Seismic inversion method for mechanical parameter of fracture-vug reservoir based on well logging ground stress constraint

Abstract

The present application relates to the field of oil and gas field exploration and development, especially to a method for seismic inversion of mechanical parameters of fracture-cave reservoir based on well logging stress constraint. Based on array sonic logging, the present application calculates the present-day stress size; based on pre-stack seismic data, the present application inverts different types of seismic attributes; through optimization of seismic attributes and threshold value, the present application realizes the sculpture of fracture-cave geometry; based on the sensitivity of fracture-cave seismic attributes, the present application establishes seismic identification standards of different types of fracture-cave; through rock mechanics parameter inversion cycle verification, the present application establishes rock mechanics parameter assignment models of different types of fracture-cave; considering stress constraint, the present application optimizes rock mechanics parameter assignment models of different types of fracture-cave, and finally realizes the three-dimensional rock mechanics parameter inversion of fracture-cave reservoir. The present application proposes a method for seismic inversion of mechanical parameters of fracture-cave reservoir based on well logging stress constraint, which has reference value for fracture-cave reservoir geomechanical modeling, stress field numerical simulation and "engineering sweet spot" evaluation and other aspects.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field exploration and development, and in particular to a seismic inversion method for mechanical parameters of fractured-vuggy reservoirs based on well logging stress constraints. Background Technology

[0002] Rock mechanics parameters, including Young's modulus and Poisson's ratio, are crucial foundational data for reservoir geomechanical modeling and numerical simulation of in-situ stress fields. Traditional well-seismic combined methods can invert rock mechanics parameters and the distribution of maximum and minimum horizontal principal stresses. However, for fractured-vuggy reservoirs, accurate inversion of rock mechanics parameters is difficult, resulting in significant discrepancies between simulated maximum and minimum horizontal principal stresses and well-logged calculated current in-situ stress values, hindering large-scale application in geomechanical modeling and analysis. The main reason is the high randomness of traditional well-seismic combined rock mechanics parameter inversion models, leading to mechanical inconsistencies and inaccurate stress values. Based on stochastic simulation, excessive randomness results in large variations in rock mechanics parameters at the matrix, indicating excessive heterogeneity. Furthermore, the lack of calibration standards for rock mechanics parameters at fractured-vuggy locations makes it impossible to classify and characterize complex geological conditions. Moreover, under stochastic simulation, constraints are only affected by a single seismic attribute, which is insufficient to adequately represent the development characteristics of fractured-vuggy bodies. Ultimately, the simulated current in-situ stress model does not match the current in-situ stress values ​​calculated from a single well, exhibiting significant deviations. Therefore, a scientific scheme for assigning rock mechanical parameters to fractured-vuggy reservoirs is needed, directly constraining them with the current in-situ stress values ​​calculated from a single well. This invention patent employs reservoir geomechanical methods and proposes a seismic inversion method for mechanical parameters of fractured-vuggy reservoirs based on well logging in-situ stress constraints. Summary of the Invention

[0003] This invention aims to solve the above problems and provides a seismic inversion method for mechanical parameters of fractured-vuggy reservoirs based on well logging stress constraints. This method can determine the three-dimensional rock mechanical parameter distribution of fractured-vuggy reservoirs.

[0004] The technical solution of this invention is: a seismic inversion method for mechanical parameters of fractured-vuggy reservoirs based on well logging stress constraints, the specific steps of which are as follows:

[0005] The first step is to calculate the current geostress level based on array acoustic logging;

[0006] Using array acoustic logging data and combining it with rock density, the Young's modulus and Poisson's ratio of the rock are calculated. Based on the Young's modulus and Poisson's ratio of the rock, an elasticity model is used to calculate the current horizontal maximum principal stress, horizontal minimum principal stress, and vertical principal stress, and a current geostress profile of a single well is established.

[0007] The elasticity model is as follows:

[0008] The calculation of horizontal stress adopts the combined spring model theory, which assumes that the strata are homogeneous and isotropic linear elastic materials, and that no faulting occurs between strata during geological tectonic movements, so the stress change in the horizontal direction remains constant. Based on Hooke's law, the following calculation formula is derived:

[0009]

[0010] In formulas (1)-(2), σ Hmax The maximum horizontal principal stress is σ, MPa; hmin The minimum principal stress is σ, MPa; v P is the vertical principal stress, MPa; p ρ is pore pressure, MPa; v is Poisson's ratio, dimensionless; E is elastic modulus, GPa; α is Biot coefficient, dimensionless; ξ H and ξ h , respectively, are the strains in the directions of the maximum and minimum horizontal principal stresses, dimensionless;

