A reservoir permeability prediction method and system based on formation tectonic stress

Abstract

This invention provides a method and system for predicting reservoir permeability based on formation tectonic stress. The method includes: acquiring reservoir rock mechanics test data, formation test data, core permeability test data, fracturing operation data, and well logging data; constructing an effective stress model using the formation test data and well logging data to calculate formation pressure; calculating various rock mechanics parameters and performing dynamic-static conversion of Poisson's ratio using the reservoir rock mechanics test data and well logging data; obtaining the horizontal maximum principal stress based on the Huang model, using the fracturing operation data and the obtained rock mechanics parameters; and establishing a fitting relationship between the horizontal maximum principal stress and core permeability to predict permeability. The system can implement the method described above. The advantage of this invention is that the obtained carbonate rock permeability has higher accuracy.

Description

Technical Field

[0001] This invention relates to the field of formation fluid seepage technology, specifically to a method and system for predicting reservoir permeability based on formation tectonic stress. Background Technology

[0002] In oil and gas reservoir evaluation, accurate calculation of the permeability of carbonate formations is crucial for ensuring oil and gas production and recovery. Tectonic stress profoundly affects the microscopic pore-throat structure of rocks, thereby influencing the physical properties and fluid flow characteristics of reservoirs with complex structures. Traditional permeability calculation methods often neglect the impact of tectonic stress on rock flow properties, leading to significant discrepancies between calculated results and actual conditions.

[0003] Currently widely used permeability calculation models focus on the analysis of well logging data, lacking a comprehensive consideration of rock mechanics and regional tectonic stress. However, in the development of carbonate reservoirs, fracture formation plays a crucial role in reservoir permeability. Due to their planar development characteristics, fractures are significantly affected by stress; even slight changes in formation tectonic stress can alter the physical and permeability properties of carbonate reservoirs. If permeability models that do not consider the influence of formation tectonic stress are still used, the calculated permeability results will deviate significantly from reality. Therefore, providing a reservoir permeability prediction method and system based on formation tectonic stress is of great significance. Summary of the Invention

[0004] The purpose of this invention is to address at least one of the aforementioned shortcomings of the existing technology. For example, one objective of this invention is to provide a reservoir permeability prediction method based on formation tectonic stress that can ensure the reliability of permeability evaluation in complex oil and gas reservoirs. Another objective of this invention is to provide a reservoir permeability prediction system based on formation tectonic stress that can achieve high-precision permeability calculation.

[0005] To achieve the above objectives, this invention provides a method for predicting reservoir permeability based on formation tectonic stress. The method includes: acquiring reservoir rock mechanics test data, formation test data, core permeability test data, fracturing operation data, and well logging data; constructing an effective stress model using the formation test data and well logging data to calculate formation pressure; calculating various rock mechanics parameters and performing dynamic-static conversion of Poisson's ratio using the reservoir rock mechanics test data and well logging data; obtaining the minimum and maximum horizontal principal stresses based on the Huang model, using the fracturing operation data and the obtained rock mechanics parameters; and establishing a fitting relationship between the maximum horizontal principal stress and core permeability to predict permeability.

[0006] According to one or more exemplary embodiments of one aspect of the present invention, the reservoir rock mechanical test data may include the reservoir rock Poisson's ratio and P-wave and S-wave velocities.

[0007] According to one or more exemplary embodiments of one aspect of the present invention, the core permeability test data may include core permeability.

[0008] According to one or more exemplary embodiments of one aspect of the present invention, the logging data may include density, P-wave transit time, and S-wave transit time.

[0009] According to one or more exemplary embodiments of one aspect of the present invention, the formation test data may include formation pressure.

[0010] According to one or more exemplary embodiments of one aspect of the present invention, the fracturing construction data may include formation fracturing pressure, formation re-tensioning pressure, and formation tensile strength.

[0011] According to one or more exemplary embodiments of one aspect of the present invention, the calculation of formation pressure by constructing an effective stress model may include: calculating the overlying formation pressure based on the average density of the formation without logging density, the cumulative vertical depth of the formation without logging density, the logging sampling depth interval, and the logging density; the difference between the overlying formation pressure and the formation pressure is the effective stress; fitting the effective stress with the ratio of P-wave and S-wave velocities obtained from reservoir rock mechanics test data to establish an effective stress model; and calculating the formation pressure based on the effective stress model.

[0012] According to one or more exemplary embodiments of one aspect of the present invention, the calculation of overlying formation pressure may include:

[0013]

[0014] In the formula, σ v The overlying strata pressure is expressed in MPa; g represents gravitational acceleration in N / Kg; ρ represents the pressure of the overlying strata. a This represents the average density of the formation without well logging density, in g / cm³. 3 H a ρ represents the cumulative vertical depth of the formation without logging density, in meters (m). i This indicates the density measured in well logging, in g / cm³. 3 H i The sampling depth interval is represented in meters (m); n represents the number of sampling intervals from the formation termination depth without logging density to the target depth.

