A method for dividing shale water-rock interaction stages through continuous nuclear magnetic resonance testing

Abstract

The invention provides a method for dividing shale water-rock interaction stages through continuous nuclear magnetic resonance testing, which belongs to the technical field of oil and gas development. The method comprises the following steps: selecting multiple groups of core samples from the same reservoir from which bound water has been removed to perform liquid nitrogen adsorption and gas permeability tests, determining the time range of the nuclear magnetic resonance test, performing continuous nuclear magnetic resonance hydrogen spectrum tests on cores saturated with formation water, obtaining T2 spectrum relaxation signals of each group of core samples, and obtaining a porosity-time variation curve, selecting the immersion time corresponding to when the derivative of each group of core samples is 0 and 2 to perform factor analysis, and obtaining a principal component matrix, performing arithmetic averaging on the result values ​​in the principal component matrix, and then weighting the average value in combination with the above immersion time to obtain a final rock sample porosity and imbibition time formula, and dividing the water-rock interaction stages of the core samples; the data processing method in the invention takes into account the inaccurate precision caused by experimental errors, and can accurately obtain the time period and time point of the imbibition action in each stage.

Description

Technical Field

[0001] The invention relates to the technical field of oil and gas development, and in particular to a method for dividing shale water-rock interaction stages through continuous nuclear magnetic resonance testing. Background Art

[0002] Unlike conventional reservoirs, shale will produce a series of water-rock interactions during fracturing and well soaking, such as pressure saturation, spontaneous imbibition and porosity changes caused by hydration, which will significantly affect the production effect of shale gas after pressure relief. However, it is currently difficult to conduct control variable research on a single factor in the laboratory, and it is also impossible to clarify the impact of a certain water-rock interaction on later production. Therefore, the present invention proposes a method for dividing the shale water-rock interaction stages through continuous nuclear magnetic resonance testing, which is of great significance for studying the water-rock interaction mechanism and improving gas well production.

[0003] Guo Jingjing et al. analyzed the imbibition curve of shale through experiments and believed that shale imbibition can be divided into three stages: initial rapid, mid-term transition, and late stable (Guo Jingjing, Di Kaixiang. Research on the imbibition law of fracturing fluid under in-situ conditions in shale support fractures based on nuclear magnetic resonance (NMR) - Taking the Longmaxi Formation shale in southern Sichuan as an example [C]. Proceedings of the 33rd National Natural Gas Academic Annual Conference (2023) (03 Unconventional Gas Reservoirs), 2023: 154-169.); Sun Yuping et al. pointed out that different surfactants have a significant effect on the imbibition time of shale (Sun Yu Ping, Wang Xuewu, Chang Cheng, et al. Research on the dynamic law of shale core imbibition based on nuclear magnetic resonance technology [C]. Proceedings of the 33rd National Natural Gas Academic Annual Conference (2023) (03 Unconventional Gas Reservoirs), 2023: 569-576.); Guo Jianchun et al. experimentally proposed the dynamic spatial distribution law of porosity in shale and the effect of migration state on shale imbibition (Guo Jianchun, Tao Liang, Hu Kejian, et al. Experimental law of water phase imbibition in shale reservoirs [J]. Acta Petrolei Sinica, 2022, 43(09): 1295-1304.).

[0004] The above experiments did not clearly define the quantitative relationship to find the corresponding stage of shale water-rock interaction, and did not use continuous nuclear magnetic resonance to test the hydrogen spectrum corresponding to shale absorption. The present invention uses the relationship between continuous nuclear magnetic resonance and quantitative equations, controls the experimental error through multiple core samples of the corresponding reservoir, and combines the mathematical processing method of factor analysis to clarify the stage of shale water-rock interaction. Summary of the invention

[0005] In view of this, the present invention proposes a method for dividing the stages of shale water-rock interaction through continuous nuclear magnetic resonance testing. According to the conversion of nuclear magnetic resonance hydrogen spectrum, the curve relationship between the water-filled pores and the immersion time of the core sample is obtained to further determine the staged water-rock interaction mechanism and accurately evaluate the stage of shale hydration.

