoir classification were mixed using the Voigt–Reuss-Hill model (average shale brittleness model) to establish the matrix skeleton.

[0118] The method for generating the rock physics model in this embodiment determines the first layer and the second layer in the oil field to be tested based on the location information of the turbid zeolite and the logging curve, and then determines the first content information of the first layer and the second content information of the second layer, and then determines the mineral content based on the first content information and the second content information, thereby ensuring the data accuracy of the mineral content and thus ensuring the model accuracy of the rock physics model.

[0119] See also Figure 5 The embodiment of the present invention provides a method for generating a rock physics model, which may include the following steps:

[0120] S501, establishing a density curve corresponding to the oil field to be tested, and obtaining basic parameters of the oil field to be tested;

[0121] S502, determining the density apparent porosity and the acoustic apparent porosity of the oil field to be measured according to the density curve and basic parameters;

[0122] S503, determining the location information of the lauric zeolite in the oil field to be measured according to the density apparent porosity and the acoustic apparent porosity;

[0123] S504, performing segmented calculations based on the lauzenite position information and the well logging curve of the oil field to be tested to determine the mineral content of the oil field to be tested;

[0124] S505, establishing a model matrix skeleton according to the mineral content;

[0125] S506, setting the model matrix skeleton as the background medium;

[0126] S507, obtaining pore parameters of minerals in the oil field to be tested;

[0127] S508, filling the pores of the background medium according to the pore parameters to obtain the dry rock equivalent modulus;

[0128] S509, obtaining a first water saturation corresponding to the oil field to be tested, performing a return prediction on the first water saturation to obtain a second water saturation, and determining a fluid equivalent modulus corresponding to the oil field to be tested according to the second water saturation;

[0129] S510: Establish a rock physics model based on the model matrix skeleton, dry rock equivalent modulus and fluid equivalent modulus.

[0130] In this embodiment, the generating device sets the model matrix skeleton as the background medium and determines the pore parameters of the minerals in the oil field to be tested. The generating device fills the pores of the background medium according to the pore parameters to obtain the dry rock equivalent modulus, wherein the background medium is the background medium in the modeling process, and the pore parameters are the data parameters for the pores formed by the minerals in the oil field to be tested.

[0131] In some embodiments, the generating device may set the complex mineral rock skeleton as the background medium, and use the DEM model (digital elevation model) to add pores to the background medium to obtain the dry rock equivalent modulus.

[0132] The method for generating the rock physics model in this embodiment sets the model matrix skeleton as the background medium and determines the pore parameters of the minerals in the oil field to be tested. The generating device fills the pores of the background medium according to the pore parameters to obtain the dry rock equivalent modulus, thereby ensuring the physical properties of the dry rock equivalent modulus and further ensuring the physical properties of the rock physics model.

[0133] See also Figure 6 The embodiment of the present invention provides a method for generating a rock physics model, which may include the following steps:

[0134] S601, establishing a density curve corresponding to the oil field to be tested, and obtaining basic parameters of the oil field to be tested;

[0135] S602, determining the density apparent porosity and the acoustic apparent porosity of the oil field to be measured according to the density curve and basic parameters;

[0136] S603, determining the location information of the lauric zeolite in the oil field to be tested according to the density apparent porosity and the acoustic apparent porosity;

[0137] S604, performing segmented calculations based on the lauric zeolite position information and the well logging curve of the oil field to be tested to determine the mineral content of the oil field to be tested;

[0138] S605, establishing a model matrix skeleton according to the mineral content;

[0139] S606, establishing the dry rock equivalent modulus corresponding to the oil field to be tested according to the model matrix skeleton;

[0140] S607, obtaining a first water saturation corresponding to the oil field to be tested, and performing a return prediction on the first water saturation to obtain a second water saturation;

[0141] S608, obtaining static parameters corresponding to the oil field to be tested, and determining the fluid equivalent modulus according to the static parameters and the second water saturation;

[0142] S609. Establish a rock physics model based on the model matrix skeleton, dry rock equivalent modulus and fluid equivalent modulus.

[0143] In this embodiment, the generating device performs data correction on the first water saturation according to the reservoir resistivity of the oil field to be measured to obtain the second water saturation, wherein the reservoir resistivity is the resistivity of the reservoir in the oil field to be measured, and the second water saturation is the water saturation after the first water saturation is corrected.

