Reservoir rock upscaled spectral induced polarization characterization method and system

Abstract

The application discloses a reservoir rock upscaling spectral induced polarization characterization method and system. Based on limited spectral induced polarization data of different pores and saturation states of reservoir rocks, combined with the numerical simulation advantages of the random impedance network algorithm in adapting to the non-homogeneous structure, complex pore and fluid distribution characteristics of the reservoir, and combined with the grid upscaling method, the accurate and quantitative characterization of the rock spectral induced polarization characteristics of the reservoir containing large-scale structure characteristics under the dynamic changes of the pore structure and water saturation is realized, and technical support is provided for the time-domain electromagnetic exploration fluid identification and quantitative evaluation of the induced polarization method physical parameters of the complex non-homogeneous reservoir.

Description

Technical Field

[0001] This invention relates to the field of geophysical exploration and reservoir resource development technology, and in particular to a method and system for upscale spectral induced polarization characterization of reservoir rocks. Background Technology

[0002] Spectral induced polarization (PEP) characterization of reservoir rocks is a core foundational technology for the refined exploration, reserve evaluation, and efficient development of oil, gas, and geothermal reservoir resources. Its accuracy directly determines the accuracy of reservoir pore structure identification, fluid property discrimination, and oil and gas saturation assessment, and is a crucial prerequisite for achieving refined and quantitative reservoir evaluation. Accurately characterizing the PEP response of rock electrical parameters across large-scale reservoir spaces, dynamically varying with pore structure and water saturation, has significant engineering value and theoretical implications for improving reservoir rock physical mechanisms, optimizing exploration interpretation models, and enhancing the efficiency and accuracy of reservoir resource exploration and development.

[0003] Currently, existing reservoir induced polarization (IP) characterization techniques mainly focus on qualitative analysis and pattern fitting of measured data. They lack systematic numerical simulation and inversion characterization methods that can integrate measured spectral IIP data and adapt to the random heterogeneous characteristics of reservoirs. As a result, they cannot establish accurate quantitative mapping relationships between different pore structures, water saturation and rock spectral IIP parameters in complex reservoirs. This leads to low accuracy and poor adaptability in large-scale reservoir IIP response characterization, making it difficult to meet the technical requirements of modern refined reservoir exploration and development. Summary of the Invention

[0004] This invention provides a method and system for upscale spectral induced polarization characterization of reservoir rocks, which solves the technical problem of the lack of systematic numerical simulation and inversion characterization methods in the prior art that can integrate measured spectral induced polarization data and adapt to the random heterogeneous characteristics of reservoirs. It realizes the establishment of accurate quantitative mapping relationship between different pore structures, water saturation and rock spectral induced polarization parameters of complex reservoirs, and improves the technical effect of large-scale reservoir induced polarization response characterization accuracy and adaptability.

[0005] This invention provides a method for upscale spectral induced polarization characterization of reservoir rocks, comprising: Combining M rock samples at different porosities With water saturation Under the condition of constrained digital rock porosity Water saturation Under the given conditions, the proportion of MN pore types in digital rock is determined using the least squares method. , One type of pore corresponds to a set of porosity and water saturation; Network nodes are connected to their neighboring nodes via impedance units. Based on the reservoir's heterogeneous characteristics, a corresponding spatial allocation mode is selected to assign pore types to each impedance unit and assign it the corresponding spectral induced electrical response parameters for that pore type. The measured electrical characteristics at the core scale are mapped to the network units, resulting in an impedance network digital rock. The number of each pore type to be allocated to each impedance unit is determined by the specified ratio. Decide; Through expressions The network nodes in the digital rock flowing through the impedance network are calculated. and Complex current of impedance unit ;in, The complex conductivity of this impedance unit is... Porosity Water saturation Complex resistivity spectrum curves of rock samples , For network nodes The complex potential at the point, For network nodes The complex potential at the point; For the network node Applying Kirchhoff's current law, the sum of the complex currents flowing into and out of the node is zero, i.e. ; Expanding the complex current yields... ; Applying Kirchhoff's current law to all internal nodes of the impedance network digital rock yields the following results: A system of linear equations, with fixed voltages applied to the upper and lower boundary nodes. and No current flows out from the lateral boundary. This can be obtained by solving this system of linear equations. Complex potential of each internal node Through expressions The total complex current connected to the edge of the boundary node is calculated. ;in, , For the network nodes in the impedance network digital rock Connect to the upper boundary node The complex conductivity of the edge impedance unit, Porosity Water saturation Complex resistivity spectrum curves of rock samples ; The potential of the upper boundary node is... For network nodes The complex potential at the point; Through expressions The spectral induced polarization curve of the digital rock obtained by the impedance network was calculated. ;in, The upscaling ratio of the impedance network digital rock is given. The potential of the lower boundary node; The MGEMTIP model was used to analyze the spectral induced polarization curves. By fitting the data, the DC resistivity can be obtained. and polarizability ; Rock samples with different porosities and water saturation Measured spectral induced polarization curves under the specified conditions The porosity was obtained by uniformly fitting the MGEMTIP model. Water saturation DC resistivity under certain conditions and polarizability ; Through expressions The effectiveness discriminant coefficient was calculated. ; If the validity discriminant coefficient Output different porosities when the porosity is less than the set threshold. Water saturation and in porosity Water saturation Spectral induced polarization curve under the condition and DC resistivity Polarizability .

[0006] Specifically, the corresponding spatial allocation patterns include: random uniform distribution allocation pattern and crack clustering distribution allocation pattern; The random uniform distribution allocation mode randomly and uniformly assigns pore types to each impedance unit of the network; the crack clustering distribution allocation mode uses a spatial clustering algorithm to divide the network nodes into k independent clusters, marking the continuous set of nodes along the current direction at the center of the network as the crack cluster, and the remaining nodes as the matrix cluster; among all pore types to be assigned, the product of porosity and water saturation corresponding to each pore type is calculated, and the average value of all products is used as the allocation threshold; pore types with a product greater than or equal to the allocation threshold are assigned to the impedance units connected to the crack cluster, and pore types with a product less than the allocation threshold are assigned to the impedance units connected to the matrix cluster.

