Evaluation method for quantitatively representing rock fracturing degree through fracture complexity

Abstract

The invention discloses an evaluation method for quantitatively representing the rock fracturing degree through fracture complexity. By comparing the difference of induced polarization parameters before and after reservoir fracturing, a fracturing development complexity parameter Cf based on the induced polarization parameters can be obtained and used for quantitatively characterizing the fracturing degree of reservoir rock, then the correlation between the Cf and delta D is obtained by combining the average absolute gradient difference delta D before and after fracturing, and then the relation fitting degree is obtained. It is verified that quantitative characterization of the rock fracturing degree through fracture complexity is effective, and technical support is provided for establishing induced polarization method-based reservoir hydraulic fracturing quality evaluation.

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 an evaluation method for quantitatively characterizing the degree of rock fracturing by means of crack complexity. Background Art

[0002] Hydraulic fracturing is the core technology for improving the physical properties of unconventional reservoirs and achieving effective development of unconventional oil and gas resources. Dynamic monitoring of hydraulic fracturing can evaluate the degree and scale of fracture development during the fracturing process, determine the direction of fracturing fluid, delineate the distribution range of proppants, and achieve volume evaluation of reservoir fracturing transformation, which is crucial for reservoir production capacity prediction and resource development. Compared with microseismic monitoring, electromagnetic monitoring has the advantages of low monitoring cost, high efficiency, and electrical parameters are more sensitive than elastic parameters. It provides a physical basis for monitoring the initiation and subsequent expansion of fractures during hydraulic fracturing. At present, the monitoring technology for reservoir fracturing transformation is mainly based on determining the range of fracturing, and lacks quantitative characterization technology for the degree of fracturing. Summary of the invention

[0003] The present invention can quantitatively characterize the degree of rock fracturing by providing an evaluation method for quantitatively characterizing the degree of rock fracturing through crack complexity.

[0004] The present invention provides an evaluation method for quantitatively characterizing the degree of rock fracturing by means of crack complexity, comprising:

[0005] For each sample of the studied reservoir, the mass of the sample is obtained by drying, which is m1. The reservoir rock is saturated with formation water in the measured area to reach the mineralization and saturation state of the formation. The mass of the sample is recorded as m2.

[0006] The complex resistivity measurement of the reservoir temperature T and pressure P is simulated for the rock samples that have reached the state of formation mineralization and saturation, and the complex resistivity curve is obtained. The true conductivity σ before fracturing of the reservoir rock is obtained by combining the parameter estimation algorithm based on the MGEMTIP model. b and pre-pressure polarization η b ;

[0007] The rock samples that have reached the state of formation mineralization and saturation are washed with salt and dried, and the dried samples are image scanned and grayed to obtain the average absolute gradient D before pressure on the rock measurement plane. b ;

[0008] Perform rock fracturing on the rock samples that have reached the formation mineralization and saturation state, preserve or supplement the material loss during the fracturing process, and satisfy the mass of the sample at this time is m1; after the sample is shaped, the reservoir rock is saturated with the formation water in the measurement area until the mass of the sample reaches m2;

[0009] The complex resistivity measurement of reservoir temperature T and pressure P was simulated for saturated fractured samples to obtain the complex resistivity curve. The post-fracture true conductivity σ of the reservoir rock was obtained by combining the parameter estimation algorithm based on the MGEMTIP model. a and the post-compression polarization η a ;

[0010] The saturated fracturing sample is washed with salt and dried, and the dried sample is image scanned and grayed to obtain the average absolute gradient D of the rock measurement plane after fracturing. a ;

[0011] By formula The measured crack complexity C is calculated f ;

[0012] By the formula ΔD=D a -D b The average absolute gradient difference ΔD before and after fracturing was calculated;

[0013] Establish the C f The correlation between ΔD and the relationship fitting degree is then obtained, and the evaluation result is obtained through the relationship fitting degree.

[0014] Specifically, the salt washing and drying operations on the rock samples that have reached the formation mineralization and saturation state include:

[0015] The rock samples that have reached the state of formation mineralization and saturation are subjected to salt washing operation, soaked in pure water for 24 hours, during which the pure water is replaced every 8 hours, and then dried.

[0016] Specifically, the drying operation includes:

[0017] The sample after the salt washing operation was dried in a drying oven at 70°C until the mass change of the sample was less than 0.01g for 2 consecutive hours.

