Brittleness index calculation method and device for superior paleozoic mud shale formation

Abstract

The invention relates to a brittleness index calculation method and device for a superior paleozoic mud shale stratum. The brittleness index is an arithmetic mean value of an intermediate parameter obtained through Young modulus data and an intermediate parameter obtained through Poisson's ratio data. Wherein the intermediate parameter obtained through the Young modulus data is a normalized value of the Young modulus, and the intermediate parameter obtained through the Poisson's ratio data is a normalized value of the Poisson's ratio. According to the method, multiple linear regression is carried out by using conventional logging data, the shear wave time difference model is constructed to fit the shear wave data, the correlation coefficient between the obtained brittleness index and the rock brittleness index obtained by the array acoustic logging data is high, and the method is suitable for solving the rock brittleness index in the absence of the array acoustic logging data. And calculating the brittleness index of the strong-heterogeneity shale formation aiming at complex mineral components in the paleozoic region.

Description

Technical Field

[0001] The present invention relates to the fields of stratigraphy, rock mechanics, mathematics, etc. According to the characteristics of complex mineral composition and strong heterogeneity of Paleozoic mud shale formations, a mathematical method is used to reconstruct shear waves, which effectively solves the difficulty in evaluating the brittleness index of Paleozoic mud shale formations and provides an efficient and accurate brittleness index calculation method and device. Background Art

[0002] At present, there are two methods for calculating and evaluating the brittleness index of Paleozoic mudstone: laboratory static measurement method and logging data dynamic calculation method. Although the laboratory static measurement method is accurate, it has great limitations: 1. Although the brittle mineral content data obtained in the laboratory is more accurate, the data are scattered and discontinuous scattered data, which cannot provide continuous evaluation in the vertical direction; 2. The ancient mudstone formation contains a variety of mineral components, and different minerals have different pore structures. Their destruction process under mechanical compaction is also different, and the brittle characteristics they show are also different; 3. The brittle characteristics of the formation rock are also affected by factors such as rock particle size, cementation, confining pressure, and pore fluid.

[0003] There are two types of dynamic calculation methods for logging data: direct measurement of full-wave acoustic waves and shear wave fitting of conventional longitudinal and acoustic waves. Full-wave acoustic logging calculates the brittleness index. It is a common engineering method that directly obtains the longitudinal and shear wave information of the formation through logging instruments and then obtains the brittleness index. However, due to the high cost of full-wave acoustic logging, it is not easy to promote and use on a large scale, and complex lithological characteristics will increase the difficulty of calculating the brittleness index. Summary of the invention

[0004] In view of the above problems, the purpose of the present invention is to provide a method for calculating the brittleness index of the Upper Paleozoic shale formation with complex mineral composition and strong heterogeneity, so as to provide an economical and relatively accurate calculation method for the brittleness index evaluation in oil and gas engineering geology.

[0005] The technical solution of the present invention is: A method for calculating the brittleness index of Upper Paleozoic shale formations, wherein the brittleness index is calculated by Young's modulus. E Intermediate parameters for data acquisition BR E and through Poisson's ratio μ Intermediate parameters for data acquisition BR μ The arithmetic mean of E Intermediate parameters for data acquisition BR E is Young's modulus E The normalized value of μ Intermediate parameters for data acquisitionBR μ Poisson's ratio μ The normalized value of .

[0006] The Young's modulus E and Poisson's ratio μ Calculated from logging data. If the logging data includes array acoustic logging data, Young's modulus E and Poisson's ratio μ The specific solution processes are: ; Where: μ is Poisson’s ratio, dimensionless; E is Young's modulus, GPa; △ t s is the shear wave time difference DTDR, μs / m; t p is the longitudinal wave time difference DTCR, μs / m; ρ b Lithology density curve DEN, g / cm 3 .