[0015] The effective stress is fitted to the ratio of the longitudinal and transverse wave velocities to obtain the following relationship:

[0016] σ = a + b * (DTS / DTC);

[0017] In the formula, σ e The effective stress is expressed in MPa; DTS represents the transverse wave transit time in μs / ft; DTC represents the longitudinal wave transit time in μs / ft; a and b are coefficients.

[0018] The calculation of formation pressure includes:

[0019] P p =σ v -σ e ;

[0020] In the formula, σ e σ represents the effective stress, in MPa; v P represents the overlying formation pressure, in MPa; p This represents formation pressure, expressed in MPa.

[0021] According to one or more exemplary embodiments of one aspect of the present invention, the Poisson's ratio dynamic-static conversion may include: calculating the dynamic Poisson's ratio based on the P-wave and S-wave transit time obtained from well logging data; and fitting the dynamic Poisson's ratio with the static Poisson's ratio obtained from rock mechanics test data to achieve the dynamic-static conversion of Poisson's ratio.

[0022] According to one or more exemplary embodiments of one aspect of the present invention, the calculation of the dynamic Poisson ratio may include:

[0023] μ d = (0.5 × DTS) 2 -DTC 2 ) / (DTS 2 -DTC 2 );

[0024] In the formula, μ d The dynamic Poisson's ratio is dimensionless; DTS represents the transverse wave time difference, in μs / ft; DTC represents the longitudinal wave time difference, in μs / ft.

[0025] The relationship between the dynamic and static transformation of Poisson's ratio is as follows:

[0026] μs=a×μ d +b;

[0027] In the formula, μ s μd represents the static Poisson ratio, which is dimensionless; μd represents the dynamic Poisson ratio, which is dimensionless; a and b are both coefficients.

[0028] According to one or more exemplary embodiments of one aspect of the present invention, the rock mechanical parameters may include Poisson's ratio, reservoir bulk modulus, skeleton bulk modulus, and porosity elastic coefficient.

[0029] According to one or more exemplary embodiments of one aspect of the present invention, the calculation of the rock mechanical parameters may include:

[0030] The reservoir bulk modulus calculation includes calculations based on the P-wave transit time, S-wave transit time, and density of the reservoir obtained from well logging data:

[0031]

[0032] In the formula, K b DTS represents reservoir bulk modulus, MPa; DTC represents shear wave transit time, μs / ft; ρ represents logging density, g / cm³. 3 β represents the unit conversion factor, which is dimensionless.

[0033] The calculation of the bulk modulus of the rock skeleton includes calculations based on the P-wave transit time, S-wave transit time, and density of the rock skeleton obtained from well logging data:

[0034]

[0035] In the formula, K ma DTS represents the bulk modulus of the skeleton, in MPa; ma DTC represents the frame shear wave time difference, in μs / ft; ma The longitudinal wave time difference (LWD) is expressed in μs / ft; ρ represents the time difference between the longitudinal and lateral waves ma This represents the skeletal density, in g / cm³. 3 β represents the unit conversion factor, which is dimensionless.

[0036] The calculation of the porosity elastic coefficient includes calculations based on the reservoir bulk modulus and the framework bulk modulus:

[0037]

[0038] In the formula, η represents the porosity elastic coefficient, which is dimensionless; K b Represents the reservoir bulk modulus, in MPa; K ma This represents the bulk modulus of the skeleton, in MPa.

[0039] According to one or more exemplary embodiments of one aspect of the present invention, the minimum horizontal principal stress and the maximum horizontal principal stress may include: the minimum horizontal principal stress being the formation re-tension pressure in the fracturing operation data; and the maximum horizontal principal stress being calculated based on the minimum horizontal principal stress, the porosity coefficient, the formation pressure, and the formation fracturing pressure and formation tensile strength in the fracturing operation data.

[0040] According to one or more exemplary embodiments of one aspect of the present invention, calculating the maximum horizontal principal stress may include:

[0041] σ H =3σ h -ηP p -P f +S t ;

[0042] In the formula, σ h =P s ;σ hσ represents the minimum horizontal principal stress, in MPa; H P represents the maximum horizontal principal stress, in MPa. s P represents the formation retensile pressure, MPa; η represents the porosity coefficient, dimensionless; p P represents formation pressure, in MPa; f Represents formation fracture pressure, MPa; S t This represents the tensile strength of the formation, expressed in MPa.

[0043] According to one or more exemplary embodiments of one aspect of the present invention, establishing a fitting relationship between the maximum horizontal principal stress and permeability may include:

[0044]

[0045] In the formula, K i The permeability measured in the core is expressed in mD; σ H This represents the maximum horizontal principal stress, in MPa; a, b, and c are coefficients.