[0018] Specifically, the average absolute gradient D before pressure measurement of the rock measurement plane is obtained. b ,include:

[0019] By formula The average absolute gradient D before pressure is calculated b ; Among them, D bx and D by The average absolute gradients in the x-direction and y-direction before compression are respectively expressed as:

[0020]

[0021] Among them, S is the pixel set of data points of the rock test surface image, G b (i, j) is the gray value of the corresponding pixel in the image before fracturing, G bx (i, j) is the x-direction gradient before compression of the corresponding coordinate point, G by (i, j) is the y-direction gradient before compression of the corresponding coordinate point.

[0022] Specifically, the rock fracturing is performed on the rock sample that has reached the formation mineralization and saturation state, and the material loss during the fracturing process is preserved or supplemented, so that the mass of the sample at this time is m1, including:

[0023] The rock sample that has reached the state of formation mineralization and saturation is subjected to rock fracturing by means of fracturing, splitting and cutting; during the fracturing or splitting process, the rock sample is always wrapped in a colloid to ensure that the sample debris in the process is confined inside the rock sample to meet the mass of the sample at this time being m1; by comparing the mass difference of the sample before and after cutting, the same mass of debris is filled to make up for the material loss in the fracturing process to meet the mass of the sample at this time being m1.

[0024] Specifically, after the sample is shaped, the reservoir rock is saturated with formation water in the measuring area until the mass of the sample reaches m2, and the method further includes:

[0025] The fracturing fluid of a sample with a mass of m2 is pressurized through a pressure chamber until the mass change of the sample is less than 0.01g for 2 consecutive hours.

[0026] Specifically, the post-compression average absolute gradient D of the rock measurement plane is obtained. a ,include:

[0027] By formula The average absolute gradient after compression D is calculated a ; Among them, D ax and D ay The average absolute gradient in the post-compression direction corresponding to the x-direction and y-direction respectively, the corresponding expressions are:

[0028]

[0029] Among them, S is the pixel set of data points of the rock test surface image, G a (i, j) is the gray value of the corresponding pixel in the image after fracturing, G ax (i, j) is the x-direction gradient of the corresponding coordinate point after compression, G ay (i, j) is the y-direction gradient of the corresponding coordinate point after compression.

[0030] Specifically, the establishment of the C fand the correlation between ΔD, and then obtain the relationship fitting degree, and obtain the evaluation result through the relationship fitting degree, including:

[0031] By the C f Establish a correlation relationship C with the ΔD f * =a*exp(bΔD); where a and b are fitting coefficients, C f * To calculate the crack complexity;

[0032] By formula Calculate the relationship fit R 2 ; Where n is the total number of samples, C fi is the measured crack complexity of the ith sample, C fi * is the calculated crack complexity after the i-th sample is brought into the correlation relationship, is the average measured crack complexity of n samples;

[0033] If the relationship fit R 2 If it is equal to or greater than the set threshold, it is evaluated as valid.

[0034] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0035] By comparing the differences in IP parameters before and after reservoir fracturing, the fracturing development complexity parameter C based on IP parameters can be obtained. f , which is used to quantitatively characterize the degree of fracturing of reservoir rocks, and combined with the average absolute gradient difference ΔD before and after fracturing, C f The correlation between ΔD and ΔD is then used to obtain the relationship fit to verify that the quantitative characterization of rock fracturing degree by fracture complexity is effective. Among them, the average absolute gradient difference ΔD is a quantitative characterization of the visual fracturing degree of the sample before and after fracturing, and the fracture complexity C f It is an indirect quantitative characterization of the degree of fracturing obtained by the conductivity development behind the rock fracturing based on the induced polarization method. It is very suitable for underground exploration. Underground exploration can directly obtain induced polarization parameters, which can be used to evaluate the underground fracturing effect. The correlation between the two can verify the complexity of the fracture C f It is an effective parameter to characterize the degree of rock fracturing and provides technical support for establishing reservoir hydraulic fracturing quality assessment based on induced polarization method. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A flow chart of an evaluation method for quantitatively characterizing the degree of rock fracturing by fracture complexity provided in an embodiment of the present invention;

[0037] Figure 2 It is a schematic diagram of the measurement surface and significant surface crack development of the sample in the embodiment of the present invention;

[0038] Figure 3 4 is a fitting relationship diagram between the average absolute gradient difference and the crack complexity based on the induced polarization parameters in an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The embodiment of the present invention provides an evaluation method for quantitatively characterizing the degree of rock fracturing by using the complexity of cracks, thereby being able to quantitatively characterize the degree of rock fracturing.