[0007] Alternatively, the Young's modulus E and Poisson's ratio μ It is calculated through well logging data. If the well logging data does not contain array acoustic logging data, the shear wave fitting model is used to calculate the fitting shear wave data, that is: DTDR=0.477GR +0.594AC+3.658CNL+0.788U+136.576 Where: GR is the natural gamma curve, API; AC is the compensated acoustic wave curve, μs / m; CNL is the compensated neutron curve, %; U is the gamma spectrum uranium content curve, % Then replace △t with the shear wave time difference DTDR s , replace △t with the compensation sound wave curve AC p , and then calculate the Young's modulus according to the situation that the logging data includes array acoustic logging data E and Poisson's ratio μ .

[0008] The Young's modulus E Intermediate parameters for data acquisition BR E , through Poisson's ratio μ Intermediate parameters for data acquisition BR μ The specific solution process is: BRE =( E - E min ) / ( E max -E min ) BR μ =( μ - μ max ) / ( μ min - μ max ) Where: E min is the minimum value of Young's modulus in a certain well layer section, GPa; E max is the maximum value of Young's modulus in a certain well layer section, GPa; μ min is the minimum value of Poisson's ratio in a certain well layer section, dimensionless; μ max It is the maximum value of Poisson's ratio in a certain well layer section and is dimensionless.

[0009] The specific solution process of the brittleness index is: BR = ( BR E + BR μ ) / 2×100% Where: BR is the brittleness index, %.

[0010] The logging data include conventional logging curves and special logging curves; the conventional logging curves include at least compensated acoustic wave curves AC, natural gamma curves GR, compensated neutron curves CNL, lithology density curves DEN and gamma energy spectrum uranium content curves U; the special logging curves include logging data that can obtain longitudinal wave time difference DTCR and shear wave time difference DTDR.

[0011] The logging data capable of obtaining the longitudinal wave time difference DTCR and the shear wave time difference DTDR include array acoustic logging data.

[0012] A brittleness index calculation device for Upper Paleozoic mudstone strata, comprising: A data acquisition module, used to acquire conventional logging curves and special logging curves of target formations; Intermediate parameter acquisition module, used to calculate Young's modulus through conventional logging curves and special logging curves of the target formation E and Poisson's ratio μ, and calculate their normalized values, respectively, through Young's modulus E Intermediate parameters for data acquisition BR E and through Poisson's ratio μ Intermediate parameters for data acquisition BR μ ; The brittleness index acquisition module is used to obtain the Young's modulus E Intermediate parameters for data acquisition BR E and through Poisson's ratio μ Intermediate parameters for data acquisition BR μ The arithmetic mean was obtained as the brittleness index.

[0013] The technical effects of the present invention are: The present invention uses conventional logging curves to perform multivariate linear regression, constructs a shear wave fitting model to fit shear wave data, and the calculated brittleness index is consistent with the measured Poisson's ratio. μ and Young's modulus E The calculated brittleness index has good conformity and is suitable for calculating the brittleness index of Paleozoic shale formations with complex mineral composition and strong heterogeneity in the absence of array acoustic logging data. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 The figure is a calculation flow chart of the present invention.

[0015] Figure 2 Calculated for actual measurement BR Compared with conventional logging BR Intersection diagram. DETAILED DESCRIPTION

[0016] Example 1 A method for calculating the brittleness index of Upper Paleozoic shale formations is as follows: Step 1: Acquire logging data; the logging data include conventional logging curves and special logging curves; conventional logging curves include compensated acoustic curves AC, natural gamma curves GR, compensated neutron curves CNL, lithology density curves DEN and gamma energy spectrum uranium content curves U; special logging curves include logging data that can obtain longitudinal wave time difference DTCR and shear wave time difference DTDR.

