Method for identifying tight sandstone reservoir

Abstract

The invention discloses an identification method of a tight sandstone reservoir. Various physical properties of a rock sample of the tight sandstone are measured, the change rule of various parameters of the rock is obtained through analysis according to measured data, and induced polarization parameters of the rock are extracted through inversion based on an MGEMTIP model. According to the method, the relationship among the electrical property, elasticity and physical property parameters of the rock is constructed, the electrical-elastic rock physical model is established, and then the measured data is input into the model for reservoir parameter analysis, so that the reservoir parameters can be more accurately and quantitatively predicted, and the precision of the physical property parameters for oil gas detection is further improved.

Description

Technical Field

[0001] The present invention relates to the fields of oil and gas exploration and development, unconventional and new energy technologies, and in particular to a method for identifying a tight sandstone reservoir. Background Art

[0002] As one of the tight reservoirs, tight sandstone has large reserves, wide distribution, and great economic utilization and mining value. Compared with conventional sandstone reservoirs with high porosity, high permeability, and simple pore structure, tight sandstone reservoirs have complex pore structure and complex elastic parameter influence.

[0003] At present, a single parameter is used to identify reservoirs. However, due to the strong nonlinear characteristics of porosity and permeability of tight sandstone reservoirs, the weak ability of elastic parameters to identify fluids, and the influence of multiple factors such as clay mineral composition, pore structure and physical properties on electrical parameter identification of reservoirs, the use of a single parameter to identify reservoirs has great limitations. Summary of the invention

[0004] The present invention provides a method for identifying a tight sandstone reservoir and adopts a comprehensive electrical and elastic combined technology to identify the reservoir, which can more accurately and quantitatively predict reservoir parameters and further improve the accuracy of physical property parameters used for oil and gas detection.

[0005] The present invention provides a method for identifying a tight sandstone reservoir, comprising:

[0006] The temperature, pressure and mineralization conditions corresponding to the formation depth are simulated, and the saturated density ρ and porosity of each dense sandstone sample are obtained through reservoir physical property experimental measurement.

[0007] At different fluid water saturation S w Under the condition of combining with the core measuring instrument, the elastic wave longitudinal wave velocity V of each dense sandstone sample is obtained. p and shear wave velocity V s ;

[0008] By formula The bulk modulus K of the dense sandstone sample was calculated;

[0009] Through the formula μ=ρV s 2 (2) Calculate the shear modulus μ of the dense sandstone sample;

[0010] In different fluids at different fluid water saturation S w Under the condition of 1.5 ℃ and 1.5 ℃, the complex resistivity curve of each dense sandstone sample is obtained by combining with the core measuring instrument, and the zero-frequency resistivity ρ of the dense sandstone sample is extracted by inversion using the MGEMTIP model through the complex resistivity curve. 0 and polarizability η;

[0011] By the porosity The bulk modulus K is used to establish a bulk modulus equivalent model of the rock skeleton using the Reuss-Vigot average model;

[0012] By the porosity The shear modulus μ is used to establish a shear modulus equivalent model of the rock skeleton using the Reuss-Vigot average model;

[0013] By the porosity The zero-frequency resistivity ρ 0 The electrical model of induced polarization parameters and physical parameters is constructed with the polarizability η; wherein the resistivity, porosity and water saturation satisfy the Archie relationship: Among them, ρ w is the pore fluid resistivity, F is the formation factor, m and n are the cementation factor and water saturation index, respectively;

[0014] Through the formula σ s =η / ρ 0 (3) Calculate the surface conductivity σ of the dense sandstone sample s ;

[0015] According to Archie's formula, the surface conductance σ is derived s and porosity Water saturation S w The relationship between and is used to obtain the surface conductance model;

[0016] The porosity and water saturation S w According to the preset requirements, the reservoir parameters are divided equally and gridded to form a grid composed of porosity. and water saturation S w The grid composed of

[0017] For the porosity corresponding to each grid node in the grid and water saturation S w The bulk modulus K and shear modulus μ are calculated using formulas (1)-(2), and the zero-frequency resistivity ρ is determined by inversion using the MGEMTIP model. 0 and polarizability η, and the surface conductivity σ is obtained according to formula (3): s , so that for each grid node corresponding to the reservoir parameter data The corresponding elastic parameters (K, μ) and electrical parameters (ρ, σ) are calculated and determined using the bulk modulus equivalent model, the shear modulus equivalent model, the electrical model and the surface conductivity model. S ), the grid corresponding to the reservoir parameters is associated with the electrical and elastic parameters to obtain a reservoir analysis version based on the electrical and elastic parameters;

[0018] The measured data are input into the reservoir analysis volume plate for reservoir parameter analysis.

