Shale movable fluid signal correction method and device, electronic equipment and storage medium

Abstract

The present disclosure provides a shale movable fluid signal correction method and device, electronic equipment and storage medium, wherein the method comprises: obtaining a shale sample to be tested; performing a nuclear magnetic resonance test on the shale sample to be tested to obtain an actual one-dimensional nuclear magnetic spectrum and an actual two-dimensional nuclear magnetic spectrum; the actual one-dimensional nuclear magnetic spectrum and the actual two-dimensional nuclear magnetic spectrum include movable fluid signals; constructing an ideal two-dimensional nuclear magnetic spectrum of the shale sample to be tested; forward modeling the ideal two-dimensional nuclear magnetic spectrum to obtain an echo train signal; inverting the echo train signal to obtain an inverted nuclear magnetic spectrum; based on the inverted nuclear magnetic spectrum and the ideal two-dimensional nuclear magnetic spectrum, determining a waiting time correction factor and an inversion correction factor; based on the waiting time correction factor and the inversion correction factor, correcting the movable fluid signals in the actual one-dimensional nuclear magnetic spectrum and the actual two-dimensional nuclear magnetic spectrum.

Description

Technical Field

[0001] This disclosure relates to the field of oil and gas development technology, and in particular to a method, apparatus, electronic device and storage medium for correcting movable fluid signals in shale. Background Technology

[0002] Accurate evaluation of unconventional resources such as shale oil and gas is crucial for ensuring national energy security, with mobile fluids being a major contributor to production. Nuclear magnetic resonance (NMR) technology, due to its advantages of being rapid, non-destructive, and capable of specifically detecting hydrogen-containing components such as oil, gas, water, and organic matter, has become a core tool for evaluating the pore structure and fluid occurrence of shale oil and gas reservoirs. In practical applications, because mobile fluids in shale typically have large pore sizes and the longest lateral relaxation time T2 and longitudinal relaxation time T1, the complete detection of their NMR signals highly depends on two key aspects: first, the waiting time (TW) in the acquisition parameters must be long enough to ensure complete fluid polarization; second, the inversion algorithm must have sufficiently high accuracy to accurately separate weak-signal, long-relaxation mobile fluid peaks against a background of strong-signal, short-relaxation components (such as kerogen, bitumen, and adsorbed fluids), avoiding significant underestimation of mobile fluids due to "peak swallowing."

[0003] However, as shale oil and gas evaluation delves deeper into in-situ environments such as well sites and logging, the requirements for testing efficiency are becoming increasingly stringent. Long waiting times and multi-dimensional data acquisition significantly extend the time required for a single test, impacting operational efficiency and leading to instrument overheating and core signal loss. Furthermore, frontline operators have long relied on fixed, experience-based inversion algorithms and parameter systems to ensure the comparability and stability of results, making changes to these algorithms or parameters extremely difficult in engineering practice. Summary of the Invention

[0004] This disclosure provides a method, apparatus, electronic device, and storage medium for correcting movable fluid signals in shale, thereby at least solving the above-mentioned technical problems existing in the prior art.

[0005] According to a first aspect of this disclosure, a method for correcting movable fluid signals in shale is provided, the method comprising: Obtain the shale sample to be tested; The shale sample to be tested was subjected to nuclear magnetic resonance (NMR) testing to obtain actual one-dimensional NMR spectrum and actual two-dimensional NMR spectrum; the actual one-dimensional NMR spectrum and the actual two-dimensional NMR spectrum include mobile fluid signals; Construct the ideal two-dimensional nuclear magnetic resonance spectrum of the shale sample to be tested; The ideal two-dimensional nuclear magnetic resonance spectrum was forward modeled to obtain the echo train signal; The echo train signal is inverted to obtain the inverted nuclear magnetic spectrum; Based on the inverted NMR spectrum and the ideal two-dimensional NMR spectrum, the waiting time correction factor and the inversion correction factor are determined. Based on the waiting time correction factor and the inversion correction factor, the movable fluid signal in the actual one-dimensional NMR spectrum and the actual two-dimensional NMR spectrum is corrected.

[0006] In one possible implementation, constructing the ideal two-dimensional NMR spectrum of the shale sample to be tested includes: The nuclear magnetic resonance signals of the shale sample to be tested are divided into solid framework signals, adsorbed oil signals, bound oil signals and mobile fluid signals; Obtain the ideal values ​​of each parameter in the solid skeleton signal, adsorbed oil signal, bound oil signal and movable fluid signal; Based on the ideal values ​​of each parameter, the solid skeleton signal, adsorbed oil signal, bound oil signal and movable fluid signal are accumulated by a two-dimensional Gaussian function to obtain an ideal two-dimensional nuclear magnetic spectrum.

[0007] In one possible implementation, the solid framework signal, adsorbed oil signal, bound oil signal, and mobile fluid signal are summed based on the following formula to obtain an ideal two-dimensional NMR spectrum:

[0008] in, The signal amplitude at each point in an ideal two-dimensional nuclear magnetic spectrum; , 1, 2, 3, ..., m, where m is the number of points. =1, 2, 3, ... , The number of signals; and They represent the first The first signal line, number The lateral relaxation time and longitudinal relaxation time of the array points; and The first The peak center of the transverse relaxation time and longitudinal relaxation time distribution of a signal; and Indicates the first The distribution width of the signal in the transverse relaxation time and longitudinal relaxation time directions; For the first The ideal signal amplitude of a signal.

[0009] In one possible implementation, the step of performing forward modeling on the ideal two-dimensional NMR spectrum to obtain the echo train signal includes: The echo train signal is obtained based on the following formula:

[0010] in, It is the waiting time; It is the echo time, determined by the echo interval. and echo number The calculation yielded that, ; It is the waiting time. With echo time The amplitude of the echo train signal below; It is the longitudinal relaxation time in an ideal two-dimensional NMR spectrum. Lateral relaxation time The signal amplitude below.