[0046] Another aspect of the present invention provides a reservoir permeability prediction system based on formation tectonic stress. The system may include a data unit, a first calculation unit, a second calculation unit, a third calculation unit, and a prediction unit. The data unit is connected to the first, second, third, and prediction units respectively; the third calculation unit is connected to the first and second calculation units; and the third calculation unit is connected to the prediction unit. The data unit is configured to acquire reservoir rock mechanics test data, formation test data, core permeability test data, fracturing operation data, and well logging data. The first calculation unit is configured to construct an effective stress model using the formation test data and well logging data to calculate formation pressure. The second calculation unit is configured to calculate various rock mechanics parameters and perform dynamic-static conversion of Poisson's ratio using the reservoir rock mechanics test data and well logging data. The third calculation unit is configured to obtain the minimum and maximum horizontal principal stresses based on the Huang model, using fracturing operation data and the obtained rock mechanics parameters. The prediction unit is configured to establish a fitting relationship between the maximum horizontal principal stress and core permeability to predict permeability.

[0047] Compared with the prior art, the beneficial effects of the present invention include at least one of the following:

[0048] (1) The method proposed in this invention can ensure the reliability of permeability evaluation of complex oil and gas reservoirs and improve the efficiency of oil and gas reservoir exploitation.

[0049] (2) The method proposed in this invention systematically realizes high-precision calculation of permeability of complex reservoirs under the condition of considering tectonic stress.

[0050] (3) The method of the present invention has higher accuracy in calculating the permeability of carbonate rocks under complex tectonic stress conditions, and fully considers various uncertainties in actual engineering such as formation heterogeneity and reservoir stress sensitivity. The calculation error can be reduced by 10% to 20% compared with the existing method, which can improve the reliability of carbonate rock permeability calculation results. Attached Figure Description

[0051] The above and other objects and features of the present invention will become clearer from the following description taken in conjunction with the accompanying drawings, in which:

[0052] Figure 1 A schematic flowchart of the reservoir permeability prediction method based on formation tectonic stress of the present invention is shown.

[0053] Figure 2 The cross plot of P-wave velocity ratio-effective stress for Example 1 is shown;

[0054] Figure 3 The dynamic-static transformation diagram of Poisson's ratio for Example 1 is shown;

[0055] Figure 4 The horizontal maximum principal stress-log permeability cross plot of Example 1 is shown;

[0056] Figure 5 The calculated permeability-core permeability verification diagram for Example 1 is shown;

[0057] Figure 6 A schematic diagram of the reservoir permeability prediction method based on tectonic stress of the present invention is shown. Detailed Implementation

[0058] In the following, a reservoir permeability prediction method and system based on formation tectonic stress according to the present invention will be described in detail with reference to the accompanying drawings and exemplary embodiments.

[0059] In the description of this application, it should be understood that the terms "first," "second," "third," etc., are used merely for convenience of description and distinction, and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first," "second," "third," etc., may explicitly or implicitly include one or more of that feature.

[0060] Exemplary Example 1

[0061] This exemplary embodiment provides a method for predicting reservoir permeability based on tectonic stress.

[0062] like Figure 1As shown, the reservoir permeability prediction method based on formation tectonic stress mainly includes: acquiring reservoir rock mechanics test data, formation test data, core permeability test data, fracturing operation data, and well logging data; constructing an effective stress model using formation test data and well logging data to calculate formation pressure; calculating various rock mechanics parameters using reservoir rock mechanics test data and well logging data; obtaining the minimum and maximum horizontal tectonic stress coefficients based on the Huang model, using fracturing operation data and the obtained rock mechanics parameters, and calculating the maximum horizontal principal stress of the formation by combining well logging data; and establishing an optimal fitting relationship between the maximum horizontal principal stress and core test permeability to achieve permeability prediction.

[0063] Specifically, the reservoir permeability prediction method based on formation tectonic stress in this exemplary embodiment may include the following steps:

[0064] S1. Obtain reservoir rock mechanics test data, formation test data, core permeability test data, fracturing operation data, and well logging data.

[0065] S2. Construct an effective stress model using formation test data and well logging data to calculate formation pressure; use reservoir rock mechanics test data and well logging data to calculate various rock mechanics parameters and perform dynamic-static conversion of Poisson's ratio.

[0066] S3. Based on the Huang model, using fracturing construction data and obtained rock mechanics parameters, the minimum and maximum horizontal tectonic stress coefficients are obtained, and the maximum horizontal principal stress of the formation is calculated by combining well logging data.

[0067] S4. Establish a fitting relationship between the maximum horizontal principal stress and the core permeability to predict permeability.

