A Smart Method for Determining Oil-Water Saturation in Shale Samples Based on Two-Dimensional Nuclear Magnetic Resonance Technology

Abstract

This invention relates to the field of rock sample oil-water saturation measurement technology based on nuclear magnetic resonance (NMR) technology, and proposes an intelligent method for measuring the oil-water saturation of shale samples based on two-dimensional NMR technology. The method includes: collecting the volume, echo signal, and signal-to-noise ratio of a preset number of rock samples; marking the target rock sample and comparison rock samples, and determining the comprehensive interference degree of volume influence and the noise amplification coefficient of the target echo signal; obtaining the denoised target echo signal based on the target echo signal, the volume of the rock sample corresponding to the target echo signal, and the noise amplification coefficient of the echo signal; dividing the rock sample into ineffective pore regions and effective pore regions corresponding to the two-dimensional NMR T1-T2 spectrum, and the oil-water distribution region of the effective pore region, using a fluid with a distribution close to that of the reservoir oil and water, to recover the two-dimensional NMR spectrum of the rock sample, extract the oil-water content corresponding to the NMR signal, and obtain the rock sample oil-water saturation measurement results based on NMR technology.

Description

Technical Field

[0001] This invention relates to the field of rock sample oil-water saturation measurement technology based on nuclear magnetic resonance (NMR) technology, specifically to an intelligent method for measuring oil-water saturation in shale samples based on two-dimensional NMR technology. Background Technology

[0002] In the field of core testing in the petroleum industry, nuclear magnetic resonance (NMR) is generally used to determine the oil-water saturation of rock samples. NMR technology is based on the T2 spectrum of the core, and determines oil-water saturation by analyzing the NMR signals of the oil and water phases. Two-dimensional NMR technology refers to the combined testing of longitudinal relaxation time T1 and transverse relaxation time T2 using high-frequency NMR, which can solve problems related to oil-water distribution and occurrence in shale oil reservoirs.

[0003] In magnetic resonance imaging (MRI), the gradient field generated by gradient coils in three orthogonal directions (x, y, z) is used for spatial encoding, which can determine the signal at different locations in the rock sample, independently control and achieve three-dimensional spatial localization. To obtain a clear image, the current in the gradient coils changes rapidly, generating a changing magnetic field; however, this rapidly changing current is also one of the biggest noise sources in MRI. Due to the small volume of the rock sample and the weak echo amplitude, the measured NMR signal is easily affected by noise. Furthermore, when using NMR to measure the NMR of rock samples, the NMR signal often contains noise due to the low NMR porosity of shale oil reservoirs. This noisy NMR signal can affect the accuracy of oil-water saturation determination in the rock sample.

[0004] Two-dimensional nuclear magnetic resonance (NMR) measurements of shale oil samples require noise control during signal acquisition. After measurement, the resulting NMR spectrum needs to be analyzed. High-frequency two-dimensional NMR shale oil sample measurement technology, which combines longitudinal relaxation time T1 and transverse relaxation time T2, is a newly developed technology. Many testing techniques are still immature and under development. The result of the combined T1-T2 NMR measurement of shale oil samples is a T1-T2 NMR signal distribution spectrum containing information on hydrogen-bearing compounds in the sample. Shale oil fluid saturation analysis based on this NMR technology not only requires analyzing the T1-T2 NMR signal distribution spectrum to determine the different properties and characteristics of hydrogen-bearing compounds represented by the NMR signals at each position within the spectrum, but also requires quantitative calculation from qualitative analysis of the NMR signals representing hydrogen-bearing compounds with different properties. Shale oil reservoir rocks contain various hydrogen-containing compounds, including structural water / crystallization water, clay-adsorbed water, pore water, organic matter, and oil and gas of different compositions and states. Different hydrogen-containing compounds have different implications for fluid saturation. The accuracy of saturation calculations is directly affected by the correct identification and quantitative analysis of fluid properties on the T1-T2 NMR spectra. Therefore, a suitable method for determining fluid saturation in shale oil rock samples based on two-dimensional NMR technology is still lacking. This method aims to analyze the physical properties of the NMR signals from the T1-T2 map of shale oil samples and achieve oil-water saturation determination using two-dimensional NMR. Summary of the Invention

[0005] This invention provides an intelligent method for determining the oil-water saturation of shale samples based on two-dimensional nuclear magnetic resonance (NMR) technology. This method addresses the problem that noise in the acquired NMR signals affects the accuracy of oil-water saturation determination, and also overcomes the lack of technology for quantitatively analyzing hydrogen-containing compounds in the two-dimensional NMR spectra of shale oil samples, which hinders accurate determination of saturation using two-dimensional NMR. The specific technical solution adopted is as follows:

[0006] One embodiment of the present invention provides a method for intelligent determination of oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology. The method includes the following steps:

[0007] Collect the volume, echo signal, and signal-to-noise ratio of a preset number of rock samples;

[0008] Any rock sample is designated as the target rock sample, and all other rock samples are designated as comparison rock samples. Based on the frequency values ​​of the echo signals of the target and comparison rock samples, the range of target frequency is defined, and the power spectrum and power spectral density of the target and comparison rock samples are obtained. Based on the similarity between the power spectral densities of the target and comparison rock samples, the difference between the power spectral densities, the distribution of peak values ​​in the power spectrum, and the volume difference, the volume influence of the target rock sample on echo interference is determined. Based on the volume influence of all rock samples on echo interference, the comprehensive volume influence is determined. Combining the peak distribution and peak value of the echo signal and signal-to-noise ratio of the target rock sample, the noise amplification factor of the target echo signal is obtained.

[0009] Based on the target echo signal, the volume of the rock sample corresponding to the target echo signal, and the noise amplification factor of the echo signal, the adjustment threshold of the target echo signal is determined, and the denoised target echo signal is obtained based on the determined adjustment threshold of the target echo signal.

[0010] The rock samples were subjected to water content calibration, oil-water content calibration, water distribution experiments, oil distribution experiments, porosity characteristic experiments of naturally leached rock samples, porosity characteristic experiments of rock samples dehydrated at low temperature, and porosity characteristic experiments of rock samples deoiled at low temperature. The water distribution area and oil distribution area were determined, and two-dimensional nuclear magnetic resonance (NMR) spectra were obtained. Based on the two-dimensional NMR spectra, ineffective porosity areas and effective porosity areas were divided. The boundary lines of NMR signals between effective porosity areas and ineffective porosity areas were delineated. The boundaries between water distribution areas and oil distribution areas in the effective porosity areas were delineated. The porosity of the rock samples was then restored.

[0011] Based on the measured NMR signal values ​​in the water and oil distribution areas, the oil-water saturation of the rock samples was calculated using the two-dimensional NMR saturation calculation method to obtain the NMR-based oil-water saturation measurement results.

[0012] Furthermore, the method for preparing the rock sample is as follows:

[0013] Rock samples were collected from the pressure-maintaining core locations of the shale oil reservoir in the exploration area. After the rock samples were brought to the surface through drilling and brought out of the casing, they were completely frozen and preserved in a freezer at a temperature of -40°C or less using freezing technology. The rock samples had to be completely frozen and were large, sheet-like rock samples with a diameter of 15 mm or more and a diameter of 20 mm or less. The cutting tools should be used to cut along the direction perpendicular to the bedding planes and bedding end faces of the rock samples to ensure that the geometry of the rock samples met the testing requirements. The samples were then frozen again to keep them in a frozen state.

[0014] Furthermore, the specific method for defining the target frequency range based on the frequency values ​​of the echo signals of the target rock sample and the comparison rock sample, and obtaining the power spectrum and power spectral density of the target rock sample and the comparison rock sample, includes:

[0015] The echo signals of the target rock sample and the comparison rock sample were converted into frequency domain signals using Fast Fourier Transform, and the power spectrum diagrams and power spectral densities were obtained based on the frequency domain signals.

[0016] The minimum value of all frequency domain signals is recorded as the minimum frequency value, the maximum value of all frequency domain signals is recorded as the maximum frequency value, and all natural numbers greater than or equal to the minimum frequency value and less than or equal to the maximum frequency value are taken as the range of values ​​for the target frequency.

[0017] Furthermore, the method for determining the volume-related echo interference of the target rock sample based on the similarity between the power spectral densities of the target rock sample and the comparison rock samples, the difference between their power spectral densities, the distribution of peak values ​​in the power spectra, and the volume difference includes the following specific methods:

[0018] The absolute value of the Pearson correlation coefficient between the power spectral density of the target rock sample and the comparison rock sample is denoted as the power spectral correlation between the target rock sample and the comparison rock sample, and the mean value of the power spectral correlation between the target rock sample and all comparison rock samples is denoted as the rock sample attribute similarity of the target rock sample.

[0019] The peak values ​​of the power spectra of the target rock sample and the comparison rock sample are obtained respectively. The minimum absolute value of the difference between the target frequency and all peak values ​​of the target rock sample is recorded as the shortest frequency difference of the target rock sample at the target frequency. The minimum absolute value of the difference between the target frequency and all peak values ​​of the comparison rock sample is recorded as the shortest frequency difference of the comparison rock sample at the target frequency. At the target frequency, the absolute value of the difference between the shortest frequency differences of the target rock sample and the comparison rock sample is recorded as the shortest frequency difference between the target rock sample and the comparison rock sample at the target frequency. The mean of the shortest frequency differences between the target rock sample and all comparison rock samples at the target frequency is recorded as the first difference of the target rock sample at the target frequency.

[0020] The absolute value of the difference between the power spectral density of the target rock sample and the comparison rock sample at the target frequency is denoted as the power spectral difference between the target rock sample and the comparison rock sample at the target frequency. The mean of the power spectral differences between the target rock sample and all comparison rock samples at the target frequency is denoted as the second difference of the target rock sample at the target frequency.

[0021] The average volume of all the comparative rock samples is denoted as the average volume of the comparative rock samples, and the absolute value of the difference between the volume of the target rock sample and the average volume of the comparative rock samples is denoted as the volume difference of the target rock sample.

[0022] The volume influence of the target rock sample on echo interference is determined based on the volume difference of the target rock sample, the similarity of rock sample properties, and the first and second differences of the target rock sample at the target frequency.

[0023] Furthermore, the specific method for determining the volume influence echo interference of the target rock sample based on the volume difference, rock sample property similarity, and the first and second differences of the target rock sample at the target frequency includes:

[0024] The product of the first and second differences of the target rock sample at the target frequency is denoted as the third difference of the target rock sample at the target frequency. The sum of the third differences corresponding to the values ​​of the target rock sample at all target frequencies is denoted as the fourth difference of the target rock sample.

[0025] The product of the volume difference and the fourth difference of the target rock sample is recorded as the first product of the target rock sample. The difference between the number 1 and the rock sample attribute similarity of the target rock sample is recorded as the rock sample attribute difference degree of the target rock sample. The product of the first product of the target rock sample and the rock sample attribute difference degree is recorded as the volume influence echo interference degree of the target rock sample.

[0026] Furthermore, the method for obtaining the overall interference degree caused by the volume effect is as follows:

[0027] The sum of the volumetric influence echo interference of all rock samples is denoted as the comprehensive volumetric influence interference.

[0028] Furthermore, the specific method for obtaining the noise amplification coefficient of the target echo signal by combining the peak distribution and peak value of the signal-to-noise ratio of the target rock sample's echo signal includes:

[0029] The peak values ​​of the echo signals and the peak values ​​of the signal-to-noise ratio (SNR) of the target rock sample were obtained separately. The peak values ​​of the echo signals of the target rock sample were arranged in chronological order of their acquisition time to obtain the echo signal peak sequence. The peak values ​​of the SNR of the target rock sample were arranged in chronological order of their acquisition time to obtain the SNR peak sequence. The null hypothesis was that there was no significant difference between the echo signal peak sequence and the SNR peak sequence, and the alternative hypothesis was that there was a significant difference between the echo signal peak sequence and the SNR peak sequence. The t-test algorithm was used to calculate the p-value, and the p-value was recorded as the statistical significance of the target echo signal and the SNR.