[0007] Specifically, it also includes: For the same upscaling ratio The impedance network digital rock is solved n times in a loop to obtain the frequency resistivity amplitude in the j-th cycle and resistivity phase ; Through expressions Calculated frequency The coefficient of variation of resistivity amplitude between j cycles ;in, ; Through expressions Calculated frequency Phase variation coefficient between j cycles ;in, ; Through expressions The amplitude stability discriminant coefficient was calculated. ;in, For frequency The number of; Through expressions The phase stability discrimination coefficient was calculated. ; If the amplitude stability discriminant coefficient and phase stability discrimination coefficient All values ​​are less than a set threshold, for the rock samples at different porosities. and water saturation Measured spectral induced polarization curves under the specified conditions The MGEMTIP model was used for unified fitting.

[0008] Specifically, it also includes: Through expressions The complex resistivity spectrum curve of the rock sample was calculated. ;in, For different frequencies The complex impedance curve below, The diameter of the columnar rock sample. The length of the columnar rock sample is given.

[0009] Specifically, it also includes: Through expressions Porosity was calculated ;in, , For the first Porosity of rock samples corresponding to different pore types. Digital rock constrained porosity conditions; Through expressions The water saturation was calculated. ;in, , Assigned to the first in the digital rock porosity The sum of the proportions of impedance units of different pore types corresponding to different water saturation levels. For the first The rock sample corresponding to the pore type in the first Water saturation under various water saturation conditions For digital rock constrained saturation conditions.

[0010] The present invention also provides a reservoir rock upscale spectral induced polarization characterization system, comprising: The pore type proportion acquisition module is used to combine M rock samples at different porosities. With water saturation Under the condition of constrained digital rock porosity Water saturation Under the given conditions, the proportion of MN pore types in digital rock is determined using the least squares method. , One type of pore corresponds to a set of porosity and water saturation; The impedance network digital rock construction module connects network nodes to their adjacent nodes via impedance units. Based on the reservoir's heterogeneous characteristics, it selects a corresponding spatial allocation mode to assign pore types to each impedance unit and assigns it the corresponding spectral induced electrical response parameters for that pore type. It maps the measured electrical characteristics at the core scale to the network units, thus obtaining the impedance network digital rock. The number of each pore type to be assigned to each impedance unit is determined by the specified ratio. Decide; Impedance unit complex current calculation module, used to calculate complex current through expression The network nodes in the digital rock flowing through the impedance network are calculated. and Complex current of impedance unit ;in, The complex conductivity of this impedance unit is... Porosity Water saturation Complex resistivity spectrum curves of rock samples , For network nodes The complex potential at the point, For network nodes The complex potential at the point; The linear equations solving module is used to solve the network nodes. Applying Kirchhoff's current law, the sum of the complex currents flowing into and out of the node is zero, i.e. Expanding the complex current yields Applying Kirchhoff's current law to all internal nodes of the impedance network digital rock yields a result containing... A system of linear equations, with fixed voltages applied to the upper and lower boundary nodes. and No current flows out from the lateral boundary. This can be obtained by solving this system of linear equations. Complex potential of each internal node Through expressions The total complex current connected to the edge of the boundary node is calculated. ;in, , For the network nodes in the impedance network digital rock Connect to the upper boundary node The complex conductivity of the edge impedance unit, Porosity Water saturation Complex resistivity spectrum curves of rock samples ; The potential of the upper boundary node is... For network nodes The complex potential at the point; The spectral induced polarization curve calculation module is used to calculate the induced polarization curve using an expression. The spectral induced polarization curve of the digital rock obtained by the impedance network was calculated. ;in, The upscaling ratio of the impedance network digital rock is given. The potential of the lower boundary node; The digital rock spectral induced polarization curve fitting module is used to fit the spectral induced polarization curve using the MGEMTIP model. By fitting the data, the DC resistivity can be obtained. and polarizability ; The measured spectral induced polarization curve fitting module is used to fit rock samples at different porosities. and water saturation Measured spectral induced polarization curves under the specified conditions The porosity was obtained by uniformly fitting the MGEMTIP model. Water saturation DC resistivity under certain conditions and polarizability ; The validity discrimination coefficient calculation module is used to calculate the validity discrimination coefficient through an expression. The effectiveness discriminant coefficient was calculated. ; The reservoir rock upscale spectral induced polarization characterization module is used to determine the validity discrimination coefficient. Output different porosities when the porosity is less than the set threshold. Water saturation and in porosity Water saturation Spectral induced polarization curve under the condition and DC resistivity Polarizability .

[0011] Specifically, the corresponding spatial allocation patterns include: random uniform distribution allocation pattern and crack clustering distribution allocation pattern; The random uniform distribution allocation mode randomly and uniformly assigns pore types to each impedance unit of the network; the crack clustering distribution allocation mode uses a spatial clustering algorithm to divide the network nodes into k independent clusters, marking the continuous set of nodes along the current direction at the center of the network as the crack cluster, and the remaining nodes as the matrix cluster; among all pore types to be assigned, the product of porosity and water saturation corresponding to each pore type is calculated, and the average value of all products is used as the allocation threshold; pore types with a product greater than or equal to the allocation threshold are assigned to the impedance units connected to the crack cluster, and pore types with a product less than the allocation threshold are assigned to the impedance units connected to the matrix cluster.