[0040] 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.

[0041] like Figure 1 As shown, the evaluation method for quantitatively characterizing the degree of rock fracturing by fracture complexity provided by the embodiment of the present invention includes:

[0042] Step S110: For each sample of the studied reservoir, the mass of the sample is obtained by drying, and the mass of the sample is m1. The reservoir rock is saturated with formation water in the measured area to reach the formation mineralization and saturation state, and the mass of the sample is recorded as m2;

[0043] Step S120: Simulate the complex resistivity measurement of reservoir temperature T and pressure P for rock samples that have reached the state of formation mineralization and saturation, obtain the complex resistivity curve, and combine the parameter estimation algorithm based on the MGEMTIP model to obtain the true conductivity σ before fracturing of the reservoir rock b and pre-pressure polarization η b ;

[0044] Step S130: Perform salt washing and drying operations on rock samples that have reached the state of formation mineralization and saturation, perform image scanning and grayscale processing on the dried samples, and obtain the average absolute gradient D before pressure measurement on the rock measurement plane. b ;

[0045] Specifically, the rock samples that have reached the mineralization and saturation state of the formation are subjected to salt washing and drying operations, including:

[0046] The rock samples that have reached the mineralization and saturation state of the formation are subjected to salt washing operation and soaked in pure water for 24 hours. The pure water is replaced every 8 hours during this period, and then the samples are dried.

[0047] The drying operation includes:

[0048] The sample after the salt washing operation was dried in a drying oven at 70°C until the mass change of the sample was less than 0.01g for 2 consecutive hours.

[0049] Obtain the average absolute gradient D of the rock measurement plane before compression b ,include:

[0050] By formula The average absolute gradient D before pressure is calculated b ; Among them, D bx and D by The average absolute gradients in the x-direction and y-direction before compression are respectively expressed as:

[0051]

[0052] Among them, S is the pixel set of data points of the rock test surface image, G b (i, j) is the gray value of the corresponding pixel in the image before fracturing, G bx (i, j) is the x-direction gradient before compression of the corresponding coordinate point, G by (i, j) is the y-direction gradient before compression of the corresponding coordinate point.

[0053] Step S140: rock fracturing is performed on the rock sample that has reached the formation mineralization and saturation state, and the material loss during the fracturing process is preserved or supplemented, so that the mass of the sample at this time is m1; after the sample is shaped, the reservoir rock is saturated in combination with the formation water in the measurement area until the mass of the sample reaches m2;

[0054] Specifically, rock fracturing is performed on rock samples that have reached the mineralization and saturation state of the formation to preserve or supplement the material loss during the fracturing process, so that the mass of the sample at this time is m1, including:

[0055] Rock fracturing is performed on rock samples that have reached the state of formation mineralization and saturation by means of fracturing, splitting and cutting; during the fracturing or splitting process, the rock sample is always wrapped in a colloid to ensure that the sample debris in the process is constrained inside the rock sample to meet the mass of the sample at this time being m1; by comparing the mass difference of the sample before and after cutting, the same mass of debris is filled to make up for the material loss in the fracturing process to meet the mass of the sample at this time being m1.

[0056] After the sample is shaped, the reservoir rock is saturated with formation water in the measurement area until the sample mass reaches m2, which also includes:

[0057] The fracturing fluid of a sample with a mass of m2 is pressurized through a pressure chamber until the mass change of the sample is less than 0.01g for 2 consecutive hours. The pressure value during the pressurization process is the pressure difference during the fracturing process.

[0058] Step S150: Conduct a simulation study on the complex resistivity measurement of the reservoir temperature T and pressure P for the saturated fractured sample, obtain the complex resistivity curve, and obtain the post-fracture true conductivity σ of the reservoir rock in combination with the parameter estimation algorithm based on the MGEMTIP model. a and the post-compression polarization η a ;

[0059] Step S160: salt washing and drying of the saturated sample after fracturing, image scanning and graying of the dried sample, and obtaining the average absolute gradient D after fracturing of the rock measurement plane. a ;

[0060] Specifically, the saturated fracturing sample is subjected to salt washing and drying operations, including:

[0061] The saturated samples after fracturing were washed with salt and soaked in pure water for 24 hours, during which the pure water was replaced every 8 hours, and then dried.

[0062] The drying operation includes:

[0063] The sample after the salt washing operation was dried in a drying oven at 70°C until the mass change of the sample was less than 0.01g for 2 consecutive hours.