[0030] Arrange the peak values ​​of the echo signals of the target rock sample in ascending order to obtain the echo signal peak value arrangement sequence; arrange the peak values ​​of the signal-to-noise ratio of the target rock sample in ascending order to obtain the signal-to-noise ratio peak value arrangement sequence; and record the DTW distance between the echo signal peak value arrangement sequence and the signal-to-noise ratio peak value arrangement sequence as the time variation difference between the target echo signal and the signal-to-noise ratio.

[0031] The noise amplification factor of the target echo signal is obtained based on the comprehensive interference caused by volume, the statistical significance of the target echo signal and the signal-to-noise ratio, and the time variation difference.

[0032] Furthermore, the specific method for obtaining the noise amplification factor of the target echo signal based on the comprehensive interference degree of volume influence, the statistical significance of the target echo signal and the signal-to-noise ratio, and the time variation difference is as follows:

[0033] The normalized value of the product of the statistical significance of the target echo signal and the signal-to-noise ratio and the time variation difference is denoted as the second product of the target echo signal. The difference between the digital 1 and the second product of the target echo signal is denoted as the third product of the target echo signal. The product of the volume influence comprehensive interference degree and the third product of the target echo signal is denoted as the noise amplification factor of the target echo signal.

[0034] Furthermore, the method for determining the adjustment threshold of the target echo signal is as follows:

[0035] The volume of the rock sample is taken as the independent variable, and the noise amplification factor of the echo signal corresponding to the rock sample is taken as the dependent variable. A straight line is fitted to the independent and dependent variables to obtain the fitted straight line. The slope of the fitted straight line is recorded as the regression coefficient.

[0036] The noise level of the target echo signal is obtained using the median absolute deviation (MAD).

[0037] Based on the regression coefficients and noise level of the target echo signal, the adjustment threshold of the target echo signal is determined using the following formula:

[0038]

[0039] In the formula, T represents the adjustment threshold of the target echo signal; tanh represents the hyperbolic tangent function; β1 represents the regression coefficient of the target echo signal; σ1 represents the first parameter adjustment coefficient; and σ represents the noise level of the target echo signal.

[0040] Furthermore, the specific method for obtaining the denoised target echo signal based on the determined adjustment threshold of the target echo signal includes:

[0041] The adjustment threshold of the target echo signal is used as the value of the soft threshold. Wavelet transform is used to denoise the echo signal of the rock sample to obtain the denoised target echo signal.

[0042] Furthermore, the method for calibrating the water volume value is as follows:

[0043] Seven rock samples were selected, and the water inside the samples was removed by high temperature. Deionized water was then added to each rock sample, with the amounts of water added to the seven samples being 0.100 ml, 0.200 ml, 0.300 ml, 0.400 ml, 0.500 ml, 0.700 ml, and 0.900 ml, respectively. T2 NMR spectroscopy was performed on each rock sample to obtain two-dimensional NMR results.

[0044] Furthermore, the method for calibrating the oil-water content is as follows:

[0045] All seven rock samples were selected, and a fixed amount of kerosene was added to the rock sample test cups. The kerosene amounts in the rock sample cups were 0.500 ml, 1.000 ml, 1.500 ml, 2.000 ml, 2.500 ml, 3.000 ml, and 3.500 ml, respectively. Nuclear magnetic resonance (NMR) measurements were performed on each rock sample to obtain two-dimensional NMR results.

[0046] Furthermore, the method for determining the water distribution area is as follows:

[0047] Water distribution experiments were conducted on rock samples that did not contain hydrogen-containing compounds and rock samples that contained solid or near-solid hydrogen-containing compounds.

[0048] The process of conducting experiments on water distribution in rock samples that do not contain hydrogen-containing substances is as follows:

[0049] Select any shale rock sample, place the rock sample in a 700℃ dry distillation oven to remove hydrogen-containing substances, and perform a two-dimensional nuclear magnetic resonance experiment until the hydrogen-containing substances in the rock sample are completely removed.

[0050] The rock sample was placed in a humidifier with a humidity of not less than 85% to absorb moisture. After the mass of the rock sample remained unchanged, a two-dimensional nuclear magnetic resonance experiment was carried out again to obtain the T1-T2 distribution spectrum and determine the water distribution area.

[0051] Furthermore, the process of conducting water distribution experiments on rock samples containing solid or near-solid hydrogen-bearing materials is as follows:

[0052] Select any shale rock sample, perform two-dimensional nuclear magnetic resonance (NMR) measurements, and obtain a two-dimensional NMR spectrum.

[0053] The rock sample was placed in an alcohol-benzene solvent to remove oil, and then dehumidified at 115℃ to constant weight. Two-dimensional nuclear magnetic resonance experiments were then performed to obtain the T1-T2 distribution spectrum under the conditions of oil removal and dehumidification.

[0054] The rock sample was placed in a humidifier with a humidity of not less than 85% to absorb moisture, and after being weighed to a constant mass, a two-dimensional nuclear magnetic resonance (NMR) measurement was performed again to obtain a water-saturated two-dimensional NMR spectrum.

[0055] The rock sample was broken open and then re-moistened. After the mass was kept constant, a two-dimensional nuclear magnetic resonance (NMR) measurement was performed to obtain the water absorption two-dimensional NMR spectrum of the rock sample under the condition of external force damage and crack formation.

[0056] Furthermore, the method for determining the oil distribution area is as follows:

[0057] Select any shale rock sample, remove oil with alcohol and benzene solvent, dehumidify at 115℃, and conduct a two-dimensional nuclear magnetic resonance experiment to obtain the two-dimensional nuclear magnetic resonance spectrum of the rock sample under the conditions of oil removal and dehumidification.

[0058] After the rock sample was placed in an environment with a humidity of not less than 85% and absorbed water, two-dimensional nuclear magnetic resonance (NMR) measurements were performed to obtain the two-dimensional NMR spectrum of the rock sample under water absorption conditions.

[0059] The rock sample was immersed in kerosene to absorb saturated kerosene. After the quality stabilized, two-dimensional nuclear magnetic resonance (NMR) measurements were performed to obtain the two-dimensional NMR spectrum of the rock sample under water and oil absorption conditions.

[0060] The oil distribution area was determined based on the two-dimensional NMR spectra of rock samples under oil and moisture removal conditions, under water absorption conditions, and under water and oil absorption conditions.

[0061] Furthermore, the method for the experimental characteristics of the porosity properties of the naturally lost rock samples is as follows:

[0062] Two rock samples collected from the central part of the pressure-maintaining core of a shale oil reservoir were selected. Before complete thawing, two-dimensional nuclear magnetic resonance (NMR) measurements were performed. The samples were then placed in sample bottles and allowed to thaw slowly under natural conditions. After complete thawing, the samples were placed under vacuum at 60°C for 8 hours to remove pore water, and then subjected to NMR measurements to obtain their two-dimensional NMR spectra. One of the dehydrated samples was placed under constant humidity (greater than 85%) to allow it to self-absorb water and become saturated with water. After maintaining its mass, the sample was then placed in kerosene to allow it to self-absorb kerosene and become saturated with oil. Again, after maintaining its mass, two-dimensional NMR measurements were performed to obtain its two-dimensional NMR spectrum. The other dehydrated sample was first placed in kerosene, then under constant humidity (greater than or equal to 85%) to allow it to self-absorb kerosene and water, respectively. After maintaining its mass, two-dimensional NMR measurements were performed on both samples to obtain their two-dimensional NMR spectra.

[0063] Furthermore, the method for the low-temperature dehydration rock sample pore property characteristic experiment is as follows:

[0064] After selecting any rock sample and performing two-dimensional nuclear magnetic resonance (NMR) measurements, the rock sample was placed under vacuum low temperature (60℃) for 8 hours to remove pore water. Two-dimensional NMR analysis of the rock sample was then carried out to obtain the T1-T2 distribution spectrum under the condition of removing pore water.

[0065] Rock samples were placed under constant humidity conditions with a humidity greater than 85% to allow them to absorb water and remain saturated with water. Two-dimensional nuclear magnetic resonance (NMR) measurements were then performed to obtain the T1-T2 oil-water distribution spectrum under water absorption conditions. The reproducibility of pore water was determined by comparing and analyzing the NMR data under different conditions.

[0066] Furthermore, the method for the low-temperature oil removal rock sample pore property characteristic experiment is as follows:

[0067] Rock samples were collected from the central part of the pressure-maintaining core of the shale oil reservoir. After two-dimensional nuclear magnetic resonance (NMR) analysis, chloroform was used for low-temperature degreasing and dehumidification at 60°C. The degreasing time was generally no less than 70 hours. Two-dimensional NMR experiments were carried out on the rock samples to obtain the two-dimensional NMR spectrum after degreasing and dehumidification.

[0068] The rock sample was immersed in kerosene to allow it to self-absorb and become saturated with kerosene. After the mass remained constant, a two-dimensional nuclear magnetic resonance (NMR) experiment was conducted to obtain the two-dimensional NMR spectrum under saturated kerosene conditions.

[0069] The rock sample was placed under constant humidity conditions with a humidity greater than 85% to allow it to absorb water and remain saturated with water. Then, two-dimensional nuclear magnetic resonance (NMR) measurements were performed on the rock sample again to obtain the two-dimensional NMR spectrum under the condition of re-absorbing water.

[0070] Furthermore, the specific method for dividing the ineffective porosity region and the effective porosity region based on the two-dimensional NMR spectrum includes:

[0071] The rock samples were deoiled using alcohol and benzene solvent, and then dehumidified at 115℃ to constant weight. Two-dimensional nuclear magnetic resonance experiments were then performed to obtain the T1-T2 distribution spectrum of solid or near-solid hydrogen-containing substances that could not be removed after deoiling and dehumidification. The samples were then saturated with oil and water by self-absorption, and after the mass was kept constant, two-dimensional nuclear magnetic resonance measurements were performed to obtain the pore oil and water distribution spectrum.

[0072] The region containing the two-dimensional nuclear magnetic resonance (NMR) spectrum of solid or near-solid hydrogen-containing substances such as crystalline water or structural water, organic matter, and bituminous matter within clay minerals is defined as the ineffective porosity region. The region composed of the self-absorbed saturated water distribution region and the oil distribution region is denoted as the effective porosity region.

[0073] Furthermore, the method for delineating the NMR signal boundary between the effective porosity region and the ineffective porosity region is as follows:

[0074] The abscissa of the weakest NMR signal between the effective porosity region and the ineffective porosity region in the two-dimensional NMR spectrum is marked as 'a'. The straight line with the abscissa 'a' is used as the boundary between the effective porosity region and the ineffective porosity region. The region less than or equal to the line 'a' is the ineffective porosity region, and the region greater than the line 'a' is the effective porosity region.

[0075] Furthermore, the method for defining the boundary between the water distribution zone and the oil distribution zone in the effective pore space is as follows:

[0076] The ordinate of the weakest NMR signal between the oil distribution area and the water distribution area in the effective pore region is marked as b. The straight line with the ordinate of b is used as the boundary between the oil distribution area and the water distribution area. Between the oil distribution area and the water distribution area, the area with the ordinate greater than b is called the oil distribution area, and the area with the ordinate less than or equal to b is called the water distribution area.

[0077] Furthermore, the specific method for restoring the porosity of the rock sample includes:

[0078] When the water distribution is greater than the oil distribution, place the rock sample in a rock sample bottle containing kerosene to allow it to absorb the kerosene. After the rock sample mass remains constant, place the rock sample in a constant humidity chamber with a humidity of not less than 85% to allow the rock sample to absorb water until the mass is constant.

[0079] When the water distribution is much smaller than the oil distribution, place the rock sample in a constant humidity chamber with a humidity of not less than 85% to allow the rock sample to absorb water until the mass is constant. Then, place the rock sample in a rock sample bottle containing kerosene to allow the rock sample to absorb kerosene until the mass is constant.

[0080] When the water distribution is the same as the oil distribution, place the rock sample in a rock sample bottle containing kerosene to allow it to absorb the kerosene. After the rock sample mass remains unchanged, place the rock sample in a constant humidity chamber with a humidity of not less than 85% to allow the rock sample to absorb water until the mass remains unchanged.