[0012] Specifically, it also includes: Impedance network digital rock cyclic solution module, used for solving the same upscaling ratio The impedance network digital rock is solved n times in a loop to obtain the frequency resistivity amplitude in the j-th cycle and resistivity phase ; The resistivity amplitude variation coefficient calculation module is used to calculate the coefficient of variation of resistivity using the expression. Calculated frequency The coefficient of variation of resistivity amplitude between j cycles ;in, ; The phase variation coefficient calculation module is used to calculate the phase variation coefficient using the expression. Calculated frequency Phase variation coefficient between j cycles ;in, ; The amplitude stability discrimination coefficient calculation module is used to calculate the amplitude stability discrimination coefficient through the expression. The amplitude stability discriminant coefficient was calculated. ;in, For frequency The number of; The phase stability discrimination coefficient calculation module is used to calculate the phase stability discrimination coefficient through the expression. The phase stability discrimination coefficient was calculated. ; The stability discrimination module is used to determine if the amplitude stability discrimination coefficient is... and phase stability discrimination coefficient All values ​​are less than a set threshold, for the rock samples at different porosities. and water saturation Measured spectral induced polarization curves under the specified conditions The MGEMTIP model was used for unified fitting.

[0013] Specifically, it also includes: The complex resistivity spectrum curve calculation module is used to calculate the complex resistivity spectrum curve using the expression. The complex resistivity spectrum curve of the rock sample was calculated. ;in, For different frequencies The complex impedance curve below, The diameter of the columnar rock sample. The length of the columnar rock sample is given.

[0014] Specifically, it also includes: The porosity calculation module is used to calculate porosity using an expression. Porosity was calculated ;in, , For the first Porosity of rock samples corresponding to different pore types. Digital rock constrained porosity conditions; The water saturation calculation module is used to calculate water saturation using an expression. The water saturation was calculated. ;in, , Assigned to the first in the digital rock porosity The sum of the proportions of impedance units of different pore types corresponding to different water saturation levels. For the first The rock sample corresponding to the pore type in the first Water saturation under various water saturation conditions For digital rock constrained saturation conditions.

[0015] One or more technical solutions provided in this invention have at least the following technical effects or advantages: Based on limited spectral induced polarization (IP) data of reservoir rocks under different pore sizes and saturation states, and combined with the numerical simulation advantages of the stochastic impedance network algorithm to adapt to the heterogeneous structure, complex pore size, and fluid distribution characteristics of reservoirs, and combined with the grid upscaling method, we can achieve accurate and quantitative characterization of the spectral IIP characteristics of reservoirs under dynamic changes in pore structure and water saturation, which can include large-scale structural features. This provides technical support for fluid identification in time-domain electromagnetic exploration and quantitative evaluation of physical parameters of complex heterogeneous reservoirs using IIP. Attached Figure Description

[0016] Figure 1 A flowchart of the reservoir rock upscale spectral induced polarization characterization method provided in the embodiments of the present invention; Figure 2 This is a schematic diagram of the impedance unit in the digital rock impedance network in an embodiment of the present invention; Figure 3 The scaling factor of the network constructed using the three-dimensional impedance network method. A digital rock diagram; Figure 4 This is a clustering effect diagram in an embodiment of the present invention; Figure 5 A comparison of resistivity spectrum data of reservoir samples and digital rocks with induced polarization parameter inversion based on the MGEMTIP model; Figure 6 A comparison of digital rock induced polarization parameters generated from a random uniform distribution with the induced polarization parameters of the fitted model; Figure 7 The spectral induced polarization curves of digital rocks with different distribution patterns under the same porosity and water saturation conditions are shown. Figure 8 A comparison of the digital rock induced polarization parameters generated for fracture clustering distribution with the induced polarization parameters of the fitted model; Figure 9 Spectral induced polarization curves of digital rocks with different porosities and water saturation. Detailed Implementation

[0017] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0018] like Figure 1 As shown, the reservoir rock upscale spectral induced polarization characterization method provided in this embodiment of the invention includes: Combining M rock samples at different porosities With water saturation Under the condition of constrained digital rock porosity Water saturation Under the given conditions, the proportion of MN pore types in digital rock is determined using the least squares method. , One type of pore corresponds to a set of porosity and water saturation; Network nodes are connected to their adjacent nodes via impedance units. Based on the reservoir's heterogeneous characteristics, a corresponding spatial allocation mode is selected to assign pore types to each impedance unit and assign it the corresponding spectral induced electrical response parameters. The measured electrical characteristics at the core scale are mapped to the network units, resulting in an impedance network digital rock. An upscaling digital rock is constructed using a three-dimensional impedance network method. This digital rock represents the reservoir space in the form of a three-dimensional node-impedance unit network, with the upscaling ratio denoted as [missing information]. .like Figure 2 As shown, each impedance unit is assigned to a pore type, and each pore type corresponds to a different state / type of rock sample. For example... Figure 3 As shown, the number of network nodes is the internal total. Nodes and the top and bottom sides Each node has a boundary node, with nodes on its upper and lower sides connected to an external voltage. The cylinders connecting adjacent nodes in the network represent impedance elements, which are assigned to different aperture types. The number of each aperture type to be assigned to the impedance elements is determined by a ratio. Decide; Specifically, the corresponding spatial allocation patterns include: random uniform distribution pattern and crack clustering distribution pattern; The random uniform distribution allocation mode randomly and uniformly assigns pore types to each impedance unit of the network, making the network spatially independent. The crack clustering distribution allocation mode uses a spatial clustering algorithm to divide the network nodes into k independent clusters. The set of continuous nodes along the current direction at the center of the network is marked as the crack cluster, and the remaining nodes are marked as the matrix cluster. Among all the pore types to be assigned, the product of porosity and water saturation corresponding to each pore type is calculated, and the average value of all products is used as the allocation threshold. Pore types with a product greater than or equal to the allocation threshold are assigned to the impedance units connected to the crack cluster, and pore types with a product less than the allocation threshold are assigned to the impedance units connected to the matrix cluster. Figure 4 This diagram illustrates the spatial structure that satisfies both random uniform distribution and fracture clustering. The clustering algorithm categorizes all pore types into two classes: fractures and matrix. The top image shows the clustering effect under the random uniform distribution mode, while the bottom image shows the fracture clustering effect. The fracture class in the middle of the network is assigned to pore types with a larger product of porosity and water saturation.

