Quantitative prediction method for reservoir geomechanical parameters of complex structure superposition area

Abstract

The invention provides a quantitative prediction method for geomechanical parameters of a reservoir in a complex structure superposition area, and is suitable for the fields of petroleum and natural gas geology and rock mechanics. The method comprises the following steps: firstly, collecting drilling rock cores, conventional logging, imaging logging and three-dimensional seismic data in a complex structure superposition area, calculating rock mechanical parameters by utilizing experiments and logging, and constructing a single well rock mechanical parameter profile S0; then, fracture parameters are picked up, the relation f1 and f2 between fracture density of upper and lower walls of a fault and the distance from the fault and a fracture weakening rock mechanical property model F are established, S0 is converted into a rock mechanical parameter profile S1 under the actual stratum fracture-containing condition, and the relation between the rock mechanical parameter profile S1 and seismic attributes is established; and finally, constructing a natural fracture field and a rock mechanical field of the complex structure superposition area, and realizing quantitative prediction of reservoir geomechanical parameters. The method is comprehensive and rigorous in considered factors, high in operability and high in prediction result credibility.

Description

Technical Field

[0001] The invention relates to the fields of petroleum and natural gas geology and rock mechanics, and in particular to a quantitative prediction method for reservoir geomechanics parameters in a complex structural superposition area. Background Art

[0002] The Kuqa Depression is affected by intense tectonic activity and the presence of the Kumugeliemu Group gypsum-salt rock layer has developed a series of thrust-nappe structural systems with the structural characteristics of "north-south zoning, east-west segmentation, and vertical superposition". In complex structural superposition areas such as the Kuqa Depression, quantitative prediction of the development and distribution of reservoir geomechanical parameters is crucial for oil and gas development.

[0003] Previous studies have focused on the analysis of north-south zoning and east-west segmentation characteristics, and there are few targeted studies on vertical superposition characteristics. The Chinese invention patent application with publication number CN112764097A proposes a spatial superposition three-dimensional structural modeling method, device and computer storage medium, obtains seismic interpretation data in the depth domain, divides adjacent layers with exactly the same fault development into a group, establishes a section model and a layer model in each structural model, and spatially superimposes the section models in adjacent structural models to obtain a three-dimensional section model of the entire layer. The layer models in adjacent structural models are spatially superimposed to obtain a three-dimensional layer model of the entire layer. The Chinese invention patent application with publication number CN116411942A proposes a high-angle well trajectory design method for complex superimposed oil reservoirs. This method refines the units of the target layer system based on existing exploration data, establishes the corresponding relationship between high-precision sequence cycles and reservoir stratigraphic units, and determines the optimal drilling orientation for multi-layer stereoscopic exploration. The Chinese invention patent with publication number CN103913774A proposes a reservoir geomechanical parameter inversion method based on microseismic events. The method includes the steps of processing the microseismic event cloud with a Gaussian distribution function continuously, selecting a prediction model, calculating the Kalman filter factor, updating the reservoir geomechanical parameters, obtaining the actual reservoir geomechanical parameters, and establishing an accurate underground reservoir geomechanical model. However, it fails to take into account the complex structural superposition characteristics and is not applicable to areas with complex superimposed structures such as the Kuche Depression. Summary of the invention

[0004] In order to solve the problems existing in the prior art, the present invention provides a method for quantitatively predicting reservoir geomechanical parameters in complex structural superposition areas with comprehensive consideration of factors and high credibility of results. It comprehensively considers the distance from the fault and the rock mechanical property model of fracture weakening, combines experimental testing, well logging interpretation and three-dimensional seismic data, constructs the natural fracture field and rock mechanical field in the complex structural superposition area, and realizes quantitative prediction.

[0005] In order to achieve the above objectives, the present invention provides a method for quantitatively predicting reservoir geomechanical parameters in a complex structural superposition area. First, drilling cores, conventional logging, imaging logging and three-dimensional seismic data in the complex structural superposition area are collected, rock mechanical parameters are calculated by experiments and logging, and a single well rock mechanical parameter profile S0 is constructed; then, fracture parameters are picked up, and the relationship between the fracture density of the upper and lower plates of the fault and the distance from the fault f1, f2 and the fracture weakening rock mechanical property model F are established, and then S0 is converted into a rock mechanical parameter profile S1 under the actual formation fracture condition, and the relationship between it and the seismic attributes is established, and finally the natural fracture field and rock mechanical field in the complex structural superposition area are constructed to achieve quantitative prediction of reservoir geomechanical parameters.