[0081] Furthermore, based on the measured NMR signal values ​​within the water and oil distribution areas, the saturation is calculated using the two-dimensional NMR saturation calculation method, and the formula is as follows:

[0082]

[0083]

[0084] In the formula, S W1 S indicates the water saturation measured by nuclear magnetic resonance (NMR). W2 Indicates the oil saturation measured by NMR; k water The conversion coefficient between the rock sample NMR signal and the water signal is represented; M1 represents the sum of all NMR signals within the water distribution area; K oil M1 represents the conversion coefficient between the rock sample NMR signal and the oil signal; M2 represents the sum of all NMR signals in the oil distribution area.

[0085] The beneficial effects of this invention are:

[0086] This application evaluates the amplifying effect of rock sample volume changes on noise generated during gradient field switching based on the similarity, difference, peak distribution, and volume differences between the power spectral density of the target rock sample and the comparison rock samples. It determines the overall interference level caused by volume influence. Furthermore, considering that volume differences between different rock samples can amplify and interfere with echo signals, and that echo signal intensity is directly related to noise, the application further analyzes the impact of echo signals on noise. By combining the peak distribution and peak value of the echo signal and signal-to-noise ratio of the target rock sample, the application obtains the target echo signal. The noise amplification factor of the target echo signal is considered. A larger noise amplification factor indicates greater sensitivity of the rock sample volume change to the noise generated during gradient field switching; that is, a greater impact of rock sample volume change on the noise generated during gradient field switching. Based on the target echo signal, the volume of the corresponding rock sample, and the noise amplification factor of the echo signal, the target echo signal is denoised to obtain the denoised target echo signal. This allows for more precise control of the wavelet transform's processing intensity at different frequencies, enabling the denoising process to adaptively adjust according to the rock sample volume difference and noise amplification effect, thereby improving noise suppression. This invention preserves the effective information of the signal while reducing noise, improving the accuracy and reliability of NMR signal processing and solving the problem that noise in the acquired NMR signal affects the accuracy of oil-water saturation determination in rock samples. Furthermore, through oil-water distribution experiments, this invention clarifies the oil-water distribution regions in the two-dimensional NMR spectrum, and establishes a method for delineating the boundaries between these regions, avoiding serious distortions in two-dimensional NMR oil-water saturation determination caused by unclear oil-water distribution delineation. The invention also clarifies the distribution of effective and ineffective porosity regions through experiments and establishes a method for delineating effective and ineffective porosity regions. The effective pore region method avoids the drawbacks of inaccurate oil-water content and pore volume measurements due to unclear delineation between the two, leading to significant deviations in oil-water saturation analysis. This greatly improves the accuracy of two-dimensional nuclear magnetic resonance (NMR) oil-water saturation determination. Through characteristic experiments on shale oil sample properties, it was clarified that shale oil reservoir rock sample pores have dual oil-water wettability. Based on this, a two-dimensional NMR saturation experimental method was established, enabling accurate determination of water content, oil content, and pore volume, thus improving the accuracy of shale rock sample oil-water saturation determination. It was also applied to routine coring, solving the problem of the inability to correct for oil and gas loss during core drilling. Based on the quantitative analysis of oil-water distribution in two-dimensional NMR T1-T2 spectra, a method for quantitative extraction of oil and water from the T1-T2 oil-water distribution spectrum and calculation of oil-water saturation was established. This method is convenient, fast, simple, and clear, with a short experimental cycle, high production efficiency, and is non-toxic and harmless, conforming to HSE safety, health, and environmental protection principles. Attached Figure Description

[0087] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0088] Figure 1 This is a schematic flowchart of an intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology, provided in one embodiment of the present invention.

[0089] Figure 2 This is a schematic diagram illustrating the relationship between water content and NMR signal according to an embodiment of the present invention.

[0090] Figure 3 This is a schematic diagram illustrating the relationship between kerosene quantity and NMR signal according to an embodiment of the present invention.

[0091] Figure 4 This is a schematic diagram of the two-dimensional nuclear magnetic resonance (NMR) distribution spectrum of a rock sample water distribution experiment provided in one embodiment of the present invention;

[0092] Figure 5 This is a two-dimensional NMR spectrum of water distribution under different conditions provided in an embodiment of the present invention;

[0093] Figure 6 This is a two-dimensional NMR spectrum of oil distribution provided in an embodiment of the present invention.

[0094] Figure 7 This is a two-dimensional nuclear magnetic resonance (NMR) spectrum of rock sample oil porosity characteristics obtained from a low-temperature dehydration experiment, provided in one embodiment of the present invention.

[0095] Figure 8 This is a two-dimensional nuclear magnetic resonance (NMR) spectrum of the porosity characteristics of rock sample oil under low-temperature degreasing, provided in one embodiment of the present invention.

[0096] Figure 9 This is a two-dimensional NMR spectrum oil-water distribution zone delineation diagram of a shale sample provided in one embodiment of the present invention;

[0097] Figure 10 This is a map showing the oil-water distribution area of ​​a shale sample obtained from two-dimensional nuclear magnetic resonance (NMR) data extraction, provided in one embodiment of the present invention. Detailed Implementation

[0098] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0099] Please see Figure 1 The diagram illustrates a flowchart of an intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology, according to an embodiment of the present invention. The method includes the following steps:

[0100] Step S001: Collect the volume, echo signal and signal-to-noise ratio of a preset number of rock samples.

[0101] Rock samples were collected from the pressure-maintaining core locations of shale oil reservoirs in the exploration area. After the rock samples were brought to the surface through drilling and brought out of the casing, they were completely frozen and preserved in a freezer at a temperature of -40°C or less to avoid a large loss of fluid from the rock samples.

[0102] The rock sample must be completely frozen. It should be cut into large, sheet-like rock samples with a diameter of 15 mm or more and a diameter of 20 mm or less using a core cutting tool or a core-specific machete along the bedding plane. The core cutting tool or core-specific machete should cut along a direction perpendicular to the bedding plane and the bedding end face. The geometric shape should meet the testing requirements. The sample should then be frozen again to keep it in a frozen state.

[0103] For each rock sample, a 3D scanner was used to acquire three-dimensional data, and the volume of the rock sample was determined based on this data. An NMR analyzer was used to acquire echo signals and measure the signal-to-noise ratio of the rock samples.

[0104] Preferably, in one embodiment of this application, seven rock samples are collected, with varying masses and thicknesses of 15 mm or more and 20 mm or less. In this embodiment, the data sampling frequency for acquiring echo signals and signal-to-noise ratio (SNR) is 21 MHz, and a total of 10 seconds of echo signal and SNR data are collected. In practical applications, as other implementation methods, the implementer can determine the number of rock samples collected, the sampling frequency of the echo signals and SNR, and the sampling duration according to the actual situation; this application does not impose any special limitations.

[0105] Thus, the volume, echo signal, and signal-to-noise ratio of different rock samples were obtained.

[0106] Step S002: Designate any one rock sample as the target rock sample, and designate all other rock samples as comparison rock samples. Define the target frequency range based on the frequency values ​​of the echo signals of the target and comparison rock samples, and obtain the power spectrum and power spectral density of the target and comparison rock samples. Determine the volume influence echo interference of the target rock sample based on the similarity between the power spectral densities of the target and comparison rock samples, the difference between the power spectral densities, the distribution of peak values ​​in the power spectrum, and the volume difference. Determine the comprehensive volume influence echo interference based on the volume influence echo interference of all rock samples. Combine the peak distribution and peak value of the echo signal and signal-to-noise ratio of the target rock sample to obtain the noise amplification coefficient of the target echo signal.

[0107] The echo signal from the rock sample records the relaxation process of hydrogen nuclei in the magnetic field. However, the magnetic field generated during rapid gradient field switching is one of the biggest noise sources in magnetic resonance imaging (MRI). The switching of the gradient field causes the metal wire in the coil to vibrate violently under the Lorentz force, generating noise that interferes with the echo signal. In particular, when the porosity of shale oil reservoirs is small, the acquired fluid signal is weak and contains noise. Therefore, the quality of the echo signal is directly affected by the noise generated during gradient field switching; the greater the noise, the lower the clarity and accuracy of the echo signal.

[0108] First, the echo signal was analyzed to evaluate the effect of rock sample volume changes on the noise generated by gradient field switching.

[0109] Any rock sample is designated as the target rock sample, and all other rock samples are designated as comparison rock samples. Fast Fourier Transform (FFT) is used to convert the echo signals of the target and comparison rock samples into frequency domain signals. Power spectrum diagrams are plotted based on the frequency domain signals, and the power spectral density is obtained. The minimum value of all frequency domain signals is designated as the minimum frequency value, and the maximum value of all frequency domain signals is designated as the maximum frequency value. A target frequency is defined; specifically, all natural numbers greater than or equal to the minimum frequency value and less than or equal to the maximum frequency value are considered as the range of values ​​for the target frequency.

[0110] Power spectral density shows the power distribution of the echo signal at different frequencies, with different frequency components corresponding to different pore structures in the rock sample. The pore structure of shale oil reservoirs is determined by the inherent properties of the rock, such as organic matter abundance, maturity, and lithology. These inherent properties vary little in similar geological environments. Furthermore, the pore types in shale oil reservoirs mainly include primary and secondary pores, primarily residual intergranular pores and secondary dissolution pores. The poor connectivity between these pores further limits the variability of the pore structure. Therefore, rock samples with the same inherent properties exhibit relatively consistent pore structure characteristics.

[0111] The absolute value of the Pearson correlation coefficient between the power spectral density of the target rock sample and the comparison rock samples is denoted as the power spectral correlation between the target rock sample and the comparison rock samples. The mean value of the power spectral correlation between the target rock sample and all comparison rock samples is denoted as the rock sample attribute similarity of the target rock sample.

[0112] The greater the similarity of the rock sample properties of the target rock sample, the greater the consistency of the pore structure characteristics between the target rock sample and the comparison rock sample.

[0113] Peak detection algorithms were used to obtain the peak values ​​of the power spectra of the target rock sample and the comparison rock sample. The minimum absolute value of the difference between the target frequency and all peak values ​​of the target rock sample was recorded as the shortest frequency difference of the target rock sample at the target frequency. The minimum absolute value of the difference between the target frequency and all peak values ​​of the comparison rock sample was also recorded as the shortest frequency difference of the comparison rock sample at the target frequency. At the target frequency, the absolute value of the difference between the shortest frequency differences of the target rock sample and the comparison rock sample was recorded as the shortest frequency difference between the target rock sample and the comparison rock sample at the target frequency. The mean of the shortest frequency differences between the target rock sample and all comparison rock samples at the target frequency was recorded as the first difference of the target rock sample at the target frequency.

[0114] Using peak detection algorithms to obtain the peak values ​​of a power spectrum is a well-known technique and will not be elaborated further. It is understood that a power spectrum typically has multiple peak values, and the horizontal axis of each peak in the power spectrum represents the frequency of the signal in the frequency domain.

[0115] The first difference of the target rock sample at the target frequency reflects the difference in pore structure characteristics between the target rock sample and the comparison rock sample at the target frequency. The greater the first difference of the target rock sample at the target frequency, the more significant the difference in pore structure characteristics between the target rock sample and the comparison rock sample at the target frequency, and the greater the possibility that the echo signal of the target rock sample will be interfered with.

[0116] The absolute value of the difference between the power spectral density of the target rock sample and the comparison rock sample at the target frequency is denoted as the power spectral difference between the target rock sample and the comparison rock sample at the target frequency. The mean of the power spectral differences between the target rock sample and all comparison rock samples at the target frequency is denoted as the second difference of the target rock sample at the target frequency.

[0117] The second difference of the target rock sample at the target frequency reflects the difference in power spectral density between the target rock sample and the comparison rock sample at the target frequency. The greater the second difference of the target rock sample at the target frequency, the greater the difference in power spectral density between the target rock sample and the comparison rock sample at the target frequency, and the greater the possibility that the echo signal of the target rock sample is interfered with.

[0118] The average volume of all the comparative rock samples is recorded as the average volume of the comparative rock samples. The absolute value of the difference between the volume of the target rock sample and the average volume of the comparative rock samples is recorded as the volume difference of the target rock sample.