[0019] Through expressions Calculation of network nodes in digital rock through flow impedance network and Complex current of impedance unit ;in, The complex conductivity of this impedance unit is... Porosity Water saturation Complex resistivity spectrum curves of rock samples , For network nodes The complex potential at the point, For network nodes The complex potential at the point; For network nodes Applying Kirchhoff's current law, the sum of the complex currents flowing into and out of the node is zero, i.e. ; Expanding the complex current yields... ; Applying Kirchhoff's current law to all internal nodes of the impedance network digital rock yields the following results: A system of linear equations, with fixed voltages applied to the upper and lower boundary nodes. and No current flows out from the lateral boundary. This can be obtained by solving this system of linear equations. Complex potential of each internal node Through expressions The total complex current connected to the edge of the boundary node is calculated. ;in, , For impedance network digital rock network nodes Connect to the upper boundary node The complex conductivity of the edge impedance unit, Porosity Water saturation Complex resistivity spectrum curves of rock samples ; The potential at the upper boundary node is used to simulate the voltage measurement by applying a fixed potential to the upper and lower boundary nodes. For network nodes The complex potential at the point; Through expressions The spectral induced polarization curves of the digital rock obtained by impedance network were calculated. ;in, To achieve the upscaling ratio of digital rocks in the impedance network, The potential of the lower boundary node is given by the network measurement voltage, which is the potential difference between the upper and lower boundary nodes. .

[0020] The MGEMTIP model was used to analyze the spectral induced polarization curves. By fitting the data, the DC resistivity can be obtained. and polarizability ; Rock samples with different porosities and water saturation Measured spectral induced polarization curves under the specified conditions The porosity was obtained by uniformly fitting the MGEMTIP model. Water saturation DC resistivity under certain conditions and polarizability ; DC resistivity obtained through two methods ( , and polarizability ( , The expressions for the two excitation parameters are shown in Table 1: Table 1 MGEMTIP Model Parameters

[0021] in, and The corresponding time constant and the polarization of the time constant within the study frequency band are respectively , The total number of time constants. DC resistivity. and polarizability These are the undetermined coefficients in the MGEMTIP model, obtained by fitting the spectral induced polarization curve using the nonlinear least squares method:

[0022] in, For parameter set, The measured spectral induced polarization curve, i.e. or Solving the problem iteratively through optimization algorithms To obtain the optimal parameter set The induced polarization parameters can be obtained by combining the optimal parameters with the formulas in Table 1. For example... Figure 5 As shown, the results of typical data were fitted using the MGEMTIP model while suppressing low-frequency electrode polarization.

[0023] To verify the ability of upscaled digital rocks to characterize the induced polarization properties of actual reservoir rocks, the following also includes: For the same upscaling ratio The impedance network digital rock is solved n times in a loop to obtain the frequency resistivity amplitude in the j-th cycle and resistivity phase ; Through expressions Calculated frequency The coefficient of variation of resistivity amplitude between j cycles ;in, ; Through expressions Calculated frequency Phase variation coefficient between j cycles ;in, ; Through expressions The amplitude stability discriminant coefficient was calculated. ;in, For frequency The number of elements, i.e., the number of elements present in the spectral curve. Each frequency.

[0024] Through expressions The phase stability discrimination coefficient was calculated. ; If the amplitude stability discriminant coefficient and phase stability discrimination coefficient All values ​​were less than the set threshold for rock samples with different porosities. and water saturation Measured spectral induced polarization curves under the specified conditions The MGEMTIP model is used for unified fitting. Specifically, if... Then it is determined that the spectral induced electric response of digital rocks has reached statistical stability at the current upscaling ratio; if Then increase the upscaling ratio. Repeatedly construct and calculate upscaled digital rock spectral induced polarization curves. The process.

[0025] Through expressions The effectiveness discriminant coefficient was calculated. ; If the validity discriminant coefficient Output different porosities when the porosity is less than the set threshold. Water saturation and in porosity Water saturation Spectral induced polarization curve under the condition and DC resistivity Polarizability This completed the quantitative characterization of the spectral induced polarization characteristics of large-scale reservoir rocks. Specifically, It can be used to determine the equivalence between upscale and downscale digital rocks under arbitrary porosity and water saturation conditions. The smaller the value, the closer the spectral responses of the two structures are. Considering the errors caused by sampling at the actual exploration scale and measurement at the laboratory scale, if If so, it means the method is effective. If the study area contains heterogeneous structures such as large-scale cracks and karst caves, it is necessary to consider whether the study area contains heterogeneous structures such as large-scale cracks and karst caves. It is also necessary to adjust the pore type distribution pattern by combining prior information such as well logging or seismic data and to reconstruct the digital rock.

[0026] The method for upscale spectral induced polarization characterization of reservoir rocks provided in the embodiments of the present invention is described in detail, and also includes: Through expressions The complex resistivity spectrum curve of the rock sample was calculated. ;in, For different frequencies The complex impedance curve below, The diameter of the columnar rock sample. denoted as the length of the columnar rock sample. Specifically, the porosity of M rock samples is calculated under simulated formation depth conditions corresponding to temperature, pressure, and mineralization. Measure and simultaneously obtain the length of columnar rock samples and diameter , Using the Autolab1000 multi-functional core measuring instrument, the core samples were analyzed under N controlled water saturation conditions (…). By performing complex impedance measurements, different frequencies can be obtained. Complex impedance curves below (Including amplitude and phase data).

[0027] Through expressions Porosity was calculated ;in, , For the first Porosity of rock samples corresponding to different pore types. Digital rock constrained porosity conditions; Through expressions The water saturation was calculated. ;in, , Assigned to the first in digital rocks porosity The sum of the proportions of impedance units of different pore types corresponding to different water saturation levels. For the first The rock sample corresponding to the pore type in the first Water saturation under various water saturation conditions For digital rock constrained saturation conditions.