[0068] In this exemplary embodiment, obtaining reservoir rock mechanical test data in step S1 may specifically include:

[0069] Stress and strain tests were performed on reservoir core samples to obtain data such as Poisson's ratio and P-wave and S-wave velocities. Formation test data specifically included formation pressure (pressure at formation test points). Core permeability test data specifically included core permeability data. Fracturing operation data specifically included fracturing operation curves. Well logging data specifically included density, P-wave transit time, and S-wave transit time.

[0070] Furthermore, fracturing operation data may include fracturing operation curves. The formation fracture pressure can be obtained by reading the peak value of the first fracturing curve, and the formation re-tension pressure can be obtained by reading the peak value of the second fracturing curve. The formation tensile strength can be obtained by subtracting the formation re-tension pressure from the formation fracture pressure.

[0071] In this exemplary embodiment, step S2, constructing an effective stress model to calculate formation pressure, may include: calculating the overlying formation pressure based on the average density of the formation section without logging density, the cumulative vertical depth of the formation section without logging density, the logging sampling depth interval, and the logging density; calculating the effective stress based on the overlying formation pressure and the formation pressure from formation testing data; fitting the effective stress with the P-wave and S-wave velocity ratio obtained from reservoir rock mechanics testing data to establish an effective stress model; and calculating the formation pressure based on the effective stress model. It should be noted that most wells lack formation testing data and only have test point data. To obtain the formation pressure for the entire well section, a calculation model needs to be established, and the formation pressure is calculated using the effective stress model.

[0072] Specifically, constructing an effective stress model to calculate formation pressure may include the following:

[0073] (1) Calculate the pressure of the overlying strata:

[0074]

[0075] In the formula, σ v The overlying strata pressure is expressed in MPa; g represents gravitational acceleration in N / Kg; ρ represents the pressure of the overlying strata. a This represents the average density of the formation without well logging density, in g / cm³. 3 H a ρ represents the cumulative vertical depth of the formation without logging density, in meters (m). i This indicates the density measured in well logging, in g / cm³. 3 H i represents the well logging sampling depth interval, in meters; n represents the number of sampling intervals from the formation termination depth without logging density to the target depth, in units.

[0076] (2) Based on the formation test data, obtain the formation pressure data and calculate the effective stress using the following formula:

[0077] σ e =σ v -P p .

[0078] In the formula, σ e σ represents the effective stress, in MPa; v P represents the overlying formation pressure, in MPa; p This represents formation pressure, expressed in MPa.

[0079] (3) By fitting the effective stress to the ratio of P-wave to S-wave velocity, the following relationship is obtained:

[0080] σ e = a + b * (DTS / DTC).

[0081] In the formula, σ edenoted by , effective stress (MPa); DTS represents transverse wave transit time (μs / ft); DTC represents longitudinal wave transit time (μs / ft); a and b are coefficients.

[0082] (4) Establish an effective stress model based on the P-wave and S-wave velocity ratio. Calculate the formation pressure throughout the logging section using the following formula based on the calculation results of the effective stress model:

[0083] P p =σ v -σ e .

[0084] In the formula, σ e σ represents the effective stress, in MPa; v P represents the overlying formation pressure, in MPa; p This represents formation pressure, expressed in MPa.

[0085] In this exemplary embodiment, the dynamic-static conversion of Poisson's ratio may include: calculating the dynamic Poisson's ratio based on the P-wave and S-wave transit time obtained from well logging data; and fitting the dynamic Poisson's ratio with the static Poisson's ratio obtained from rock mechanics test data to achieve the dynamic-static conversion of Poisson's ratio, thereby obtaining the relationship between the dynamic Poisson's ratio and the static Poisson's ratio.

[0086] Specifically, implementing the dynamic-static transformation of Poisson's ratio can include:

[0087] (1) Based on the P-wave and S-wave time difference, the dynamic Poisson's ratio is calculated using the following formula:

[0088] μ d = (0.5 × DTS) 2 -DTC 2 ) / (DTS 2 -DTC 2 ).

[0089] In the formula, μ d The dynamic Poisson ratio is dimensionless; DTS represents the transverse wave time difference in μs / ft; and DTC represents the longitudinal wave time difference in μs / ft.

[0090] (2) Based on the static Poisson's ratio obtained from rock mechanics test data, the dynamic and static Poisson's ratios are fitted to obtain the following relationship:

[0091] μ s =a×μ d +b.

[0092] In the formula, μ s μd represents the static Poisson ratio, which is dimensionless; μd represents the dynamic Poisson ratio, which is dimensionless; a and b are both coefficients.

[0093] In this exemplary embodiment, rock mechanical parameters may include Poisson's ratio, reservoir bulk modulus, skeleton bulk modulus, and porosity elastic coefficient.

[0094] Specifically, the calculation of rock mechanics parameters may include the following:

[0095] (1) Calculate the reservoir bulk modulus.