[0006] The technical solution adopted by the present invention to solve the above problem is a method for dividing the shale water-rock interaction stages by continuous nuclear magnetic resonance testing, comprising the following steps:

[0007] Step S1: selecting multiple groups of core samples of the same target reservoir from which bound water has been removed by drying to conduct liquid nitrogen adsorption and gas permeability tests;

[0008] Step S2: fully saturating each group of core samples with simulated formation water, and performing continuous nuclear magnetic resonance hydrogen spectrum tests on the saturated cores to obtain the liquid nitrogen adsorption amount and nuclear magnetic resonance T2 spectrum relaxation signal corresponding to each group of core samples;

[0009] Step S3: converting the nuclear magnetic resonance T2 spectrum relaxation signal of each group of core samples into the relationship between pore size distribution and immersion time, and further fitting to obtain the porosity-time variation curve of each group of core samples;

[0010] Step S4: Deriving the porosity-time variation curve of each group of core samples, respectively, to obtain the derivatives corresponding to the porosity-time variation curve of each group of core samples, and then selecting the immersion time corresponding to the derivatives f'(x)=0 and f'(x)=2 corresponding to each group of core samples for factor analysis, to obtain the principal component matrix containing the factor coefficients;

[0011] Step S5: Perform arithmetic averaging on the result values ​​in the principal component matrix, and then weight the average value according to the immersion time corresponding to each group of core derivatives f'(x)=0 and f'(x)=2 to obtain the final rock sample porosity and imbibition time formula, and use the final rock sample porosity and imbibition time formula to calculate the imbibition time corresponding to different derivatives after weighted averaging, and divide the water-rock interaction stage of the core sample.

[0012] The specific effects of the present invention are:

[0013] (1) The present invention can be measured by continuous nuclear magnetic resonance, without measuring experimental data in stages, and the method is simple and easy to understand.

[0014] (2) The data processing method in the present invention takes into account the inaccurate precision caused by experimental errors. Through this mathematical data processing method, the accuracy of the imbibition process can be further improved, and the time period and time point of the imbibition effect at each stage can be clarified. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below.

[0016] Figure 1 is a time variation curve function of the porosity corresponding to the immersion time of the rock sample 1 in the present invention;

[0017] Figure 2 is a time variation curve function of the porosity corresponding to the immersion time of the rock sample 2 in the present invention;

[0018] Figure 3 It is the time variation curve function of the porosity corresponding to the immersion time of the rock sample 3 in the present invention. DETAILED DESCRIPTION

[0019] In order to facilitate those skilled in the art to better understand the present invention, the present invention is further described in detail below in conjunction with embodiments and drawings, but the embodiments of the present invention are not limited thereto.

[0020] Example:

[0021] Step S1: Select three groups of core samples of the same target reservoir from which bound water has been removed by drying, and record them as rock sample 1, rock sample 2 and rock sample 3, respectively, and conduct liquid nitrogen adsorption and gas permeability tests. The test methods are the same as the liquid nitrogen adsorption and gas permeability test methods in the prior art.

[0022] Step S2: determine the test time range, fully saturate each group of core samples with simulated formation water, and perform continuous nuclear magnetic resonance hydrogen spectrum tests on the saturated cores. The test time range in this embodiment is determined to be 0 to 200 hours. In the time period of 0 to 3 hours, the nuclear magnetic resonance T2 spectrum is tested every 0.25 hours. After 3 hours, the nuclear magnetic resonance T2 spectrum is tested every 1 hour until the nuclear magnetic resonance hydrogen spectrum area is stable. After stabilization, select a group of time periods from 12 hours and 24 hours as the test time interval to test the nuclear magnetic resonance T2 spectrum once until the hydrogen spectrum area does not change significantly, and obtain the liquid nitrogen adsorption amount and nuclear magnetic resonance T2 spectrum relaxation signal corresponding to each group of core samples. The test time points in this embodiment are 0.5 hours, 1 hours, 2 hours, 3 hours, 5 hours, 9 hours, 15 hours, 24 hours, 48 ​​hours, and 168 hours, respectively.

[0023] Step S3: converting the nuclear magnetic resonance T2 spectrum relaxation signal of each group of core samples into the relationship between pore size distribution and immersion time, and further fitting to obtain the porosity-time variation curve of each group of core samples, wherein the conversion formula between nuclear magnetic resonance hydrogen spectrum relaxation signal and pore size distribution is shown in formula (3):

[0024]

[0025] In formula (3), T2 is the fluid relaxation time, ms;

[0026] ρ2——fluid relaxation rate, μm / ms;

[0027] F g ——dimensionless;

[0028] r——pore size, μm;

[0029] After obtaining the pore size distribution of the rock sample, the pore size at the same time point is summed to further obtain the curve relationship between the porosity of the rock sample and the immersion time change, as shown in formula (4):

