Shale oil reservoir geology and engineering double-dessert quantitative evaluation method and shale oil reservoir geology and engineering double-dessert quantitative evaluation system

Abstract

The invention discloses a shale oil reservoir geology and engineering double-dessert quantitative evaluation method and system. The method comprises the following steps: acquiring pre-stack earthquake and logging data; based on a Zeoppritz equation, utilizing a pre-stack seismic inversion technology to obtain reservoir elastic parameters; calculating longitudinal and transverse wave impedance according to the reservoir elastic parameters; calculating a brittleness index as an engineering dessert parameter according to the reservoir elastic parameter and the longitudinal and transverse wave impedance; calculating the bulk modulus and shear modulus of the reservoir according to the elastic parameters of the reservoir; obtaining TOC content, porosity and free hydrocarbon as geological dessert parameters by combining logging data, reservoir elastic parameters, bulk modulus and shear modulus; calculating formation pressure; and performing comprehensive quantitative evaluation based on the engineering dessert parameters, the geological dessert parameters and the formation pressure. According to the method, the overlapping area of the geological and engineering double sweet spots is effectively identified, well position deployment and fracturing design are optimized, the balanced fracturing effect is ensured, the oil and gas recovery efficiency is improved, and the exploitation efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the field of shale oil and gas exploration and development, and particularly relates to a method and system for quantitatively evaluating geological and engineering double sweet spots in shale oil reservoirs. Background Art

[0002] With the gradual reduction of global conventional oil resources, shale oil has become an important alternative energy resource. Shale oil refers to the oil stored in rich organic matter shale formations, and usually special process technologies are required to achieve industrial oil production. Different from conventional oil reservoirs, shale oil shows the characteristics of "self-generation and self-storage", with short oil and gas migration distance and wide distribution, but low resource abundance and great exploitation difficulty. Due to its huge resource volume, shale oil has become an important way to solve energy demand.

[0003] The identification of shale oil sweet spots is one of the core technologies in current exploration and development. Shale oil sweet spots are usually divided into geological sweet spots and engineering sweet spots. Geological sweet spots focus on identifying the oil-bearing property and reservoir property of reservoirs, and are usually predicted through geological parameters such as TOC (total organic carbon content), porosity and free hydrocarbons; while engineering sweet spots focus on the compressibility and transformability of reservoirs, and are evaluated through engineering parameters such as brittleness index, bulk modulus and shear modulus. Through these methods, the industry usually combines various data such as seismic data, logging data and mud logging data to comprehensively evaluate shale oil reservoirs, and then deploy horizontal wells and carry out fracturing operations.

[0004] However, the existing evaluation methods have low prediction accuracy for the distribution of geological sweet spots and engineering sweet spots, and cannot accurately identify the overlapping areas of geological sweet spots and engineering sweet spots, which affects well placement and exploitation efficiency. At the same time, the existing technologies have low prediction accuracy for brittleness parameters and formation pressure, resulting in uneven fracturing effects and affecting the ultimate oil and gas recovery rate. Summary of the Invention

[0005] The present invention is proposed to solve the problems that the existing evaluation methods have low prediction accuracy for the distribution of geological sweet spots and engineering sweet spots, cannot accurately identify the overlapping areas of geological sweet spots and engineering sweet spots, which affects well placement and exploitation efficiency. At the same time, the existing technologies have low prediction accuracy for brittleness parameters and formation pressure, resulting in uneven fracturing effects and affecting the ultimate oil and gas recovery rate. The purpose of the present invention is to provide a method and system for quantitatively evaluating geological and engineering double sweet spots in shale oil reservoirs.

[0006] The present invention is achieved by the following technical solutions:

[0007] A method for quantitatively evaluating geological and engineering double sweet spots in shale oil reservoirs, comprising the following steps:

[0008] S1. Obtain pre-stack seismic data and logging data of the reservoir section;

[0009] S2. Based on the Zoeppritz equation, using prestack seismic inversion technology, obtain the reservoir elastic parameters from the prestack seismic data acquired in step S1.

[0010] S3. Calculate the P-wave impedance and S-wave impedance based on the reservoir elastic parameters obtained in step S2.

[0011] S4. Calculate the brittleness index based on the reservoir elastic parameters obtained in step S2 and the P-wave impedance and S-wave impedance obtained in step S3, and use the brittleness index as the engineering sweet spot parameter.

[0012] S5. Calculate the reservoir bulk modulus and reservoir shear modulus based on the reservoir elastic parameters obtained in step S2.

[0013] S6. Combining the logging data obtained in step S1, the reservoir elastic parameters obtained in step S2, and the reservoir bulk modulus and reservoir shear modulus obtained in step S5, use the Bayesian inversion method to obtain the TOC content, porosity, and free hydrocarbons, and use the TOC content, porosity, and free hydrocarbons as the geological sweet spot parameters.

[0014] S7. Through core measurement and mud logging measurement, use the Voigt rock physics model to calculate the formation pressure.