[0096] Based on the P-wave transit time, S-wave transit time, and density of the reservoir obtained from well logging data, the following formula is used for calculation:

[0097]

[0098] In the formula, K b DTS represents reservoir bulk modulus, MPa; DTC represents shear wave transit time, μs / ft; ρ represents logging density, g / cm³. 3 β represents the unit conversion factor, which is dimensionless.

[0099] (2) Calculate the bulk modulus of the skeleton.

[0100] Based on the P-wave transit time, S-wave transit time, and density of the rock skeleton obtained from well logging data, the following formula is used for calculation:

[0101]

[0102] In the formula, K ma DTS represents the bulk modulus of the skeleton, in MPa; ma DTC represents the frame shear wave time difference, in μs / ft; ma The longitudinal wave time difference (LWD) is expressed in μs / ft; ρ represents the time difference between the longitudinal and lateral waves ma This represents the skeletal density, in g / cm³. 3 β represents the unit conversion factor, which is dimensionless.

[0103] (3) Calculate the porosity elastic coefficient.

[0104] The following formula is used to calculate based on the reservoir bulk modulus and the framework bulk modulus:

[0105]

[0106] In the formula, η represents the porosity elastic coefficient, which is dimensionless; K b Represents the reservoir bulk modulus, in MPa; K ma This represents the bulk modulus of the skeleton, in MPa.

[0107] In this exemplary embodiment, in step S3, the minimum horizontal principal stress is the formation re-tension pressure in the fracturing data; the maximum horizontal principal stress can be calculated based on the minimum horizontal principal stress, the porosity coefficient, the formation pressure, and the formation fracturing pressure and formation tensile strength in the fracturing data.

[0108] Specifically, obtaining the minimum and maximum horizontal principal stresses may include:

[0109] (1) Based on fracturing construction data, the minimum horizontal principal stress is calculated using the following formula:

[0110] σ h =P s .

[0111] In the formula, σ h P represents the minimum horizontal principal stress, in MPa. s This represents the formation retension pressure, expressed in MPa.

[0112] (2) Calculate the maximum horizontal principal stress using the following formula:

[0113] σ H =3σ h -ηP p -P f +S t .

[0114] In the formula, σ h σ represents the minimum horizontal principal stress, in MPa; H P represents the maximum horizontal principal stress, in MPa; η represents the porosity coefficient, dimensionless; p P represents formation pressure, in MPa; f Represents formation fracture pressure, MPa; S t This represents the tensile strength of the formation, expressed in MPa.

[0115] In this exemplary embodiment, in step S3, the Huang model:

[0116]

[0117] In the formula, α H α represents the maximum horizontal tectonic stress coefficient, which is dimensionless; h σ represents the minimum horizontal structural stress coefficient, which is dimensionless; H σ represents the maximum horizontal principal stress, in MPa; h P represents the minimum principal stress in MPa; η represents the porosity coefficient, dimensionless; p Represents formation pressure, MPa; μ s σ represents the static Poisson's ratio, which is dimensionless; v This indicates the pressure of the overlying strata, in MPa.

[0118] By obtaining the tectonic stress coefficients that represent the tectonic stress characteristics of the study area, the maximum and minimum horizontal principal stresses can be calculated using the Huang model.

[0119] It should be noted that the tectonic stress coefficient can be regarded as a constant. The maximum and minimum horizontal principal stresses can be estimated using the fracturing construction data of developed wells. The regional tectonic stress coefficients can be calculated by substituting them into the Huang model, which is then used to calculate the maximum horizontal principal stress of new wells. The maximum horizontal principal stress is obtained by calculating the Huang model. The horizontal tectonic stress coefficient mainly indicates that the horizontal principal stress is provided by the horizontal tectonic stress. In the Huang model, the maximum horizontal principal stress is provided not only by the horizontal tectonic stress but also by the strain caused by the pressure of the overlying strata.

[0120] In this exemplary embodiment, establishing an optimal fitting relationship between the maximum horizontal principal stress and the core permeability to predict permeability may include the following:

[0121] By intersecting the maximum horizontal principal stress and permeability at the corresponding depth in the core sample, and fitting the relationship using an exponential decay relationship, the following equation is obtained:

[0122]

[0123] In the formula, K i The permeability measured in the core is expressed in mD; σ H This represents the maximum horizontal principal stress, in MPa; a, b, and c are coefficients.

[0124] Based on the fitting relationship of the horizontal maximum principal stress-permeability model, an optimal regression model is established to predict permeability.

[0125] Exemplary Example 2

[0126] This exemplary embodiment provides a reservoir permeability prediction system based on formation tectonic stress.

[0127] The reservoir permeability prediction system based on tectonic stress can realize the reservoir permeability prediction method based on tectonic stress described in Exemplary Example 1 above.