[0006] The specific steps are as follows:

[0007] Step 1: Collect cross-fault drilling cores in complex structural overlapping areas and collect conventional logging, imaging logging and 3D seismic data;

[0008] Step 2, using the drilling core and conventional logging data obtained in step 1 to carry out triaxial rock mechanics experiments and logging rock mechanics parameter calculations, respectively, to obtain static and dynamic rock mechanics parameters, and then establish a dynamic and static rock mechanics parameter conversion model to construct a single well rock mechanics parameter profile S0;

[0009] Step 3, using the imaging logging data obtained in step 1 to extract natural fracture parameters, calculate fracture density, and respectively establish the relationship between fracture density and distance from the fault in the upper and lower walls of the fault, f1 and f2, and then construct a fracture field in the complex structural superposition area based on fracture density and distance from the fault;

[0010] Step 4, constructing a fracture-weakened rock mechanical property model F based on theoretical analysis;

[0011] Step 5, using the relationships f1 and f2 obtained in step 3 and the model F obtained in step 4, the rock mechanics profile S0 constructed in step 1 is converted into a rock mechanics parameter profile S1 under the actual formation fracture condition;

[0012] Step 6, using the three-dimensional seismic data obtained in step 1 to extract the seismic attribute volume, establish the relationship between it and the rock mechanics profile S1 obtained in step 5, and construct the rock mechanics field of the complex structural superposition area.

[0013] Furthermore, the drilling core collected in step 1 needs to be processed into a size of 25mm diameter × height × 50mm. Conventional logging data at least includes gamma GR, acoustic wave time difference AC, density DEN curve and core filling altitude and core filling height. The three-dimensional seismic data needs to be depth domain data.

[0014] Furthermore, in step 2, the rock mechanical parameters are calculated by conventional logging data mainly through the following formula:

[0015]

[0016]

[0017] Where: μ is the Poisson's ratio of rock, E is the elastic modulus of rock, Δt s and Δt p are the transverse wave and longitudinal wave time differences of the stratum respectively, and ρ is the rock density.

[0018] Furthermore, the crack density in step 3 is expressed in the form of line density, that is, the number of cracks per unit length:

[0019]

[0020] Where: f d is the crack density, n is the number of cracks, and l is the length of the measurement section.

[0021] The relationship between the density of the cracks in the upper and lower walls of the fault and the distance from the fault f1 and f2 are:

[0022]

[0023] Where: f1 and f2 are the fracture densities of the upper and lower walls of the fault, respectively; g1 and g2 are the distances between f1 and f2 and the fault; and d is the distance between the measuring point and the fault.

[0024] Furthermore, the fracture-weakening rock mechanical property model F constructed in step 4 using two groups of fractures as an example is:

[0025]

[0026]

[0027] Where: E eq and μ eq are the equivalent rock elastic modulus, E and μ are the intact rock elastic modulus and Poisson's ratio, α and β are the acute angles between the first group of cracks and the horizontal plane, and between the second group and the first group of cracks, S1 and S2 are the spacings between the second group and the first group of cracks, respectively. K n1 and K n2 are the normal stiffness of the second and first group of cracks, respectively, K s1 and K s2 are the shear stiffnesses of the second and first groups of cracks, respectively.

[0028] Furthermore, in step 6, the seismic attributes at least include the coherence volume and the wave impedance, and the following relationship is established:

[0029]

[0030] Where: Eeq and μ eq are the equivalent rock elastic modulus, X is the coherent body attribute, and P is the wave impedance attribute.