[0015] S8. Based on the engineering sweet spot parameters obtained in step S4, the geological sweet spot parameters obtained in step S6, and the formation pressure obtained in step S7, conduct a comprehensive quantitative evaluation of the geological and engineering double sweet spots of shale oil in the study area.

[0016] In the above technical solution, the reservoir elastic parameters include P-wave velocity, S-wave velocity, and density.

[0017] In the above technical solution, the specific calculation formula for the P-wave impedance is:

[0018] Ip = Vp * Rho

[0019] Where: Ip represents the P-wave impedance, with the unit of g / cm 3 *m / s; Vp represents the P-wave velocity, with the unit of m / s; Rho represents the density, with the unit of g / cm 3 .

[0020] In the above technical solution, the calculation formula for the S-wave impedance is:

[0021] Is = Vs * Rho

[0022] Where: Is represents the S-wave impedance, with the unit of g / cm 3 *m / s; Vs represents the S-wave velocity, with the unit of m / s; Rho represents the density, with the unit of g / cm 3 .

[0023] In the above technical solution, the calculation formula of the brittleness index is as follows:

[0024]

[0025] In the formula: BI represents the brittleness index, with the unit of %; Ip represents the longitudinal wave impedance, with the unit of g / cm 3 *m / s; Is represents the shear wave impedance, with the unit of g / cm 3 *m / s; Rho represents the density, with the unit of g / cm 3 .

[0026] In the above technical solution, the calculation formula of the reservoir bulk modulus is as follows:

[0027] K = Rho(Vp 2 - 4Vs 2 / 3)

[0028] In the formula: K represents the reservoir bulk modulus, with the unit of ; Rho represents the density, with the unit of g / cm 3 ; Vp represents the longitudinal wave velocity, with the unit of m / s; Vs represents the shear wave velocity, with the unit of m / s.

[0029] In the above technical solution, the calculation formula of the reservoir shear modulus is as follows:

[0030] μ = RhoVs 2

[0031] In the formula: μ represents the reservoir shear modulus, with the unit of Pa; Rho represents the density, with the unit of g / cm 3 ; Vs represents the shear wave velocity, with the unit of m / s.

[0032] In the above technical solution, step S7 specifically includes the following steps:

[0033] S71. Determine the bulk modulus component and the shear modulus component through core measurement and logging measurement, and use the Voigt rock physics model to calculate the maximum modulus value and the minimum modulus value of the bulk modulus component and the shear modulus component respectively;

[0034] S72. Calculate the maximum velocity value according to the maximum modulus value of the bulk modulus component obtained in step S71 and the maximum modulus value of the shear modulus component; at the same time, calculate the minimum velocity value according to the minimum modulus value of the bulk modulus component obtained in step S71 and the minimum modulus value of the shear modulus component;

[0035] S73. Calculate the formation pressure according to the maximum velocity value, the minimum velocity value obtained in step S72 and the reservoir elastic parameters obtained in step S2.

[0036] In the above technical solution, the calculation formula for the maximum modulus value of the bulk modulus component is:

[0037]

[0038] In the formula: K max represents the maximum modulus value of the bulk modulus component, with the unit of Pa; f i represents the i-th bulk modulus component; K i represents the i-th bulk modulus, with the unit of Pa; i = 1, 2... N, where N represents the number of classifications of different parameters.

[0039] In the above technical solution, the calculation formula for the maximum modulus value of the shear modulus component is:

[0040]

[0041] In the formula: μ max represents the maximum modulus value of the shear modulus component, with the unit of Pa; f i represents the i-th bulk modulus component; μ i represents the i-th shear modulus, with the unit of Pa; i = 1, 2... N, where N represents the number of classifications of different parameters.

[0042] In the above technical solution, the calculation formula for the minimum modulus value of the bulk modulus component is:

[0043]

[0044] In the formula: K min represents the minimum modulus value of the bulk modulus component in Pa; f i represents the i-th bulk modulus component; K i represents the i-th bulk modulus, with the unit of Pa; i = 1, 2... N, where N represents the number of classifications of different parameters.

[0045] In the above technical solution, the calculation formula for the minimum modulus value of the shear modulus component is:

[0046]

[0047] In the formula: μ min represents the minimum modulus value of the shear modulus component in Pa; f i represents the i-th bulk modulus component; μ i represents the i-th shear modulus, with the unit of Pa; i = 1, 2... N, where N represents the number of classifications of different parameters.

[0048] In the above technical solution, the calculation formula for the maximum speed value is:

[0049]

[0050] Where: Vp max represents the maximum velocity value, with the unit of m / s; K max represents the maximum modulus value of the bulk modulus component, with the unit of Pa; μ max represents the maximum modulus value of the shear modulus component, with the unit of Pa.

[0051] In the above technical solution, the calculation formula for the minimum velocity value is:

[0052]

[0053] Where: Vp min represents the minimum velocity value, with the unit of m / s; K min represents the minimum modulus value of the bulk modulus component, with the unit of Pa; μ min represents the minimum modulus value of the shear modulus component, with the unit of Pa.