[0017] Step 2: Calculate Poisson's ratio μ and Young's modulus E ; The Young's modulus E and Poisson's ratio μ Calculated from logging data. If the logging data includes array acoustic logging data, Young's modulus E and Poisson's ratioμ The specific solution processes are: ; ; Step 3: Convert Poisson's ratio μ and Young's modulus E Normalized, we get the Young's modulus E Intermediate parameters for data acquisition BR E and through Poisson's ratio μ Intermediate parameters for data acquisition BR μ ; BR E =( E - E min ) / ( E max -E min ) BR μ =( μ - μ max ) / ( μ min - μ max ).

[0018] Step 4: Calculate the brittleness index BR ; BR = ( BR E + BR μ ) / 2×100%.

[0019] Example 2 On the basis of Example 1, step 2 in Example 1 is replaced by the following steps: Step 2: Calculate Poisson's ratio μ and Young's modulus E ; The Young's modulus E and Poisson's ratio μ It is calculated through well logging data. If the well logging data does not contain array acoustic logging data, the shear wave fitting model is used to calculate the fitting shear wave data, that is: DTDR=0.477GR +0.594AC+3.658CNL+0.788U+136.576 Then replace △t with the shear wave time difference DTDR s , replace △t with the compensation sound wave curve AC p, and then calculate the Young's modulus according to the situation that the logging data includes array acoustic logging data E and Poisson's ratio μ .

[0020] Specific experimental example: Well H in Yanchang Gas Field A method for calculating the brittleness index of Upper Paleozoic shale formations is as follows.

[0021] Step 1: Obtain logging data, including formation information, conventional logging curves and array acoustic logging data of Well H; conventional logging curves include: compensated acoustic curve AC, natural gamma curve GR, compensated neutron curve CNL, lithology density curve DEN and gamma spectrum uranium content curve U; at the same time, as a test result reliability, obtain the measured Poisson's ratio of Well H μ and Young's modulus E The target layer is Shanxi section, the well depth is 2299-2360m, and the lithology is shale.

[0022] Step 2: Calculate Poisson's ratio μ and Young's modulus E ; (1) The logging data includes array acoustic logging data, Young's modulus E and Poisson's ratio μ The specific solution process refers to step 2 of Example 1, and some calculation results are shown in Table 1; Table 1 Poisson's ratio calculated from array acoustic logging data μ and Young's modulus E Calculation results (2) Calculation of Young's modulus using conventional logging curves E and Poisson's ratio μ , the specific solution process refers to Example 2, and the calculation results are shown in Table 2; Table 2 Young's modulus calculated from conventional logging curves E and Poisson's ratio μ Calculation results . Step 3: Convert Poisson's ratio μ and Young's modulus E Normalized, we get the Young's modulus E Intermediate parameters for data acquisition BR E and through Poisson's ratio μ Intermediate parameters for data acquisition BR μ , see Table 3; where the 3rd and 4th columns are the calculated results of Table 1, the 6th and 7th columns are the calculated results of Table 2, and the 9th and 10th columns are the measured Poisson's ratiosμ and Young's modulus E The calculation results of Table 3 Poisson's ratio μ and Young's modulus E The normalized value of . Step 4: Calculate the brittleness index BR ; The 8th column in Table 3 is the brittleness index calculated from the array acoustic logging data in Table 1, the 5th column is the brittleness index calculated from the conventional logging curve in Table 2, and the 11th column is the measured Poisson's ratio. μ and Young's modulus E Calculated brittleness index.

[0023] Calculated by actual measurement BR Compared with conventional logging BR Intersection diagram ( Figure 2 ) analysis, the brittleness index calculated from conventional logging curves and the measured Poisson's ratio μ and Young's modulus E The calculated brittleness index has a good degree of conformity, with a deviation of less than ±5%, meeting the accuracy requirements. This shows that the method of calculating the brittleness index using conventional logging curves is feasible and the modeling is reliable.

Claims

1. A method for calculating the brittleness index of Upper Paleozoic shale formations, characterized by: The brittleness index is expressed by Young's modulus E Intermediate parameters for data acquisition BR E and through Poisson's ratio μ Intermediate parameters for data acquisition BR μ The arithmetic mean of E Intermediate parameters for data acquisition BR E is Young's modulus E The normalized value of μ Intermediate parameters for data acquisition BR μ Poisson's ratio μ The normalized value of .