[0030]

[0031] In the formula, —Porosity corresponding to time period i, %;

[0032] r i —Aperture corresponding to time period i, μm;

[0033] The relationship between the porosity of rock sample 1 and time in this embodiment is shown in Table 1:

[0034] Table 1 Relationship between porosity and immersion time of rock sample 1

[0035] Test time (h) 0.5 1 2 3 5 Porosity(%) 2.592 3.291 3.794 3.970 4.113 Test time (h) 9 15 24 48 168 Porosity(%) 4.139 4.160 4.149 4.147 4.125

[0036] The relationship between the porosity of rock sample 2 and the immersion time is shown in Table 2:

[0037] Table 2 Relationship between porosity and immersion time of rock sample 2

[0038] Test time (h) 0.5 1 2 3 5 Porosity(%) 2.180 2.891 3.364 3.507 3.651 Test time (h) 9 15 24 48 168 Porosity(%) 3.721 3.752 3.753 3.726 3.693

[0039] The relationship between the porosity of rock sample 3 and the immersion time is shown in Table 3:

[0040] Table 3 Relationship between porosity and immersion time of rock sample 3

[0041] Test time (h) 0.5 1 2 3 5 Porosity(%) 2.436 2.911 3.327 3.417 3.539 Test time (h) 9 15 24 48 168 Porosity(%) 3.611 3.635 3.651 3.642 3.637

[0042] In order to fully obtain the results of other points of the curve, linear interpolation is performed on the basis of formula (4). The specific steps are as follows. Linear interpolation is used to approximate the values ​​of other points with the known function f. The error line of the approximate method is shown in formula (5):

[0043] R T =f(x)-ρ(x) (5)

[0044] In the formula, R T —Interpolation error line, dimensionless;

[0045] f(x) — primitive function, dimensionless;

[0046] ρ(x)—linear interpolation polynomial, dimensionless;

[0047] Where ρ(x) can be expressed as the result shown in formula (6):

[0048]

[0049] In the formula, x0 and x1 are the abscissas of the interpolation points;

[0050] f(x1) and f(x0) are the ordinates of the interpolation points;

[0051] The error range is expressed as shown in Equation (7):

[0052]

[0053] In the formula, x0 and x1 are the abscissas of the interpolation points;

[0054] f’(x) is the derivative of the original function;

[0055] R T —is the error range.

[0056] Interpolate the above data using the linear interpolation method. The interpolation time points are 0.25 h, 0.75 h, 7 h, 12 h, 19 h, 36 h, 96 h, and 200 h. Use Equations (5) to (7) to fit the porosity-time change curves of each core sample.

[0057] Step S4: Differentiate the porosity-time change curve of each core sample to obtain the derivative corresponding to the porosity-time change curve of each core sample. According to the shale water-rock interaction situation, use the soaking moments corresponding to f’(x) = 0 and f’(x) = 2 as the separation points to divide the porosity-time change curve of the core sample into three stages. Then, select the soaking moments corresponding to f’(x) = 0 and f’(x) = 2 of each core sample for factor analysis to obtain the principal component matrix containing factor coefficients. The analysis software used in this embodiment is SPSS. Among them, the factors include the pore size spatial distribution, pore size, and influence of clay mineral swelling of the core sample;

[0058] Obtain the porosity-time change curve function through three groups of experimental data, calculate the derivative of the porosity-time change curve to obtain f'(x). Determine the range of f'(x) values according to the definition of the water-rock interaction stage separation point in the existing literature. Specifically: when f'(x) > 2, it is the shale undergoing pressurized saturation, spontaneous imbibition, and water-rock interaction; when 0 < f'(x) < 2, the shale undergoes spontaneous imbibition and water-rock interaction; when f'(x) < 0, the shale only undergoes water-rock interaction.