[0144] The generating device obtains static parameters corresponding to the oil field to be measured, and determines the fluid equivalent modulus according to the static parameters and the second water saturation, wherein the static parameters are static parameters corresponding to the oil field to be measured.

[0145] In some embodiments, the static parameters may specifically include temperature, pressure, oil density, formation water salinity, and gas-oil ratio.

[0146] In some embodiments, the generating device can use Archie's formula, Indonesian formula and Simandoux formula to obtain the water saturation curve, among which Archie's formula is mainly an interpretation method for water-containing pure sandstone, Indonesian formula is suitable for areas with low mineralization of formation water, and Simandoux formula is suitable for areas with high mineralization of formation water.

[0147] Specifically, the Indonesian formula is as follows:

[0148]

[0149] Where V cl is the clay content, c is the clay content related parameter, R cl is the resistivity of clay, R cl =R sh (1-SI) 2 , R sh is the base resistivity, SI is the silt index of mud, is the effective porosity of the target layer, R w is the formation water resistivity, unit Ω·m, a is the additional conductivity correction factor of lithology, R t is the resistivity of the target layer, S w is the water saturation of the target layer; Rt' is the resistivity value of the reservoir containing turbid zeolite but not oil; x is the intercept, unit Ω·m, R t '=0.717×V laumontite +8.23, the above formula is the scatter intersection fitting formula for reservoirs containing turbid zeolite but without oil, V laumontite It is the content of lauric zeolite.

[0150] In some embodiments, the Woods model (a mixing model) is applied to generate a temperature-pressure gradient curve using temperature and pressure PVT data (data describing the properties of reservoir fluids). At the same time, based on known parameters such as crude oil density, formation water salinity, gas-oil ratio, and the corrected water saturation obtained in the previous step, the oil, gas and water in the rock are mixed to obtain a mixed fluid.

[0151] The method for generating the rock physics model in this embodiment performs data correction on the first water saturation according to the reservoir resistivity of the oil field to be measured to obtain the second water saturation, and then obtains the static parameters corresponding to the oil field to be measured. According to the static parameters and the second water saturation, the fluid equivalent modulus is determined, thereby ensuring the physical properties of the fluid equivalent modulus, and further ensuring the physical properties of the rock physics model.

[0152] See also Figure 7 The embodiment of the present invention provides a method for generating a rock physics model, which may include the following steps:

[0153] S701, establishing a density curve corresponding to the oil field to be tested, and obtaining basic parameters of the oil field to be tested;

[0154] S702, determining the density apparent porosity and the acoustic apparent porosity of the oil field to be measured according to the density curve and basic parameters;

[0155] S703, determining the location information of the lauric zeolite in the oil field to be measured according to the density apparent porosity and the acoustic apparent porosity;

[0156] S704, performing segmented calculations based on the lauzenite position information and the well logging curve of the oil field to be tested to determine the mineral content of the oil field to be tested;

[0157] S705, establishing a model matrix skeleton according to the mineral content;

[0158] S706, establishing the dry rock equivalent modulus corresponding to the oil field to be tested according to the model matrix skeleton;

[0159] S707, obtaining a first water saturation corresponding to the oil field to be tested, performing a return prediction on the first water saturation to obtain a second water saturation, and determining a fluid equivalent modulus corresponding to the oil field to be tested according to the second water saturation;

[0160] S708. Based on the model matrix skeleton, perform fluid replacement on the dry rock equivalent modulus and the fluid equivalent modulus to obtain a rock physics model.

[0161] In this embodiment, the generating device performs fluid replacement on the dry rock equivalent modulus and the fluid equivalent modulus based on the model matrix skeleton, thereby determining the rock physics model.

[0162] In some embodiments, the generating device may perform fluid replacement through a Gassmann model (a multiphase medium theoretical model), thereby establishing an equivalent model of turbid zeolite conglomerate that is close to the actual situation.

[0163] The method for generating the rock physics model in this embodiment is based on the model matrix skeleton, performs fluid replacement on the dry rock equivalent modulus and the fluid equivalent modulus, determines the rock physics model, and thus ensures the physical properties of the rock physics model and the model accuracy of the rock physics model.