2. The method for calculating the brittleness index of the Upper Paleozoic shale formation according to claim 1, characterized in that: The Young's modulus E and Poisson's ratio μ Calculated from logging data. If the logging data includes array acoustic logging data, Young's modulus E and Poisson's ratio μ The specific solution processes are: ； Where: μ is Poisson’s ratio, dimensionless; E is Young's modulus, GPa; △ t s is the shear wave time difference DTDR, μs / m; △ t p is the longitudinal wave time difference DTCR, μs / m; ρ b Lithology density curve DEN, g / cm 3 .

3. The method for calculating the brittleness index of the Upper Paleozoic shale formation according to claim 2, characterized in that: The Young's modulus E and Poisson's ratio μ It is calculated through well logging data. If the well logging data does not contain array acoustic logging data, the shear wave fitting model is used to calculate the fitting shear wave data, that is: DTDR=0.477GR +0.594AC+3.658CNL+0.788U+136.576 Where: GR is the natural gamma curve, API; AC is the compensated acoustic wave curve, μs / m; CNL is the compensated neutron curve, %; U is the gamma spectrum uranium content curve, % Then replace △t with the shear wave time difference DTDR s , replace △t with the compensation sound wave curve AC p , and then calculate the Young's modulus according to the situation that the logging data includes array acoustic logging data E and Poisson's ratio μ .

4. The method for calculating the brittleness index of the Upper Paleozoic shale formation according to claim 2 or 3, characterized in that: The Young's modulus E Intermediate parameters for data acquisition BR E , through Poisson's ratio μ Intermediate parameters for data acquisition BR μ The specific solution process is: BR E = ( E － E min ) / ( E max －E min ) BR μ =( μ － μ max ) / ( μ min － μ max ) Where: E min is the minimum value of Young's modulus in a certain well layer section, GPa; E max is the maximum value of Young's modulus in a certain well layer section, GPa; μ min is the minimum value of Poisson's ratio in a certain well layer section, dimensionless; μ max It is the maximum value of Poisson's ratio in a certain well layer section and is dimensionless.

5. The method for calculating the brittleness index of the Upper Paleozoic shale formation according to claim 4, characterized in that: The specific solution process of the brittleness index is: BR = ( BR E + BR μ ) / 2×100% Where: BR is the brittleness index, %.

6. The method for calculating the brittleness index of the Upper Paleozoic shale formation according to claim 2 or 3, characterized in that: The logging data include conventional logging curves and special logging curves; the conventional logging curves include at least compensated acoustic wave curves AC, natural gamma curves GR, compensated neutron curves CNL, lithology density curves DEN and gamma energy spectrum uranium content curves U; the special logging curves include logging data that can obtain longitudinal wave time difference DTCR and shear wave time difference DTDR.

7. The method for calculating the brittleness index of the Upper Paleozoic shale formation according to claim 6, characterized in that: The logging data capable of obtaining the longitudinal wave time difference DTCR and the shear wave time difference DTDR include array acoustic logging data.

8. A brittleness index calculation device for Upper Paleozoic shale formations, characterized in that: include: A data acquisition module, used to acquire conventional logging curves and special logging curves of target formations; Intermediate parameter acquisition module, used to calculate Young's modulus through conventional logging curves and special logging curves of the target formation E and Poisson's ratio μ , and calculate their normalized values, respectively, through Young's modulus E Intermediate parameters for data acquisition BR E and through Poisson's ratio μ Intermediate parameters for data acquisition BR μ ; The brittleness index acquisition module is used to obtain the Young's modulus E Intermediate parameters for data acquisition BR E and through Poisson's ratio μ Intermediate parameters for data acquisition BR μ The arithmetic mean value was obtained as the brittleness index.

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