[0054] In the above technical solution, the calculation formula for the formation pressure is:

[0055]

[0056] Where: P f represents the formation pressure, with the unit of; Vp max represents the maximum velocity value, with the unit of m / s; Vp min represents the minimum velocity value, with the unit of m / s; Vp represents the P-wave velocity, with the unit of m / s; h represents the formation depth, with the unit of m; G represents the acceleration due to gravity, with the unit of N / kg; H represents the upper limit of integration, with the unit of m; Rho represents the density, with the unit of g / cm 3 .

[0057] In the above technical solution, the calculation formula for the comprehensive quantitative evaluation of the geological and engineering double sweet spots of shale oil in the study area is:

[0058]

[0059] Where: SOQF represents the quality factor of the oil shale double sweet spot, with the unit of; i = 1, 2, 3, respectively representing the I, II, and III types of sweet spots; A i represents the weighting coefficient of the i-th type of sweet spot, A1 = 1.0 for type I, A2 = 0.7 for type II, and A3 = 0.4 for type III; n is the total number of geological and engineering sweet spot parameters participating in the calculation, dimensionless; C j represents the single-parameter weight corresponding to the j-th parameter, and for the three types of oil shale, namely matrix type, laminar type, and interlayer type, the sum of the single-parameter weights of each parameter participating in the calculation of the sweet spot of each type of oil shale is equal to 1.

[0060] A geological and engineering double sweet spot quantitative evaluation system for shale oil reservoirs, comprising a processor and a memory, wherein computer-readable instructions are stored on the memory, and characterized in that: when the computer-readable instructions are executed by the processor, the foregoing geological and engineering double sweet spot quantitative evaluation method for shale oil reservoirs is implemented.

[0061] The beneficial effects of the present invention are:

[0062] The present invention provides a geological and engineering double sweet spot quantitative evaluation method and system for shale oil reservoirs. By calculating the brittleness index and combining well logging data, reservoir elastic parameters and Bayesian inversion method, TOC content, porosity and free hydrocarbons are obtained as geological sweet spot parameters, improving the recognition accuracy of geological sweet spots. Through core and mud logging measurements, the formation pressure is accurately calculated using the Voigt model, improving the pressure prediction accuracy. The geological sweet spot, engineering sweet spot and formation pressure are comprehensively and quantitatively evaluated to effectively identify the overlapping area of geological and engineering double sweet spots, optimize well location deployment and fracturing design, ensure balanced fracturing effects, improve oil and gas recovery rate and increase production efficiency. Description of the Drawings

[0063] Figure 1 is the method flow chart of the present invention.

[0064] For those of ordinary skill in the art, other related drawings can be obtained based on the above drawings without creative efforts. Detailed Embodiments

[0065] In order to enable those skilled in the art of the present technology to better understand the technical solutions of the present invention, the technical solutions of the present invention will be further described below with reference to the drawings in the specification and through specific embodiments.

[0066] Example 1

[0067] As Figure 1 shown, a geological and engineering double sweet spot quantitative evaluation method for shale oil reservoirs includes the following steps:

[0068] S1. Obtain prestack seismic data and well logging data of the reservoir section;

[0069] The prestack seismic data refers to the original seismic data that has not been stacked when the seismic wave is reflected back to the ground after passing through the underground medium; the prestack seismic data includes the reflection wave information of each seismic receiving point at different incident angles (i.e., offset), retaining rich elastic wave parameters, which is the initial stage of data processing and is used for more accurate seismic inversion and elastic parameter extraction. Due to retaining more physical information, the prestack seismic data can help determine parameters such as the lithology, porosity, and fluid content of the reservoir. Especially in shale oil exploration, it can provide more detailed formation characteristics and sweet spot identification;

[0070] The logging data (LoggingData) refers to the data obtained by continuously measuring the underground formation during the drilling process with specialized logging tools, which is used to evaluate and analyze the physical properties, oil-bearing property, gas-bearing property, and lithology of the formation, etc.; logging data is an indispensable key data source in the process of oil and gas exploration and development, and can provide an important basis for reservoir evaluation and well location optimization.

[0071] In the present invention, by introducing pre-stack seismic data, richer physical information (such as elastic wave parameters, reflected wave information at different incident angles, etc.) is retained, making subsequent seismic inversion and elastic parameter extraction more accurate. Especially in shale oil exploration, the use of pre-stack data can help to more accurately determine the lithology, porosity, and fluid content of the reservoir, and improve the recognition accuracy of formation characteristics and sweet spots.

[0072] S2. According to the principle of seismic exploration, based on the Zoeppritz equation, using the pre-stack seismic data obtained in step S1, and applying the pre-stack seismic inversion technique, the elastic parameters of the reservoir are obtained.

[0073] The elastic parameters of the reservoir include P-wave velocity, S-wave velocity, and density.

[0074] The Zoeppritz equation is a set of mathematical equations used to describe the reflection and transmission behavior of seismic waves when propagating at the interface of different media, and is widely used in geophysics, especially in oil and gas exploration, to explain the reflection coefficient and transmission coefficient of seismic waves between different rock layers.