[0019] Specifically, the bulk modulus equivalent model is Among them, K fl ,K 0 are the bulk moduli of fluid and mineral respectively, and α is the weight coefficient.

[0020] Specifically, the shear modulus equivalent model is: Among them, μ fl , μ 0 are the shear moduli of fluid and mineral respectively, and α is the weight coefficient.

[0021] Specifically, the surface conductance model is Among them, σ w is the conductivity of water, and β is the correlation coefficient.

[0022] Specifically, after obtaining the reservoir analysis data based on electrical and elastic parameters, the method further includes:

[0023] The zero-frequency resistivity ρ obtained by the inversion 0 The polarizability η is projected onto the reservoir analysis plate to correct the basic parameters of the plate, and the plate is reconstructed according to the corrected parameters.

[0024] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0025] Various physical property measurements were conducted on the rock samples of tight sandstone. Based on the measured data, the variation patterns of various rock parameters were analyzed, and the rock induced polarization parameters were extracted based on the MGEMTIP model inversion. The relationship between rock electrical, elastic and physical parameters was constructed, and an electrical-elastic rock physics model was established. The measured data was then put into the model for reservoir parameter analysis, which can more accurately predict reservoir parameters quantitatively and further improve the accuracy of physical parameters used for oil and gas detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A flow chart of a method for identifying a tight sandstone reservoir provided by an embodiment of the present invention;

[0027] Figure 2 An inversion curve of the MGEMTIP model in the method for identifying a tight sandstone reservoir provided in an embodiment of the present invention;

[0028] Figure 3 A resistivity-bulk modulus measurement plate at normal temperature and pressure in a method for identifying a tight sandstone reservoir provided in an embodiment of the present invention;

[0029] Figure 4 A high temperature and high pressure resistivity-bulk modulus measurement plate in a method for identifying a tight sandstone reservoir provided in an embodiment of the present invention;

[0030] Figure 5 A surface conductivity-bulk modulus measurement plate at normal temperature and pressure in a method for identifying a tight sandstone reservoir provided in an embodiment of the present invention;

[0031] Figure 6 A high temperature and high pressure surface conductivity-bulk modulus measurement plate in a method for identifying a tight sandstone reservoir provided in an embodiment of the present invention;

[0032] Figure 7 A resistivity-shear modulus measurement plate at normal temperature and pressure in a method for identifying a tight sandstone reservoir provided in an embodiment of the present invention;

[0033] Figure 8 A high temperature and high pressure resistivity-shear modulus measurement plate in a method for identifying a tight sandstone reservoir provided in an embodiment of the present invention;

[0034] Fig. 9 A surface conductivity-shear modulus measurement plate at normal temperature and pressure in a method for identifying a tight sandstone reservoir provided in an embodiment of the present invention;

[0035] Fig.10 A high temperature and high pressure surface conductivity-shear modulus measurement plate in a method for identifying a tight sandstone reservoir provided in an embodiment of the present invention;

[0036] Fig.11 The resistivity-bulk modulus measurement plate under different conditions in the method for identifying a tight sandstone reservoir provided in an embodiment of the present invention;

[0037] Fig.12 The surface conductivity-bulk modulus measurement plate under different conditions in the method for identifying tight sandstone reservoirs provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The embodiment of the present invention provides a method for identifying a tight sandstone reservoir, and adopts a comprehensive electrical and elastic combined technology to identify the reservoir, which can more accurately and quantitatively predict reservoir parameters and further improve the accuracy of physical parameters used for oil and gas detection.

[0039] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0040] like Figure 1 As shown, the method for identifying a tight sandstone reservoir provided by an embodiment of the present invention includes:

[0041] Step S110: Simulate the temperature, pressure and mineralization conditions corresponding to the formation depth, and obtain the saturated density ρ and porosity of each dense sandstone sample through reservoir physical property experimental measurement.