[0119] The volume influence of the target rock sample on echo interference is determined based on the volume difference of the target rock sample, the similarity of rock sample properties, and the first and second differences of the target rock sample at the target frequency.

[0120] Preferably, as an embodiment of this application, the product of the first difference and the second difference of the target rock sample at the target frequency is recorded as the third difference of the target rock sample at the target frequency; the sum of the third differences corresponding to the values ​​of the target rock sample at all target frequencies is recorded as the fourth difference of the target rock sample; the product of the volume difference and the fourth difference of the target rock sample is recorded as the first product of the target rock sample; the difference between the number 1 and the rock sample attribute similarity of the target rock sample is recorded as the rock sample attribute difference degree of the target rock sample; and the product of the first product and the rock sample attribute difference degree of the target rock sample is recorded as the volume influence echo interference degree of the target rock sample.

[0121] The overall volumetric interference level is determined based on the volumetric influence echo interference level of all rock samples.

[0122] Preferably, as an embodiment of this application, the sum of the volume influence echo interference of all rock samples is denoted as the comprehensive volume influence interference.

[0123] The comprehensive interference assessment of volume influence evaluates the likelihood of echo signal interference caused by differences in rock sample volume. The greater the volume difference in the target rock sample, the greater the impact of the likelihood of echo signal interference on the comprehensive interference assessment of volume influence. Conversely, the greater the comprehensive interference assessment of volume influence, the more significant the interference effect of rock sample volume differences on the echo signal.

[0124] The volume difference between different rock samples can amplify and interfere with the echo signal, and the intensity of the echo signal is directly related to the noise. Further analysis is needed to understand the effect of the echo signal on the noise.

[0125] Peak detection algorithms were used to process the echo signals and signal-to-noise ratio (SNR) of the target rock samples, obtaining the peak values ​​of the echo signals and SNR. The peak values ​​of the echo signals were arranged chronologically by their acquisition times to obtain the echo signal peak sequence; similarly, the peak values ​​of the SNR were arranged chronologically by their acquisition times to obtain the SNR peak sequence. The null hypothesis was that there was no significant difference between the echo signal peak sequence and the SNR peak sequence; the alternative hypothesis was that there was a significant difference between them. A t-test was used to calculate the p-value. The p-value was denoted as the statistical significance of the target echo signal and SNR.

[0126] The greater the statistical significance of the target echo signal and the signal-to-noise ratio, the greater the possibility that the echo signal of the target rock sample is interfered with.

[0127] The peak values ​​of the echo signals from the target rock sample are arranged in ascending order to obtain the echo signal peak value sequence; the peak values ​​of the signal-to-noise ratio (SNR) of the target rock sample are also arranged in ascending order to obtain the SNR peak value sequence. The DTW distance between the echo signal peak value sequence and the SNR peak value sequence is denoted as the time variation difference between the target echo signal and the SNR.

[0128] The smaller the difference in time variation between the target echo signal and the signal-to-noise ratio, the more consistent the trend of the target rock sample's echo signal and signal-to-noise ratio over time.

[0129] The noise amplification factor of the target echo signal is obtained based on the comprehensive interference caused by volume, the statistical significance of the target echo signal and the signal-to-noise ratio, and the time variation difference.

[0130] Preferably, as an embodiment of this application, the normalized value of the product of the statistical significance of the target echo signal and the signal-to-noise ratio and the time variation difference is recorded as the second product of the target echo signal; the difference between the digit 1 and the second product of the target echo signal is recorded as the third product of the target echo signal; and the product of the volume influence comprehensive interference degree and the third product of the target echo signal is recorded as the noise amplification factor of the target echo signal.

[0131] It should be noted that this embodiment uses the Z-Score standard normalization method to calculate the normalized value. In practical applications, implementers may use other methods of existing technology, such as the maximum-minimum normalization method or the sigmoid function, to calculate the normalized value, and no limitation is made here.

[0132] When the statistical significance of the target echo signal and the signal-to-noise ratio is smaller than the difference in time variation, and the comprehensive interference of volume influence is greater, the noise amplification factor of the target echo signal is greater. At this time, the sensitivity of the volume change of the rock sample to the noise generated by the gradient field switching is greater, that is, the volume change of the rock sample has a greater impact on the noise generated during the gradient field switching.

[0133] Thus, the noise amplification factor of the target echo signal is obtained. The noise amplification factor of any rock sample can be obtained using the same method.

[0134] Step S003: Determine the adjustment threshold of the target echo signal based on the target echo signal, the volume of the rock sample corresponding to the target echo signal, and the noise amplification coefficient of the echo signal. Obtain the denoised target echo signal based on the determined adjustment threshold of the target echo signal.

[0135] The volume of the rock sample is used as the independent variable, and the noise amplification factor of the echo signal corresponding to the rock sample is used as the dependent variable. The least squares method is used to fit the independent and dependent variables to obtain the fitted line, and the slope of the fitted line is recorded as the regression coefficient.

[0136] The least squares method for line fitting is a well-known technique and will not be elaborated further. This embodiment uses the least squares method for line fitting. In practical applications, as other implementation methods, in addition to achieving the purpose of line fitting, implementers may use other existing methods such as polynomial fitting techniques to fit the line. This application does not impose any special restrictions.

[0137] The regression coefficient is used to evaluate the strength of the linear relationship between the volume of a rock sample and the noise amplification factor. The stronger the linear relationship, the larger the absolute value of the regression coefficient.

[0138] The noise level of the target echo signal is obtained using the median absolute deviation (MAD).

[0139] Wavelet transform can be used to denoise the echo signal of rock samples. The soft threshold in wavelet transform determines the ability to distinguish between noise and valid signals in the echo signal.

[0140] The adjustment threshold for the target echo signal is determined based on the regression coefficients and noise level of the target echo signal. The formula for calculating the adjustment threshold of the target echo signal is:

[0141]

[0142] In the formula, T represents the adjustment threshold of the target echo signal; tanh represents the hyperbolic tangent function; β1 represents the regression coefficient of the target echo signal; σ1 represents the first parameter adjustment coefficient, which is set to 1 in this embodiment; and σ represents the noise level of the target echo signal.

[0143] The adjustment threshold of the target echo signal is used as the value of the soft threshold. Wavelet transform is used to denoise the echo signal of the rock sample to obtain the denoised target echo signal.

[0144] The same method can be used to obtain the denoised target echo signal corresponding to the echo signal of any rock sample.

[0145] Using the adjustment threshold of the target echo signal as the soft threshold value can effectively suppress noise while preserving the effective information of the signal. It can also more accurately control the signal processing intensity of wavelet transform at different frequencies, enabling the denoising process to adaptively adjust according to the volume difference of the rock sample and the noise amplification effect. This allows the effective information of the signal to be preserved while suppressing noise, thereby improving the accuracy and reliability of nuclear magnetic resonance signal processing.

[0146] It should be noted that, unless otherwise specified, wavelet transform is used for noise reduction in subsequent NMR measurements in this embodiment to ensure the accuracy of NMR signal processing.

[0147] At this point, the denoised target echo signals corresponding to the echo signals of all rock samples have been obtained.

[0148] Step S004: Perform water content calibration, oil-water content calibration, water distribution experiment, oil distribution experiment, natural loss rock sample pore property characteristic experiment, low temperature dewatering rock sample pore property characteristic experiment, and low temperature deoiling rock sample pore property characteristic experiment on the rock sample. Determine the water distribution area and oil distribution area, as well as the ineffective pore area and effective pore area partition. Provide a boundary delineation method between the ineffective pore area and effective pore area partition in two-dimensional nuclear magnetic resonance spectroscopy, and a boundary delineation method between the water distribution area and oil distribution area in the effective pore area partition. Measure the original sample, perform pore volume recovery and testing on the rock sample, delineate the boundary between the water distribution area and oil distribution area of ​​the shale sample, and obtain the oil-water saturation data of the shale sample according to the given saturation calculation method based on the oil-water distribution boundary value.

[0149] Shale samples cannot be prepared by crushing. To improve the success rate of sample preparation and reduce breakage, specialized cutting tools must be used to prepare shale samples. This also avoids creating cracks in the prepared samples, which could affect the shale test results. The preparation method is as follows: Freeze the full-diameter shale sample to be collected using liquid nitrogen or a -40°C cryogenic freezer; ensure the sample is completely frozen; use a core cutting tool or a specialized core cutter to cut the full-diameter sheet sample along the bedding plane of the core to meet the testing requirements, and then freeze it again to keep it in a frozen state. The required thickness for testing is generally 15mm to 20mm. Use a core cutting tool to cut the full-diameter sheet of core along a direction perpendicular to the bedding and bedding end faces into block samples with geometric shapes that meet the testing requirements.

[0150] The water content of the rock samples was calibrated.

[0151] Specifically, the required rock samples were selected, and the water content inside the rock samples was removed by high temperature. Different amounts of deionized water or distilled water were dripped into each rock sample. The water volumes dripped into the seven rock samples were 0.100 ml, 0.200 ml, 0.300 ml, 0.400 ml, 0.500 ml, 0.700 ml, and 0.900 ml, respectively. Nuclear magnetic resonance (NMR) T2 spectroscopy was performed on each rock sample to obtain the relationship between water content and NMR signal. The relationship between water content and NMR signal is the two-dimensional NMR measurement result.

[0152] A schematic diagram showing the relationship between water content and NMR signal is shown below. Figure 2 As shown, in Figure 2In the graph, the horizontal axis represents the NMR signal, and the vertical axis represents the water content. The water content and the NMR signal show a direct linear relationship. Therefore, NMR technology has high accuracy and reliability in determining water content, and the water content in rock samples can be accurately inferred by measuring the NMR signal.

[0153] The oil content of the rock samples was determined.

[0154] Specifically, all rock samples were selected, and a fixed amount of kerosene was added to the rock sample test cups. The amounts of kerosene in the rock sample cups were 0.500 ml, 1.000 ml, 1.500 ml, 2.000 ml, 2.500 ml, 3.000 ml, and 3.500 ml, respectively. Nuclear magnetic resonance (NMR) measurements were performed on each rock sample to obtain the relationship between the amount of kerosene and the NMR signal. The relationship between the amount of kerosene and the NMR signal is the two-dimensional NMR measurement result.

[0155] A schematic diagram showing the relationship between kerosene quantity and NMR signal is shown below. Figure 3 As shown, in Figure 3 In the graph, the horizontal axis represents the NMR signal, and the vertical axis represents the kerosene content. The kerosene content and the NMR signal have a directly proportional linear relationship. Therefore, NMR technology has high accuracy and reliability in determining the kerosene content, and the amount of kerosene in a rock sample can be accurately inferred by measuring the NMR signal.

[0156] Water distribution experiments were conducted on the rock samples. Specifically, water distribution experiments were performed on rock samples that did not contain hydrogen-containing compounds and rock samples that contained solid or near-solid hydrogen-containing compounds.

[0157] Water distribution experiments were conducted on shale samples that did not contain hydrogen-containing compounds. Specifically, for any hydrogen-containing rock sample, the sample was placed in a 700℃ dry distillation oven to remove the hydrogen-containing compounds, and a two-dimensional nuclear magnetic resonance (NMR) experiment was performed to obtain a two-dimensional NMR spectrum. The two-dimensional NMR spectrum is shown below. Figure 4 As shown in (a), the process continued until all hydrogen-containing compounds in the rock sample were removed. The rock sample was then placed in a humidifier with a humidity level of at least 85% to absorb moisture. Once the mass of the rock sample remained constant, a two-dimensional nuclear magnetic resonance (NMR) experiment was performed again to obtain the T1-T2 distribution spectrum, as shown in Figure (a). Figure 4 As shown in (b), the water distribution area is determined.

[0158] The T1-T2 distribution spectrum is a two-dimensional NMR spectrum, also known as a combined T1-T2 measurement spectrum. A schematic diagram of the two-dimensional NMR distribution spectrum in a rock sample water distribution experiment is shown below. Figure 4 In (a), after the rock sample was dried in a 700℃ dry distillation chamber, the hydrogen-containing compounds were basically removed. After water was added to the rock sample, the NMR signal in the two-dimensional NMR T1-T2 spectrum was distributed near the diagonal of the T1-T2 map. Figure 4 In the schematic diagram (b) of the two-dimensional NMR spectrum of the rock sample water distribution experiment, relative to the rock sample water distribution, Figure 4In (a), the newly added NMR signal is the NMR signal of water.