[0128] The reservoir permeability prediction system based on formation tectonic stress in this exemplary embodiment may include, for example: Figure 6 The data unit, first calculation unit, second calculation unit, third calculation unit, and prediction unit are shown.

[0129] The data unit is connected to the first, second, third, and prediction units, respectively. The third calculation unit is connected to the first and second calculation units, and also to the prediction unit. The data unit is configured to acquire reservoir rock mechanics test data, formation test data, core permeability test data, fracturing operation data, and well logging data. The first calculation unit is configured to use formation test data and well logging data to construct an effective stress model to calculate formation pressure. The second calculation unit is configured to use reservoir rock mechanics test data and well logging data to calculate various rock mechanics parameters and perform dynamic-static conversion of Poisson's ratio. The third calculation unit is configured to use the Huang model, fracturing operation data, and the obtained rock mechanics parameters to obtain the horizontal minimum principal stress and horizontal maximum principal stress. The prediction unit is configured to establish a fitting relationship between the horizontal maximum principal stress and core permeability to predict permeability.

[0130] To better understand the exemplary embodiments of the present invention described above, further explanation is provided below with reference to specific examples.

[0131] Example 1

[0132] The present invention will be further elaborated in detail using a well XX in a carbonate reservoir in the central Sichuan Basin as an example.

[0133] Step 1: Perform stress and strain tests on reservoir core samples to obtain data such as Poisson's ratio and P-wave and S-wave velocities of the reservoir rock.

[0134] The data is shown in Table 1, which contains partial data from stress and strain tests of six core samples from Well XX in the central Sichuan Basin.

[0135] Table 1. Partial data from stress and strain tests of 6 core samples from Well XX.

[0136]

[0137]

[0138] Formation testing and fracturing operations were carried out on the target formations of multiple wells in the study area to obtain data such as formation pressure, formation fracturing pressure, formation re-tensioning pressure, and tensile strength.

[0139] The data shown in Table 2 are part of the formation testing and fracturing data of several developed wells in the central Sichuan Basin.

[0140] Table 2. Partial data on formation testing and fracturing operations of several developed wells in the target layer.

[0141]

[0142] Porosity and permeability data were obtained by conducting porosity and permeability tests on several core samples from the target layer of Well XX in the study area.

[0143] The data is shown in Table 3, which contains partial data on porosity and permeability of several core samples from the target layer of Well XX.

[0144] Table 3. Partial data on porosity and permeability of several core samples from the target layer of Well XX.

[0145] serial number Porosity (%) Permeability (mD) 1 4.63 0.324 2 4.01 0.879 3 1.84 0.003 4 2.89 0.021 5 3.13 0.034 …… …… ……

[0146] Collect logging data from well XX in the study area to obtain data such as density, compensated neutron, P-wave time difference, and S-wave time difference.

[0147] Step 2: Construct an effective stress model using formation test data to calculate formation pressure. Based on the formation pressure data obtained from the formation test data, fit the effective stress to the ratio of P-wave and S-wave velocities, such as... Figure 2 The following relation can be obtained:

[0148]

[0149] In the formula, σ e The effective stress is expressed in MPa; DTS represents transverse wave transit time in μs / ft; and DTC represents longitudinal wave transit time in μs / ft.

[0150] An effective stress model is established by using the ratio of P-wave to S-wave velocity; the dynamic Poisson's ratio is calculated based on the P-wave and S-wave travel time difference.

[0151] Based on the static Poisson's ratio obtained from rock mechanics test data, the dynamic and static Poisson's ratios are fitted together, as follows: Figure 3 The following relationship can be obtained:

[0152] μ s =1.9×μ d +0.3.

[0153] In the formula, μ s μ represents the static Poisson's ratio, which is dimensionless. d This represents the dynamic Poisson's ratio, which is dimensionless.

[0154] Based on logging data such as P-wave transit time, S-wave transit time, and density, the reservoir bulk modulus, framework bulk modulus, and porosity elastic coefficient are calculated.

[0155] Step 3: Based on fracturing operation data, calculate the minimum and maximum horizontal principal stresses. Using the Huang model, calculate the maximum and minimum horizontal tectonic stress coefficients. By analyzing several typical wells in the study area, obtain the tectonic stress coefficients that represent the stratigraphic tectonic stress characteristics of the study area. The maximum and minimum horizontal tectonic stresses can then be calculated using the Huang model.

[0156] Step 4: Calculate the maximum horizontal principal stress using well logging data, establish the optimal fitting relationship with core permeability, and achieve permeability prediction.

[0157] The maximum horizontal principal stress at the corresponding depth in the core sample was intersected with the permeability, and the result was fitted using an exponential decay relationship, such as... Figure 4 The following relation can be obtained:

[0158]

[0159] In the formula, K i The permeability measured in the core is expressed in mD; σ H This represents the maximum horizontal principal stress, expressed in MPa.