[0028] Furthermore, embodiments of the present invention also provide a reservoir rock upscale spectral induced polarization characterization system, comprising: The pore type proportion acquisition module is used to combine M rock samples at different porosities. With water saturation Under the condition of constrained digital rock porosity Water saturation Under the given conditions, the proportion of MN pore types in digital rock is determined using the least squares method. , One type of pore corresponds to a set of porosity and water saturation; The impedance network digital rock construction module connects network nodes to their adjacent nodes via impedance units. Based on the reservoir's heterogeneous characteristics, it selects the corresponding spatial allocation mode to assign pore types to each impedance unit and assigns it the corresponding spectral induced electrical response parameters for that pore type. It maps the measured electrical characteristics at the core scale to the network units, obtaining the impedance network digital rock. An upscaling digital rock is constructed using a three-dimensional impedance network method. This digital rock represents the reservoir space in the form of a three-dimensional node-impedance unit network, with the upscaling ratio denoted as [missing information]. The number of each pore type to be allocated to the impedance unit is determined by a ratio. Decide; Specifically, the corresponding spatial allocation patterns include: random uniform distribution pattern and crack clustering distribution pattern; The random uniform distribution allocation mode randomly and uniformly assigns pore types to each impedance unit of the network, making the network spatially independent. The crack clustering distribution allocation mode uses a spatial clustering algorithm to divide the network nodes into k independent clusters. The set of continuous nodes along the current direction at the center of the network is marked as the crack cluster, and the remaining nodes are marked as the matrix cluster. Among all the pore types to be assigned, the product of porosity and water saturation corresponding to each pore type is calculated, and the average value of all products is used as the allocation threshold. Pore types with a product greater than or equal to the allocation threshold are assigned to the impedance units connected to the crack cluster, and pore types with a product less than the allocation threshold are assigned to the impedance units connected to the matrix cluster.

[0029] Impedance unit complex current calculation module, used to calculate complex current through expression Calculation of network nodes in digital rock through flow impedance network and Complex current of impedance unit ;in, The complex conductivity of this impedance unit is... Porosity Water saturation Complex resistivity spectrum curves of rock samples , For network nodes The complex potential at the point, For network nodes The complex potential at the point; The linear equations solving module is used to solve network nodes. Applying Kirchhoff's current law, the sum of the complex currents flowing into and out of the node is zero, i.e. Expanding the complex current yields Applying Kirchhoff's current law to all internal nodes of the impedance network digital rock yields results containing A system of linear equations, with fixed voltages applied to the upper and lower boundary nodes. and No current flows out from the lateral boundary. This can be obtained by solving this system of linear equations. Complex potential of each internal node Through expressions The total complex current connected to the edge of the boundary node is calculated. ;in, , For impedance network digital rock network nodes Connect to the upper boundary node The complex conductivity of the edge impedance unit, Porosity Water saturation Complex resistivity spectrum curves of rock samples ; The potential at the upper boundary node is used to simulate the voltage measurement by applying a fixed potential to the upper and lower boundary nodes. For network nodes The complex potential at the point; The spectral induced polarization curve calculation module is used to calculate the induced polarization curve using an expression. The spectral induced polarization curves of the digital rock obtained by impedance network were calculated. ;in, To achieve the upscaling ratio of digital rocks in the impedance network, The potential of the lower boundary node is given by the network measurement voltage, which is the potential difference between the upper and lower boundary nodes. .

[0030] The digital rock spectral induced polarization curve fitting module is used to fit spectral induced polarization curves using the MGEMTIP model. By fitting the data, the DC resistivity can be obtained. and polarizability ; The measured spectral induced polarization curve fitting module is used to fit rock samples at different porosities. and water saturation Measured spectral induced polarization curves under the specified conditions The porosity was obtained by uniformly fitting the MGEMTIP model. Water saturation DC resistivity under certain conditions and polarizability ; To verify the ability of upscaled digital rocks to characterize the induced polarization properties of actual reservoir rocks, the following also includes: Impedance network digital rock cyclic solution module, used for solving the same upscaling ratio The impedance network digital rock is solved n times in a loop to obtain the frequency resistivity amplitude in the j-th cycle and resistivity phase ; The resistivity amplitude variation coefficient calculation module is used to calculate the coefficient of variation of resistivity using the expression. Calculated frequency The coefficient of variation of resistivity amplitude between j cycles ;in, ; The phase variation coefficient calculation module is used to calculate the phase variation coefficient using the expression. Calculated frequency Phase variation coefficient between j cycles ;in, ; The amplitude stability discrimination coefficient calculation module is used to calculate the amplitude stability discrimination coefficient through the expression. The amplitude stability discriminant coefficient was calculated. ;in, For frequency The number of elements, i.e., the number of elements present in the spectral curve. Each frequency.

[0031] The phase stability discrimination coefficient calculation module is used to calculate the phase stability discrimination coefficient through the expression. The phase stability discrimination coefficient was calculated. ; The stability discrimination module is used to determine the amplitude stability discrimination coefficient. and phase stability discrimination coefficient All values ​​were less than the set threshold for rock samples with different porosities. and water saturation Measured spectral induced polarization curves under the specified conditions The MGEMTIP model is used for unified fitting. Specifically, if... Then it is determined that the spectral induced electric response of digital rocks has reached statistical stability at the current upscaling ratio; if Then increase the upscaling ratio. Repeatedly construct and calculate upscaled digital rock spectral induced polarization curves. The process.