[0011] In one possible implementation, the step of inverting the echo train signal to obtain the inverted NMR spectrum includes: Multiple inverted one-dimensional nuclear magnetic spectra were obtained by inverting the one-dimensional echo train under several different first inversion conditions. Multiple inverted two-dimensional echo trains were obtained by inverting them under several different second inversion conditions.

[0012] In one possible implementation, determining the waiting time correction factor and the inversion correction factor based on the inverted NMR spectrum and the ideal two-dimensional NMR spectrum includes: Based on multiple inverted one-dimensional NMR spectra, the one-dimensional signal amplitude of the mobile fluid signal under optimal inversion conditions is determined; The one-dimensional waiting time correction factor is determined by the ratio of the ideal signal amplitude of the movable fluid signal in the ideal two-dimensional NMR spectrum to the one-dimensional signal amplitude of the movable fluid signal under the optimal inversion conditions. Based on multiple inverted one-dimensional NMR spectra, the one-dimensional signal amplitude of the mobile fluid signal under a first specific inversion condition is determined, wherein the first specific inversion condition is the same as the condition for obtaining the actual one-dimensional NMR spectrum. The one-dimensional inversion correction factor is determined by the ratio of the one-dimensional signal amplitude of the movable fluid signal under the optimal inversion condition to that under the first specific inversion condition. Based on multiple inverted two-dimensional NMR spectra, the two-dimensional signal amplitude of the mobile fluid signal under optimal inversion conditions is determined; The two-dimensional waiting time correction factor is determined by the ratio of the ideal signal amplitude of the movable fluid signal in the ideal two-dimensional NMR spectrum to the two-dimensional signal amplitude of the movable fluid signal under the optimal inversion conditions. Based on multiple inverted two-dimensional NMR spectra, the two-dimensional signal amplitude of the mobile fluid signal under a second specific inversion condition is determined, wherein the second specific inversion condition is the same as the condition for obtaining the actual two-dimensional NMR spectrum. The two-dimensional inversion correction factor is determined by the ratio of the two-dimensional signal amplitude of the movable fluid signal under the optimal inversion condition to that under the second specific inversion condition.

[0013] In one possible implementation, the correction of the mobile fluid signal in the actual one-dimensional NMR spectrum and the actual two-dimensional NMR spectrum based on the waiting time correction factor and the inversion correction factor includes: Based on the one-dimensional waiting time correction factor and the one-dimensional inversion correction factor, the mobile fluid signal in the actual one-dimensional NMR spectrum is corrected; The movable fluid signal in the actual two-dimensional NMR spectrum is corrected based on the two-dimensional waiting time correction factor and the two-dimensional inversion correction factor.

[0014] According to a second aspect of this disclosure, a shale movable fluid signal correction device is provided, the device comprising: Acquisition unit, used to acquire shale samples to be tested; The testing unit is used to perform nuclear magnetic resonance testing on the shale sample to be tested, and to obtain actual one-dimensional nuclear magnetic spectrum and actual two-dimensional nuclear magnetic spectrum; the actual one-dimensional nuclear magnetic spectrum and the actual two-dimensional nuclear magnetic spectrum include mobile fluid signals; The construction unit is used to construct the ideal two-dimensional nuclear magnetic spectrum of the shale sample to be tested. The forward modeling unit is used to perform forward modeling on the ideal two-dimensional nuclear magnetic spectrum to obtain the echo train signal; The inversion unit is used to invert the echo train signal to obtain the inverted nuclear magnetic spectrum; The determining unit is used to determine the waiting time correction factor and the inversion correction factor based on the inverted NMR spectrum and the ideal two-dimensional NMR spectrum; The correction unit is used to correct the movable fluid signal in the actual one-dimensional NMR spectrum and the actual two-dimensional NMR spectrum based on the waiting time correction factor and the inversion correction factor.

[0015] According to a third aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and a memory communicatively connected to said at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the methods described in this disclosure.

[0016] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions for causing a computer to perform the methods described in this disclosure.

[0017] Technical Effects: The shale movable fluid signal correction method, device, electronic equipment, and storage medium disclosed herein obtain an echo train through forward modeling using an ideal two-dimensional NMR spectrum. An inverted NMR spectrum is then obtained by inverting the echo train. Based on the inverted NMR spectrum and the ideal two-dimensional NMR spectrum, a waiting time correction factor and an inversion correction factor are derived. These two correction factors are then used to correct the actual movable fluid signal. The waiting time correction factor quantitatively compensates for fluid polarization losses caused by short waiting times, without extending the test duration or sacrificing on-site operational efficiency. The inversion correction factor accurately offsets signal deviations caused by a fixed inversion system, without requiring modifications to the long-standing inversion algorithms and parameters used in the field. This method significantly improves the accuracy of NMR testing of shale movable fluids without increasing test time or using conventional inversion algorithms and parameters, demonstrating good universality and transferability.

[0018] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0019] The above and other objects, features, and advantages of this disclosure will become readily apparent from the following detailed description of exemplary embodiments, taken in conjunction with the accompanying drawings. Several embodiments of this disclosure are illustrated in the drawings by way of example and not limitation, in which: In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts.