[0011] The Biot coefficient in formulas (1)-(2) is the porous elastic constant, and the Biot coefficient is estimated using the following formula:

[0012]

[0013] In formula (3), C ma - The compression ratio of the skeleton; C b - Compressibility of the skeleton and pore space;

[0014] In formulas (1)-(2), ξ H and ξ h The coefficient is difficult to determine directly; therefore, σ at a specific location is determined using hydraulic fracturing construction data. hmin The measured data serves as a constraint and calibration basis, indirectly determining ξ. H and ξ h The value of σ; during hydraulic fracturing, the pump shutdown pressure is the fracture closure pressure, which is equal to the minimum horizontal principal stress σ. hmin The calculation formula is:

[0015] σh min =p c (4)

[0016] σ Hmax =3σ hmin -p r -p p (5)

[0017] In formulas (4)-(5), p c Pump shutdown pressure, MPa; p r Pressure required to reopen the crack, MPa.

[0018] The second step involves inverting different types of seismic attributes based on pre-stack seismic data.

[0019] Using pre-stack seismic data, pre-stack data preprocessing was carried out to interpret key layers and faults, and a rock physics template was constructed to establish the mapping relationship between elastic parameters and reservoir characteristics. P-wave velocity, S-wave velocity and density were obtained through AVO inversion, anisotropic parameters were extracted through elastic impedance inversion, and a high-precision velocity field was reconstructed through full waveform inversion. A well-seismic combined method was used to invert different types of seismic attributes.

[0020] The inversion of different types of seismic attributes includes maximum likelihood attributes, ant-body attributes, root mean square amplitude attributes, and porosity attributes.

[0021] The third step involves carving the geometric shape of the well-seismic combination cavity;

[0022] Based on the optimal seismic attributes and threshold values, the inverted seismic attribute model is gridded, and the fracture-cavity model of the target layer in the study area is sculpted by filtering through the threshold values.

[0023] The threshold value refers to the seismic attribute value that can effectively identify cracks and complex cavities in the body.

[0024] The aforementioned preferred seismic attributes and threshold values ​​refer to using seismic data from the study area to determine the effectiveness of different seismic attributes in identifying fractures and complex fracture-cavity structures, and to select the most sensitive seismic attributes for fracture-cavity structures; based on well logging values, the range of inverted seismic attributes is preliminarily determined.

[0025] The fourth step is to establish seismic identification standards for different types of fissures and cavities;

[0026] Different types of fissures and cavities exhibit varying degrees of sensitivity to seismic properties. Based on these varying degrees of sensitivity, seismic identification criteria for different types of fissures and cavities are established.

[0027] The earthquake identification criteria for different types of fissures and cavities are as follows: based on the earthquake-sensitive properties of different types of fissures and cavities, the most important parameters and their values ​​for classifying fissure and cavities are selected.

[0028] The fifth step is to establish rock mechanical parameter assignment models for different types of fractured caverns;

[0029] Based on the seismic identification criteria for fracture-cavity bodies in the study area, the rock mechanical parameters were inverted and verified cyclically. Finally, a rock mechanical parameter assignment model for fracture-cavity bodies that conforms to the laws of geomechanics was obtained.

[0030] The aforementioned geomechanical laws refer to the fact that the rock mechanical parameters near the crevices will change, with the Young's modulus of the rock decreasing and the Poisson's ratio increasing.

[0031] Step 6: Optimization of rock mechanical parameter assignment models for different types of fractured caverns based on well logging stress constraints;

[0032] Through continuous simulation testing and iteration, combined with the current geostress magnitude of the target layer in a single well, the assignment scheme is revised, and the assignment scheme for different types of fractured caverns is optimized.

[0033] The aforementioned cyclic verification of rock mechanics parameter inversion refers to continuously simulating and testing to screen out the seismic attributes that affect the strength of identification of different types of fractures and cavities. Combined with the current geostress magnitude of the target layer in a single well, the calculation function is adjusted, and the assignment schemes for different types of fractures and cavities are optimized to finally obtain a model calculation formula suitable for the target layer in the study area.

[0034] Step 7: Inversion of three-dimensional rock mechanical parameters of fractured-vuggy reservoirs;

[0035] Based on the rock mechanical parameter assignment model of complex fractured-vuggy reservoirs, a Young's modulus and Poisson's ratio model of the target strata in the study area was established to reveal the three-dimensional rock mechanical parameter distribution of fractured-vuggy reservoirs.