[0032] The validity discrimination coefficient calculation module is used to calculate the validity discrimination coefficient through an expression. The effectiveness discriminant coefficient was calculated. ; The reservoir rock upscaled spectral induced polarization characterization module is used to determine the validity of the coefficient of determination. Output different porosities when the porosity is less than the set threshold. Water saturation and in porosity Water saturation Spectral induced polarization curve under the condition and DC resistivity Polarizability This completed the quantitative characterization of the spectral induced polarization characteristics of large-scale reservoir rocks. Specifically, It can be used to determine the equivalence between upscale and downscale digital rocks under arbitrary porosity and water saturation conditions. The smaller the value, the closer the spectral responses of the two structures are. Considering the errors caused by sampling at the actual exploration scale and measurement at the laboratory scale, if If so, it means the method is effective. If the study area contains heterogeneous structures such as large-scale cracks and karst caves, it is necessary to consider whether the study area contains heterogeneous structures such as large-scale cracks and karst caves. It is also necessary to adjust the pore type distribution pattern by combining prior information such as well logging or seismic data and to reconstruct the digital rock.

[0033] The reservoir rock upscale spectral induced polarization characterization system provided in the embodiments of the present invention is described in detail, and also includes: The complex resistivity spectrum curve calculation module is used to calculate the complex resistivity spectrum curve using the expression. The complex resistivity spectrum curve of the rock sample was calculated. ;in, For different frequencies The complex impedance curve below, The diameter of the columnar rock sample. denoted as the length of the columnar rock sample. Specifically, the porosity of M rock samples is calculated under simulated formation depth conditions corresponding to temperature, pressure, and mineralization. Measure and simultaneously obtain the length of columnar rock samples and diameter , Using the Autolab1000 multi-functional core measuring instrument, the core samples were analyzed under N controlled water saturation conditions (…). By performing complex impedance measurements, different frequencies can be obtained. Complex impedance curves below (Including amplitude and phase data).

[0034] The porosity calculation module is used to calculate porosity using an expression. Porosity was calculated ;in, , For the first Porosity of rock samples corresponding to different pore types. Digital rock constrained porosity conditions; The water saturation calculation module is used to calculate water saturation using an expression. The water saturation was calculated. ;in, , Assigned to the first in digital rocks porosity The sum of the proportions of impedance units of different pore types corresponding to different water saturation levels. For the first The rock sample corresponding to the pore type in the first Water saturation under various water saturation conditions For digital rock constrained saturation conditions.

[0035] Example Ten well core samples with different porosities were selected from a region in the Sichuan Basin. For each sample, spectral induced polarization (PI) data were measured under simulated formation temperature and pressure conditions for five different water saturation states, resulting in 50 sets of measured data. This data was input into a digital rock impedance network to generate upscaled digital rock PI curves under two spatial distribution modes: random uniform distribution and fracture clustering distribution. Figure 6 As shown, the black circles represent the induced polarization (ICP) parameters (DC resistivity and polarizability) of digital rocks under different porosity and saturation conditions, while the colored panels represent the ICP spectrum of the fitted model under different porosity and saturation conditions. Under the condition that the large-scale digital rocks satisfy a random uniform distribution, the ICP response of the overall reservoir digital rocks and the small-scale cores is consistent, and the projection results basically satisfy this phenomenon. Under the random uniform distribution model, the ICP parameters such as DC resistivity and polarizability extracted from the digital rocks have good consistency with the ICP spectrum modeled by fitting the data Archie relation, and the average validity discrimination coefficient is small, indicating that this method can effectively characterize the spectral ICP response of large-scale reservoir rocks under the homogeneous assumption. Figure 7 As shown, under the same porosity and water saturation conditions, the spectral curves generated by the two spatial distribution patterns show significant differences. The crack clustering distribution, due to the introduction of a strongly heterogeneous pore structure, exhibits induced polarization parameters that deviate from the homogeneous fitting model. For example... Figure 8As shown, the black circles represent the induced polarization parameters (DC resistivity and polarizability) of the digital rock under different porosity and saturation conditions with fracture clustering distribution. The colored charts show the induced polarization parameter spectra of the fitted model under different porosity and saturation conditions. Due to the introduction of a strongly heterogeneous pore structure, the fracture clustering distribution causes its induced polarization parameters to deviate from the homogeneous fitted model. The validity discrimination coefficient is also shown. This indicates that the distribution pattern can capture the induced polarization (IP) response of complex reservoirs that cannot be described by homogeneous models. Combined with the stability discrimination coefficient results shown in Table 2, the network upscaling factor that meets the accuracy requirements can be determined, ensuring the statistical stability of the digital rock spectral response. These results demonstrate that this method not only verifies the effectiveness of methods within the traditional homogeneous characterization framework but also extends its application to the spectral IIP characterization of heterogeneous reservoir spaces, achieving an effective characterization of the spectral IIP response of complex reservoirs varying with porosity and saturation.

[0036] Table 2. Stability discriminant coefficients under random uniform distribution

[0037] In summary, the embodiments of this invention aim to construct a method for characterizing the spectral induced polarization (IPD) of large-scale spatial reservoirs as a function of porosity and water saturation, using a random impedance network algorithm and reservoir rock physical spectral IPD measurement data. This method overcomes the technical bottleneck of lacking large-scale pore and fracture structure information in the transition from mesoscopic core IPD data to macroscopic formation IPD responses. It can assign large-scale pore and fracture structures to complex reservoir spaces through spatial clustering algorithms, while simultaneously satisfying the heterogeneity of reservoir spaces at both small and large scales, further realizing the spectral IPD characterization of complex reservoir spaces. Figure 9 As shown, spectral induced polarization curves (amplitude and phase) under different porosity and water saturation conditions can be obtained through a set of reservoir rock physical test results. The stability discrimination coefficient is then used to determine the spectral induced polarization curves. Determine the upscaling ratio of stable networks Under a uniform random structure, the extracted induced polarization (IP) parameters are consistent with those modeled by fitting the data Archie relation. The results indicate that the IIP parameters of the digital rock generated by the random impedance network are formally consistent with those of the theoretical model. The average validity discriminant coefficients of the IIP parameters of the digital rock and the theoretical model are also consistent. This indicates that the spectral induced electrical response of reservoir rocks under large-scale structures can be effectively characterized.