[0075] The pre-stack seismic inversion technique (Pre-stackSeismicInversion) is a key technique used in seismic exploration. By inverting the pre-stack seismic data, the elastic parameters of the underground medium (such as P-wave velocity, S-wave velocity, and density, etc.) are obtained.

[0076] In the present invention, using the Zoeppritz equation in combination with pre-stack seismic data can accurately describe the reflection and transmission behavior of seismic waves between different rock layers; the pre-stack seismic inversion technique can more accurately invert the elastic parameters of the underground medium (such as P-wave velocity, S-wave velocity, and density) by using the unstacked seismic data (i.e., the original data containing more offset and incident angle information), thereby improving the accuracy of the inversion result.

[0077] S3. Calculate the P-wave impedance and S-wave impedance according to the elastic parameters of the reservoir obtained in step S2.

[0078] The specific calculation formula for the P-wave impedance is:

[0079] Ip = Vp * Rho

[0080] In the formula: Ip represents the longitudinal wave impedance, with the unit of g / cm 3 *m / s; Vp represents the longitudinal wave velocity, with the unit of m / s; Rho represents the density, with the unit of g / cm 3 ;

[0081] The calculation formula for the shear wave impedance is as follows:

[0082] Is = Vs * Rho

[0083] In the formula: Is represents the shear wave impedance, with the unit of g / cm 3 *m / s; Vs represents the shear wave velocity, with the unit of m / s; Rho represents the density, with the unit of g / cm 3 .

[0084] In the present invention, by calculating the longitudinal wave impedance and the shear wave impedance, the physical properties of the reservoir can be more accurately characterized; the longitudinal wave impedance and the shear wave impedance are important parameters for evaluating the reservoir lithology and hydrocarbon-bearing property, and they are closely related to the density and elastic parameters (such as the longitudinal wave velocity and the shear wave velocity) of the reservoir; at the same time, the longitudinal wave impedance is sensitive to the compression property of the rock, while the shear wave impedance is more sensitive to the shear property and the fluid; by comprehensively using the longitudinal wave and the shear wave impedance, the physical property characteristics of the reservoir can be more comprehensively analyzed, especially for the identification of sweet spots in complex reservoirs (such as shale oil and gas, tight sandstone, etc.) is more effective; this comprehensive analysis improves the accuracy of reservoir identification.

[0085] S4. Calculate the brittleness index based on the reservoir elastic parameters obtained in step S2, the longitudinal wave impedance obtained in step S3, and the shear wave impedance, and use the brittleness index as the engineering sweet spot parameter;

[0086] The brittleness index (BrittlenessIndex, BI) is a parameter used to evaluate the ability of a rock to undergo brittle fracture when subjected to an external force; the brittleness index is an important index in oil and gas exploration and development, especially in the development of shale oil and gas and other unconventional oil and gas resources, and it is used to judge whether the reservoir is suitable for transformation by hydraulic fracturing technology;

[0087] The calculation formula for the brittleness index is as follows:

[0088]

[0089] In the formula: BI represents the brittleness index, with the unit of %; Ip represents the longitudinal wave impedance, with the unit of g / cm 3 *m / s; Is represents the shear wave impedance, with the unit of g / cm 3 *m / s; Rho represents the density, with the unit of g / cm 3 ;

[0090] The engineering dessert parameters are key parameters used to evaluate the producibility and transformability of reservoirs in engineering operations (such as hydraulic fracturing) during oil and gas exploration and development. They are mainly used to determine whether a reservoir is suitable for transformation and exploitation through technical means, so as to achieve better economic benefits.

[0091] In the present invention, by using the brittleness index calculation formula of longitudinal wave impedance, transverse wave impedance and density, the brittle characteristics of the reservoir can be quantified. This calculation method combines different physical parameters and can more accurately evaluate the brittleness of the reservoir, rather than relying only on a single parameter. High-brittleness reservoirs are more likely to generate fractures during hydraulic fracturing, thereby improving the fluidity and recovery rate of oil and gas. At the same time, through the brittleness index, reservoir areas with high brittleness and easy to transform can be identified. By selecting these areas for fracturing operations, the production efficiency can be greatly improved, the operation cost can be reduced, and the economic benefits of the oil and gas field can be increased.

[0092] S5. Calculate the bulk modulus and shear modulus of the reservoir according to the reservoir elastic parameters obtained in step S2.

[0093] The bulk modulus (BulkModulus, K) of the reservoir is a physical parameter that measures the ability of a rock to resist volume change under the action of external pressure. It represents the difficulty of volume change of a unit volume of rock when uniformly compressed. For reservoir rocks, the bulk modulus reflects its compressibility and is closely related to characteristics such as porosity and fluid content of the reservoir.