[0059] The pore size spatial distribution in the factor is characterized by the percentage of the peak area of nuclear magnetic resonance hydrogen spectrum, as shown in Equation (8):

[0060]

[0061] In Equation (8): A i—NMR hydrogen spectrum peak area percentage, %;

[0062] a i —NMR hydrogen spectrum peak area corresponding to each core sample;

[0063] The pore size in the factor is calculated by taking the amount of liquid nitrogen as the adsorption mass equivalent to the pore volume, as shown in formula (9):

[0064]

[0065] In formula (9): r K —Kelvin radius;

[0066] P—nitrogen partial pressure, MPa;

[0067] P0—liquid nitrogen saturation partial pressure, MPa;

[0068] The effect of clay mineral expansion in the factor is characterized by the ratio of the volume of imbibed liquid to the core mass, as shown in formula (10):

[0069]

[0070] In formula (10): V i —Imbsorbed liquid volume, cm 3 ;

[0071] M—rock sample mass, g;

[0072] P c —capillary pressure, Pa;

[0073] K w —gas permeability of rock samples, mD;

[0074] μ W —Liquid viscosity, pa·s;

[0075] φ i —Porosity corresponding to time i, %;

[0076] Sw water saturation;%,

[0077] A i Rock sample surface area; cm 2

[0078] t—corresponding immersion time of shale, h.

[0079] The factor analysis model is shown in formula (1):

[0080] x=Af+ε (1)

[0081] In formula (1), f is the unobservable mutual influence factor between factors, which is dimensionless; A is the pore size spatial distribution, pore size, and clay mineral influence factor loading matrix, which is dimensionless; ε is a special factor, which is dimensionless;

[0082] When calculating, formula (1) can be written as the specific form shown in formula (11):

[0083]

[0084] See also Figure 1 to Figure 3 In this embodiment, the immersion time corresponding to the independent variables x=0 and x=2 in the derivative corresponding to each group of core samples is specifically shown in Table 4:

[0085] Table 4 Immersion schedule when the derivative of the porosity time variation curve is 0 and 2

[0086] Rock sample group Rock sample 1 Rock sample 2 Rock sample 3 f'(x)=0 immersion time (h) 20.588 19.634 23.765 f'(x)=2immersion time (h) 6.732 6.489 6.156

[0087] Formulas (8) to (10) are used to calculate the pore size spatial distribution, pore size, and clay mineral expansion effect corresponding to the immersion time of each group of rock samples, and then they are brought into the factor loading matrix A shown in formula (11) for calculation. The factor loading matrix A in this embodiment is specifically shown in formula (12):

[0088]

[0089] On this basis, the corresponding factor coefficients of pore space distribution, pore size, and clay mineral expansion are analyzed and the principal component matrix is ​​constructed using the factor coefficients, as shown in Table 5:

[0090] Table 5 Principal component matrix

[0091] Element Factor coefficient Aperture spatial distribution 0.943 Aperture size 0.924 Clay mineral effects 0.958

[0092] Step S5: Perform arithmetic averaging on the result values ​​in the principal component matrix, and then weight the average value according to the immersion time corresponding to each group of core derivatives f'(x)=0 and f'(x)=2 to obtain the final rock sample porosity and imbibition time formula, and use the final rock sample porosity and imbibition time formula to calculate the imbibition time corresponding to different derivatives after weighted averaging, and divide the water-rock interaction stage of the core sample. The final rock sample porosity and imbibition time formula is shown in formula (2):

[0093] f(t)=at ij +bt ij +ct ij (0≤t ij ≤200, i=1, 2, 3, j=0, 2) (2)

[0094] In formula (2), f(t) is the imbibition time corresponding to different derivatives after weighted average, h;

[0095] a, b, c—arithmetic mean of factor coefficients in the principal component matrix, dimensionless, t ij is the weighted time when the corresponding derivative in the i-th group of samples is j, i is the number of sample groups, and j is the derivative corresponding to each group of core samples.

[0096] The number of samples tested in this embodiment is 3 groups. Combined with the above matrix calculation results, the final rock sample porosity and imbibition time formula obtained in this embodiment is shown in formula (13):

[0097] f(t)=0.334t 1j +0.327t 2j +0.339t 3j (0≤t i ≤200, j=0, 2) (13)

[0098] Substituting the soaking time in Table 4 into formula (13), we can calculate that the time interval Δt1 is the time period of shale pressure saturation and spontaneous imbibition, Δt2 is the time period of shale spontaneous soaking, and Δt3 is the time period of shale water-rock interaction, as shown in formulas (14) to (18):

[0099] After substituting the immersion time when the derivative of the porosity time variation curve shown in Table 4 is 2 into formula (13), the weighted average imbibition time t1 when the derivative is 2 is obtained. The specific result is shown in formula (14):

[0100] t1=0.334×6.732+0.327×6.489+0.339×6.156=6.457h (14)

[0101] After substituting the immersion time when the derivative of the porosity time variation curve shown in Table 4 is 0 into formula (13), the weighted average imbibition time t2 when the derivative is 0 is obtained. The specific result is shown in formula (14):

[0102] t2=0.334×20.588+0.327×19.634+0.339×23.765=21.353h (15)

[0103] The division process of the water-rock interaction stage of the core sample is shown in equations (16) to (18) by the weighted average imbibition time t1 when the derivative on the porosity time variation curve is 2 and the weighted average imbibition time t2 when the derivative on the porosity time variation curve is 0:

[0104] Δt1=t1-0=6.457h (16)

[0105] Δt2=t2-t1=14.896h (17)

[0106] Δt3=t max -t2=178.647h (18)

[0107] In formula (18), t max is the maximum value in the test time range. In this embodiment, t max =200h.