[0036] The beneficial effects of this invention are as follows: Based on array acoustic logging data, the current magnitude of in-situ stress is calculated; different types of seismic attributes are inverted using a well-seismic combination method; the geometric morphology of fractured-vuggy reservoirs is sculpted by optimizing seismic attributes and threshold values; seismic identification standards for different types of fractured-vuggy reservoirs are established based on the seismic attribute sensitivity of the fractured-vuggy reservoirs; rock mechanics parameter inversion models for different types of fractured-vuggy reservoirs are established through iterative verification; and the rock mechanics parameter inversion models for different types of fractured-vuggy reservoirs are optimized considering stress constraints by combining the current magnitude of in-situ stress in the target layer of a single well. Finally, the three-dimensional rock mechanics parameter inversion of fractured-vuggy reservoirs is achieved. This invention patent proposes a seismic inversion method for the mechanical parameters of fractured-vuggy reservoirs based on well logging stress constraints, which has reference value for multiple aspects such as geomechanical modeling of fractured-vuggy reservoirs, numerical simulation of in-situ stress fields, and evaluation of "engineering sweet spots." Attached Figure Description

[0037] Figure 1 This is a flowchart of a seismic inversion method for mechanical parameters of fractured-vuggy reservoirs based on well logging stress constraints.

[0038] Figure 2 A columnar section for the comprehensive interpretation of geostress in a single well.

[0039] Figure 3 The seismic attributes retrieved are: (A) maximum likelihood attribute; (B) porosity attribute.

[0040] Figure 4 To conduct detailed sculpting and geological geometric modeling of the three-dimensional fissures in the study area.

[0041] Figure 5 This document presents the seismic identification criteria and classification map for different types of fissures and cavities in the study area.

[0042] Figure 6 This is a diagram illustrating the cyclic verification process for inverting rock mechanics parameters.

[0043] Figure 7 This is a comparison chart of rock mechanics parameters before and after optimization.

[0044] Figure 8 The rock mechanics parameter models for the study area are: (A) Young's modulus model; (B) Poisson's ratio model. Detailed Implementation

[0045] The specific embodiments of the present invention are described below with reference to the accompanying drawings:

[0046] This invention patent uses the carbonate reservoir of the Fuman Oilfield in the Tarim Basin of western China as an example to illustrate the specific implementation process of the invention. The main body of the Fuman Oilfield is located in the Aman transition zone of the northern depression. The Manshen block is situated on the slope of the Tarim Basin's northern uplift, having undergone multiple tectonic movements. Currently, the overall structure is gentle, exhibiting a southwest-dipping slope. The study area has undergone multiple phases of tectonic activity, superimposed with multiple phases and types of karstification, resulting in typical carbonate fracture-vuggy oil and gas reservoirs controlled by strike-slip faults. This is currently the main area for increasing crude oil reserves and production in the Tarim Oilfield. Conventional well-seismic combined inversion rock mechanics parameter models have high randomness, exhibiting problems such as mechanical inconsistencies and inaccurate stress, especially near fracture-vuggy bodies, making them difficult to apply on a large scale to geomechanical modeling of fracture-vuggy reservoirs. Therefore, a scientific rock mechanics parameter assignment scheme is needed to support research such as geomechanical modeling of ultra-deep fracture-vuggy reservoirs and numerical simulation of geostress fields.

[0047] The first step is to calculate the current geostress level based on array acoustic logging;

[0048] Using array acoustic logging data and combining it with rock density, the Young's modulus and Poisson's ratio of the rock are calculated. Based on the Young's modulus and Poisson's ratio, an elasticity model is used to calculate the current horizontal maximum principal stress, horizontal minimum principal stress, and vertical principal stress, establishing a current geostress profile for a single well. Figure 2 ).

[0049] The second step involves inverting different types of seismic attributes based on pre-stack seismic data.

[0050] Using pre-stack seismic data, pre-stack data preprocessing was performed to interpret key stratigraphic levels and faults, and a rock physics template was constructed to establish a mapping relationship between elastic parameters and reservoir characteristics. P-wave velocity, S-wave velocity, and density were obtained through AVO inversion, anisotropic parameters were extracted through elastic impedance inversion, and a high-precision velocity field was reconstructed through full waveform inversion. A combined well-seismic approach was used to invert different types of seismic attributes. Figure 3 ).