[0094] The calculation formula for the bulk modulus of the reservoir is:

[0095] K = Rho(Vp 2 - 4Vs 2 / 3)

[0096] In the formula: K represents the bulk modulus of the reservoir, with the unit of Pa; Rho represents density, with the unit of g / cm 3 ; Vp represents the longitudinal wave velocity, with the unit of g / cm 3 ; Vs represents the transverse wave velocity, with the unit of m / s;

[0097] The shear modulus (ShearModulus) of the reservoir is an important physical parameter that reflects the deformation ability of a rock under the action of shear force. It describes the difficulty of a reservoir rock to resist deformation when subjected to shear stress. The shear modulus is one of the elastic properties of the reservoir and plays an important role in oil and gas exploration and development, especially in aspects such as hydraulic fracturing design, reservoir evaluation and brittleness evaluation.

[0098] The calculation formula for the shear modulus of the reservoir is:

[0099] μ = RhoVs 2

[0100] Where: μ represents the reservoir shear modulus, with the unit of Pa; Rho represents the density, with the unit of g / cm 3 ; Vs represents the shear wave velocity, with the unit of m / s;

[0101] In the present invention, the reservoir bulk modulus reflects the compressibility of the rock, while the reservoir shear modulus reflects the deformation ability of the rock under shear force; reservoirs with low bulk modulus and low shear modulus are more easily transformed by external forces to form complex fracture networks; by accurately calculating these two parameters, it can provide an important basis for hydraulic fracturing design, ensure more efficient fracturing operations, and improve oil and gas recovery rates.

[0102] S6. Combining the logging data obtained in step S1, the reservoir elastic parameters obtained in step S2, the reservoir bulk modulus and the reservoir shear modulus obtained in step S5, using the Bayesian inversion method, obtain the TOC content, porosity and free hydrocarbons, and use the TOC content, porosity and free hydrocarbons as geological sweet spot parameters;

[0103] The Bayesian inversion method is an inversion technique based on Bayesian statistical theory for inferring the physical parameters of underground media from observed data. It is widely used in fields such as oil and gas exploration, seismic inversion and geological modeling, especially suitable for physical property prediction and uncertainty analysis of complex reservoirs; this application uses the method disclosed in the patent "A Joint Bayesian Inversion Method and System for Reservoir Lithology and Physical Property Parameters - CN114563823A" for inversion;

[0104] In the present invention, by combining various physical parameters such as logging data, reservoir elastic parameters, bulk modulus and shear modulus, and using the Bayesian inversion method, the advantages of various data sources can be comprehensively utilized, so as to more comprehensively and accurately evaluate the physical properties of the reservoir; the fusion of such multi-source data improves the prediction accuracy of geological parameters such as TOC content, porosity and free hydrocarbons.

[0105] S7. Through core measurement and logging measurement, use the Voigt rock physics model to calculate the formation pressure;

[0106] The core measurement is to obtain core samples of underground rock formations during the drilling process, analyze and measure them to obtain the detailed physical, chemical, and geological properties of the formation; the mud logging measurement refers to a technical means of evaluating and monitoring the physical properties, oil and gas bearing properties, and other geological characteristics of the formation and reservoir by collecting and analyzing cuttings, gas, drilling fluid, and other data from the wellbore during the drilling operation; the Voigt rock physics model is a classic elastic homogenization model used to estimate the equivalent elastic modulus of rocks. This model assumes that the rock is composed of multiple minerals or different types of components, and the strain of each component is the same, that is, each component undergoes the same strain under the action of external forces (i.e., assuming that each component is in a state of uniform strain); the Voigt model is mainly used to calculate the effective elastic modulus of composite materials or rocks under specific stress conditions, such as the bulk modulus and shear modulus;

[0107] The specific steps of step S7 include the following steps:

[0108] S71. Through core measurement and mud logging measurement, determine the bulk modulus components and shear modulus components, and use the Voigt rock physics model to calculate the maximum modulus value and minimum modulus value of the bulk modulus components and shear modulus components respectively;

[0109] The calculation formula for the maximum modulus value of the bulk modulus component is:

[0110]

[0111] In the formula: K max represents the maximum modulus value of the bulk modulus component, with the unit of Pa; f i represents the i-th bulk modulus component; K i represents the i-th bulk modulus, with the unit of Pa; i = 1, 2…N, where N represents the classification quantity of different parameters;

[0112] The calculation formula for the maximum modulus value of the shear modulus component is:

[0113]

[0114] In the formula: μ max represents the maximum modulus value of the shear modulus component, with the unit of Pa; f i represents the i-th bulk modulus component; μ i represents the i-th shear modulus, with the unit of Pa; i = 1, 2…N, where N represents the classification quantity of different parameters;

[0115] The calculation formula for the minimum modulus value of the bulk modulus component is:

[0116]

[0117] where: K min represents the minimum modulus value of the bulk modulus component, with the unit of Pa; f i represents the i-th bulk modulus component; K i represents the i-th bulk modulus, with the unit of Pa; i = 1, 2…N, where N represents the number of classifications of different parameters;

[0118] The calculation formula for the minimum modulus value of the shear modulus component is:

[0119]

[0120] where: μ min represents the minimum modulus value of the shear modulus component; f i represents the i-th bulk modulus component; μ i represents the i-th shear modulus, with the unit of Pa; i = 1, 2…N, where N represents the number of classifications of different parameters;