[0020] Figure 1 A flowchart of a shale movable fluid signal correction method provided in this embodiment of the disclosure; Figure 2 This is the ideal two-dimensional nuclear magnetic resonance spectrum of the shale sample to be tested in the embodiments of this disclosure; Figure 3 Multiple two-dimensional echo trains with different waiting times; Figure 4 For a one-dimensional echo train with a waiting time of 3000ms; Figure 5 The one-dimensional spectrum obtained by using the SIRT algorithm in this embodiment of the disclosure is the inverted one-dimensional spectrum of the one-dimensional echo train. Figure 6 The one-dimensional spectrum obtained by using the BRD algorithm for the one-dimensional echo train in this embodiment of the present disclosure; Figure 7 The two-dimensional echo train in this embodiment of the present disclosure is the inverted two-dimensional spectrum obtained by the BRD algorithm. Figure 8 A graph showing the amplitude relationship between one-dimensional and two-dimensional NMR signals of the movable fluid before correction; Figure 9The amplitude relationship between one-dimensional and two-dimensional NMR signals of the corrected movable fluid signal; Figure 10 This is a schematic diagram of the structure of the shale movable fluid signal correction device provided in the embodiments of this disclosure; Figure 11 A schematic diagram of the composition structure of an electronic device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0021] To make the objectives, features, and advantages of this disclosure more apparent and understandable, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort are within the scope of protection of this disclosure.

[0022] This disclosure provides a method for correcting movable fluid signals in shale formation. Figure 1 A flowchart of the shale movable fluid signal correction method provided in the embodiments of this disclosure is shown below. Figure 1 As shown, the method includes: Step 101: Obtain the shale sample to be tested.

[0023] In this embodiment, shale oil reservoir core samples were selected as the research object. The core samples were first processed into standard cylinders using a waterless wire cutting process, with dimensions of 2.5 cm in diameter and 3 cm in length, totaling 12 samples. After processing, the core samples were washed with an oil-washing solution of acetone and dichloromethane at a volume ratio of 1:3, under the conditions of 85°C and 0.18 MPa. After washing, the core samples were placed in a vacuum drying oven and dried under vacuum at 110°C to thoroughly remove residual fluids. The dried core samples were then placed in a vacuum pressurization saturation device and vacuumed for 6 hours, followed by pressurization saturation treatment at 15 MPa to obtain shale samples in a saturated oil state. These saturated oil-state shale samples are the shale samples to be tested.

[0024] Step 102: Perform nuclear magnetic resonance (NMR) testing on the shale sample to be tested to obtain the actual one-dimensional NMR spectrum and the actual two-dimensional NMR spectrum; the actual one-dimensional NMR spectrum and the actual two-dimensional NMR spectrum include the signal of movable fluid.

[0025] After obtaining saturated oil-bearing shale samples, one-dimensional and two-dimensional nuclear magnetic resonance (NMR) tests were conducted. The resonance frequency of the NMR tests was approximately 12 MHz, and the magnetic field strength was 0.3 T ± 0.05 T. The one-dimensional NMR T2 test employed a Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence with an echo interval of T. EThe waiting time T is 0.07ms. w The time interval was 3000ms, the number of stacks (NS) was 32, and the number of echoes (NECH) was 8192. The two-dimensional T1-T2 test used a saturation recovery-carr-purcell-Meiboom-Gill (SR-CPMG) pulse sequence, which consisted of multiple CPMG echo trains with different waiting times. The number of echoes (NECH) was 4096, and the waiting time was set to 15 logarithmically uniform distribution points, ranging from 0.058 to 1000ms. The other parameters were consistent with the one-dimensional test.

[0026] The actual one-dimensional NMR spectrum, namely the T2 spectrum, of the shale sample under test was obtained by one-dimensional NMR testing; the actual two-dimensional NMR spectrum, namely the T1-T2 spectrum, of the shale sample under test was obtained by two-dimensional NMR testing.

[0027] Based on the two-dimensional T1-T2 spectral characteristics of saturated oil-bearing shale samples and combined with fluid identification charts, the NMR signals were divided into four typical component regions: Region A: solid framework signal (T2 < 0.1 ms); Region B: adsorbed oil signal (T2: 0.1~1 ms, T1>0.1 ms, T1 / T2≈2); Region C: bound oil signal (T2: 1~10 ms, T1>1 ms, T1 / T2≈5); Region D: mobile fluid signal (T2>10 ms, T1>10 ms). The mobile fluid is essentially mobile oil.

[0028] Step 103: Construct the ideal two-dimensional nuclear magnetic spectrum of the shale sample to be tested.

[0029] In this disclosure, because there are NMR signals of multiple components, it is necessary to accumulate the NMR signals of multiple components when constructing an ideal two-dimensional NMR spectrum.

[0030] In one embodiment, constructing an ideal two-dimensional NMR spectrum for a shale sample to be tested includes: The NMR signals of the shale samples to be tested were divided into solid framework signals, adsorbed oil signals, bound oil signals, and mobile fluid signals. Obtain the ideal values ​​of each parameter in the solid skeleton signal, adsorbed oil signal, bound oil signal and movable fluid signal; Based on the ideal values ​​of each parameter, the solid skeleton signal, adsorbed oil signal, bound oil signal and movable fluid signal are accumulated by a two-dimensional Gaussian function to obtain an ideal two-dimensional nuclear magnetic spectrum.

[0031] In one embodiment, the solid framework signal, adsorbed oil signal, bound oil signal, and mobile fluid signal are summed based on the following formula to obtain an ideal two-dimensional NMR spectrum:

[0032] in, The signal amplitude at each point in an ideal two-dimensional nuclear magnetic spectrum; , 1, 2, 3, ..., m, where m is the number of points. =1, 2, 3, ... , The number of signals (in this embodiment of the disclosure, (equals 4) and They represent the first The first signal line, number The lateral relaxation time and longitudinal relaxation time of the array points; and The first The peak center of the transverse relaxation time and longitudinal relaxation time distribution of a signal; and Indicates the first The distribution width of the signal in the transverse relaxation time and longitudinal relaxation time directions; For the first The ideal signal amplitude of each signal. Among them, =lnW, where W is used to adjust the broadening of the relaxation time distribution, therefore , , To regulate the first The degree of broadening of the transverse relaxation time distribution of a signal. To regulate the first The degree of broadening of the longitudinal relaxation time distribution of a signal.