[0064] Obtain the average absolute gradient D of the rock measurement plane after compression a ,include:

[0065] By formula The average absolute gradient after compression D is calculated a ; Among them, D ax and D ay The average absolute gradient in the post-compression direction corresponding to the x-direction and y-direction respectively, the corresponding expressions are:

[0066]

[0067] Among them, S is the pixel set of data points of the rock test surface image, G a (i, j) is the gray value of the corresponding pixel in the image after fracturing, G ax (i, j) is the x-direction gradient of the corresponding coordinate point after compression, G ay (i, j) is the y-direction gradient of the corresponding coordinate point after compression.

[0068] Step S170: By formula The measured crack complexity C is calculated f ;

[0069] Step S180: By formula ΔD=D a -D bThe average absolute gradient difference ΔD before and after fracturing was calculated;

[0070] Step S190: Establish C f The correlation between ΔD and ΔD is then obtained, and the relationship fit is used to obtain the evaluation result.

[0071] This step is explained in detail to establish C f The correlation between ΔD and ΔD is then used to obtain the relationship fit, and the evaluation results are obtained through the relationship fit, including:

[0072] By C f Establish the correlation relationship C with ΔD f * =a*exp(bΔD); where a and b are fitting coefficients, C f * To calculate the crack complexity;

[0073] By formula Calculate the relationship fit R 2 ; Where n is the total number of samples, C fi is the measured crack complexity of the ith sample, C fi * is the calculation crack complexity after the correlation equation is brought into the i-th sample, is the average measured crack complexity of n samples;

[0074] If the relationship fit R 2 If it is equal to or greater than the set threshold, it is evaluated as effective. 2 The larger the value, the greater the crack complexity C f The better the effectiveness of characterizing the survey area.

[0075] The method provided by the embodiment of the present invention was verified for the reservoir shale in a certain measurement area. Five samples were used to conduct experiments before and after fracturing. The test results are shown in Table 1.

[0076] Table 1 Correspondence between the average absolute gradient difference of samples and the complexity of the tested electrical cracks

[0077]

[0078] See attached for columnar samples before and after fracturing. Figure 2 The samples were fractured by wire cutting, splitting and hydraulic fracturing, and the fracture development was arranged from simple to complex. Figure 3It is a correlation analysis between the average absolute gradient difference and the fracture complexity based on induced polarization parameters. The results show a high degree of fit, indicating that the induced polarization fracture complexity defined by this method can effectively characterize the complexity of rock fracturing fracture development and can be further applied to actual survey areas, providing technical support for establishing reservoir hydraulic fracturing quality assessment based on induced polarization method.

[0079] The embodiment of the present invention compares the differences in induced polarization parameters of reservoir rocks before and after fracturing, extracts development complexity parameters based on complex conductivity, which are used to quantitatively characterize the fracturing degree of reservoir rocks, thereby realizing the evaluation of fracturing quality in fracturing monitoring and providing technical support for establishing reservoir hydraulic fracturing quality evaluation based on induced polarization method.

[0080] 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 evaluating the degree of rock fracturing by quantitatively characterizing the degree of rock fracturing by means of fracture complexity, characterized in that: include: For each sample of the studied reservoir, the mass of the sample is obtained by drying, which is m1. The reservoir rock is saturated with formation water in the measured area to reach the mineralization and saturation state of the formation. The mass of the sample is recorded as m2. The complex resistivity measurement of the reservoir temperature T and pressure P is simulated for the rock samples that have reached the state of formation mineralization and saturation, and the complex resistivity curve is obtained. The true conductivity σ before fracturing of the reservoir rock is obtained by combining the parameter estimation algorithm based on the MGEMTIP model. b and pre-pressure polarization η b ; The rock samples that have reached the state of formation mineralization and saturation are washed with salt and dried, and the dried samples are image scanned and grayed to obtain the average absolute gradient D before pressure on the rock measurement plane. b ; Perform rock fracturing on the rock samples that have reached the formation mineralization and saturation state, preserve or supplement the material loss during the fracturing process, and satisfy the mass of the sample at this time is m1; after the sample is shaped, the reservoir rock is saturated with the formation water in the measurement area until the mass of the sample reaches m2; The complex resistivity measurement of reservoir temperature T and pressure P was simulated for saturated fractured samples to obtain the complex resistivity curve. The post-fracture true conductivity σ of the reservoir rock was obtained by combining the parameter estimation algorithm based on the MGEMTIP model. a and the post-compression polarization η a ; The saturated fracturing sample is washed with salt and dried, and the dried sample is image scanned and grayed to obtain the average absolute gradient D of the rock measurement plane after fracturing. a ; By formula The measured crack complexity C is calculated f ; By the formula ΔD=D a -D b The average absolute gradient difference ΔD before and after fracturing was calculated; Establish the C f The correlation between ΔD and the relationship fitting degree is then obtained, and the evaluation result is obtained through the relationship fitting degree.