[0042] Step S120: At different fluid water saturation S w Under the condition of combining with the core measuring instrument, the elastic wave longitudinal wave velocity V of each dense sandstone sample is obtained. p and shear wave velocity V s , unit is m / s;

[0043] Step S130: By formula The bulk modulus K of the dense sandstone sample is calculated in MPa;

[0044] Step S140: Using the formula μ=ρV s 2 (2) Calculate the shear modulus μ of the dense sandstone sample, in MPa;

[0045] Step S150: In different fluids at different fluid water saturation S w Under the condition of the core measuring instrument, the complex resistivity curve (amplitude and phase under different frequency conditions) of each dense sandstone sample is obtained. The complex resistivity curve changes with the frequency, in which the real part represents the actual resistance of the rock to the current, and the imaginary part reflects the response of the rock to the electromagnetic field. The zero-frequency resistivity ρ of the dense sandstone sample is extracted by inversion of the complex resistivity curve using the MGEMTIP model. 0 and polarizability η;

[0046] In this embodiment, the core measuring instrument is an Autolab1000 multifunctional core measuring instrument.

[0047] Specifically, the MGEMTIP model is combined to perform model inversion. The inversion process suppresses the low-frequency polarization caused by the electrode material and obtains the corresponding IP parameters (zero-frequency resistivity ρ 0 and polarizability ),like Figure 2 shown.

[0048] Among them, the MGEMTIP model is:

[0049]

[0050]

[0051] c l =c l

[0052] Among them, ρ 0 is the zero-frequency resistivity, ρe is the overall complex resistivity of the inhomogeneous medium, ρ e0 The resistivity of the background medium without the disturbance body, ρ l is the resistivity of the lth disturbance body, in Ω·m; N is the number of disturbance bodies; ω is the angular frequency, in rad / s; f is the frequency, in Hz; f l The volume fraction of the lth disturbance body in the sample; a l is the spherical radius of the lth disturbance body, in m; is the surface polarization parameter, in units of Relaxation time τ l Indicates how fast the polarization process reaches a steady state, in seconds.

[0053] Step S160: Porosity The bulk modulus equivalent model of rock skeleton is established by using the Reuss-Vigot average model and bulk modulus K. Specifically, the bulk modulus equivalent model is: Among them, K fl, K 0 are the bulk moduli of fluid and mineral respectively, in MPa; α is the weight coefficient, which is obtained by combining the measured data.

[0054] Step S170: Porosity The shear modulus equivalent model of rock skeleton is established by using the Reuss-Vigot average model and shear modulus μ; specifically, the shear modulus equivalent model is: Among them, μ fl , μ 0 are the shear moduli of fluid and mineral respectively, in MPa; α is the weight coefficient.

[0055] Step S180: Porosity Zero frequency resistivity ρ 0 The electrical model of induced polarization parameters and physical parameters is constructed by using the polarizability η; the resistivity, porosity and water saturation satisfy the Archie relationship: Among them, ρ w is the pore fluid resistivity, which is controlled by experiments, F is the formation factor, m and n are the cementation factor and water saturation index, respectively, which are determined by fitting the experimental data;

[0056] Step S190: By formula σ s =η / ρ 0 (3) Calculate the surface conductivity σ of the dense sandstone sample s , unit is S / m 2 ;

[0057] Step S200: According to Archie's formula, derive the surface conductance σ sand porosity Water saturation S w The relationship between and is used to obtain the surface conductivity model. Specifically, the surface conductivity model is Among them, σ w is the electrical conductivity of water, in S / m; β is the correlation coefficient, which is determined by fitting the experimental data.

[0058] Step S210: Porosity and water saturation S w According to the preset requirements, the reservoir parameters are divided equally and gridded to form a grid composed of porosity. and water saturation S w The mesh composed of The range of variation is 0-0.54, divided equally into intervals of 0.06, and its equipotential lines are represented by solid lines; water saturation S w The range of variation is 0.1-1, which is divided into a geometric series with a common ratio of 0.3162. The equipotential lines are represented by dotted lines. and water saturation S w The intersection points of the equipotential lines are the grid nodes, thus forming a grid composed of porosity and water saturation.