[0159] Water distribution experiments were conducted on shale samples containing solid or near-solid hydrogen-containing materials.

[0160] Specifically, a random shale sample was selected, and two-dimensional nuclear magnetic resonance (NMR) measurements were performed to obtain a two-dimensional NMR spectrum. The sample was then placed in an alcohol-benzene solvent for degreasing, dehumidified at 115℃ to constant weight, and subjected to another two-dimensional NMR experiment to obtain the T1-T2 distribution spectrum under degreasing and dehumidification conditions. The sample was then placed in a humidifier with a humidity level of at least 85% to absorb moisture, and after being weighed to a constant mass, another two-dimensional NMR measurement was performed to obtain a water-saturated two-dimensional NMR spectrum. The sample was then broken open, dehumidified again, and after being weighed to a constant mass, another two-dimensional NMR measurement was performed to obtain a water-absorbing two-dimensional NMR spectrum of the sample containing fractures under external force damage conditions. The results of the two-dimensional NMR measurements under different conditions were compared to determine the location of water distribution. In this process, the two-dimensional NMR distribution spectra of water distribution experiments under different conditions are shown below. Figure 5 As shown.

[0161] exist Figure 5 Image (a) shows the two-dimensional NMR spectrum obtained from the original rock sample. The T1-T2 NMR map shows strong NMR signals in the oil-water distribution area, indicating good oil-water distribution in the sample. Figure 5 In (b), the NMR signal belongs to hydrogen-containing compounds that cannot be removed by solvent degreasing and dehumidification at 115℃. These unremovable hydrogen-containing compounds are mainly crystal water or structural water within clay minerals, organic matter, and asphaltenes, and are solid or near-solid hydrogen-containing compounds; Figure 5 In the middle (c), the rock sample absorbed water and showed new NMR signals. The basic distribution of the new NMR signals is similar to... Figure 4 Similar to (b), in the region near the diagonal of the two-dimensional NMR spectrum, i.e., in the region where T1 / T2 = 10⁻¹, the signal appearing belongs to the water signal; Figure 5 In the middle (d), after the rock sample is subjected to external force and cracks are generated, it is re-saturated with water and obtains a new two-dimensional nuclear magnetic spectrum with a new nuclear magnetic signal. The new nuclear magnetic signal is the water that is re-saturated, and its two-dimensional nuclear magnetic signal is basically distributed along the region of T1 / T2 = 10-1.

[0162] The above experimental process shows that in the two-dimensional nuclear magnetic resonance distribution spectrum of the rock sample, water is distributed along the diagonal of the T1-T2 two-dimensional spectrum, that is, the two-dimensional nuclear magnetic resonance distribution area of ​​water is basically in the range of T1 / T2 = 10-1.

[0163] Oil distribution experiments were conducted on the rock samples.

[0164] Specifically, an arbitrary rock sample was selected, degreased using an alcohol-benzene solvent, and dehumidified at 115℃. A two-dimensional nuclear magnetic resonance (NMR) experiment was then conducted to obtain the two-dimensional NMR spectrum of the rock sample under the degreased and dehumidified conditions. The two-dimensional NMR spectrum of the two-dimensional NMR experiment is shown below. Figure 6As shown in (a); after the rock sample absorbed water in an environment with a humidity of not less than 85%, two-dimensional nuclear magnetic resonance (NMR) measurements were performed to obtain the two-dimensional NMR spectrum of the rock sample under water absorption conditions. The two-dimensional NMR spectrum of the rock sample under water absorption conditions is shown in Figure 1. Figure 6 As shown in (b), the rock sample was immersed in kerosene to absorb saturated kerosene. After the mass stabilized, two-dimensional nuclear magnetic resonance (NMR) measurements were performed to obtain the two-dimensional NMR spectrum of the rock sample under water and oil absorption conditions. The two-dimensional NMR spectrum of the rock sample under water and oil absorption conditions is shown in the figure. Figure 6 As shown in (c).

[0165] Two-dimensional NMR spectrum of oil distribution experiment as shown in the figure. Figure 6 As shown, where, Figure 6 In (a), only the NMR signal at the left edge is present, which belongs to hydrogen-containing substances that cannot be removed by degreasing and dehumidification, while the pore fluid has been removed; Figure 6 In (b), a new signal was detected to the right of the original indelible NMR signal. The new signal was the NMR signal of the inhaled water. Its distribution range was consistent with the previous water distribution experiment, and it was basically distributed in the T1 / T2 = 10-1 region. The NMR signal belonged to the inhaled water. Figure 6 The new signal detected in (c) is the two-dimensional NMR signal of the absorbed oil, distributed in the region with a high T1 value, above the water signal and with a slightly increased T2, i.e., T1 / T2>10, indicating a stratification phenomenon with water. This oil distribution experiment shows that under the condition of a two-phase medium containing both water and oil, the two-dimensional NMR spectrum of shale samples exhibits oil-water stratification, with oil distributed in the region of T1 / T2>10 and water similarly distributed in the range of T1 / T2=10⁻¹.

[0166] Experiments were conducted on the porosity characteristics of naturally dissipated rock samples.

[0167] Specifically, two shale samples collected from the central part of the shale oil reservoir core were selected. Before complete thawing, two-dimensional nuclear magnetic resonance (NMR) measurements were performed. The samples were then placed in sample bottles and allowed to thaw slowly under natural conditions. After complete thawing, the samples were placed under vacuum at 60°C for 8 hours to remove pore water, and then subjected to NMR measurements to obtain their two-dimensional NMR spectra. One of the dehydrated samples was placed under constant humidity conditions (greater than 85%) to allow it to self-absorb water and remain at constant mass. Then, the sample was placed in kerosene to allow it to self-absorb kerosene and remain at constant mass, and then subjected to NMR measurements to obtain its two-dimensional NMR spectrum. The other dehydrated sample was first placed in kerosene, then under constant humidity conditions (greater than or equal to 85%) to allow it to self-absorb kerosene and water respectively, and then subjected to NMR measurements.

[0168] Table 1 shows the NMR analysis data of the water-absorbing and oil-absorbing rock samples.

[0169] Table 1. Nuclear magnetic resonance analysis data of water-absorbing and oil-absorbing rock samples.

[0170]

[0171]

[0172] As shown in Table 1, after rock sample 1 absorbed water to saturate, the water volume increased by 0.045 ml, and the oil and gas content remained basically unchanged. After absorbing oil to saturate, the oil and gas content increased by 0.027 ml, and the water content remained unchanged. For rock sample 2, after absorbing oil to saturate, the oil volume increased by 0.034 ml, and the pore water content remained basically unchanged. After absorbing water to saturate, the pore water content increased by 0.047 ml, and the oil and gas content remained unchanged. The oil and water volume measured after the rock sample absorbed oil and water was slightly greater than the oil and water volume measured during pressure freezing.

[0173] Therefore, when a rock sample containing oil and water in its pores is saturated with oil and water through self-absorption, water can only enter the pore space where water is present, i.e., water-wetted pores, under the action of capillary force. Pores containing oil are oil-wetted and have a repulsive force on water, so water cannot enter the oil-wetted pores. Similarly, oil can be self-absorbed into oil-wetted pores under the action of capillary force, while pores containing water, because the capillaries contain water and the pore surface is adsorbed with water, are water-wetted and have a repulsive force on oil, so oil cannot enter the water-wetted pore space. Therefore, the pores of rock samples containing some oil and water are selective for the oil and water absorbed. In other words, the pores of shale rock samples with some oil and water loss in the original rock sample are selective for the oil and water absorbed. Oil can only enter the pores where oil is present, and water can only enter the pores where water is present. Moreover, naturally lost rock samples can be saturated with oil and water through self-absorption, which means that oil and water loss rock samples can be restored to have an oil and water distribution close to that of the reservoir through self-absorption saturation.

[0174] Experiments were conducted on the porosity characteristics of rock samples after low-temperature dehydration.

[0175] Two-dimensional nuclear magnetic resonance (NMR) measurements were performed on any rock sample. The rock sample was placed under vacuum and low temperature (60℃) for 8 hours to remove pore water, and then two-dimensional NMR analysis was conducted to obtain the T1-T2 distribution spectrum under the condition of pore water removal. The rock sample was then placed under constant humidity conditions (humidity greater than 85%) to allow it to absorb water and remain saturated with water. After the mass remained unchanged, two-dimensional NMR measurements were performed to obtain the T1-T2 oil-water distribution spectrum under the condition of water reabsorption. The reproducibility of pore water was determined by comparing and analyzing the two-dimensional NMR data under different conditions.

[0176] Specifically, rock samples collected from the core section of the shale oil reservoir under pressure were subjected to two-dimensional nuclear magnetic resonance (NMR) analysis before complete thawing. The two-dimensional NMR spectra are shown below. Figure 7As shown in (a); then, the rock sample was placed in a sample bottle and allowed to thaw slowly under natural conditions for 4 hours to ensure complete thawing. The rock sample was then placed under vacuum at 60°C for 8 hours to remove pore water, and a two-dimensional nuclear magnetic resonance (NMR) analysis was performed on the dewatered rock sample. The two-dimensional NMR spectrum is shown in (a). Figure 7 As shown in (b); the dehydrated rock sample was placed under constant humidity conditions (greater than 85%) to allow it to absorb water and remain saturated with water. Afterward, a second two-dimensional nuclear magnetic resonance (NMR) measurement was performed on the rock sample, and the NMR spectrum is shown below. Figure 7 As shown in (c).

[0177] Two-dimensional NMR spectrum of rock sample porosity characteristics under low-temperature dehydration is shown in the figure. Figure 7 As shown. In Figure 7 In the diagram, (a) indicates that the selected rock sample contains a good oil-water distribution, (b) indicates that the pore water has been basically removed and some oil has also been removed, and (c) indicates that the rock sample is rehydrated and saturated, and can reabsorb water into the pores where the pore water has been removed, while water cannot enter the pores where oil is present.

[0178] The rock samples collected from the pressure-maintaining core of the shale oil reservoir contain a good distribution of oil and water. After the rock samples are placed under vacuum low temperature of 60℃ for 8 hours, the pore water is basically removed and some oil is also removed. After the rock samples are saturated with moisture, they can reabsorb water into the pores where the pore water has been removed, while water cannot enter the pores where oil is present.

[0179] Therefore, pore water is reproducible, meaning that under capillary action, water can enter the pores originally occupied by pore water, but water cannot enter the pores where oil is present.

[0180] Experiments were conducted on the porosity characteristics of rock samples after low-temperature oil removal.

[0181] Specifically, rock samples collected from the pressure-maintaining core sections of shale oil reservoirs were subjected to two-dimensional nuclear magnetic resonance (NMR) measurements. The two-dimensional NMR spectra are shown below. Figure 8 As shown in (a), chloroform was used for low-temperature degreasing and dehumidification at 60℃, with a degreasing time generally not less than 70 hours. Two-dimensional nuclear magnetic resonance (NMR) experiments were conducted on the rock samples to obtain the two-dimensional NMR spectra after degreasing and dehumidification. The two-dimensional NMR spectra are shown below. Figure 8 As shown in (b), the rock sample was immersed in kerosene until it was saturated with kerosene through self-absorption. After maintaining the same mass, a two-dimensional nuclear magnetic resonance (NMR) experiment was conducted to obtain the two-dimensional NMR spectrum under water-free conditions. The two-dimensional NMR spectrum is shown below. Figure 8 As shown in (c); the rock sample was placed under constant humidity conditions (greater than 85%), allowing it to absorb water and remain saturated with constant mass. Two-dimensional nuclear magnetic resonance (NMR) measurements were then performed on the rock sample again to obtain the NMR spectrum under the conditions of re-absorbing water. The two-dimensional NMR spectrum is shown below. Figure 8 As shown in (d).

[0182] It is important to understand that two-dimensional NMR spectroscopy refers to the combined T1-T2 measurement spectrum.