[0051] The third step involves carving the geometric shape of the well-seismic combination cavity;

[0052] Based on the optimal selection of seismic attributes and threshold values, the inverted seismic attribute model is gridded, and the fracture-cavity model of the target layer in the study area is sculpted through threshold value screening. Figure 4 The threshold value refers to the seismic attribute value that can effectively identify cracks and complex fracture cavities; the preferred seismic attribute and threshold value refer to using seismic data of the study area to judge the identification effect of different seismic attributes on cracks and complex fracture cavities, and to select the seismic attribute sensitive to fracture cavities; based on well logging values, the range of inverted seismic attributes is preliminarily determined.

[0053] The fourth step is to establish seismic identification standards for different types of fissures and cavities;

[0054] Different types of fissures exhibit varying degrees of sensitivity to seismic properties. Based on these varying degrees of sensitivity, seismic identification criteria for different types of fissures are established. Figure 5 The earthquake identification criteria for different types of fissures and cavities are as follows: based on the earthquake-sensitive properties of different types of fissures and cavities, the most important parameters and their values ​​for classifying fissure and cavities are selected.

[0055] The fifth step is to establish rock mechanical parameter assignment models for different types of fractured caverns;

[0056] Based on the seismic identification criteria for fractured-cavity bodies in the study area, cyclical verification of rock mechanical parameter inversion was conducted, and finally, a rock mechanical parameter assignment model for fractured-cavity bodies that conforms to the laws of geomechanics was obtained. Figure 6 The aforementioned geomechanical laws refer to the fact that the rock mechanical parameters near the crevices will change, with the Young's modulus of the rock decreasing and the Poisson's ratio increasing.

[0057] Step 6: Optimization of rock mechanical parameter assignment models for different types of fractured caverns based on well logging stress constraints;

[0058] Through continuous simulation testing and iteration, combined with the current geostress magnitude of the target layer in a single well, the assignment scheme was revised, and the assignment scheme for different types of fractured cavities was optimized. Figure 7The cyclic verification of rock mechanics parameter inversion refers to continuously simulating and testing to screen out the seismic attributes that affect the strength of identification of different types of fractures and cavities. Combined with the current geostress magnitude of the target layer in a single well, the calculation function is adjusted, and the assignment schemes for different types of fractures and cavities are optimized to finally obtain the model calculation formula applicable to the target layer in the study area.

[0059] Step 7: Inversion of three-dimensional rock mechanical parameters of fractured-vuggy reservoirs;

[0060] Based on the rock mechanical parameter assignment model of complex fractured cavities, a model for Young's modulus and Poisson's ratio of the target strata rocks in the study area was established. Figure 8 This study reveals the distribution of three-dimensional rock mechanical parameters in fractured-vuggy reservoirs.

[0061] In one exemplary embodiment, a computer-readable storage medium is included, on which a computer program is stored, which, when executed by a processor, implements the steps in the above-described reservoir geomechanical experimental method under multi-stage tectonic stress.

[0062] The present invention has been described above by way of example, but the present invention is not limited to the specific embodiments described above. Any modifications or variations made based on the present invention are within the scope of protection claimed by the present invention.

Claims

1. A method for seismic inversion of mechanical parameters of fracture-cave reservoirs based on logging stress constraints, the steps of which are as follows: Step 1: Calculate the present-day stress magnitude based on array sonic logging; Using array sonic logging data, combined with rock density, calculate the Young's modulus and Poisson's ratio of the rock; according to the size of the Young's modulus and Poisson's ratio of the rock, calculate the size of the present-day horizontal maximum principal stress, horizontal minimum principal stress and vertical principal stress using the elastic mechanics model, and establish the present-day stress profile of a single well; Step 2: Invert different types of seismic attributes based on pre-stack seismic data; Using pre-stack seismic data, carry out pre-stack data preprocessing, complete the interpretation of key horizons and faults, build a rock physics template to establish the mapping relationship between elastic parameters and reservoir characteristics; obtain P-wave velocity, S-wave velocity and density through AVO inversion, extract anisotropic parameters through elastic impedance inversion, reconstruct high-precision velocity field through full waveform inversion, and invert different types of seismic attributes using the well-to-seismic combination method; Step 3: Carve the geometry of fracture-cave bodies based on well-to-seismic combination; On the basis of optimizing seismic attributes and threshold values, grid the inverted seismic attribute model, and carve the fracture-cave body model of the target layer in the study area through threshold screening; Step 4: Establish seismic identification standards for different types of fracture-cave bodies; Different types of fracture-cave bodies have different sensitivities to seismic attributes, and based on the sensitivity of different types of fracture-cave bodies to seismic attributes, establish seismic identification standards for different types of fracture-cave bodies; Step 5: Establish rock mechanics parameter assignment models for different types of fracture-cave bodies; According to the seismic identification standards of fracture-cave bodies in the study area, carry out cyclic verification of rock mechanics parameter inversion, and finally obtain the rock mechanics parameter assignment model of fracture-cave bodies that conforms to the geomechanics law; Step 6: Optimize the rock mechanics parameter assignment model of different types of fracture-cave bodies based on logging stress constraints; Through continuous simulation testing and iteration, combined with the present-day stress magnitude of the target layer in a single well, the assignment scheme is corrected, and the assignment scheme for different types of fracture-cave bodies is optimized; Step 7: Three-dimensional rock mechanics parameter inversion of fracture-cave reservoirs.