[0121] In the present invention, by using the Voigt rock physics model and calculating the maximum modulus value and the minimum modulus value, the effective elastic moduli of the reservoir, including the bulk modulus and the shear modulus, can be obtained more precisely; this helps to more comprehensively evaluate the elastic properties of the reservoir and makes the pressure prediction under complex formation conditions more accurate;

[0122] S72. Calculate the maximum velocity value based on the maximum modulus value of the bulk modulus component and the maximum modulus value of the shear modulus component obtained in step S71; meanwhile, calculate the minimum velocity value based on the minimum modulus value of the bulk modulus component and the minimum modulus value of the shear modulus component obtained in step S71;

[0123] The calculation formula for the maximum velocity value is:

[0124]

[0125] where: Vp max represents the maximum velocity value, with the unit of m / s; K max represents the maximum modulus value of the bulk modulus component, with the unit of Pa; μ max represents the maximum modulus value of the shear modulus component, with the unit of Pa;

[0126] The calculation formula for the minimum velocity value is:

[0127]

[0128] where: Vp min represents the minimum velocity value, with the unit of m / s; K min represents the minimum modulus value of the bulk modulus component, with the unit of Pa; μ minRepresents the minimum modulus value of the shear modulus component, with the unit of Pa;

[0129] In the present invention, by calculating the formation pressure through the maximum velocity value, the minimum velocity value and the reservoir elastic parameters, the pressure distribution of the reservoir can be predicted more accurately; the accurate estimation of the formation pressure is crucial for well control and drilling safety, which can effectively reduce the risk of accidents such as blowouts and improve the development safety and efficiency;

[0130] S73. Calculate the formation pressure according to the maximum velocity value and the minimum velocity value obtained in step S72 and the reservoir elastic parameters obtained in step S2;

[0131] The calculation formula of the formation pressure is as follows:

[0132]

[0133] In the formula: P f Represents the formation pressure, with the unit of MPa; Vp max Represents the maximum velocity value, with the unit of m / s; Vp min Represents the minimum velocity value, with the unit of m / s; Vp represents the longitudinal wave velocity, with the unit of m / s; h represents the formation depth, with the unit of m; G represents the acceleration of gravity, with the unit of N / kg; H represents the upper limit of integration, with the unit of m; Rho represents the density, with the unit of g / cm 3 ;

[0134] In the present invention, through the high-precision prediction of the formation pressure, the well location deployment and drilling operations can be optimized, and the risks in the development process can be reduced.

[0135] In summary, by combining core measurement and logging measurement, using the Voigt rock physics model to calculate the bulk modulus and shear modulus, and then calculating the formation pressure based on these parameters, more accurate reservoir physical properties and pressure information can be provided. This not only improves the accuracy of formation pressure prediction, but also helps to optimize the engineering design, reduce the development risks, improve the recovery rate and economic benefits, and at the same time enhance the safety and efficiency of oil and gas development.

[0136] After calculating the shale oil sweet spot parameters TOC, POR, S1, BI and P f According to the value range distribution of each parameter of the shale oil reservoir in the study area and the results of well testing and production testing, establish the classification criteria for the shale oil reservoir of each parameter, and divide the shale oil reservoir into three categories: I, II, III.

[0137] For example, when TOC > 4%, it is classified as Class I; when 1.5% < TOC < 4%, it is classified as Class II; when TOC < 1.5%, it is classified as Class III; when porosity > 10%, it is classified as Class I; when 6% < porosity < 10%, it is classified as Class II; when porosity < 6%, it is classified as Class III; and so on. After the reservoir classification is determined, the weighted coefficients A of these three categories are set according to their contribution degrees to the shale oil reserve scale and the benefits of oil testing and production i , for Class I: A1 = 1.0, for Class II: A2 = 0.7; for Class III: A3 = 0.4. A i is the weight coefficient of Class I, II, and III, and has nothing to do with specific shale oil sweet spot parameters such as TOC, POR, S1, BI, P f and so on. The values of A for different shale oil reservoirs i will be different and are set according to the actual situation and regional experience.

[0138] In the present invention, by classifying according to the sweet spot parameters of the shale oil reservoir, the reservoir can be clearly divided into Class I, Class II, and Class III. This classification method enables the development team to quickly identify high-potential reservoirs (Class I) and give priority to development, reducing the tentativeness and uncertainty during the development process.

[0139] For different types of shale oil, such as the common matrix type, laminar type, and interlayer type, the importance of shale oil sweet spot parameters such as TOC, POR, S1, BI, P f and so on is also different. For example: The lithology of the matrix type section is mainly oil shale, and the laminar type section contains a small amount of thin siltstone or calcareous or dolomitic sandstone laminations in large sets of oil shale. Therefore, the main parameters for evaluating the sweet spots of these two types of shale oil are TOC, which contributes the most; the lithology of the interlayer type shale oil section is an interbed of unequal-thickness sandstone, calcareous or dolomitic bands and shale. The main parameters for evaluating the sweet spots of this type of shale oil are porosity, movable parameter S1, etc., which contribute a lot. Therefore, the weighted coefficients C of these parameters are set according to the contribution degrees of the parameters of different shale oil types and regional experience j (j = 1, 2, 3…), and the sum of the weighted coefficients of each parameter of the same type of shale oil (such as the matrix type) is 1.