[0160] Based on the fitting relationship of the horizontal maximum principal stress-permeability model, an optimal regression model can be established. Permeability is then predicted, and the predicted permeability is verified against core permeability, such as... Figure 5 The relative error is 19.8%. It can be seen that the reservoir permeability prediction method based on tectonic stress of this invention, through comparative analysis with field measured data, shows that this invention has higher accuracy in calculating carbonate rock permeability under complex tectonic stress conditions, thus improving the reliability of carbonate rock permeability calculation results.

[0161] In summary, the beneficial effects include:

[0162] This invention provides a method and system for predicting reservoir permeability based on formation tectonic stress, primarily applied in the field of formation fluid seepage technology. This invention addresses the shortcomings of traditional reservoir permeability evaluation, which often relies solely on borehole logging data while neglecting formation tectonic stress. Furthermore, it addresses the issue that currently used porosity-permeability models are not well-suited for complex or unconventional reservoir structures. By introducing maximum horizontal tectonic stress, a permeability model more suitable for complex and stress-sensitive reservoirs is established, thereby improving the accuracy of reservoir permeability prediction and enhancing oil and gas reservoir production and recovery rates. This invention has significant potential for widespread application.

[0163] Although the invention has been described above in conjunction with exemplary embodiments, those skilled in the art will understand that various modifications and changes can be made to the exemplary embodiments of the invention without departing from the spirit and scope defined by the claims.

Claims

1. A method for predicting reservoir permeability based on tectonic stress, characterized in that, The method includes: Obtain reservoir rock mechanics test data, formation test data, core permeability test data, fracturing operation data, and well logging data; An effective stress model is constructed using formation test data and well logging data to calculate formation pressure. Reservoir rock mechanics test data and well logging data are used to calculate various rock mechanics parameters and perform dynamic-static conversion of Poisson's ratio. Based on the Huang model, the minimum and maximum horizontal principal stresses were obtained using fracturing construction data and the resulting rock mechanics parameters. By establishing a fitting relationship between the maximum horizontal principal stress and the core permeability, permeability can be predicted.

2. The reservoir permeability prediction method based on tectonic stress according to claim 1, characterized in that, The reservoir rock mechanical test data includes the Poisson's ratio and P-wave and S-wave velocities of the reservoir rock.

3. The reservoir permeability prediction method based on tectonic stress according to claim 1, characterized in that, The core permeability test data includes core permeability.

4. The reservoir permeability prediction method based on tectonic stress according to claim 1, characterized in that, The logging data includes density, P-wave transit time, and S-wave transit time.

5. The reservoir permeability prediction method based on tectonic stress according to claim 1, characterized in that, The formation test data includes formation pressure.

6. The reservoir permeability prediction method based on tectonic stress according to claim 1, characterized in that, The fracturing data includes formation fracturing pressure, formation re-tensioning pressure, and formation tensile strength.

7. The reservoir permeability prediction method based on tectonic stress according to claim 1, characterized in that, The calculation of formation pressure by constructing an effective stress model includes: The overlying formation pressure is calculated based on the average density of the formation without logging density, the cumulative vertical depth of the formation without logging density, the logging sampling depth interval, and the logging density. The difference between the overlying stratum pressure and the formation pressure is the effective stress; An effective stress model is established by fitting the effective stress with the ratio of P-wave to S-wave velocity obtained from reservoir rock mechanics test data. Formation pressure is calculated based on the effective stress model.

8. The reservoir permeability prediction method based on tectonic stress according to claim 7, characterized in that, The calculation of the overlying formation pressure includes: In the formula, σ v The overlying strata pressure is expressed in MPa; g represents gravitational acceleration in N / Kg; ρ represents the pressure of the overlying strata. a This represents the average density of the formation without well logging density, in g / cm³. 3 H a ρ represents the cumulative vertical depth of the formation without logging density, in meters (m). i This indicates the density measured in well logging, in g / cm³. 3 H i The sampling depth interval is represented in meters (m); n represents the number of sampling intervals from the formation termination depth without logging density to the target depth. The effective stress is fitted to the ratio of the longitudinal and transverse wave velocities to obtain the following relationship: σ e =a+b*(DTS / DTC); In the formula, σ e The effective stress is expressed in MPa; DTS represents the transverse wave transit time in μs / ft; DTC represents the longitudinal wave transit time in μs / ft; a and b are coefficients. The calculation of formation pressure includes: P p =s v -s e ; In the formula, σ e σ represents the effective stress, in MPa; v P represents the overlying formation pressure, in MPa; p This represents formation pressure, expressed in MPa.

9. The reservoir permeability prediction method based on tectonic stress according to claim 1, characterized in that, The Poisson ratio dynamic-static transformation includes: Calculate the dynamic Poisson's ratio based on the P-wave and S-wave transit time differences obtained from well logging data; The dynamic Poisson's ratio is fitted with the static Poisson's ratio obtained from rock mechanics test data to achieve the dynamic-static conversion of Poisson's ratio.