[0164] Based on the same inventive concept, Figure 8 As shown, the embodiment of the present invention further provides a device for generating a rock physics model, which is used for an oil field to be tested. The device 800 for generating a rock physics model includes:

[0165] Processing module 802, used to establish a density curve corresponding to the oil field to be tested and obtain basic parameters of the oil field to be tested;

[0166] The processing module 802 is also used to determine the density apparent porosity and the acoustic apparent porosity of the oil field to be measured according to the density curve and the basic parameters;

[0167] The processing module 802 is also used to determine the location information of the lauric zeolite in the oil field to be tested according to the density apparent porosity and the acoustic apparent porosity;

[0168] The processing module 802 is also used to perform segmented calculations based on the lauric zeolite position information and the well logging curve of the oil field to be tested, so as to determine the mineral content of the oil field to be tested;

[0169] The processing module 802 is also used to establish a model matrix skeleton according to the mineral content;

[0170] The processing module 802 is also used to establish the dry rock equivalent modulus corresponding to the oil field to be tested according to the model matrix skeleton;

[0171] The processing module 802 is further used to obtain a first water saturation corresponding to the oil field to be tested, perform a return prediction on the first water saturation to obtain a second water saturation, and determine a fluid equivalent modulus corresponding to the oil field to be tested according to the second water saturation;

[0172] The processing module 802 is also used to establish a rock physics model based on the model matrix skeleton, dry rock equivalent modulus and fluid equivalent modulus.

[0173] In this embodiment, a rock physics model generation device 800 is provided, which is used for an oil field to be tested. The oil field to be tested is an oil field to be surveyed, and the rock physics model is a physical model corresponding to the rock in the oil field to be tested. The processing module 802 establishes a density curve corresponding to the oil field to be tested and obtains basic parameters of the oil field to be tested, wherein the density curve is a curve that can represent the density characteristics of the oil field to be tested, and the basic parameters are parameters that can represent the basic characteristics of the oil field to be tested.

[0174] In some embodiments, the area where the oil field to be tested is located can be specifically a set of regional mudstone caprocks. Due to the water absorption and expansion of clay minerals and the horizontal stress of the formation, the well wall collapses, and density logging cannot perform true wall logging, resulting in distortion.

[0175] The processing module 802 determines the density apparent porosity and the acoustic apparent porosity of the oil field to be measured according to the density curve and the basic parameters, wherein the density apparent porosity is the apparent porosity determined by the density curve, and the acoustic apparent porosity is the apparent porosity determined by the acoustic wave.

[0176] The processing module 802 determines the lauricite location information of the oil field to be tested according to the density apparent porosity and the acoustic apparent porosity, wherein the lauricite location information is the location information of the lauricite in the oil field to be tested.

[0177] The processing module 802 obtains the mineral content of the oil field to be tested by segmenting the well logging curve based on the determined location information of the lauzenite, wherein the mineral content is the content information of each mineral in the oil field to be tested.

[0178] It should be noted that the halogenite minerals in the conglomerate are special, which will cause the reservoir resistivity to be high, affecting the accuracy of well logging interpretation, reservoir evaluation, and rock physics modeling.

[0179] In some embodiments, according to the location information of lauric zeolite, the oil field to be tested is divided into layers containing lauric zeolite and layers not containing lauric zeolite, and the mineral content of the layers containing lauric zeolite and the layers not containing lauric zeolite are determined separately to obtain the mineral content of the oil field to be tested.

[0180] The processing module 802 establishes a model matrix skeleton corresponding to the oil field to be measured according to the model matrix skeleton, wherein the model matrix skeleton is the skeleton of the physical model corresponding to the oil field to be measured.

[0181] In some embodiments, the model matrix skeleton may be specifically equivalent to a complex mineral rock skeleton.

[0182] The processing module 802 creates a dry rock equivalent modulus corresponding to the oil field to be tested based on the model matrix skeleton, obtains a first water saturation corresponding to the oil field to be tested, and performs a return prediction on the first water saturation to obtain a second water saturation, wherein the dry rock equivalent modulus is the equivalent modulus of the dry rock material in the oil field to be tested, the first water saturation is the preset water saturation corresponding to the oil field to be tested, and the second water saturation is the calibrated water saturation.