[0038] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0039] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0040] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0041] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0042] Any aspects of this invention not described in detail in the embodiments are well-known techniques to those skilled in the art. Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this invention and not to limit it. Although this invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of this invention without departing from the spirit and scope of this invention, and all such modifications and substitutions should be covered within the scope of the claims of this invention.

Claims

1. A method for upscale spectral induced polarization characterization of reservoir rocks, characterized in that, include: Combining M rock samples at different porosities With water saturation Under the condition of constrained digital rock porosity Water saturation Under the given conditions, the proportion of MN pore types in digital rock is determined using the least squares method. , One type of pore corresponds to a set of porosity and water saturation; Network nodes are connected to their neighboring nodes via impedance units. Based on the reservoir's heterogeneous characteristics, a corresponding spatial allocation mode is selected to assign pore types to each impedance unit and assign it the corresponding spectral induced electrical response parameters for that pore type. The measured electrical characteristics at the core scale are mapped to the network units, resulting in an impedance network digital rock. The number of each pore type to be allocated to each impedance unit is determined by the specified ratio. Decide; Through expression The network nodes in the digital rock flowing through the impedance network are calculated. and Complex current of impedance unit ;in, The complex conductivity of this impedance unit is... Porosity Water saturation Complex resistivity spectrum curves of rock samples , For network nodes The complex potential at the point, For network nodes The complex potential at the point; For the network node Applying Kirchhoff's current law, the sum of the complex currents flowing into and out of the node is zero, i.e. ; Expanding the complex current yields... ; Applying Kirchhoff's current law to all internal nodes of the impedance network digital rock yields the following results: A system of linear equations, with fixed voltages applied to the upper and lower boundary nodes. and No current flows out from the lateral boundary. This can be obtained by solving this system of linear equations. Complex potential of each internal node Through expressions The total complex current connected to the edge of the boundary node is calculated. ;in, , For the network nodes in the impedance network digital rock Connect to the upper boundary node The complex conductivity of the impedance unit on the edge, Porosity Water saturation Complex resistivity spectrum curves of rock samples ; Let be the potential of the upper boundary node. For network nodes The complex potential at the point; Through expression The spectral induced polarization curve of the digital rock obtained by the impedance network was calculated. ;in, The upscaling ratio of the impedance network digital rock is given. The potential of the lower boundary node; The MGEMTIP model was used to analyze the spectral induced polarization curves. By fitting the data, the DC resistivity can be obtained. and polarizability ; Rock samples with different porosities and water saturation Measured spectral induced polarization curves under the specified conditions The porosity was obtained by uniformly fitting the MGEMTIP model. Water saturation DC resistivity under certain conditions and polarizability ; Through expression The effectiveness discriminant coefficient was calculated. ; If the validity discriminant coefficient Output different porosities when the porosity is less than the set threshold. Water saturation and in porosity Water saturation Spectral induced polarization curve under the condition and DC resistivity Polarizability .

2. The reservoir rock upscale spectral induced polarization characterization method as described in claim 1, characterized in that, The corresponding spatial allocation patterns include: random uniform distribution allocation pattern and crack clustering distribution allocation pattern; The random uniform distribution allocation mode randomly and uniformly assigns pore types to each impedance unit of the network; the crack clustering distribution allocation mode uses a spatial clustering algorithm to divide the network nodes into k independent clusters, marking the continuous set of nodes along the current direction at the center of the network as the crack cluster, and the remaining nodes as the matrix cluster; among all pore types to be assigned, the product of porosity and water saturation corresponding to each pore type is calculated, and the average value of all products is used as the allocation threshold; pore types with a product greater than or equal to the allocation threshold are assigned to the impedance units connected to the crack cluster, and pore types with a product less than the allocation threshold are assigned to the impedance units connected to the matrix cluster.

3. The reservoir rock upscale spectral induced polarization characterization method as described in claim 1, characterized in that, Also includes: For the same upscaling ratio The impedance network digital rock is solved n times in a loop to obtain the frequency resistivity amplitude in the j-th cycle and resistivity phase ; Through expressions Calculated frequency The coefficient of variation of resistivity amplitude between j cycles ;in, ; Through expressions Calculated frequency Phase variation coefficient between j cycles ;in, ; Through expression The amplitude stability discriminant coefficient was calculated. ;in, For frequency The number of; Through expression The phase stability discrimination coefficient was calculated. ; If the amplitude stability discriminant coefficient and phase stability discrimination coefficient All values ​​are less than a set threshold, for the rock samples at different porosities. and water saturation Measured spectral induced polarization curves under the specified conditions The MGEMTIP model was used for unified fitting.

4. The reservoir rock upscale spectral induced polarization characterization method as described in claim 1, characterized in that, Also includes: Through expressions The complex resistivity spectrum curve of the rock sample was calculated. ;in, For different frequencies The complex impedance curve below, The diameter of the columnar rock sample. The length of the columnar rock sample is given.

5. The reservoir rock upscale spectral induced polarization characterization method as described in claim 1, characterized in that, Also includes: Through expression Porosity was calculated ;in, , For the first Porosity of rock samples corresponding to different pore types. Digital rock constrained porosity conditions; Through expression The water saturation was calculated. ;in, , Assigned to the first in the digital rock porosity The sum of the proportions of impedance units of different pore types corresponding to different water saturation levels. For the first The rock sample corresponding to the pore type in the first Water saturation under various water saturation conditions For digital rock constrained saturation conditions.