2. The method for seismic inversion of mechanical parameters of fracture-cave reservoirs based on logging stress constraints according to claim 1, characterized in that: The elastic mechanics model in the first step is as follows: For the calculation of horizontal stress, a combined spring model theory is used, which assumes that the formation is a homogeneous and isotropic linear elastic material, and that no faulting occurs between the formations during geological tectonic movement, and the stress change in the horizontal direction remains constant; based on Hooke's law, the following calculation formula is obtained: In Equations (1)-(2), σ Hmax is the horizontal maximum principal stress, MPa; σ hmin is the horizontal minimum principal stress, MPa; σ v is the vertical principal stress, MPa; P p is the pore pressure, MPa; v is the Poisson's ratio, dimensionless; E is the elastic modulus, GPa; and a is the Biot's coefficient, dimensionless. ξ H and ξ h are the strain quantities in the directions of the horizontal maximum and minimum principal stresses, respectively, dimensionless; The Biot coefficient in formula (1)-(2) is a porous elastic constant, and the Biot coefficient is estimated using the following formula: In equation (3), C ma - compressibility of the skeleton; C b - compressibility of the skeleton and the pore space; ξ in formula (1)-(2) H and ξ h The coefficient is difficult to determine directly, and the σ hmin of a specific position is determined indirectly by using the measured point data as the constraint and scale basis to determine the value of ξ H and ξ h During the hydraulic fracturing process, the pump-off pressure is the fracture closure pressure value, which is equal to the horizontal minimum principal stress σ hmin , and the calculation formula is: σ hmin = p c (4) σ Hmax = 3σ hmin -p r -p p (5) In formulas (4)-(5), p c is the pump shutdown pressure, MPa; p r is the fracture reopening pressure, MPa.

3. The method according to claim 1, wherein the method is characterized by: The inverted different types of seismic attributes in the second step include maximum likelihood attribute, ant body attribute, and root mean square amplitude attribute, and porosity attribute.

4. The method according to claim 1, wherein the method is characterized by: The threshold value in the third step refers to the seismic attribute value that can effectively identify fractures and complex fracture-cave pore holes.

5. The method according to claim 1, wherein the method is characterized by: The preferred seismic attribute in the third step is a threshold value indicating the effect of different seismic attributes on the identification of fractures and complex fracture-cavity pores by using seismic data of the study area, and the fracture-cavity sensitive seismic attribute is preferred; the interval of the inverted seismic attribute is preliminarily determined according to the logging values.

6. The method according to claim 1, wherein the method is characterized by: The different types of fracture-cavity seismic identification criteria in the fourth step are to screen out the most important parameters and their values for dividing the fracture-cavity types according to the fracture-cavity sensitive seismic attribute of different types.

7. The method according to claim 1, wherein the method is characterized by: The geomechanics law in the fifth step refers to the change of the rock mechanics parameters near the fracture-cavity, the decrease of the rock Young's modulus and the increase of the Poisson's ratio.

8. The method according to claim 1, wherein the method is characterized by: The cycle verification of the rock mechanics parameter inversion in the fifth and sixth steps refers to the screening of the seismic attributes affecting the identification of different types of fracture-cavities by continuous simulation and testing, the adjustment of the calculation function combined with the present-day in-situ stress size of the target layer of the single well, the optimization of the assignment scheme of different types of fracture-cavities, and the final derivation of the model calculation formula suitable for the target layer of the study area.

9. The method according to claim 1, wherein the method is characterized by: The specific steps of the three-dimensional rock mechanics parameter inversion of the fracture-cavity reservoir in the seventh step are to establish the rock Young's modulus and Poisson's ratio model of the target layer of the study area based on the complex fracture-cavity rock mechanics parameter assignment model, and to reveal the three-dimensional rock mechanics parameter distribution of the fracture-cavity reservoir.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to realize the steps in the logging in-situ stress constrained fracture-cavity reservoir mechanics parameter seismic inversion method according to any one of claims 1-9.

Images