[0059] Step S220: For each mesh node in the mesh, the porosity corresponding to the mesh node is and water saturation S w The bulk modulus K and shear modulus μ are calculated using formulas (1)-(2), and the zero-frequency resistivity ρ is determined by inversion using the MGEMTIP model. 0 and polarizability η, and the surface conductivity σ is obtained according to formula (3): s , so that for each grid node corresponding to the reservoir parameter data The corresponding elastic parameters (K, μ) and electrical parameters (ρ, σ) were calculated and determined using the bulk modulus equivalent model, shear modulus equivalent model, electrical model and surface conductivity model. S ), the grid corresponding to the reservoir parameters is associated with the electrical and elastic parameters to obtain a reservoir analysis version based on the electrical and elastic parameters;

[0060] Step S230: input the measured data into the reservoir analysis plate to perform reservoir parameter analysis.

[0061] In order to improve the recognition accuracy of reservoir parameters, after obtaining the reservoir analysis volume based on electrical and elastic parameters, it also includes:

[0062] The zero-frequency resistivity ρ obtained by inversion 0The polarizability η is projected onto the reservoir analysis plate to calibrate the plate basic parameters, and the plate is reconstructed based on the calibrated parameters. Based on the calibrated plate, combined with the projection position of the data on the plate, the data change law is analyzed to effectively identify the reservoir.

[0063] In this embodiment, the constructed measurement plates include the resistivity and bulk modulus measurement plate under different temperature and pressure conditions, the resistivity and shear modulus measurement plate, the surface conductivity and bulk modulus measurement plate, and the surface conductivity and shear modulus measurement plate. Among them, the relationship between resistivity and bulk modulus under normal temperature and pressure conditions is as follows: Figure 3 As shown in the figure, it indicates that when the formation pressure is relatively low, the greater the rock porosity, the higher the water saturation, the lower the resistivity, the lower the oil and gas content, and the lower the formation storage capacity. The relationship between resistivity and bulk modulus under high temperature and high pressure conditions is shown in the figure. Figure 4 As shown, compared Figure 3 It can be seen that under the influence of pressure and temperature, the resistivity of rock decreases. This is because under the action of pressure, the porosity of rock becomes smaller, and under the action of temperature, the mobility of conductive ions in the pore fluid is enhanced, making the rock more conductive and the resistivity decrease. The relationship between surface conductivity and bulk modulus under normal temperature and pressure conditions is shown in the figure below: Figure 5 As shown in the figure, the greater the porosity, the higher the saturation, and the lower the rock surface conductivity; the relationship between surface conductivity and bulk modulus under high temperature and high pressure conditions is shown in Figure 6 As shown, compared Figure 5 It can be seen that the greater the porosity, the higher the saturation, and the lower the rock surface conductivity. The relationship between resistivity and shear modulus under normal temperature and pressure conditions is shown in the figure below: Figure 7 As shown in Figure 1, an increase in porosity usually leads to a decrease in shear modulus, because more pores weaken the deformation capacity of the rock. At the same time, in a water-saturated state, an increase in porosity will reduce resistivity; the relationship between resistivity and shear modulus under high temperature and high pressure conditions is shown in Figure 1. Figure 8 As shown, Figure 7 By comparison, it is found that under high temperature and high pressure environment, the increase of shear modulus is mainly affected by pressure, while the decrease of resistivity is mainly affected by temperature. The relationship between surface conductivity and shear modulus under normal temperature and pressure conditions is shown in the figure below: Fig. 9 As shown in Figure 2, the porosity increases, the saturation increases, the rock shear modulus decreases, and the surface conductivity increases. The relationship between surface conductivity and shear modulus under high temperature and high pressure conditions is shown in Figure 2. Fig.10 As shown, with the increase of pressure, the compaction effect of rock is obvious and the shear modulus becomes larger; with the increase of temperature, the resistivity of rock decreases, but the polarizability increases, so the overall surface conductivity increases.

[0064] In addition, in this embodiment, the rock cementation factor and saturation index are determined by data fitting. Under normal temperature and pressure conditions, the cementation factor is m=1.8326, and the saturation index is n=2; under high temperature and high pressure conditions, the cementation factor is m=1.31, and the saturation index is n=3; the bulk modulus of the pore fluid is K fl =1.8GPa, shear modulus is μ fl =0.1GPa; the bulk modulus of rock minerals is K 0 =37GPa, shear modulus is μ 0 =33GPa;σ w =2S / m. Based on this, the measured data was projected onto the measurement board, and it was found that the rock samples with high resistivity and low polarizability have better oil content. Fig.11 and Fig.12 As shown, the area with relatively good oil content is marked with a wireframe.