[0031] The beneficial effects of the present invention are:

[0032] At present, there is no research method for reservoir geomechanical parameters in complex structural superposition areas. In order to quantitatively characterize the superposition characteristics of complex structures and predict reservoir geomechanical parameters, the patent of this invention comprehensively considers the distance from the fault and the rock mechanical property model of fracture weakening, realizes the quantitative prediction of underground natural fracture distribution and accurate characterization of rock mechanical properties, and combines experimental testing, well logging interpretation and three-dimensional seismic data to construct the natural fracture field and rock mechanical field in the complex structural superposition area, and realizes the quantitative prediction of reservoir geomechanical parameters. This method considers factors comprehensively and rigorously, has strong operability, and has a high degree of credibility in the prediction results, which solves the problem of low prediction accuracy of reservoir geomechanical parameters in complex structural superposition areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] 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 the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 A schematic diagram of the process flow of a method for quantitatively predicting reservoir geomechanical parameters in a complex structural superposition area provided by the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0036] like Figure 1As shown, a quantitative prediction method for reservoir geomechanical parameters in a complex structural superposition area of ​​the present invention first collects drilling cores, conventional logging, imaging logging and three-dimensional seismic data in the complex structural superposition area, calculates rock mechanical parameters by experiments and logging, and constructs a single well rock mechanical parameter profile S0; then picks up fracture parameters, establishes the relationship between the fracture density of the upper and lower plates of the fault and the distance from the fault f1, f2 and the fracture weakening rock mechanical property model F, and then converts S0 into a rock mechanical parameter profile S1 under the actual formation fracture condition, establishes the relationship between it and the seismic attributes, and finally constructs the natural fracture field and rock mechanical field in the complex structural superposition area to achieve quantitative prediction of reservoir geomechanical parameters.

[0037] The specific steps are as follows:

[0038] Step 1: Collect cross-fault drilling cores in complex structural overlapping areas and collect conventional logging, imaging logging and 3D seismic data;

[0039] The collected drilling cores need to be processed into the size of 25mm diameter × height × 50mm. Conventional logging data at least include gamma GR, acoustic time difference AC, density DEN curve and core filling altitude and core filling height. The three-dimensional seismic data must be depth domain data.

[0040] Step 2, using the drilling core and conventional logging data obtained in step 1 to carry out triaxial rock mechanics experiments and logging rock mechanics parameter calculations, respectively, to obtain static and dynamic rock mechanics parameters, and then establish a dynamic and static rock mechanics parameter conversion model to construct a single well rock mechanics parameter profile S0;

[0041] The rock mechanical parameters are calculated from conventional logging data mainly through the following formula:

[0042]

[0043]

[0044] Where: μ is the Poisson's ratio of rock, E is the elastic modulus of rock, Δt s and Δt p are the transverse wave and longitudinal wave time differences of the stratum respectively, and ρ is the rock density.

[0045] Step 3, using the imaging logging data obtained in step 1 to extract natural fracture parameters, calculate fracture density, and respectively establish the relationship between fracture density and distance from the fault in the upper and lower walls of the fault, f1 and f2, and then construct a fracture field in the complex structural superposition area based on fracture density and distance from the fault;

[0046] The crack density is expressed in the form of line density, that is, the number of cracks per unit length:

[0047]

[0048] Where: f d is the crack density, n is the number of cracks, and l is the length of the measurement section.

[0049] The relationship between the density of the cracks in the upper and lower walls of the fault and the distance from the fault f1 and f2 are:

[0050]

[0051] Where: f1 and f2 are the fracture densities of the upper and lower walls of the fault, respectively; g1 and g2 are the distances between f1 and f2 and the fault; and d is the distance between the measuring point and the fault.

[0052] Step 4, constructing a fracture-weakened rock mechanical property model F based on theoretical analysis;

[0053] The fracture-weakening rock mechanical property model F constructed by taking two groups of fractures as an example is expressed as follows:

[0054]

[0055]

[0056] Where: E eq and μ eq are the equivalent rock elastic modulus, E and μ are the intact rock elastic modulus and Poisson's ratio, α and β are the acute angles between the first group of cracks and the horizontal plane, and between the second group and the first group of cracks, S1 and S2 are the spacings between the second group and the first group of cracks, respectively. K n1 and K n2 are the normal stiffness of the second and first group of cracks, respectively, K s1 and K s2 are the shear stiffnesses of the second and first groups of cracks, respectively.