[0033] Based on the actual saturated oil state of the core, four groups of hydrogen-containing components (solid framework, adsorbed oil, bound oil, and mobile fluid) were constructed. The ideal values ​​of the parameters for each signal were set as follows: Solid framework: ideal signal amplitude M=40. =0.04ms, T2 width W2=5, =1ms, T1 width W1=5; Adsorbed oil: ideal signal amplitude M=10. =0.5ms, T2 width W2=8, =0.8ms, T1 width W1=80; binding oil: ideal signal amplitude M=20, =4ms, T2 width W2=8 =20ms, T1 width W1=100; Movable oil: ideal signal amplitude M=2. =40ms, T2 width W2=5 =250ms, T1 width W1=8. Substitute these values ​​into the above formula, and obtain the ideal two-dimensional NMR spectrum of the shale sample to be tested by superposition (e.g., Figure 2 (As shown). Among them, Figure 2 The area below the dashed line L in the diagram is the no-signal area.

[0034] Understandably, the conditions Tw=3000ms and NECH=8192 can also be introduced to construct a theoretical one-dimensional NMR spectrum.

[0035] Step 104: Perform forward modeling on the ideal two-dimensional NMR spectrum to obtain the echo train signal.

[0036] In one embodiment, forward modeling of an ideal two-dimensional nuclear magnetic resonance spectrum is performed to obtain an echo train signal, including: The echo train signal is obtained based on the following formula:

[0037] in, It is the waiting time; It is the echo time, determined by the echo interval. and echo number The calculation yielded that, ; It is the waiting time. With echo time The amplitude of the echo train signal below; It is the longitudinal relaxation time in an ideal two-dimensional NMR spectrum. Lateral relaxation time The signal amplitude below.

[0038] Specifically, based on the aforementioned ideal two-dimensional NMR spectrum, the signal response mechanism of the SR-CPMG sequence is utilized to map the frequency domain relaxation spectrum to the time domain echo signal, thereby achieving forward modeling of the echo train. During the forward modeling process, the parameter settings remain consistent with the actual NMR test in step 102. =0.07ms, echo number =4096, the waiting time was evenly distributed between 0.058 and 1000ms using 15 logarithmic points, and the resulting two-dimensional echo train is as follows. Figure 3 As shown. Simultaneously, based on the theoretical one-dimensional T2 spectrum, the conditions Tw=3000ms and NECH=8192 are introduced into the forward modeling. The corresponding echo train is the CPMG sequence response, and the specific one-dimensional echo train obtained is shown below. Figure 4 As shown.

[0039] Step 105: Invert the echo train signal to obtain the inverted NMR spectrum.

[0040] After obtaining the two-dimensional and one-dimensional echo strings, different inversion algorithms and parameters are used for one-dimensional and two-dimensional inversions. Among the many algorithms, SIRT (Simultaneous Iterative Reconstruction Technique) and BRD (Butler–Reeds–Dawson) algorithms are commonly used in one-dimensional NMR inversion, while BRD is commonly used for two-dimensional NMR inversion. Therefore, the BRD algorithm can be used for two-dimensional NMR inversion, with the smoothing factor α set to 0.01, 0.1, 0.5, 1, 5, and 10 respectively. Either SIRT or BRD can be used for one-dimensional NMR inversion. In the SIRT algorithm, the parameter is the number of iterations N. iter The number of iterations is set to 5000, 10000, 20000, 50000, 100000, and 500000 in sequence. In the BRD algorithm, the smoothing factor α is set to 0.01, 0.1, 0.5, 1, 5, and 10 in sequence.

[0041] Under the aforementioned combinations of inversion parameters, the signal amplitudes of the mobile fluid signal in the one-dimensional T2 spectrum and the two-dimensional T1-T2 spectrum are extracted respectively, constructing signal response sets under different inversion strategies. Through a systematic comparison of signal amplitudes under different waiting time sampling strategies and inversion parameter conditions, it can be found that: when the waiting time distribution does not cover the long T1 range, the mobile fluid polarization recovery is insufficient; the SIRT algorithm tends to approximate the unregularized solution under high iteration counts, exhibiting strong recovery capability for long-relaxation components (mobile fluid); while the BRD algorithm, due to the introduction of smoothing constraints, has a certain suppressive effect on the long T2 component in its inversion results. Therefore, different waiting time conditions and different combinations of inversion parameters will jointly determine the final inverted signal amplitude. To eliminate the signal deviation caused by the waiting time and inversion parameters, this embodiment introduces a ratio correction method based on theoretical two-dimensional NMR spectra.

[0042] In one embodiment, the echo train signal is inverted to obtain the inverted NMR spectrum, including: Multiple inverted one-dimensional nuclear magnetic spectra were obtained by inverting the one-dimensional echo train under several different first inversion conditions. Multiple inverted two-dimensional echo trains were obtained by inverting them under several different second inversion conditions.

[0043] Figure 5 The one-dimensional spectrum obtained by using the SIRT algorithm in this embodiment of the disclosure is the inverted one-dimensional spectrum of the one-dimensional echo train. Figure 6 The one-dimensional spectrum obtained by using the BRD algorithm for the one-dimensional echo train in this embodiment of the present disclosure is an inverted one-dimensional spectrum.

[0044] In this embodiment of the disclosure, the one-dimensional echo train can be inverted using either the SIRT or BRD algorithm. Therefore, when selecting the SIRT algorithm, different first inversion conditions can be used to select different iteration numbers, such as 5000, 10000, 20000, 50000, 100000, and 500000. The resulting one-dimensional inversion spectrum is as follows: Figure 5 As shown; if the BRD algorithm is selected, different first inversion conditions result in different smoothing factors, such as 0.01, 0.1, 0.5, 1, 5, and 10. The resulting one-dimensional inversion spectrum is shown below. Figure 6 As shown.