[0065] An embodiment of the present invention provides a method for determining reservoir parameters by using elastic and electrical rock physical quantities of sandstone. The method first obtains the complex resistivity amplitude, acoustic wave velocity, etc. of the rock sample under different temperature and pressure conditions, and then uses the MGEMTIP model to invert and extract the induced polarization parameters of the dense sandstone sample. By establishing an electrical-elastic rock physical model, the reservoir parameters can be more accurately and quantitatively predicted, further improving the accuracy of the physical parameters used for oil and gas detection.

[0066] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented 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.

[0067] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0068] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0069] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0070] The parts not described in detail in the embodiments of the present invention are all known technologies to those skilled in the art. Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A method for identifying a tight sandstone reservoir, characterized in that: include: The temperature, pressure and mineralization conditions corresponding to the formation depth are simulated, and the saturated density ρ and porosity of each dense sandstone sample are obtained through reservoir physical property experimental measurement. At different fluid water saturation S w Under the condition of combining with the core measuring instrument, the elastic wave longitudinal wave velocity V of each dense sandstone sample is obtained. p and shear wave velocity V s ; By formula The bulk modulus K of the dense sandstone sample was calculated; By formula The shear modulus μ of the dense sandstone sample is calculated; In different fluids at different fluid water saturation S w Under the conditions, the complex resistivity curves of the dense sandstone samples are obtained one by one by combining with the core measuring instrument, and the zero-frequency resistivity ρ0 and polarizability η of the dense sandstone samples are extracted by inversion of the complex resistivity curves using the MGEMTIP model; By the porosity The bulk modulus K is used to establish a bulk modulus equivalent model of the rock skeleton using the Reuss-Vigot average model; By the porosity The shear modulus μ is used to establish a shear modulus equivalent model of the rock skeleton using the Reuss-Vigot average model; By the porosity The zero-frequency resistivity ρ0 and the polarizability η construct an electrical model of induced polarization parameters and physical property parameters; wherein the resistivity, porosity and water saturation satisfy the Archie relationship: Among them, ρ w is the pore fluid resistivity, F is the formation factor, m and n are the cementation factor and water saturation index, respectively; Through the formula σ s =η / ρ0(3) The surface conductivity σ of the dense sandstone sample is calculated s ; According to Archie's formula, the surface conductance σ is derived s and porosity Water saturation S w The relationship between and is used to obtain the surface conductance model; The porosity and water saturation S w According to the preset requirements, the reservoir parameters are divided equally and gridded to form a grid composed of porosity. and water saturation S w The grid composed of For the porosity corresponding to each grid node in the grid and water saturation S w The bulk modulus K and shear modulus μ are calculated using formulas (1)-(2), the zero-frequency resistivity ρ0 and polarizability η are determined by inversion using the MGEMTIP model, and the surface conductivity σ is obtained according to formula (3): s , so that for each grid node corresponding to the reservoir parameter data ( S w ), and the corresponding elastic parameters (K, μ) and electrical parameters (ρ, σ) are calculated and determined using the bulk modulus equivalent model, the shear modulus equivalent model, the electrical model and the surface conductivity model. S ), the grid corresponding to the reservoir parameters is associated with the electrical and elastic parameters to obtain a reservoir analysis version based on the electrical and elastic parameters; The measured data are input into the reservoir analysis volume plate for reservoir parameter analysis.

2. The method for identifying a tight sandstone reservoir according to claim 1, characterized in that: The bulk modulus equivalent model is: Among them, K fl , K0 are the bulk moduli of fluid and mineral respectively, and α is the weight coefficient.

3. The method for identifying a tight sandstone reservoir according to claim 1, characterized in that: The shear modulus equivalent model is: Among them, μ fl , μ0 are the shear moduli of fluid and mineral respectively, and α is the weight coefficient.

4. The method for identifying a tight sandstone reservoir according to claim 1, characterized in that: The surface conductance model is Among them, σ w is the conductivity of water, and β is the correlation coefficient.

5. The method for identifying a tight sandstone reservoir according to any one of claims 1 to 4, characterized in that: After obtaining the reservoir analysis data based on electrical and elastic parameters, the method further includes: The zero-frequency resistivity ρ0 and polarizability η obtained by the inversion are projected onto the reservoir analysis plate to correct the plate basic parameters, and the plate is reconstructed according to the corrected parameters.

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