[0183] In some embodiments, the second water saturation may be specifically a precise water saturation.

[0184] The processing module 802 determines the fluid equivalent modulus corresponding to the oil field to be measured according to the second water saturation, wherein the fluid equivalent modulus is the equivalent modulus of the fluid material in the oil field to be measured.

[0185] In some embodiments, the dry rock equivalent modulus may specifically be the equivalent modulus of the rock in the oil field to be tested, and the fluid equivalent modulus may specifically be the equivalent modulus of the fluid material in the oil field to be tested.

[0186] The processing module 802 combines the model matrix skeleton, dry rock equivalent modulus and fluid equivalent modulus into a rock physics model.

[0187] In some embodiments, the rock physics model may specifically be a rock physics model corresponding to the lauric zeolite conglomerate in the oil field to be tested.

[0188] In some embodiments, the rock physics model is generated as follows: Fig. 9 As shown, specifically, the first step is to reconstruct the logging curve based on the Gardener formula, the second step is to obtain basic parameters, including the mud content and dry clay point, and the third step is the rock physics modeling of the turbid zeolite conglomerate. Among them, the complex mineral rock skeleton equivalence is determined by the optimal solution logging interpretation based on the apparent porosity difference method for turbid zeolite identification and the classification of turbid zeolite reservoirs, and then the dry rock equivalence and mixed fluid equivalence are determined, and then the turbid zeolite conglomerate rock reservoir equivalence is determined. The mixed fluid equivalence can be determined by the water saturation regression prediction method based on the Indonesian correction algorithm. The comparison effect of the predicted curve of the rock physics model and the measured curve is shown in Fig.10 shown.

[0189] The rock physics model generation device 800 in this embodiment establishes a density curve corresponding to the oil field to be tested, obtains the basic parameters of the oil field to be tested, establishes a model matrix skeleton corresponding to the oil field to be tested based on the density curve and the basic parameters, creates a dry rock equivalent modulus corresponding to the oil field to be tested based on the model matrix skeleton, and creates a fluid equivalent modulus corresponding to the oil field to be tested, and then combines the model matrix skeleton, dry rock equivalent modulus and fluid equivalent modulus into a rock physics model, enriching the physical properties of the rock physics model, effectively improving the model accuracy of the rock physics model, improving the practicability of the rock physics model, and shortening the creation cycle of the rock physics model.

[0190] Based on the same inventive concept, an embodiment of the present invention further provides a device for generating a rock physics model. The device 800 for generating a rock physics model includes:

[0191] The processing module 802 is also used to obtain the acoustic time difference curve corresponding to the oil field to be measured, and determine the acoustic wave velocity in the acoustic time difference curve;

[0192] The processing module 802 is further used to reconstruct the curve according to the acoustic wave velocity to obtain a density curve.

[0193] The rock physics model generation device 800 in this embodiment obtains the acoustic time difference curve corresponding to the oil field to be tested, determines the acoustic wave velocity according to the acoustic time difference curve, and reconstructs the curve according to the acoustic wave velocity to obtain a density curve, thereby ensuring the data accuracy of the density curve of the oil field to be tested, and further ensuring the data accuracy of the rock physics model.

[0194] Based on the same inventive concept, an embodiment of the present invention further provides a device for generating a rock physics model. The device 800 for generating a rock physics model includes:

[0195] The processing module 802 is also used to obtain a natural gamma curve corresponding to the oil field to be tested, and determine the gamma logging value of the oil field to be tested according to the natural gamma curve;

[0196] The processing module 802 is also used to determine the shale content according to the gamma logging value;

[0197] The processing module 802 is also used to obtain the dry clay point analysis method corresponding to the oil field to be tested;

[0198] The processing module 802 is further used to determine the dry clay point according to the dry clay point analysis method.

[0199] The rock physics model generation device 800 in this embodiment obtains the dry clay point analysis method corresponding to the oil field to be tested, and then determines the dry clay point according to the dry clay point analysis method, thereby ensuring the data accuracy of the mud content and dry clay points of the oil field to be tested, and further ensuring the data accuracy of the rock physics model.