[0045] Figure 7 The two-dimensional echo train in this embodiment of the present disclosure is the inverted two-dimensional spectrum obtained by the BRD algorithm.

[0046] In this embodiment of the device, the two-dimensional echo train can be inverted using the BRD algorithm. Therefore, different second inversion conditions can be different smoothing factors, such as 0.01, 0.1, 0.5, 1, 5, and 10. The resulting two-dimensional inversion spectrum is as follows: Figure 7 As shown.

[0047] After obtaining the inverted one-dimensional spectrum and the inverted two-dimensional spectrum, the signal amplitude of the movable fluid signal under different inversion conditions can be obtained based on the inverted one-dimensional spectrum and the inverted two-dimensional spectrum. For example, as shown in Table 1 below.

[0048] Table 1: Amplitudes of one-dimensional and two-dimensional NMR signals of movable fluid signals under different inversion conditions

[0049] Step 106: Based on the inverted NMR spectrum and the ideal two-dimensional NMR spectrum, determine the waiting time correction factor and the inversion correction factor.

[0050] In one embodiment, determining the waiting time correction factor and the inversion correction factor based on the inverted NMR spectrum and the ideal two-dimensional NMR spectrum includes: Based on multiple inverted one-dimensional NMR spectra, the one-dimensional signal amplitude of the mobile fluid signal under optimal inversion conditions is determined; The one-dimensional waiting time correction factor is determined by the ratio of the ideal signal amplitude of the movable fluid signal in the ideal two-dimensional NMR spectrum to the one-dimensional signal amplitude of the movable fluid signal under the optimal inversion conditions. Based on multiple inverted one-dimensional NMR spectra, the one-dimensional signal amplitude of the mobile fluid signal under a first specific inversion condition is determined, wherein the first specific inversion condition is the same as the condition for obtaining the actual one-dimensional NMR spectrum. The one-dimensional inversion correction factor is determined by the ratio of the one-dimensional signal amplitude of the movable fluid signal under the optimal inversion condition to that under the first specific inversion condition. Based on multiple inverted two-dimensional NMR spectra, the two-dimensional signal amplitude of the mobile fluid signal under optimal inversion conditions is determined; The two-dimensional waiting time correction factor is determined by the ratio of the ideal signal amplitude of the movable fluid signal in the ideal two-dimensional NMR spectrum to the two-dimensional signal amplitude of the movable fluid signal under the optimal inversion conditions. Based on multiple inverted two-dimensional NMR spectra, the two-dimensional signal amplitude of the mobile fluid signal under a second specific inversion condition is determined, wherein the second specific inversion condition is the same as the condition for obtaining the actual two-dimensional NMR spectrum. The two-dimensional inversion correction factor is determined by the ratio of the two-dimensional signal amplitude of the movable fluid signal under the optimal inversion condition to that under the second specific inversion condition.

[0051] Specifically, in an ideal two-dimensional NMR spectrum, the ideal signal amplitude M of the movable fluid signal can be obtained, for example, M=2. Then, by fixing the waiting time and changing the inversion algorithm and parameters, the inverted one-dimensional NMR spectrum and the inverted two-dimensional NMR spectrum under different inversion conditions can be obtained.

[0052] From the retrieved one-dimensional NMR spectrum, the one-dimensional signal amplitude of the movable fluid signal under optimal retrieval conditions and the one-dimensional signal amplitude of the movable fluid signal under the first specific retrieval conditions can be determined. Specifically, if the SIRT algorithm is used, then... Figure 5 As shown in Table 1, the optimal inversion condition is 500,000 iterations; if using the BRD algorithm, then... Figure 6 As shown in Table 1, the optimal inversion condition is a smoothing factor of 0.01. The first specific inversion condition is the same as the condition for obtaining the actual one-dimensional NMR spectrum. For example, if in step 102 the actual one-dimensional NMR spectrum is obtained using the SIRT algorithm with 10,000 iterations, then the first specific inversion condition is the SIRT algorithm with 10,000 iterations. After determining the optimal inversion condition and the first specific inversion condition, the one-dimensional signal amplitude of the movable fluid signal under these two conditions can be obtained.

[0053] Then, based on the ratio of the ideal signal amplitude of the mobile fluid signal in the ideal two-dimensional NMR spectrum to the one-dimensional signal amplitude of the mobile fluid signal under optimal inversion conditions, the one-dimensional waiting time correction factor is determined:

[0054] in, This is a one-dimensional waiting time correction factor. The ideal signal amplitude represents the mobile fluid signal in an ideal two-dimensional nuclear magnetic resonance spectrum. The amplitude of the moving fluid signal under optimal inversion conditions is a one-dimensional signal amplitude.

[0055] The one-dimensional inversion correction factor is determined by the ratio of the one-dimensional signal amplitude of the movable fluid signal under optimal inversion conditions to that under the first specific inversion conditions.

[0056] in, This is a one-dimensional inversion correction factor. The amplitude of the moving fluid signal under the first specific inversion condition is a one-dimensional signal amplitude.

[0057] From the inverted two-dimensional NMR spectrum, the two-dimensional signal amplitudes of the movable fluid signal under optimal inversion conditions and under second-specific inversion conditions can be determined. The two-dimensional inversion employs the BRD algorithm, such as... Figure 7 As shown in Table 1, the optimal inversion condition is a smoothing factor of 0.01. The second specific inversion condition is the same as the condition for obtaining the actual two-dimensional NMR spectrum. For example, if in step 102 the actual two-dimensional NMR spectrum is obtained using the BRD algorithm with a smoothing factor of 1, then the second specific inversion condition is the BRD algorithm with a smoothing factor of 1. After determining the optimal inversion condition and the second specific inversion condition, the two-dimensional signal amplitude of the movable fluid signal under these two conditions can be obtained.