[0140] In the present invention, by setting different weighted coefficients for each type of shale oil, customized evaluation can be carried out for different types of shale oil reservoirs, ensuring that the evaluation results are more consistent with the actual reservoir characteristics. This customized evaluation can improve the accuracy and reliability of reservoir sweet spot prediction.

[0141] S8, based on the engineering sweet spot parameters obtained in step S4, the geological sweet spot parameters obtained in step S6, and the formation pressure, comprehensively and quantitatively evaluate the geological and engineering double sweet spots of the shale oil in the study area;

[0142] The calculation formula for the comprehensive quantitative evaluation of the geological and engineering double sweet spots of shale oil in the research area is as follows:

[0143]

[0144] In the formula: SOQF represents the quality factor of the double sweet spots of oil shale, dimensionless; i = 1, 2, 3, respectively representing Class I, Class II, and Class III sweet spots; A i represents the weighting coefficient of the i-th type of sweet spot, A1 = 1.0 for Class I, A2 = 0.7 for Class II, and A3 = 0.4 for Class III; n is the total number of geological and engineering sweet spot parameters participating in the calculation, dimensionless; C j represents the single-parameter weight corresponding to the j-th parameter, and for the three types of oil shale, namely matrix type, laminar type, and interlayer type, the sum of the single-parameter weights of each parameter participating in the sweet spot calculation of each type of oil shale is equal to 1;

[0145] The parameters participating in the calculation of geological and engineering sweet spots usually include total organic carbon content TOC, effective porosity Por, free hydrocarbon content S1, rock brittleness index BI, formation pore pressure Pf, etc.

[0146] Example 2

[0147] A quantitative evaluation system for the geological and engineering double sweet spots of a shale oil reservoir, comprising:

[0148] A processor;

[0149] A memory, on which computer-readable instructions are stored. When the computer-readable instructions are executed by the processor, the quantitative evaluation method for the geological and engineering double sweet spots of the shale oil reservoir described in Example 1 is implemented.

[0150] The applicant declares that the above description is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention fall within the protection scope and the disclosure scope of the present invention.

Claims

1. A quantitative evaluation method for shale oil reservoir geology and engineering double sweet spots, characterized by: The following steps are involved: S1, obtaining pre-stack seismic data and well logging data of the reservoir section; S2, based on the Zeoppritz equation, using the prestack seismic inversion technology according to the prestack seismic data obtained in step S1, to obtain reservoir elastic parameters; S3, calculating the longitudinal wave impedance and the transverse wave impedance according to the reservoir elastic parameters obtained in step S2; S4, calculating a brittleness index according to the reservoir elastic parameters obtained in step S2 and the longitudinal wave impedance and the transverse wave impedance obtained in step S3, and taking the brittleness index as an engineering sweet spot parameter; S5, calculating the reservoir bulk modulus and the reservoir shear modulus according to the reservoir elastic parameters obtained in step S2; S6, combining the well logging data obtained in step S1, the reservoir elastic parameters obtained in step S2, and the reservoir bulk modulus and reservoir shear modulus obtained in step S5, using a Bayesian inversion method to obtain TOC content, porosity, and free hydrocarbons, and using TOC content, porosity, and free hydrocarbons as geological sweet spot parameters; S7, calculates formation pressure using the Voigt rock physics model through core measurements and logging measurements; S8, based on the engineering sweet spot parameters obtained in step S4, the geological sweet spot parameters obtained in step S6, and the formation pressure obtained in step S7, a comprehensive quantitative evaluation of the shale oil geology and engineering sweet spots in the study area is performed.

2. The method for quantitatively evaluating shale oil reservoir geology and engineering double sweet spots according to claim 1, characterized in that: The reservoir elastic parameters include longitudinal wave velocity, shear wave velocity and density.

3. The method for quantitatively evaluating shale oil reservoir geology and engineering double sweet spots according to claim 1, characterized in that: The calculation formula of the longitudinal wave impedance is specifically: Ip=Vp*Rho Where: Ip represents the longitudinal wave impedance, unit is g / cm 3 *m / s; Vp is the longitudinal wave velocity, the unit is m / s; Rho is the density, the unit is g / cm 3 ; The calculation formula of the shear wave impedance is: Is=Vs*Rho Where: Is represents the shear wave impedance, unit is g / cm 3 *m / s; Vs is the shear wave velocity, in m / s; Rho is the density, in g / cm 3 .

4. The method for quantitatively evaluating shale oil reservoir geology and engineering double sweet spots according to claim 1, characterized in that: The calculation formula of the brittleness index is: Where: BI represents the brittleness index, in %; Ip represents the longitudinal wave impedance, in g / cm 3 *m / s; Is represents shear wave impedance, unit is g / cm 3 *m / s; Rho represents density, the unit is m / s.