2. The evaluation method for quantitatively characterizing the degree of rock fracturing by fracture complexity according to claim 1, characterized in that: The salt washing and drying operation of the rock sample that has reached the formation mineralization and saturation state includes: The rock samples that have reached the state of formation mineralization and saturation are subjected to salt washing operation, soaked in pure water for 24 hours, during which the pure water is replaced every 8 hours, and then dried.

3. The evaluation method for quantitatively characterizing the degree of rock fracturing by fracture complexity according to claim 2, characterized in that: The drying operation comprises: The sample after the salt washing operation was dried in a drying oven at 70°C until the mass change of the sample was less than 0.01g for 2 consecutive hours.

4. The evaluation method for quantitatively characterizing the degree of rock fracturing by fracture complexity according to claim 1, characterized in that: The average absolute gradient D before the rock measurement plane is obtained b ,include: By formula The average absolute gradient D before pressure is calculated b ; Among them, D bx and D by The average absolute gradients in the x-direction and y-direction before compression are respectively expressed as: Among them, S is the pixel set of data points of the rock test surface image, G b (i, j) is the gray value of the corresponding pixel in the image before fracturing, G bx (i, j) is the x-direction gradient before compression of the corresponding coordinate point, G by (i, j) is the y-direction gradient before compression of the corresponding coordinate point.

5. The evaluation method for quantitatively characterizing the degree of rock fracturing by fracture complexity according to claim 1, characterized in that: The rock fracturing is performed on the rock sample that has reached the formation mineralization and saturation state, and the material loss during the fracturing process is preserved or supplemented, so that the mass of the sample at this time is m1, including: The rock sample that has reached the state of formation mineralization and saturation is subjected to rock fracturing by means of fracturing, splitting and cutting; during the fracturing or splitting process, the rock sample is always wrapped in a colloid to ensure that the sample debris in the process is confined inside the rock sample to meet the mass of the sample at this time being m1; by comparing the mass difference of the sample before and after cutting, the same mass of debris is filled to make up for the material loss in the fracturing process to meet the mass of the sample at this time being m1.

6. The evaluation method for quantitatively characterizing the degree of rock fracturing by fracture complexity according to claim 1, characterized in that: After the sample is shaped, the reservoir rock is saturated with formation water in the measuring area until the mass of the sample reaches m2, and the method further includes: The fracturing fluid of a sample with a mass of m2 is pressurized through a pressure chamber until the mass change of the sample is less than 0.01g for 2 consecutive hours.

7. The evaluation method for quantitatively characterizing the degree of rock fracturing by fracture complexity according to claim 1, characterized in that: The obtained rock measurement plane has an average absolute gradient D after compression. a ,include: By formula The average absolute gradient after compression D is calculated a ; Among them, D ax and D ay The average absolute gradient in the post-compression direction corresponding to the x-direction and y-direction respectively, the corresponding expressions are: Among them, S is the pixel set of data points of the rock test surface image, G a (i, j) is the gray value of the corresponding pixel in the image after fracturing, G ax (i, j) is the x-direction gradient of the corresponding coordinate point after compression, G ay (i, j) is the y-direction gradient of the corresponding coordinate point after compression.

8. The evaluation method for quantitatively characterizing the degree of rock fracturing by fracture complexity according to claim 1, characterized in that: The establishment of the C f and the correlation between ΔD, and then obtain the relationship fitting degree, and obtain the evaluation result through the relationship fitting degree, including: By the C f Establish a correlation relationship C with the ΔD f * =a*exp(bΔD); where a and b are fitting coefficients, C f * To calculate the crack complexity; By formula Calculate the relationship fit R 2 ; Where n is the total number of samples, C fi is the measured crack complexity of the i-th sample, C fi * is the calculated crack complexity after the i-th sample is brought into the correlation equation, is the average measured crack complexity of n samples; If the relationship fit R 2 If it is equal to or greater than the set threshold, it is evaluated as valid.

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