[0058] The two-dimensional waiting time correction factor is determined based on the ratio of the ideal signal amplitude of the mobile fluid signal in the ideal two-dimensional NMR spectrum to the two-dimensional signal amplitude of the mobile fluid signal under optimal inversion conditions.

[0059] in, This is a two-dimensional waiting time correction factor. The amplitude of the two-dimensional signal of the movable fluid signal under optimal inversion conditions.

[0060] The two-dimensional inversion correction factor is determined by the ratio of the two-dimensional signal amplitude of the movable fluid signal under the optimal inversion condition to that under the second specific inversion condition.

[0061] in, This is the two-dimensional inversion correction factor. The amplitude of the two-dimensional signal of the movable fluid signal under the second specific inversion condition is given.

[0062] In one specific embodiment, the actual one-dimensional NMR spectrum is corrected using the SIRT algorithm (10,000 iterations) and the actual two-dimensional NMR spectrum is corrected using the BRD algorithm (smoothing factor = 1).

[0063] In an ideal two-dimensional NMR spectrum, the ideal signal amplitude M=2 for the movable fluid signal can be obtained. Taking the SIRT algorithm as an example, in the inversion of a one-dimensional NMR spectrum, the optimal inversion condition is 500,000 iterations, yielding a movable oil signal amplitude of 1.883. The first specific inversion condition is 10,000 iterations, yielding a movable oil signal amplitude of 0.879. Therefore, the one-dimensional waiting time correction factor and the one-dimensional inversion correction factor can be obtained:

[0064]

[0065] In the inversion of two-dimensional NMR spectra, taking the BRD algorithm as an example, the optimal inversion condition is a smoothing factor of 0.01, under which the amplitude of the movable oil signal is 1.7805; the second specific inversion condition is a smoothing factor of 1, under which the amplitude of the movable oil signal is 1.5521. Therefore, the two-dimensional waiting time correction factor and the two-dimensional inversion correction factor can be obtained:

[0066]

[0067] Step 107: Based on the waiting time correction factor and the inversion correction factor, correct the movable fluid signal in the actual one-dimensional NMR spectrum and the actual two-dimensional NMR spectrum.

[0068] In one embodiment, the movable fluid signal in the actual one-dimensional NMR spectrum and the actual two-dimensional NMR spectrum is corrected based on the waiting time correction factor and the inversion correction factor, including: Based on the one-dimensional waiting time correction factor and the one-dimensional inversion correction factor, the mobile fluid signal in the actual one-dimensional NMR spectrum is corrected; Based on the two-dimensional waiting time correction factor and the two-dimensional inversion correction factor, the movable fluid signal in the actual two-dimensional NMR spectrum is corrected.

[0069] Specifically, a one-dimensional waiting time correction factor and a one-dimensional inversion correction factor are coupled to correct the mobile fluid signal in the actual one-dimensional NMR spectrum:

[0070] in, The amplitude of the mobile fluid signal in the actual one-dimensional NMR spectrum after correction. This represents the signal amplitude of the movable fluid signal in a real one-dimensional nuclear magnetic resonance spectrum.

[0071] The two-dimensional waiting time correction factor and the two-dimensional inversion correction factor are coupled to correct the mobile fluid signal in the actual two-dimensional NMR spectrum:

[0072] in, The signal amplitude of the movable fluid signal in the corrected actual two-dimensional NMR spectrum. This represents the signal amplitude of the movable fluid signal in the actual two-dimensional nuclear magnetic resonance spectrum.

[0073] Figure 8 The diagram shows the amplitude relationship between the one-dimensional and two-dimensional NMR signals of the movable fluid signal before correction. Figure 9 The amplitude relationship between one-dimensional and two-dimensional NMR signals of the corrected movable fluid signal is shown in the figure.

[0074] like Figure 8 and Figure 9 As shown, the horizontal axis x represents the two-dimensional signal amplitude of the movable fluid signal, and the vertical axis y represents the one-dimensional signal amplitude of the movable fluid signal. Under ideal conditions, the one-dimensional signal amplitude and the two-dimensional signal amplitude of the same shale sample should be equal, and the corresponding linear relationship is y=x.

[0075] from Figure 8 It can be seen that the linear relationship between the amplitudes of the one-dimensional and two-dimensional signals before correction is y=0.5435x. The amplitudes of the one-dimensional and two-dimensional NMR signals before correction are inconsistent, with the two-dimensional NMR signal amplitude being significantly higher. This indicates that the inversion algorithm and parameters have a significant impact on the amplitudes of the one-dimensional and two-dimensional movable fluid signals. Figure 9 It can be seen that the linear relationship between the amplitudes of the one-dimensional and two-dimensional signals after correction is y = 0.9598x. The amplitude of the movable fluid signal after correction is significantly increased, and the amplitudes of the one-dimensional and two-dimensional NMR signals are basically consistent, verifying the accuracy of the method in this disclosure. The coefficient of determination R0 for the two graphs before and after correction is shown. 2 R represents the goodness of fit between the one-dimensional signal amplitude and the two-dimensional signal amplitude. 2 The closer the value is to 1, the closer the point corresponding to each sample is to the fitted straight line, and the stronger the linear correlation between the one-dimensional signal amplitude and the two-dimensional signal amplitude. The coefficient of determination R between the two graphs before and after correction. 2 Both are 0.8926, indicating that the intrinsic linear correlation of the samples remains unchanged, and the correction only changes the slope and does not change the correlation trend of the data itself.