[0183] Two-dimensional NMR spectrum of rock sample porosity characteristics after low-temperature oil removal experiment is shown below. Figure 8 As shown, through comparison Figure 8 It can be seen that (a) indicates that the selected rock sample contains a certain amount of oil and water, with water distributed between T1 / t2 = 1 and 10, and oil mainly distributed in areas where T1 / T2 > 10; (b) indicates that after the rock sample is degreased and dehumidified at low temperature, the oil and water are basically removed. After the rock sample is immersed in kerosene and saturated by self-absorption, the original water distribution area has a strong nuclear magnetic resonance signal; (c) indicates that under the condition of no pore water, oil can not only enter the pore space where the original rock sample oil is located, but also enter the pore space occupied by the original rock sample pore water. The pore space refers to the pores with different properties that oil can enter when the rock sample is dry or contains only oil. (d) indicates that after the rock sample is saturated with water by self-absorption and the mass remains unchanged, the two-dimensional NMR oil-water distribution is the same as the original two-dimensional NMR distribution of the selected rock sample. This means that the water saturation of the rock sample displaces the oil at the same time. That is, the water displaces the self-absorbed saturated oil that occupies the original water distribution area of ​​the rock sample. In other words, the water reoccupies the pore space that it occupies, but the water cannot displace the oil in the pore space where the original rock sample oil is located.

[0184] Water can displace oil in water-distributed areas because the capillary surface tension of water in these areas is greater than that of oil. In other words, the capillary force exerted by water on water is greater than that exerted by oil, and the capillary pores are hydrophilic. However, water cannot displace oil in oil-distributed areas because the capillary force exerted by oil on oil is greater than that exerted by water, and the capillary pores in these areas are oleophilic. These oleophilic and hydrophilic pores are called organic pores and inorganic pores, respectively. The oleophilic organic pores and hydrophilic inorganic pores can be restored by absorbing oil and water, thus obtaining the size and distribution of organic and inorganic pores.

[0185] Based on the conclusions obtained from oil-water distribution experiments, even after removing pore water and oil from rock samples and pre-saturating them with water, water will not enter the pore spaces occupied by oil. This indicates that rock samples can self-absorb and saturate with oil and water; water can only enter the pore spaces occupied by water, not the oil-bearing pores. In the absence of pore water, oil can enter both the pores originally occupied by pore water and the oil-bearing pores, but water can displace the oil in the pore spaces originally occupied by pore water, not the oil-bearing pores. In the presence of pore water, oil can only enter the oil-bearing pores; it cannot displace the pores already occupied by water. Therefore, pore characteristics can be utilized to reconstruct the oil-water pore spaces in rock samples, enabling the determination of different porosity and oil content.

[0186] Therefore, oil also has reproducibility, meaning that oil can enter the pore space where it is stored under capillary force.

[0187] Experiment to determine the distribution locations of effective and ineffective porosity regions.

[0188] The rock samples were deoiled using alcohol and benzene solvent, and then dehumidified at 115℃ to constant weight. Two-dimensional nuclear magnetic resonance (NMR) experiments were then performed to obtain the T1-T2 distribution spectra of solid or near-solid hydrogen-containing substances such as crystalline water or structural water within clay minerals, organic matter, and bitumen under the deoiling and dehumidification conditions. Figure 6 In (a), there is no reservoir capacity, and it does not affect the distribution of oil and water in the reservoir. The pores contained therein have no practical significance for oil and gas storage. It can be used to locate the region where the nuclear magnetic signal of solid or near-solid hydrogen-containing substances such as crystalline water or structural water, organic matter and asphaltene in clay minerals is located in the T1-T2 two-dimensional nuclear magnetic resonance joint test spectrum as an invalid pore region.

[0189] The rock samples were deoiled using alcohol and benzene solvent, and then dehumidified to constant weight at 115℃. The samples were then saturated with oil and water through self-absorption, and two-dimensional NMR T1-T2 combined measurements were performed to obtain the NMR T1-T2 oil-water distribution spectra as shown below. Figure 6 (b) Figure 6 In (c), Figure 6 (b) Figure 6 (c) and Figure 6 In comparison (a), the newly emerging nuclear magnetic resonance signal is oil and water. Oil and water and the pores they contain are the main research objects of this application. The pores occupied by oil and water are the oil, gas and water storage space of shale reservoirs, which belong to the effective pore area.

[0190] Therefore, the regions containing the T1-T2 distribution spectra of solid or near-solid hydrogen-containing substances such as crystalline water or structural water, organic matter, and asphaltene within clay minerals are identified as ineffective porosity distribution regions, while the regions containing saturated oil and water are identified as effective porosity distribution regions.

[0191] The boundaries between the ineffective pore region and the effective pore region were delineated in the T1-T2 combined measurement spectrum.

[0192] Specifically, in addition to flowing pore water and near-solid crystalline water, shale oil samples also contain clay-adsorbed water adsorbed on the surface of the clay layer. The mixture of different types of water leads to a complex distribution of effective and ineffective pore regions, making it difficult to distinguish the boundary between them in many samples. To accurately extract pore water data corresponding to the saturation obtained using two-dimensional NMR spectroscopy, it is necessary to clearly define the boundary between effective and ineffective pore regions. Therefore, a suitable method for delineating effective and ineffective pore regions needs to be established. Since the T2 relaxation time of NMR spectroscopy corresponds to the pore size of the sample, the T2 relaxation time value can be used for delineation. Specific methods include:

[0193] Based on determining the distribution locations of the effective and ineffective porosity regions, the abscissa of the weakest NMR signal between the effective and ineffective porosity regions in the two-dimensional NMR spectrum is marked as 'a'. The straight line with abscissa 'a' is used as the boundary between the effective and ineffective porosity regions. The region less than or equal to the line 'a' is the ineffective porosity region, and the region greater than the line 'a' is the effective porosity region.

[0194] Since there was no obvious weakest point in the NMR signal between the effective and ineffective porosity regions, the ineffective porosity region was selected as T2≤0.2ms and the effective porosity region as T2>0.2ms in the T1-T2 rectangular coordinate system. The oil-water distribution zone delineation diagram of the two-dimensional NMR spectrum of the shale sample is shown below. Figure 9 As shown in (b), line A is the boundary between the ineffective pore region and the effective pore region.

[0195] When the NMR signal between the effective pore region and the ineffective pore region is continuously absent, i.e., the NMR signal is all in the background area of ​​the spectrum, the value of 'a' is a = (a1 + a2) / 2, where a1 is the left boundary T2 value of the continuous absence of NMR signal, and a2 is the right boundary T2 value of the continuous absence of NMR signal. Similarly, the line T2 ≤ a ms is the ineffective pore region, and T2 > a ms is the effective pore region.

[0196] Numerous experiments have shown that, under natural conditions, the corresponding regions of two-dimensional NMR signals for hydrogen-containing solids or near-solids such as crystalline water, structural water, organic matter, and asphaltene are mostly before T2 = 0.1 ms, while the NMR signals for pore water are generally after T2 = 0.2 ms. The boundary between the ineffective pore region and the effective pore region is generally between T2 = 0.1 ms and T2 = 0.2 ms. The ineffective pore region and the effective pore region in the two-dimensional NMR T1-T2 oil-water distribution spectrum of shale oil rock samples measured by equipment can be divided according to this method.

[0197] Boundary delineation between water and oil distribution.

[0198] Specifically, determining saturation requires precise and accurate oil-water data. Reservoir oil and gas are highly complex mixtures, and the composition of oil, gas, and water with different properties, along with varying occurrence states, all affect the oil-water distribution in two-dimensional NMR spectra. This can lead to unclear boundaries between water and oil distributions, necessitating the establishment of appropriate methods for delineating water and oil distribution zones. Interactions between different substances primarily affect the relaxation time T1 value, which can be used for delineation. Specific methods include:

[0199] Specifically, the ordinate of the weakest NMR signal between pore water and oil distribution areas is denoted as 'b'. The straight line with ordinate 'b' serves as the boundary between water and oil distribution areas within the effective pore region. Between the oil and water distribution areas, regions with ordinates greater than 'b' are designated as oil distribution areas, and regions with ordinates less than or equal to 'b' are designated as water distribution areas. The oil-water distribution area delineation diagram of the two-dimensional NMR spectrum of shale samples is shown below. Figure 9 As shown in (a), straight line B is the oil-water boundary line.

[0200] When there is no obvious weakest point in the NMR signal between pore water and oil, the region with a ordinate greater than 10 ms is designated as the oil distribution region, and the region with a ordinate less than or equal to 10 ms is designated as the water distribution region. The oil-water distribution region delineation diagram of the two-dimensional NMR spectrum of the shale sample is shown below. Figure 9 As shown in (c), straight line B is the oil-water boundary line.

[0201] When a region with no NMR signal appears continuously between the pore water and oil distribution areas, the midline of this continuous region is taken as the boundary between the oil and water distribution areas. The value of b is b = (b1 + b2) / 2, where b1 is the lower boundary T1 value of the continuous region with no NMR signal, and b2 is the upper boundary T1 value of the continuous region with no NMR signal. Similarly, between the oil and water distribution areas, the region with a ordinate greater than b is designated as the oil distribution area, and the region with a ordinate less than or equal to b is designated as the water distribution area. The oil-water distribution area delineation diagram of the two-dimensional NMR spectrum of the shale sample is shown below. Figure 9 As shown in (b), straight line B is the oil-water boundary line.

[0202] exist Figure 9 In the diagram, a is a data boundary delineation map of samples with relatively clear boundaries between effective and ineffective pores and between oil and water distributions; b is a data boundary delineation map of samples with unclear boundaries between effective and ineffective pores and continuous no-signal distributions between oil and water; c is a data boundary delineation map of samples with clear boundaries between effective and ineffective pores and unclear boundaries between oil and water distributions; 1 represents the ineffective pore region; 2 represents the oil-water effective pore region; 3 represents the pore water distribution region; 4 represents the oil and gas distribution region; A represents the boundary between ineffective and effective pores; B represents the boundary between oil and water distributions.

[0203] At this point, the water and oil distribution areas have been determined.

[0204] Finally, the porosity of the rock sample was restored.

[0205] Since determining saturation requires not only data on the oil and water content within the rock sample but also data on the pore volume, and since NMR measures the fluid within the pores but cannot measure the pores in the rock sample, it is necessary to reconstruct the pores of the rock sample based on pore property experiments.

[0206] Specifically, based on the two-dimensional residual oil-water determination spectrum of the rock sample, qualitative analysis was performed as follows: When the water distribution was greater than the oil distribution, the rock sample was placed in a sample bottle containing kerosene to allow it to absorb the kerosene. After the rock sample mass remained constant, the rock sample was placed in a constant humidity chamber with a humidity of not less than 85% to allow it to absorb water until the mass remained constant. When the water distribution was much smaller than the oil distribution, the rock sample was placed in a constant humidity chamber with a humidity of not less than 85% to allow it to absorb water until the mass remained constant. After the mass remained constant, the rock sample was placed in a sample bottle containing kerosene to allow it to absorb the kerosene until the mass remained constant. When the water distribution was the same as the oil distribution, the rock sample was placed in a sample bottle containing kerosene to allow it to absorb the kerosene. After the rock sample mass remained constant, the rock sample was placed in a sample bottle containing water to allow it to absorb water until the mass remained constant.

[0207] Understandably, this self-absorption saturation method can shorten the self-absorption saturation time of rock samples.

[0208] The pore volume of the rock sample was measured.

[0209] Two-dimensional nuclear magnetic resonance (NMR) equipment was used to conduct T1-T2 combined measurements on rock samples that had been saturated with oil and water by self-absorption, and two-dimensional NMR test data and spectra were obtained.

[0210] Based on the rock sample pore property experiment, after the rock sample is saturated with self-absorption oil and water, water can only enter the pores where the original pore water is located. In other words, water can only enter the water-wetting pores, and oil can only enter the oil-wetting phase pores. When the self-absorption saturation mass is constant, the rock sample pores are completely saturated, and the sum of the measured oil and water volumes is the pore volume of the rock sample.