[0200] Based on the same inventive concept, an embodiment of the present invention further provides a device for generating a rock physics model. The device 800 for generating a rock physics model includes:

[0201] The processing module 802 is further used to determine the first content information of the first layer section and the second content information of the first layer section in the oil field to be tested according to the lauric zeolite position information and the logging curve, wherein the first layer section is a layer section containing lauric zeolite and the second layer section is a layer section not containing lauric zeolite;

[0202] The processing module 802 is further used to determine the mineral content according to the first content information and the second content information.

[0203] The rock physics model generating device 800 in this embodiment determines the first layer and the second layer in the oil field to be tested according to the location information of the turbid zeolite and the logging curve, and then determines the first content information of the first layer and the second content information of the second layer, and then determines the mineral content according to the first content information and the second content information, thereby ensuring the data accuracy of the mineral content and thus ensuring the model accuracy of the rock physics model.

[0204] Based on the same inventive concept, an embodiment of the present invention further provides a device for generating a rock physics model. The device 800 for generating a rock physics model includes:

[0205] The processing module 802 is also used to set the model matrix skeleton as the background medium;

[0206] The processing module 802 is also used to obtain the pore parameters of the minerals in the oil field to be tested;

[0207] The processing module 802 is also used to fill the pores of the background medium according to the pore parameters to obtain the dry rock equivalent modulus.

[0208] The rock physics model generating device 800 in this embodiment sets the model matrix skeleton as the background medium and determines the pore parameters of the minerals in the oil field to be tested. The generating device fills the pores of the background medium according to the pore parameters to obtain the dry rock equivalent modulus, thereby ensuring the physical properties of the dry rock equivalent modulus and further ensuring the physical properties of the rock physics model.

[0209] Based on the same inventive concept, an embodiment of the present invention further provides a device for generating a rock physics model. The device 800 for generating a rock physics model includes:

[0210] The processing module 802 is further used to perform data correction on the first water saturation according to the reservoir resistivity of the oil field to be measured, so as to obtain a second water saturation;

[0211] The processing module 802 is further used to obtain static parameters corresponding to the oil field to be tested, and determine the fluid equivalent modulus according to the static parameters and the second water saturation.

[0212] The rock physics model generating device 800 in this embodiment performs data correction on the first water saturation according to the reservoir resistivity of the oil field to be measured to obtain the second water saturation, and then obtains the static parameters corresponding to the oil field to be measured, and determines the fluid equivalent modulus according to the static parameters and the second water saturation, thereby ensuring the physical properties of the fluid equivalent modulus, and further ensuring the physical properties of the rock physics model.

[0213] Based on the same inventive concept, an embodiment of the present invention further provides a device for generating a rock physics model. The device 800 for generating a rock physics model includes:

[0214] The processing module 802 is also used to perform fluid replacement on the dry rock equivalent modulus and the fluid equivalent modulus based on the model matrix skeleton to obtain a rock physics model.

[0215] The rock physics model generating device 800 in this embodiment performs fluid replacement on the dry rock equivalent modulus and the fluid equivalent modulus based on the model matrix skeleton to determine the rock physics model, thereby ensuring the physical properties of the rock physics model and the model accuracy of the rock physics model.

[0216] Based on the same inventive concept, an embodiment of the present invention further provides a storage medium on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method for generating a rock physical model in any possible implementation manner described above are implemented.

[0217] Alternatively, the storage medium may be a non-transitory computer-readable storage medium, for example, the non-transitory computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0218] Based on the same inventive concept, see Fig.11 The embodiment of the present invention also provides an electronic device, including a memory 111 (such as a non-volatile memory), a processor 112, and a computer program stored in the memory 111 and executable on the processor 112. When the processor 112 executes the program, the steps of the method for generating a rock physics model in any possible implementation manner described above are implemented, which can be equivalent to the rock physics model generation device as described above. Of course, the processor can also be used to process other data or operations. The electronic device can be a PC, a server, a terminal, and other devices.

[0219] like Fig.11 As shown, the electronic device may also generally include: a memory 113, a network interface 114, and an internal bus 115. In addition to these components, other hardware may also be included, which will not be described in detail.