5. The method for quantitatively evaluating shale oil reservoir geology and engineering double sweet spots according to claim 1, characterized in that: The calculation formula of the reservoir bulk modulus is: K=Rho(Vp 2 -4Vs 2 / 3) Where: K represents the reservoir bulk modulus, in Pa; Rho represents the density, in g / cm 3 ; Vp represents the longitudinal wave velocity, the unit is m / s; Vs represents the shear wave velocity, the unit is m / s; The calculation formula of the reservoir shear modulus is: μ=RhoVs 2 Where: μ represents the reservoir shear modulus, in Pa; Rho represents the density, in g / cm 3 ; Vs represents the shear wave velocity, the unit is m / s.

6. The method for quantitatively evaluating shale oil reservoir geology and engineering double sweet spots according to claim 1, characterized in that: The step S7 specifically includes the following steps: S71. Determine the bulk modulus component and the shear modulus component through core measurement and logging measurement, and calculate the maximum modulus value and the minimum modulus value of the bulk modulus component and the shear modulus component respectively using the Voigt rock physics model; S72, calculating the maximum speed value according to the maximum modulus value of the bulk modulus component and the maximum modulus value of the shear modulus component obtained in step S71; at the same time, calculating the minimum speed value according to the minimum modulus value of the bulk modulus component and the minimum modulus value of the shear modulus component obtained in step S71; S73. Calculate the formation pressure according to the maximum velocity value and the minimum velocity value obtained in step S72 and the reservoir elasticity parameters obtained in step S2.

7. The method for quantitatively evaluating shale oil reservoir geology and engineering double sweet spots according to claim 6, characterized in that: The maximum modulus value of the bulk modulus component is calculated as follows: Where: K max Indicates the maximum modulus value of the bulk modulus component, in Pa; f i represents the i-th bulk modulus component; K i represents the i-th bulk modulus, in Pa; i = 1, 2…N, N represents the number of classifications of different parameters; The maximum modulus value of the shear modulus component is calculated as follows: Where: μ max Indicates the maximum modulus value of the shear modulus component, in Pa; f i represents the i-th bulk modulus component; μ i Represents the i-th shear modulus, in Pa; i = 1, 2…N, N represents the number of classifications of different parameters; The minimum modulus value of the bulk modulus component is calculated as follows: Where: K min Indicates the minimum modulus value of the bulk modulus component, in Pa; f i represents the i-th bulk modulus component; K i represents the i-th bulk modulus, in Pa; i = 1, 2…N, N represents the number of classifications of different parameters; The minimum modulus value calculation formula of the shear modulus component is: Where: μ min Indicates the minimum modulus value of the shear modulus component, in Pa; f i represents the i-th bulk modulus component; μ i Represents the i-th shear modulus, in Pa; i=1,2…N, N represents the number of categories of different parameters.

8. The method for quantitatively evaluating shale oil reservoir geology and engineering double sweet spots according to claim 6, characterized in that: The calculation formula of the maximum speed value is: Where: Vp max Indicates the maximum speed value, in Pa; K max Indicates the maximum modulus value of the bulk modulus component, in Pa; μ max Indicates the maximum modulus value of the shear modulus component, in Pa; The calculation formula of the minimum speed value is: Where: Vp min Indicates the minimum speed value in m / s; K min Indicates the minimum modulus value of the bulk modulus component, in Pa; μ min Indicates the minimum modulus value of the shear modulus component, in Pa; The calculation formula of the formation pressure is: Where: P f Indicates formation pressure, in MPa; Vp max Indicates the maximum speed value in m / s; Vp min Indicates the minimum speed value in m / s; Vp represents the longitudinal wave velocity, in m / s; h represents the depth of the formation, in m; G represents the acceleration due to gravity, in N / kg; H represents the upper limit of the integral, in m; Rho represents the density, in g / cm 3 .

9. The method for quantitatively evaluating shale oil reservoir geology and engineering double sweet spots according to claim 1, characterized in that: The calculation formula for the classification, comprehensive and quantitative evaluation of the shale oil geological and engineering double sweet spots in the study area is: Where: SOQF represents the double sweet spot quality factor of oil shale, the unit is; i = 1, 2, 3, representing class I, II, and III sweet spots respectively; A i represents the weighting coefficient of the i-th sweet spot, A1=1.0 for class I, A2=0.7 for class II, and A3=0.4 for class III; n is the total number of parameters involved in the calculation of geological and engineering sweet spots, dimensionless; C j It represents the single parameter weight corresponding to the jth parameter, and for the three types of oil shales, namely matrix type, laminar type and interlayer type, the sum of the single parameter weights of each parameter involved in the calculation of the sweet spot of each type of oil shale is equal to 1.

10. A shale oil reservoir geological and engineering double sweet spot quantitative evaluation system, comprising a processor and a memory, wherein the memory stores computer-readable instructions, characterized in that: When the computer-readable instructions are executed by the processor, the shale oil reservoir geological and engineering double sweet spot quantitative evaluation method described in one of claims 1 to 9 is implemented.

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