[0076] In this disclosure, an echo train is obtained through forward modeling using an ideal two-dimensional NMR spectrum. An inverted NMR spectrum is then obtained by inverting the echo train. Based on the inverted NMR spectrum and the ideal two-dimensional NMR spectrum, a waiting time correction factor and an inversion correction factor are derived. These two correction factors are then used to correct the actual movable fluid signal. The waiting time correction factor quantitatively compensates for fluid polarization losses caused by short waiting times, without extending the test duration or sacrificing on-site operational efficiency. The inversion correction factor accurately offsets signal deviations caused by a fixed inversion system, without requiring modifications to the long-standing inversion algorithms and parameters used in the field. This method significantly improves the accuracy of NMR testing of movable shale fluids without increasing test time or using conventional inversion algorithms and parameters, demonstrating good universality and transferability.

[0077] This disclosure also provides a shale movable fluid signal correction device. Figure 10 This is a schematic diagram of the structure of the shale movable fluid signal correction device provided in the embodiments of this disclosure, as shown below. Figure 10 As shown, the device includes: Acquisition unit 1001 is used to acquire the shale sample to be tested; Test unit 1002 is used to perform nuclear magnetic resonance testing on the shale sample to be tested, and to obtain actual one-dimensional NMR spectrum and actual two-dimensional NMR spectrum; the actual one-dimensional NMR spectrum and actual two-dimensional NMR spectrum include movable fluid signals; Construction unit 1003 is used to construct the ideal two-dimensional nuclear magnetic spectrum of the shale sample to be tested. Forward modeling unit 1004 is used to perform forward modeling on an ideal two-dimensional nuclear magnetic spectrum to obtain echo train signals; Inversion unit 1005 is used to invert the echo train signal to obtain the inverted NMR spectrum; Unit 1006 is used to determine the waiting time correction factor and the inversion correction factor based on the inverted NMR spectrum and the ideal two-dimensional NMR spectrum. The correction unit 1007 is used to correct the movable fluid signal in the actual one-dimensional NMR spectrum and the actual two-dimensional NMR spectrum based on the waiting time correction factor and the inversion correction factor.

[0078] The specific details of each part of the above-mentioned device have been described in detail in the method section of the implementation plan. For any undisclosed details, please refer to the implementation plan of the method section, and therefore will not be repeated here.

[0079] According to embodiments of this disclosure, this disclosure also provides an electronic device and a readable storage medium.

[0080] Figure 11A schematic block diagram of an example electronic device 1100 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0081] like Figure 11 As shown, the electronic device 1100 includes a computing unit 1101, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1102 or a computer program loaded into a random access memory (RAM) 1103 from a storage unit 1108. The RAM 1103 may also store various programs and data required for the operation of the electronic device 1100. The computing unit 1101, ROM 1102, and RAM 1103 are interconnected via a bus 1104. An input / output (I / O) interface 1105 is also connected to the bus 1104.

[0082] Multiple components in electronic device 1100 are connected to I / O interface 1105, including: input unit 1106, such as keyboard, mouse, etc.; output unit 1107, such as various types of displays, speakers, etc.; storage unit 1108, such as disk, optical disk, etc.; and communication unit 1109, such as network card, modem, wireless transceiver, etc. Communication unit 1109 allows electronic device 1100 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0083] The computing unit 1101 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 1101 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 1101 performs the various methods and processes described above, such as the shale movable fluid signal correction method. For example, in some embodiments, the shale movable fluid signal correction method can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 1108. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 1100 via ROM 1102 and / or communication unit 1109. When the computer program is loaded into RAM 1103 and executed by the computing unit 1101, one or more steps of the shale movable fluid signal correction method described above can be performed. Alternatively, in other embodiments, the computing unit 1101 may be configured to perform a shale movable fluid signal correction method by any other suitable means (e.g., by means of firmware).

[0084] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transferring data and instructions to the storage system, the at least one input device, and the at least one output device.

[0085] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0086] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0087] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0088] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0089] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0090] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this disclosure can be achieved, and this is not limited herein.

[0091] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means two or more, unless otherwise explicitly specified.

[0092] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A method for correcting movable fluid signals in shale, characterized in that, The method includes: Obtain the shale sample to be tested; The shale sample to be tested was subjected to nuclear magnetic resonance (NMR) testing to obtain actual one-dimensional NMR spectrum and actual two-dimensional NMR spectrum; the actual one-dimensional NMR spectrum and the actual two-dimensional NMR spectrum include mobile fluid signals; Construct the ideal two-dimensional nuclear magnetic resonance spectrum of the shale sample to be tested; The ideal two-dimensional nuclear magnetic resonance spectrum was forward modeled to obtain the echo train signal; The echo train signal is inverted to obtain the inverted nuclear magnetic spectrum; Based on the inverted NMR spectrum and the ideal two-dimensional NMR spectrum, the waiting time correction factor and the inversion correction factor are determined. Based on the waiting time correction factor and the inversion correction factor, the mobile fluid signal in the actual one-dimensional NMR spectrum and the actual two-dimensional NMR spectrum is corrected; The process of inverting the echo train signal to obtain the inverted NMR spectrum includes: Multiple inverted one-dimensional nuclear magnetic spectra were obtained by inverting the one-dimensional echo train under several different first inversion conditions. Multiple inverted two-dimensional echo trains were obtained by inverting them under several different second inversion conditions; The determination of the waiting time correction factor and the inversion correction factor based on the inverted NMR spectrum and the ideal two-dimensional NMR spectrum includes: Based on multiple inverted one-dimensional NMR spectra, the one-dimensional signal amplitude of the mobile fluid signal under optimal inversion conditions is determined; The one-dimensional waiting time correction factor is determined by the ratio of the ideal signal amplitude of the movable fluid signal in the ideal two-dimensional NMR spectrum to the one-dimensional signal amplitude of the movable fluid signal under the optimal inversion conditions. Based on multiple inverted one-dimensional NMR spectra, the one-dimensional signal amplitude of the mobile fluid signal under a first specific inversion condition is determined, wherein the first specific inversion condition is the same as the condition for obtaining the actual one-dimensional NMR spectrum. The one-dimensional inversion correction factor is determined by the ratio of the one-dimensional signal amplitude of the movable fluid signal under the optimal inversion condition to that under the first specific inversion condition. Based on multiple inverted two-dimensional NMR spectra, the two-dimensional signal amplitude of the mobile fluid signal under optimal inversion conditions is determined; The two-dimensional waiting time correction factor is determined by the ratio of the ideal signal amplitude of the movable fluid signal in the ideal two-dimensional NMR spectrum to the two-dimensional signal amplitude of the movable fluid signal under the optimal inversion conditions. Based on multiple inverted two-dimensional NMR spectra, the two-dimensional signal amplitude of the mobile fluid signal under a second specific inversion condition is determined, wherein the second specific inversion condition is the same as the condition for obtaining the actual two-dimensional NMR spectrum. The two-dimensional inversion correction factor is determined by the ratio of the two-dimensional signal amplitude of the movable fluid signal under the optimal inversion condition to that under the second specific inversion condition.