10. The reservoir permeability prediction method based on tectonic stress according to claim 9, characterized in that, The calculation of the dynamic Poisson's ratio includes: μ d =(0.5×DTS 2 -DTC 2 ) / (DTS 2 -DTC 2 ); In the formula, μ d The dynamic Poisson's ratio is dimensionless; DTS represents the transverse wave time difference, in μs / ft; DTC represents the longitudinal wave time difference, in μs / ft. The relationship between the dynamic and static transformation of Poisson's ratio is as follows: m s =a×μ d +b; In the formula, μ s μ represents the static Poisson's ratio, which is dimensionless. d This represents the dynamic Poisson ratio, which is dimensionless; a and b are both coefficients.

11. The reservoir permeability prediction method based on tectonic stress according to claim 1, characterized in that, The rock mechanics parameters include Poisson's ratio, reservoir bulk modulus, framework bulk modulus, and porosity elastic coefficient.

12. The reservoir permeability prediction method based on tectonic stress according to claim 11, characterized in that, The calculation of the rock mechanical parameters includes: The reservoir bulk modulus calculation includes calculations based on the P-wave transit time, S-wave transit time, and density of the reservoir obtained from well logging data: In the formula, K b DTS represents reservoir bulk modulus, MPa; DTC represents shear wave transit time, μs / ft; ρ represents logging density, g / cm³. 3 β represents the unit conversion factor, which is dimensionless. The calculation of the bulk modulus of the rock skeleton includes calculations based on the P-wave transit time, S-wave transit time, and density of the rock skeleton obtained from well logging data: In the formula, K ma DTS represents the bulk modulus of the skeleton, in MPa; ma DTC represents the frame shear wave time difference, in μs / ft; ma The longitudinal wave time difference (LWD) is expressed in μs / ft; ρ represents the time difference between the longitudinal and lateral waves ma This represents the skeletal density, in g / cm³. 3 β represents the unit conversion factor, which is dimensionless. The calculation of the porosity elastic coefficient includes calculations based on the reservoir bulk modulus and the framework bulk modulus: In the formula, η represents the porosity elastic coefficient, which is dimensionless; K b Represents the reservoir bulk modulus, in MPa; K ma This represents the bulk modulus of the skeleton, in MPa.

13. The reservoir permeability prediction method based on tectonic stress according to claim 1, characterized in that, The minimum and maximum horizontal principal stresses include: The minimum principal stress at the horizontal level is the formation re-tension pressure in the fracturing construction data; The maximum horizontal principal stress is calculated based on the minimum horizontal principal stress, porosity coefficient, formation pressure, and formation fracturing pressure and formation tensile strength from fracturing data.

14. The reservoir permeability prediction method based on tectonic stress according to claim 13, characterized in that, The calculation of the maximum horizontal principal stress includes: s H =3σ h -ηP p -P f +S t ; In the formula, σ h =P s ;σ h σ represents the minimum horizontal principal stress, in MPa; H P represents the maximum horizontal principal stress, expressed in MPa. s P represents the formation retensile pressure, MPa; η represents the porosity coefficient, dimensionless; p P represents formation pressure, in MPa; f Represents formation fracture pressure, MPa; S t This represents the tensile strength of the formation, expressed in MPa.

15. The reservoir permeability prediction method based on tectonic stress according to claim 1, characterized in that, The fitting relationship between the maximum horizontal principal stress and permeability includes: In the formula, K i The permeability measured in the core is expressed in mD; σ H This represents the maximum horizontal principal stress, in MPa; a, b, and c are coefficients.

16. A reservoir permeability prediction system based on formation tectonic stress, characterized in that, The system includes a data processing unit, a first calculation unit, a second calculation unit, a third calculation unit, and a prediction unit, wherein... The data unit is connected to the first calculation unit, the second calculation unit, the third calculation unit, and the prediction unit, respectively. The third calculation unit is connected to the first calculation unit and the second calculation unit, and the third calculation unit is connected to the prediction unit. The data unit is configured to acquire reservoir rock mechanics test data, formation test data, core permeability test data, fracturing operation data, and well logging data; The first calculation unit is configured to construct an effective stress model using formation test data and well logging data to calculate formation pressure; The second calculation unit is configured to use reservoir rock mechanics test data and well logging data to calculate various rock mechanics parameters and perform dynamic-static conversion of Poisson's ratio. The third calculation unit is configured to obtain the minimum and maximum horizontal principal stresses based on the Huang model, using fracturing construction data and the obtained rock mechanics parameters. The prediction unit is configured to establish a fitting relationship between the maximum horizontal principal stress and the core permeability to achieve permeability prediction.

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