[0211] Two-dimensional nuclear magnetic resonance (NMR) measurements after self-absorption of oil and water can determine that the water volume is close to the reservoir water volume of the rock sample, and the oil volume is close to the reservoir oil and gas volume of the rock sample. Therefore, the accuracy of calculating the oil-water saturation of the rock sample using the amount of oil and water after self-absorption saturation is higher than that calculated using the amount of oil and water before self-absorption saturation, which is higher than the saturation of residual oil and water in the rock sample determined by two-dimensional NMR. This method solves the problem of the inability to correct for oil and gas loss during the core extraction and drilling process when the rock sample is cored.

[0212] Delineation of oil-water distribution zones in measured shale samples:

[0213] The purpose of defining the oil-water boundary in the measured sample is to accurately extract oil-water data from the two-dimensional NMR spectrum for calculating saturation. Specific methods are as follows:

[0214] In the two-dimensional NMR spectrum of the measured shale sample after oil and water absorption, the abscissa of the weakest point of the NMR signal between the effective porosity region and the ineffective porosity region is marked as 'a'. The straight line with abscissa 'a' is used as the boundary between the effective porosity region and the ineffective porosity region. The straight line A with abscissa 'a' is the left boundary line of the water distribution region, and the straight line A is also the left boundary line of the oil distribution region.

[0215] In the two-dimensional NMR spectrum of the rock sample after oil and water absorption, the ordinate of the weakest point of the NMR signal in the water distribution area and the oil distribution area is marked as b. The straight line with the ordinate as b is used as the boundary between the water distribution area and the oil distribution area. The upper side of the straight line B with the ordinate as b is the lower boundary line of the oil distribution area; the lower side of the straight line B is the upper boundary line of the water distribution area.

[0216] Other boundary lines for oil-water separation, such as Figure 10 As shown, the lower boundary line of the water data area is any perpendicular line to the T1 axis outside the lower boundary of the water data area, i.e., the area without NMR signals, such as line C. The T1 coordinate value is c. The right boundary line of the water data area is any perpendicular line to the T2 axis outside the right boundary of the water data area, such as line N. The T1 coordinate value is n. The right boundary line of the oil data area is any perpendicular line to the T2 axis outside the right boundary of the oil data area, such as line M. The T1 coordinate value is m. The upper boundary line of the oil data area is any perpendicular line to the T1 axis outside the upper boundary of the oil data area, such as line D. The T1 coordinate value is d.

[0217] The oil-water distribution zone delineation diagram of the two-dimensional NMR data extraction of shale samples is shown below. Figure 10 As shown in the figure, in Figure 10 In the diagram, 1 represents the ineffective pore region; 2 represents the effective pore region for oil and water; 3 represents the pore water distribution region; 4 represents the oil and gas distribution region; A represents the boundary between ineffective and effective pores; B represents the boundary between oil and water distribution; C represents any perpendicular line from the lower edge of the water distribution area to the T1 axis; N represents any perpendicular line from the right edge of the water distribution area to the T2 axis; D represents any perpendicular line from the upper edge of the oil distribution area to the T1 axis; and M represents any perpendicular line from the right edge of the oil distribution area to the T2 axis.

[0218] Thus, the effective pore region, ineffective pore region, water distribution region, and oil distribution region are obtained.

[0219] Step S005: Based on the measured NMR signal values ​​in the water and oil distribution areas, calculate the oil-water saturation of the rock sample using the two-dimensional NMR saturation calculation method to obtain the NMR-based oil-water saturation measurement results.

[0220] Based on the values ​​of all NMR signals in the water distribution area and the oil distribution area, the NMR determination of water saturation and NMR determination of oil saturation are calculated respectively.

[0221]

[0222]

[0223] In the formula, S W1 S indicates the water saturation measured by nuclear magnetic resonance (NMR). W2 Indicates the oil saturation measured by NMR; k waterThe conversion factor between the rock sample NMR signal and the water signal is denoted by 0.9213 in this embodiment; M1 represents the sum of all NMR signals within the water distribution area; K oil M1 represents the conversion coefficient between the rock sample NMR signal and the oil signal, and in this embodiment, the value is 1.2246; M2 represents the sum of all NMR signals in the oil distribution area.

[0224] The data for water saturation and oil saturation determined by NMR for the seven rock samples in this application are shown in Table 2.

[0225] Table 2. Data on water saturation and oil saturation determined by NMR.

[0226]

[0227] Table 2 shows the oil-water saturation data determined by two-dimensional nuclear magnetic resonance (NMR) for seven samples, measured according to the method provided in this patent application. High-frequency two-dimensional NMR determination of pore water and oil in shale oil rock samples offers visualization. Through the analysis of the two-dimensional NMR T1-T2 oil-water distribution spectrum, the measured oil-water distribution and properties can be clearly seen, enabling the assessment of pore structure. Its accuracy is higher than other methods for determining oil-water saturation, and it has achieved excellent results in practical applications. It is an indispensable source of compositional data for studying the oil-water distribution characteristics of shale oil reservoirs.

[0228] Thus, the results of the oil-water saturation determination of the rock sample based on nuclear magnetic resonance technology were obtained.

[0229] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for intelligent determination of oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance (NMR) technology, characterized in that, The method includes the following steps: Collect the volume, echo signal, and signal-to-noise ratio of a preset number of rock samples; Any rock sample is designated as the target rock sample, and all other rock samples are designated as comparison rock samples. Based on the frequency values ​​of the echo signals of the target and comparison rock samples, the range of target frequency is defined, and the power spectrum and power spectral density of the target and comparison rock samples are obtained. Based on the similarity between the power spectral densities of the target and comparison rock samples, the difference between the power spectral densities, the distribution of peak values ​​in the power spectrum, and the volume difference, the volume influence of the target rock sample on echo interference is determined. Based on the volume influence of all rock samples on echo interference, the comprehensive volume influence is determined. Combining the peak distribution and peak value of the echo signal and signal-to-noise ratio of the target rock sample, the noise amplification factor of the target echo signal is obtained. Based on the target echo signal, the volume of the rock sample corresponding to the target echo signal, and the noise amplification factor of the echo signal, the adjustment threshold of the target echo signal is determined, and the denoised target echo signal is obtained based on the determined adjustment threshold of the target echo signal. The rock samples were subjected to water content calibration, oil-water content calibration, water distribution experiments, oil distribution experiments, porosity characteristic experiments of naturally leached rock samples, porosity characteristic experiments of rock samples dehydrated at low temperature, and porosity characteristic experiments of rock samples deoiled at low temperature. The water distribution area and oil distribution area were determined, and two-dimensional nuclear magnetic resonance (NMR) spectra were obtained. Based on the two-dimensional NMR spectra, ineffective porosity areas and effective porosity areas were divided. The boundary lines of NMR signals between effective porosity areas and ineffective porosity areas were delineated. The boundaries between water distribution areas and oil distribution areas in the effective porosity areas were delineated. The porosity of the rock samples was then restored. Based on the measured NMR signal values ​​in the water and oil distribution areas, the oil-water saturation of the rock samples was calculated using the two-dimensional NMR saturation calculation method to obtain the NMR-based oil-water saturation measurement results.

2. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The method for preparing the rock sample is as follows: Rock samples were collected from the pressure-maintaining core locations of the shale oil reservoir in the exploration area. After the rock samples were brought to the surface through drilling and brought out of the casing, they were completely frozen and preserved in a freezer at a temperature of -40°C or less using freezing technology. The rock samples had to be completely frozen and were large, sheet-like rock samples with a diameter of 15 mm or more and a diameter of 20 mm or less. The cutting tools should be used to cut along the direction perpendicular to the bedding planes and bedding end faces of the rock samples to ensure that the geometry of the rock samples met the testing requirements. The samples were then frozen again to keep them in a frozen state.

3. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The specific method for defining the target frequency range based on the frequency values ​​of the echo signals of the target rock sample and the comparison rock sample, and obtaining the power spectrum and power spectral density of the target rock sample and the comparison rock sample, includes: The echo signals of the target rock sample and the comparison rock sample were converted into frequency domain signals using Fast Fourier Transform, and the power spectrum diagrams and power spectral densities were obtained based on the frequency domain signals. The minimum value of all frequency domain signals is recorded as the minimum frequency value, the maximum value of all frequency domain signals is recorded as the maximum frequency value, and all natural numbers greater than or equal to the minimum frequency value and less than or equal to the maximum frequency value are taken as the range of values ​​for the target frequency.

4. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The method for determining the volume-related echo interference of the target rock sample based on the similarity between the power spectral densities of the target rock sample and the comparison rock samples, the difference between their power spectral densities, the distribution of peak values ​​in the power spectra, and the volume difference includes the following specific methods: The absolute value of the Pearson correlation coefficient between the power spectral density of the target rock sample and the comparison rock sample is denoted as the power spectral correlation between the target rock sample and the comparison rock sample, and the mean value of the power spectral correlation between the target rock sample and all comparison rock samples is denoted as the rock sample attribute similarity of the target rock sample. The peak values ​​of the power spectra of the target rock sample and the comparison rock sample are obtained separately. The minimum absolute value of the difference between the target frequency and all peak values ​​of the target rock sample is recorded as the shortest frequency difference of the target rock sample at the target frequency. The minimum absolute value of the difference between the target frequency and all peak values ​​of the comparison rock sample is recorded as the shortest frequency difference of the comparison rock sample at the target frequency. At the target frequency, the absolute value of the difference between the shortest frequency differences of the target rock sample and the comparison rock sample is recorded as the shortest frequency difference between the target rock sample and the comparison rock sample at the target frequency. The mean of the shortest frequency differences between the target rock sample and all comparison rock samples at the target frequency is recorded as the first difference of the target rock sample at the target frequency. The absolute value of the difference between the power spectral density of the target rock sample and the comparison rock sample at the target frequency is denoted as the power spectral difference between the target rock sample and the comparison rock sample at the target frequency. The mean of the power spectral differences between the target rock sample and all comparison rock samples at the target frequency is denoted as the second difference of the target rock sample at the target frequency. The average volume of all the comparative rock samples is denoted as the average volume of the comparative rock samples, and the absolute value of the difference between the volume of the target rock sample and the average volume of the comparative rock samples is denoted as the volume difference of the target rock sample. The volume influence of the target rock sample on echo interference is determined based on the volume difference of the target rock sample, the similarity of rock sample properties, and the first and second differences of the target rock sample at the target frequency.

5. The intelligent method for determining oil-water saturation of shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 4, characterized in that, The method for determining the volume-related echo interference of a target rock sample based on its volume difference, rock sample property similarity, and first and second differences at the target frequency includes the following specific methods: The product of the first and second differences of the target rock sample at the target frequency is denoted as the third difference of the target rock sample at the target frequency. The sum of the third differences corresponding to the values ​​of the target rock sample at all target frequencies is denoted as the fourth difference of the target rock sample. The product of the volume difference and the fourth difference of the target rock sample is recorded as the first product of the target rock sample. The difference between the number 1 and the rock sample attribute similarity of the target rock sample is recorded as the rock sample attribute difference degree of the target rock sample. The product of the first product of the target rock sample and the rock sample attribute difference degree is recorded as the volume influence echo interference degree of the target rock sample.

6. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The method for obtaining the overall interference degree of the volume influence is as follows: The sum of the volumetric influence echo interference of all rock samples is denoted as the comprehensive volumetric influence interference.

7. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The method for obtaining the noise amplification factor of the target echo signal by combining the peak distribution and peak value of the signal-to-noise ratio of the target rock sample echo signal includes the following specific methods: The peak values ​​of the echo signals and the peak values ​​of the signal-to-noise ratio (SNR) of the target rock sample were obtained separately. The peak values ​​of the echo signals of the target rock sample were arranged in chronological order of their acquisition time to obtain the echo signal peak sequence. The peak values ​​of the SNR of the target rock sample were arranged in chronological order of their acquisition time to obtain the SNR peak sequence. The null hypothesis was that there was no significant difference between the echo signal peak sequence and the SNR peak sequence, and the alternative hypothesis was that there was a significant difference between the echo signal peak sequence and the SNR peak sequence. The t-test algorithm was used to calculate the p-value, and the p-value was recorded as the statistical significance of the target echo signal and the SNR. Arrange the peak values ​​of the echo signals of the target rock sample in ascending order to obtain the echo signal peak value arrangement sequence; arrange the peak values ​​of the signal-to-noise ratio of the target rock sample in ascending order to obtain the signal-to-noise ratio peak value arrangement sequence; and record the DTW distance between the echo signal peak value arrangement sequence and the signal-to-noise ratio peak value arrangement sequence as the time variation difference between the target echo signal and the signal-to-noise ratio. The noise amplification factor of the target echo signal is obtained based on the comprehensive interference caused by volume, the statistical significance of the target echo signal and the signal-to-noise ratio, and the time variation difference.

8. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 7, characterized in that, The method for obtaining the noise amplification factor of the target echo signal based on the comprehensive interference degree of volume influence, the statistical significance of the target echo signal and the signal-to-noise ratio, and the time variation difference is as follows: The normalized value of the product of the statistical significance of the target echo signal and the signal-to-noise ratio and the time variation difference is denoted as the second product of the target echo signal. The difference between the digital 1 and the second product of the target echo signal is denoted as the third product of the target echo signal. The product of the volume influence comprehensive interference degree and the third product of the target echo signal is denoted as the noise amplification factor of the target echo signal.

9. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The method for determining the adjustment threshold of the target echo signal is as follows: The volume of the rock sample is taken as the independent variable, and the noise amplification factor of the echo signal corresponding to the rock sample is taken as the dependent variable. A straight line is fitted to the independent and dependent variables to obtain the fitted straight line. The slope of the fitted straight line is recorded as the regression coefficient. The noise level of the target echo signal is obtained using the median absolute deviation (MAD). Based on the regression coefficients and noise level of the target echo signal, the adjustment threshold of the target echo signal is determined using the following formula: In the formula, T represents the adjustment threshold of the target echo signal; tanh represents the hyperbolic tangent function; β1 represents the regression coefficient of the target echo signal; σ1 represents the first parameter adjustment coefficient; and σ represents the noise level of the target echo signal.

10. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The specific method for obtaining the denoised target echo signal based on the determined adjustment threshold of the target echo signal includes: The adjustment threshold of the target echo signal is used as the value of the soft threshold. Wavelet transform is used to denoise the echo signal of the rock sample to obtain the denoised target echo signal.

11. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The method for calibrating the water volume value is as follows: Seven rock samples were selected, and the water inside the samples was removed by high temperature. Deionized water was then added to each rock sample, with the amounts of water added to the seven samples being 0.100 ml, 0.200 ml, 0.300 ml, 0.400 ml, 0.500 ml, 0.700 ml, and 0.900 ml, respectively. T2 NMR spectroscopy was performed on each rock sample to obtain two-dimensional NMR results.

12. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The method for calibrating the oil-water content is as follows: All seven rock samples were selected, and a fixed amount of kerosene was added to the rock sample test cups. The kerosene amounts in the rock sample cups were 0.500 ml, 1.000 ml, 1.500 ml, 2.000 ml, 2.500 ml, 3.000 ml, and 3.500 ml, respectively. Nuclear magnetic resonance (NMR) measurements were performed on each rock sample to obtain two-dimensional NMR results.

13. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The method for determining the water distribution area is as follows: Water distribution experiments were conducted on rock samples that did not contain hydrogen-containing compounds and rock samples that contained solid or near-solid hydrogen-containing compounds. The process of conducting experiments on water distribution in rock samples that do not contain hydrogen-containing substances is as follows: Select any shale rock sample, place the rock sample in a 700℃ dry distillation oven to remove hydrogen-containing substances, and perform a two-dimensional nuclear magnetic resonance experiment until the hydrogen-containing substances in the rock sample are completely removed. The rock sample was placed in a humidifier with a humidity of not less than 85% to absorb moisture. After the mass of the rock sample remained unchanged, a two-dimensional nuclear magnetic resonance experiment was carried out again to obtain the T1-T2 distribution spectrum and determine the water distribution area.

14. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The process of conducting water distribution experiments on rock samples containing solid or near-solid hydrogen-bearing materials is as follows: Select any shale rock sample, perform two-dimensional nuclear magnetic resonance (NMR) measurements, and obtain a two-dimensional NMR spectrum. The rock sample was placed in an alcohol-benzene solvent to remove oil, and then dehumidified at 115℃ to constant weight. Two-dimensional nuclear magnetic resonance experiments were then performed to obtain the T1-T2 distribution spectrum under the conditions of oil removal and dehumidification. The rock sample was placed in a humidifier with a humidity of not less than 85% to absorb moisture, and after being weighed to a constant mass, a two-dimensional nuclear magnetic resonance (NMR) measurement was performed again to obtain a water-saturated two-dimensional NMR spectrum. The rock sample was broken open and then re-moistened. After the mass was kept constant, a two-dimensional nuclear magnetic resonance (NMR) measurement was performed to obtain the water absorption two-dimensional NMR spectrum of the rock sample under the condition of external force damage and crack formation.

15. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The method for determining the oil distribution area is as follows: Select any shale rock sample, remove oil with alcohol and benzene solvent, dehumidify at 115℃, and conduct a two-dimensional nuclear magnetic resonance experiment to obtain the two-dimensional nuclear magnetic resonance spectrum of the rock sample under the conditions of oil removal and dehumidification. After the rock sample was placed in an environment with a humidity of not less than 85% and absorbed water, two-dimensional nuclear magnetic resonance (NMR) measurements were performed to obtain the two-dimensional NMR spectrum of the rock sample under water absorption conditions. The rock sample was immersed in kerosene to absorb saturated kerosene. After the quality stabilized, two-dimensional nuclear magnetic resonance (NMR) measurements were performed to obtain the two-dimensional NMR spectrum of the rock sample under water and oil absorption conditions. The oil distribution area was determined based on the two-dimensional NMR spectra of rock samples under oil and moisture removal conditions, under water absorption conditions, and under water and oil absorption conditions.

16. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The method for the experimental characteristics of the porosity properties of the naturally eroded rock samples is as follows: Two rock samples collected from the central part of the pressure-maintaining core of a shale oil reservoir were selected. Before complete thawing, two-dimensional nuclear magnetic resonance (NMR) measurements were performed. The samples were then placed in sample bottles and allowed to thaw slowly under natural conditions. After complete thawing, the samples were placed under vacuum at 60°C for 8 hours to remove pore water, and then subjected to NMR measurements to obtain their two-dimensional NMR spectra. One of the dehydrated samples was placed under constant humidity (greater than 85%) to allow it to self-absorb water and become saturated with water. After maintaining its mass, the sample was then placed in kerosene to allow it to self-absorb kerosene and become saturated with oil. Again, after maintaining its mass, two-dimensional NMR measurements were performed to obtain its two-dimensional NMR spectrum. The other dehydrated sample was first placed in kerosene, then under constant humidity (greater than or equal to 85%) to allow it to self-absorb kerosene and water, respectively. After maintaining its mass, two-dimensional NMR measurements were performed on both samples to obtain their two-dimensional NMR spectra.

17. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The method for the experiment on the porosity characteristics of the rock sample under low-temperature dehydration is as follows: After selecting any rock sample and performing two-dimensional nuclear magnetic resonance (NMR) measurements, the rock sample was placed under vacuum low temperature (60℃) for 8 hours to remove pore water. Two-dimensional NMR analysis of the rock sample was then carried out to obtain the T1-T2 distribution spectrum under the condition of removing pore water. Rock samples were placed under constant humidity conditions with a humidity greater than 85% to allow them to absorb water and remain saturated with water. Two-dimensional nuclear magnetic resonance (NMR) measurements were then performed to obtain the T1-T2 oil-water distribution spectrum under water absorption conditions. The reproducibility of pore water was determined by comparing and analyzing the NMR data under different conditions.

18. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The method for the low-temperature oil removal rock sample pore property characteristic experiment is as follows: Rock samples were collected from the central part of the pressure-maintaining core of the shale oil reservoir. After two-dimensional nuclear magnetic resonance (NMR) analysis, chloroform was used for low-temperature degreasing and dehumidification at 60°C. The degreasing time was generally no less than 70 hours. Two-dimensional NMR experiments were carried out on the rock samples to obtain the two-dimensional NMR spectrum after degreasing and dehumidification. Rock samples were immersed in kerosene to saturate them with kerosene, and after the mass remained constant, two-dimensional nuclear magnetic resonance (NMR) experiments were conducted to obtain two-dimensional NMR spectra under kerosene saturation conditions. The rock sample was placed under constant humidity conditions with a humidity greater than 85% to allow it to absorb water and remain saturated with water. Then, two-dimensional nuclear magnetic resonance (NMR) measurements were performed on the rock sample again to obtain the two-dimensional NMR spectrum under the condition of re-absorbing water.

19. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The specific method for dividing the ineffective porosity region and the effective porosity region based on the two-dimensional nuclear magnetic resonance spectrum is as follows: The rock samples were deoiled using alcohol and benzene solvent, and then dehumidified at 115℃ to constant weight. Two-dimensional nuclear magnetic resonance experiments were then performed to obtain the T1-T2 distribution spectrum of solid or near-solid hydrogen-containing substances that could not be removed after deoiling and dehumidification. The samples were then saturated with oil and water by self-absorption, and after the mass was kept constant, two-dimensional nuclear magnetic resonance measurements were performed to obtain the pore oil and water distribution spectrum. The region containing the two-dimensional nuclear magnetic resonance (NMR) spectrum of solid or near-solid hydrogen-containing substances such as crystalline water or structural water, organic matter, and bituminous matter within clay minerals is defined as the ineffective porosity region. The region composed of the self-absorbed saturated water distribution region and the oil distribution region is denoted as the effective porosity region.

20. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The method for delineating the NMR signal boundary between the effective porosity region and the ineffective porosity region is as follows: The abscissa of the weakest NMR signal between the effective porosity region and the ineffective porosity region in the two-dimensional NMR spectrum is marked as 'a'. The straight line with the abscissa 'a' is used as the boundary between the effective porosity region and the ineffective porosity region. The region less than or equal to the line 'a' is the ineffective porosity region, and the region greater than the line 'a' is the effective porosity region.

21. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The method for delineating the boundary between the water distribution zone and the oil distribution zone in the effective porosity partition is as follows: The ordinate of the weakest NMR signal between the oil distribution area and the water distribution area in the effective pore region is marked as b. The straight line with the ordinate of b is used as the boundary between the oil distribution area and the water distribution area. Between the oil distribution area and the water distribution area, the area with the ordinate greater than b is called the oil distribution area, and the area with the ordinate less than or equal to b is called the water distribution area.

22. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The specific methods for restoring the porosity of the rock sample are as follows: When the water distribution is greater than the oil distribution, place the rock sample in a rock sample bottle containing kerosene to allow it to absorb the kerosene. After the rock sample mass remains constant, place the rock sample in a constant humidity chamber with a humidity of not less than 85% to allow the rock sample to absorb water until the mass is constant. When the water distribution is much smaller than the oil distribution, place the rock sample in a constant humidity chamber with a humidity of not less than 85% to allow the rock sample to absorb water until the mass is constant. Then, place the rock sample in a sample bottle containing kerosene to allow the rock sample to absorb kerosene until the mass is constant. When the water distribution is the same as the oil distribution, place the rock sample in a rock sample bottle containing kerosene to allow it to absorb the kerosene. After the rock sample mass remains unchanged, place the rock sample in a constant humidity chamber with a humidity of not less than 85% to allow the rock sample to absorb water until the mass remains unchanged.

23. The intelligent method for determining oil-water saturation in shale samples based on two-dimensional nuclear magnetic resonance technology according to claim 1, characterized in that, The saturation is calculated using the two-dimensional NMR saturation method based on the measured NMR signal values ​​in the water and oil distribution areas. The formula is as follows: where S W1 represents the water saturation determined by NMR; S W2 represents the oil saturation determined by NMR; k water represents the conversion factor of the NMR signal of the rock sample to the water signal; M1 represents the cumulative sum of all NMR signals in the water distribution region; k oil represents the conversion factor of the NMR signal of the rock sample to the oil signal; M2 represents the cumulative sum of all NMR signals in the oil distribution region.

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