2. The method according to claim 1, characterized in that, Constructing the ideal two-dimensional nuclear magnetic resonance spectrum of the shale sample to be tested includes: The NMR signals of the shale sample to be tested are divided into solid framework signals, adsorbed oil signals, bound oil signals and mobile fluid signals; Obtain the ideal values ​​of each parameter in the solid skeleton signal, adsorbed oil signal, bound oil signal and movable fluid signal; Based on the ideal values ​​of each parameter, the solid skeleton signal, adsorbed oil signal, bound oil signal and movable fluid signal are accumulated by a two-dimensional Gaussian function to obtain an ideal two-dimensional nuclear magnetic spectrum.

3. The method according to claim 1, characterized in that, The forward modeling of the ideal two-dimensional NMR spectrum to obtain the echo train signal includes: The echo train signal is obtained based on the following formula: in, It is the waiting time; It is the echo time, determined by the echo interval. and echo number The calculation yielded that, ; It is the waiting time. With echo time The amplitude of the echo train signal below; It is the longitudinal relaxation time in an ideal two-dimensional NMR spectrum. Lateral relaxation time The signal amplitude below.

4. The method according to claim 1, characterized in that, The correction of the mobile fluid signal in the actual one-dimensional NMR spectrum and the actual two-dimensional NMR spectrum based on the waiting time correction factor and the inversion correction factor includes: Based on the one-dimensional waiting time correction factor and the one-dimensional inversion correction factor, the mobile fluid signal in the actual one-dimensional NMR spectrum is corrected; The movable fluid signal in the actual two-dimensional NMR spectrum is corrected based on the two-dimensional waiting time correction factor and the two-dimensional inversion correction factor.

5. A shale movable fluid signal correction device, characterized in that, The device includes: Acquisition unit, used to acquire shale samples to be tested; The testing unit is used to perform nuclear magnetic resonance testing on the shale sample to be tested, and to obtain actual one-dimensional nuclear magnetic spectrum and actual two-dimensional nuclear magnetic spectrum; the actual one-dimensional nuclear magnetic spectrum and the actual two-dimensional nuclear magnetic spectrum include mobile fluid signals; The construction unit is used to construct the ideal two-dimensional nuclear magnetic spectrum of the shale sample to be tested. The forward modeling unit is used to perform forward modeling on the ideal two-dimensional nuclear magnetic spectrum to obtain the echo train signal; The inversion unit is used to invert the echo train signal to obtain the inverted nuclear magnetic spectrum; The determining unit is used to determine the waiting time correction factor and the inversion correction factor based on the inverted NMR spectrum and the ideal two-dimensional NMR spectrum; The correction unit is used to correct the mobile fluid signal in the actual one-dimensional NMR spectrum and the actual two-dimensional NMR spectrum based on the waiting time correction factor and the inversion correction factor; The inversion unit is specifically used to invert a one-dimensional echo train under multiple different first inversion conditions to obtain multiple inverted one-dimensional nuclear magnetic spectra. Multiple inverted two-dimensional echo trains were obtained by inverting them under several different second inversion conditions; The determining unit is specifically used to determine the one-dimensional signal amplitude of the mobile fluid signal under optimal inversion conditions based on multiple inverted one-dimensional nuclear magnetic spectra. The one-dimensional waiting time correction factor is determined by the ratio of the ideal signal amplitude of the movable fluid signal in the ideal two-dimensional NMR spectrum to the one-dimensional signal amplitude of the movable fluid signal under the optimal inversion conditions. Based on multiple inverted one-dimensional NMR spectra, the one-dimensional signal amplitude of the mobile fluid signal under a first specific inversion condition is determined, wherein the first specific inversion condition is the same as the condition for obtaining the actual one-dimensional NMR spectrum. The one-dimensional inversion correction factor is determined by the ratio of the one-dimensional signal amplitude of the movable fluid signal under the optimal inversion condition to that under the first specific inversion condition. Based on multiple inverted two-dimensional NMR spectra, the two-dimensional signal amplitude of the mobile fluid signal under optimal inversion conditions is determined; The two-dimensional waiting time correction factor is determined by the ratio of the ideal signal amplitude of the movable fluid signal in the ideal two-dimensional NMR spectrum to the two-dimensional signal amplitude of the movable fluid signal under the optimal inversion conditions. Based on multiple inverted two-dimensional NMR spectra, the two-dimensional signal amplitude of the mobile fluid signal under a second specific inversion condition is determined, wherein the second specific inversion condition is the same as the condition for obtaining the actual two-dimensional NMR spectrum. The two-dimensional inversion correction factor is determined by the ratio of the two-dimensional signal amplitude of the movable fluid signal under the optimal inversion condition to that under the second specific inversion condition.

6. An electronic device, characterized in that, include: At least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-4.

7. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-4.

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