[0220] It should be pointed out that the above-mentioned rock physics model generation device can be implemented by software. As a device in a logical sense, it is formed by the processor 112 of the electronic device in which it is located reading the computer program instructions stored in the non-volatile memory into the memory 113 for execution.

[0221] The embodiments of the subject matter and functional operations described in this specification may be implemented in the following: digital electronic circuits, tangibly embodied computer software or firmware, computer hardware including the structures disclosed in this specification and their structural equivalents, or a combination of one or more of them. The embodiments of the subject matter described in this specification may be implemented as one or more computer programs, i.e., one or more modules in computer program instructions encoded on a tangible non-temporary program carrier to be executed by a data processing device or to control the operation of the data processing device. Alternatively or additionally, the program instructions may be encoded on an artificially generated propagation signal, such as a machine-generated electrical, optical or electromagnetic signal, which is generated to encode information and transmit it to a suitable receiver device for execution by a data processing device. The computer storage medium may be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of one or more of them.

[0222] The processes and logic flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform the corresponding functions by operating on input data and generating output. The processes and logic flows can also be performed by special purpose logic circuits, such as FPGAs (field programmable gate arrays) or ASICs (application specific integrated circuits), and the apparatus can also be implemented as special purpose logic circuits.

[0223] Computers suitable for executing computer programs include, for example, general and / or special microprocessors, or any other type of central processing unit. Typically, the central processing unit will receive instructions and data from a read-only memory and / or a random access memory. The basic components of a computer include a central processing unit for implementing or executing instructions and one or more memory devices for storing instructions and data. Typically, the computer will also include one or more large-capacity storage devices for storing data, such as magnetic disks, magneto-optical disks, or optical disks, or the computer will be operably coupled to this large-capacity storage device to receive data from it or to transmit data to it, or both. However, the computer does not necessarily have such a device. In addition, the computer can be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device such as a universal serial bus (USB) flash drive, to name a few.

[0224] Computer readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including, for example, semiconductor memory devices (e.g., EPROM, EEPROM and flash memory devices), magnetic disks (e.g., internal hard disks or removable disks), magneto-optical disks, and CD-ROM and DVD-ROM disks. The processor and memory may be supplemented by, or incorporated in, special purpose logic circuitry.

[0225] Although this specification includes many specific implementation details, these should not be interpreted as limiting the scope of any invention or the scope of protection claimed, but are mainly used to describe the features of the specific embodiments of specific inventions. Certain features described in multiple embodiments in this specification may also be implemented in combination in a single embodiment. On the other hand, the various features described in a single embodiment may also be implemented separately in multiple embodiments or in any suitable sub-combination. In addition, although the features may work as above in certain combinations and even initially claim protection, one or more features from the claimed combination may be removed from the combination in some cases, and the claimed combination may point to a sub-combination or a variation of a sub-combination.

[0226] Similarly, although operations are depicted in a particular order in the accompanying drawings, this should not be understood as requiring that these operations be performed in the particular order shown or performed sequentially, or requiring that all illustrated operations be performed to achieve the desired results. In some cases, multitasking and parallel processing may be advantageous. In addition, the separation of various system modules and components in the above-described embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product, or packaged into multiple software products.

[0227] Thus, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the particular order or sequential order shown to achieve the desired results. In some implementations, multitasking and parallel processing may be advantageous.

[0228] It should be noted that, in this article, 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. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0229] The above is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features applied herein.

Claims

1. A method for generating a rock physics model, characterized in that: For the oil field to be tested, the method for generating the rock physics model includes: Establishing a density curve corresponding to the oil field to be tested, and obtaining basic parameters of the oil field to be tested; Determining the density apparent porosity and the acoustic apparent porosity of the oil field to be measured according to the density curve and basic parameters; Determining the location information of the lauzenite in the oil field to be tested according to the density apparent porosity and the acoustic apparent porosity; According to the launate position information and the well logging curve of the oil field to be tested, segmented calculation is performed to determine the mineral content of the oil field to be tested; According to the mineral content, a model matrix skeleton is established; According to the model matrix skeleton, establishing the dry rock equivalent modulus corresponding to the oil field to be tested; Acquire a first water saturation corresponding to the oil field to be measured, perform a localized prediction on the first water saturation to obtain a second water saturation, and determine a fluid equivalent modulus corresponding to the oil field to be measured according to the second water saturation; The rock physics model is established according to the model matrix skeleton, the dry rock equivalent modulus and the fluid equivalent modulus.