6. A reservoir rock upscale spectral induced polarization characterization system, characterized in that, include: The pore type proportion acquisition module is used to combine M rock samples at different porosities. With water saturation Under the condition of constrained digital rock porosity Water saturation Under the given conditions, the proportion of MN pore types in digital rock is determined using the least squares method. , One type of pore corresponds to a set of porosity and water saturation; The impedance network digital rock construction module connects network nodes to their adjacent nodes via impedance units. Based on the reservoir's heterogeneous characteristics, it selects a corresponding spatial allocation mode to assign pore types to each impedance unit and assigns it the corresponding spectral induced electrical response parameters for that pore type. It maps the measured electrical characteristics at the core scale to the network units, thus obtaining the impedance network digital rock. The number of each pore type to be assigned to each impedance unit is determined by the specified ratio. Decide; Impedance unit complex current calculation module, used to calculate complex current through expression The network nodes in the digital rock flowing through the impedance network are calculated. and Complex current of impedance unit ;in, The complex conductivity of this impedance unit is... Porosity Water saturation Complex resistivity spectrum curves of rock samples , For network nodes The complex potential at the point, For network nodes The complex potential at the point; The linear equations solving module is used to solve the network nodes. Applying Kirchhoff's current law, the sum of the complex currents flowing into and out of the node is zero, i.e. Expanding the complex current yields Applying Kirchhoff's current law to all internal nodes of the impedance network digital rock yields a result containing... A system of linear equations, with fixed voltages applied to the upper and lower boundary nodes. and No current flows out from the lateral boundary. This can be obtained by solving this system of linear equations. Complex potential of each internal node Through expressions The total complex current connected to the edge of the boundary node is calculated. ;in, , For the network nodes in the impedance network digital rock Connect to the upper boundary node The complex conductivity of the edge impedance unit, Porosity Water saturation Complex resistivity spectrum curves of rock samples ; The potential of the upper boundary node is... For network nodes The complex potential at the point; The spectral induced polarization curve calculation module is used to calculate the induced polarization curve using an expression. The spectral induced polarization curve of the digital rock obtained by the impedance network was calculated. ;in, The upscaling ratio of the impedance network digital rock is given. The potential of the lower boundary node; The digital rock spectral induced polarization curve fitting module is used to fit the spectral induced polarization curve using the MGEMTIP model. By fitting the data, the DC resistivity can be obtained. and polarizability ; The measured spectral induced polarization curve fitting module is used to fit rock samples at different porosities. and water saturation Measured spectral induced polarization curves under the specified conditions The porosity was obtained by uniformly fitting the MGEMTIP model. Water saturation DC resistivity under certain conditions and polarizability ; The validity discrimination coefficient calculation module is used to calculate the validity discrimination coefficient through an expression. The effectiveness discriminant coefficient was calculated. ; The reservoir rock upscale spectral induced polarization characterization module is used to determine the validity discrimination coefficient. Output different porosities when the porosity is less than the set threshold. Water saturation and in porosity Water saturation Spectral induced polarization curve under the condition and DC resistivity Polarizability .

7. The reservoir rock upscale spectral induced polarization characterization system as described in claim 6, characterized in that, The corresponding spatial allocation patterns include: random uniform distribution allocation pattern and crack clustering distribution allocation pattern; The random uniform distribution allocation mode randomly and uniformly assigns pore types to each impedance unit of the network; the crack clustering distribution allocation mode uses a spatial clustering algorithm to divide the network nodes into k independent clusters, marking the continuous set of nodes along the current direction at the center of the network as the crack cluster, and the remaining nodes as the matrix cluster; among all pore types to be assigned, the product of porosity and water saturation corresponding to each pore type is calculated, and the average value of all products is used as the allocation threshold; pore types with a product greater than or equal to the allocation threshold are assigned to the impedance units connected to the crack cluster, and pore types with a product less than the allocation threshold are assigned to the impedance units connected to the matrix cluster.

8. The reservoir rock upscale spectral induced polarization characterization system as described in claim 6, characterized in that, Also includes: Impedance network digital rock cyclic solution module, used for solving the same upscaling ratio The impedance network digital rock is solved n times in a loop to obtain the frequency resistivity amplitude in the j-th cycle and resistivity phase ; The resistivity amplitude variation coefficient calculation module is used to calculate the coefficient of variation of resistivity using the expression. Calculated frequency The coefficient of variation of resistivity amplitude between j cycles ;in, ; The phase variation coefficient calculation module is used to calculate the phase variation coefficient using the expression. Calculated frequency Phase variation coefficient between j cycles ;in, ; The amplitude stability discrimination coefficient calculation module is used to calculate the amplitude stability discrimination coefficient using the expression. The amplitude stability discriminant coefficient was calculated. ;in, For frequency The number of; The phase stability discrimination coefficient calculation module is used to calculate the phase stability discrimination coefficient through the expression. The phase stability discrimination coefficient was calculated. ; The stability discrimination module is used to determine if the amplitude stability discrimination coefficient is... and phase stability discrimination coefficient All values ​​are less than a set threshold, for the rock samples at different porosities. and water saturation Measured spectral induced polarization curves under the specified conditions The MGEMTIP model was used for unified fitting.

9. The reservoir rock upscale spectral induced polarization characterization system as described in claim 6, characterized in that, Also includes: The complex resistivity spectrum curve calculation module is used to calculate the complex resistivity spectrum curve using the expression. The complex resistivity spectrum curve of the rock sample was calculated. ;in, For different frequencies The complex impedance curve below, The diameter of the columnar rock sample. The length of the columnar rock sample is given.

10. The reservoir rock upscale spectral induced polarization characterization system as described in claim 6, characterized in that, Also includes: The porosity calculation module is used to calculate porosity using an expression. Porosity was calculated ;in, , For the first Porosity of rock samples corresponding to different pore types. Digital rock constrained porosity conditions; The water saturation calculation module is used to calculate water saturation using an expression. The water saturation was calculated. ;in, , Assigned to the first in the digital rock porosity The sum of the proportions of impedance units of different pore types corresponding to different water saturation levels. For the first The rock sample corresponding to the pore type in the first Water saturation under various water saturation conditions For digital rock constrained saturation conditions.

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