[0108] It can be obtained that the shale pressure saturation time and spontaneous imbibition period Δt1 is 6.457h, the shale spontaneous imbibition time period Δt2 is 14.354h, and the shale water-rock interaction time period Δt3 is 178.647h.

[0109] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the embodiments of the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for dividing shale water-rock interaction stages by continuous nuclear magnetic resonance testing, characterized in that: The following steps are involved: Step S1: selecting multiple groups of core samples of the same target reservoir from which bound water has been removed by drying to conduct liquid nitrogen adsorption and gas permeability tests; Step S2: determining the test time range, fully saturating each group of core samples with simulated formation water, and performing continuous nuclear magnetic resonance hydrogen spectrum tests on the saturated cores to obtain the liquid nitrogen adsorption amount and nuclear magnetic resonance T2 spectrum relaxation signal corresponding to each group of core samples; Step S3: converting the nuclear magnetic resonance T2 spectrum relaxation signal of each group of core samples into the relationship between pore size distribution and immersion time, and further fitting to obtain the porosity-time variation curve of each group of core samples; Step S4: Deriving the porosity-time variation curve of each group of core samples, respectively, to obtain the derivatives corresponding to the porosity-time variation curve of each group of core samples, and then selecting the immersion time corresponding to the derivatives f'(x)=0 and f'(x)=2 corresponding to each group of core samples for factor analysis, to obtain a principal component matrix containing factor coefficients, wherein the factors include the pore size spatial distribution, pore size, and clay mineral expansion effect of the core samples; The factor analysis model is shown in formula (1): x=Af+ε (1) In formula (1), f is the unobservable mutual influence factor between factors, which is dimensionless; A is the pore size spatial distribution, pore size, and clay mineral influence factor loading matrix, which is dimensionless; ε is a special factor, which is dimensionless; Step S5: Perform arithmetic averaging on the result values ​​in the principal component matrix, and then weight the average value according to the immersion time corresponding to each group of core derivatives f'(x)=0 and f'(x)=2 to obtain the final rock sample porosity and imbibition time formula, and use the final rock sample porosity and imbibition time formula to calculate the imbibition time corresponding to different derivatives after weighted averaging, and divide the water-rock interaction stage of the core sample. The final rock sample porosity and imbibition time formula is shown in formula (2): f(t)=at ij +bt ij +ct ij (0≤t ij ≤200,i=1、2、3,j=0、2) (2) In formula (2), f(t) is the imbibition time corresponding to different derivatives after weighted average, h; a, b, c—arithmetic mean of factor coefficients in the principal component matrix, dimensionless, t ij is the weighted time when the corresponding derivative in the i-th group of samples is j, i is the number of sample groups, and j is the derivative corresponding to each group of core samples.

2. The method for dividing shale water-rock interaction stages by continuous nuclear magnetic resonance testing according to claim 1, characterized in that: The number of core samples selected in step S1 is 3 groups.

3. The method for dividing shale water-rock interaction stages by continuous nuclear magnetic resonance testing according to claim 1, characterized in that: The test time range described in step S2 is 0 to 200 hours.

4. The method for dividing shale water-rock interaction stages by continuous nuclear magnetic resonance testing according to claim 1, characterized in that: The continuous H NMR spectrum testing method described in step S2 is: within the time period of 0 to 3 hours, the H NMR spectrum is tested once every 0.25 hours, and after 3 hours, the H NMR spectrum is tested once every 1 hour until the H NMR spectrum area is stable. After stabilization, a group of time periods are selected between 12 hours and 24 hours as the test time interval to test the H NMR spectrum once until the test time range is exceeded.

5. The method for dividing shale water-rock interaction stages by continuous nuclear magnetic resonance testing according to claim 1, characterized in that: The fitting method described in step S3 is linear interpolation.

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