2. The method for generating a rock physics model according to claim 1, characterized in that: The step of establishing a density curve corresponding to the oil field to be measured specifically includes: Obtaining an acoustic time difference curve corresponding to the oil field to be measured, and determining the acoustic wave velocity in the acoustic time difference curve; A curve reconstruction is performed according to the acoustic wave velocity to obtain the density curve.

3. The method for generating a rock physics model according to claim 1, characterized in that: The basic parameters include mud content and dry clay points. The basic parameters of the oil field to be tested are obtained by: Obtaining a natural gamma curve corresponding to the oil field to be tested, and determining a gamma logging value of the oil field to be tested according to the natural gamma curve; Determining the shale content according to the gamma logging value; Obtaining a dry clay point analysis method corresponding to the oil field to be tested; According to the dry clay point analysis method, the dry clay point is determined.

4. The method for generating a rock physics model according to claim 1, characterized in that: The step of performing segmented calculation based on the lauzenite position information and the well logging curve of the oil field to be tested to determine the mineral content of the oil field to be tested specifically includes: Determine, according to the launic zeolite position information and the well logging curve, first content information of a first layer section and second content information of a second layer section in the oil field to be tested, wherein the first layer section is a layer section containing launic zeolite, and the second layer section is a layer section not containing launic zeolite; The mineral content is determined according to the first content information and the second content information.

5. The method for generating a rock physics model according to claim 1, characterized in that: The step of establishing the dry rock equivalent modulus corresponding to the oil field to be tested according to the model matrix skeleton specifically includes: Setting the model matrix skeleton as a background medium; Obtaining pore parameters of minerals in the oil field to be tested; According to the pore parameters, the pores of the background medium are filled to obtain the dry rock equivalent modulus.

6. The method for generating a rock physics model according to claim 1, characterized in that: Determining the fluid equivalent modulus corresponding to the oil field to be tested according to the second water saturation specifically includes: The static parameters corresponding to the oil field to be measured are obtained, and the fluid equivalent modulus is determined according to the static parameters and the second water saturation.

7. The method for generating a rock physical model according to any one of claims 1 to 6, characterized in that: The step of establishing the rock physics model according to the model matrix skeleton, the dry rock equivalent modulus and the fluid equivalent modulus specifically includes: Based on the model matrix skeleton, the dry rock equivalent modulus and the fluid equivalent modulus are subjected to fluid replacement to obtain the rock physics model.

8. A device for generating a rock physics model, characterized in that: For the oil field to be tested, the rock physics model generation device comprises: A processing module, used to establish a density curve corresponding to the oil field to be tested and obtain basic parameters of the oil field to be tested; The processing module is further used to determine the density apparent porosity and the acoustic apparent porosity of the oil field to be measured according to the density curve and basic parameters; The processing module is further used to determine the location information of the lauzenite in the oil field to be tested according to the density apparent porosity and the acoustic apparent porosity; The processing module is further used to perform segmented calculations based on the lauzenite position information and the well logging curve of the oil field to be tested, so as to determine the mineral content of the oil field to be tested; The processing module is also used to establish a model matrix skeleton according to the mineral content; The processing module is further used to establish the dry rock equivalent modulus corresponding to the oil field to be tested according to the model matrix skeleton; The processing module is further used to obtain a first water saturation corresponding to the oil field to be tested, perform a return prediction on the first water saturation to obtain a second water saturation, and determine a fluid equivalent modulus corresponding to the oil field to be tested according to the second water saturation; The processing module is also used to establish the rock physics model according to the model matrix skeleton, the dry rock equivalent modulus and the fluid equivalent modulus.

9. A storage medium, characterized in that: The storage medium stores programs or instructions, and when the programs or instructions are executed by the processor, the steps of the method for generating a rock physical model as described in any one of claims 1 to 7 are implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method for generating a rock physical model according to any one of claims 1 to 7 are implemented.

Images