[0057] Step 5, using the relationships f1 and f2 obtained in step 3 and the model F obtained in step 4, the rock mechanics profile S0 constructed in step 1 is converted into a rock mechanics parameter profile S1 under the actual formation fracture condition;

[0058] Step 6, using the three-dimensional seismic data obtained in step 1 to extract the seismic attribute volume, establish the relationship between it and the rock mechanics profile S1 obtained in step 5, and construct the rock mechanics field of the complex structural superposition area.

[0059] Seismic attributes include at least coherence volume and wave impedance, and the following relationship is established:

[0060]

[0061] Where: E eq and μ eq are the equivalent rock elastic modulus, X is the coherent body attribute, and P is the wave impedance attribute.

[0062] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A quantitative prediction method for reservoir geomechanical parameters in complex structural superposition areas, characterized in that: The specific steps include: Step 1: Collect cross-fault drilling cores in complex structural overlapping areas and collect conventional logging, imaging logging and 3D seismic data; Step 2, using the drilling core and conventional logging data obtained in step 1 to carry out triaxial rock mechanics experiments and logging rock mechanics parameter calculations, respectively, to obtain static and dynamic rock mechanics parameters, and then establish a dynamic and static rock mechanics parameter conversion model to construct a single well rock mechanics parameter profile S0; Step 3, using the imaging logging data obtained in step 1 to extract natural fracture parameters, calculate fracture density, and respectively establish the relationship between fracture density and distance from the fault in the upper and lower walls of the fault, f1 and f2, and then construct a fracture field in the complex structural superposition area based on fracture density and distance from the fault; Step 4, constructing a fracture-weakened rock mechanical property model F based on theoretical analysis; Step 5, using the relationships f1 and f2 obtained in step 3 and the model F obtained in step 4, the rock mechanics profile S0 constructed in step 1 is converted into a rock mechanics parameter profile S1 under the actual formation fracture condition; Step 6, using the three-dimensional seismic data obtained in step 1 to extract the seismic attribute volume, establish the relationship between it and the rock mechanics profile S1 obtained in step 5, and construct the rock mechanics field of the complex structural superposition area.

2. The method according to claim 1, characterized in that The drilling core collected in step 1 needs to be processed into a size of 25mm diameter × height × 50mm. Conventional logging data include gamma GR, acoustic time difference AC, density DEN curve, and core filling altitude and core filling height. The three-dimensional seismic data needs to be depth domain data.

3. The method according to claim 1, characterized in that In step 2, the rock mechanical parameters are calculated using conventional logging data using the following formula: Where: μ is the Poisson's ratio of rock, E is the elastic modulus of rock, Δt s and Δt p are the transverse wave and longitudinal wave time differences of the stratum, ρ is the rock density, and γ is the coefficient.

4. The method according to claim 3, characterized in that In step 3, the crack density is expressed in the form of line density, that is, the number of cracks per unit length: Where: f d is the crack density, n is the number of cracks, and l is the length of the measurement section; The relationship between the density of the cracks in the upper and lower walls of the fault and the distance from the fault f1 and f2 are: Where: f1 and f2 are the fracture densities of the upper and lower walls of the fault, respectively; g1 and g2 are the distances between f1 and f2 and the fault; and d is the distance between the measuring point and the fault.

5. The method according to claim 4, characterized in that The fracture-weakening rock mechanical property model F constructed in step 4 using two groups of fractures as an example is expressed as follows: Where: E eq and μ eq are the equivalent rock elastic modulus, E and μ are the intact rock elastic modulus and Poisson's ratio, α and β are the acute angles between the first group of cracks and the horizontal plane, and between the second group and the first group of cracks, S1 and S2 are the spacings between the second group and the first group of cracks, respectively. K n1 and K n2 are the normal stiffness of the second and first group of cracks, respectively, K s1 and K s2 are the shear stiffnesses of the second and first groups of cracks, respectively.

6. The method according to claim 5, characterized in that In step 6, the seismic attributes include coherence volume and wave impedance, and the following relationship is established: Where: E eq and μ eq are the equivalent rock elastic modulus and equivalent rock Poisson’s ratio, respectively. X represents the coherent body attribute. P represents the wave impedance attribute. m1() and m2() represent the functional relationship.

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