Method and system for calculating fluid-containing porosity of shale reservoir rock sample

Abstract

This invention discloses a method and system for calculating the fluid-bearing porosity of shale reservoir samples, comprising: acquiring the current rock sample to be analyzed and determining its sample volume; conducting nuclear magnetic resonance (NMR) logging experiments on the rock sample to obtain a first NMR spectrum; grinding the current rock sample to be analyzed into powder and immersing the powder in an organic solvent, then conducting NMR logging experiments on the mixture to obtain a second NMR spectrum and identifying the spectrum of solid organic precipitates; comparing the first NMR spectrum and the spectrum of solid organic precipitates to obtain a third NMR spectrum; and calculating the fluid-bearing porosity of the rock sample based on the third NMR spectrum and the sample volume. This method effectively eliminates the influence of solid organic precipitates such as kerogen on the measurement results when using NMR technology to measure the fluid-bearing porosity of shale reservoirs, thus improving the accuracy of the measurement results.

Description

Technical Field

[0001] This invention belongs to the field of petroleum engineering technology, and in particular relates to a method and system for calculating fluid-bearing porosity of shale reservoir rock samples. Background Technology

[0002] Shale oil and gas falls under the category of nano-oil and gas, encompassing source rock formations and the closely adjacent, near-source tight reservoir systems in extensive contact with them. Shale oil and gas development, as a significant direction and breakthrough in oil and gas exploration in recent years, is both a hot topic and a challenging area. Unlike conventional reservoirs, shale oil and gas reservoirs primarily consist of micron- to nanometer-scale pores and fractures, characterized by complex pore shapes and diverse pore and fracture types. Shale oil and gas reservoirs are classified as ultra-low porosity and ultra-low permeability reservoirs.

[0003] Currently, nuclear magnetic resonance (NMR) logging technology is widely used in shale oil and gas reservoir evaluation, oil and gas development testing, and other fields. As an effective means of evaluating the physical properties and hydrocarbon properties of shale reservoirs, NMR logging technology has advantages such as fast analysis speed and high quantification. In addition, NMR logging technology can also be used to measure shale reservoir samples of various shapes without damaging the samples being measured.

[0004] The basic principle of nuclear magnetic resonance (NMR) logging technology is to indirectly obtain reservoir physical parameters by detecting the 1H NMR signal in the reservoir fluid. In developing this invention, the inventors discovered that shale reservoirs are rich in solid organic precipitates such as kerogen. When using NMR logging technology to assess the fluid-bearing pore volume of shale reservoirs, the 1H NMR signal contained in these solid organic precipitates is also detected. In other words, if existing methods are used to directly measure the fluid-bearing pore volume of shale reservoir samples, the volume occupied by solid organic precipitates such as kerogen will also be included in the fluid-bearing pore volume, resulting in a measured porosity that is much larger than the actual porosity. Using the measured porosity to evaluate shale oil and gas reservoirs severely affects the accuracy of the evaluation results, posing a significant challenge to the evaluation of the corresponding oil and gas reservoirs.

[0005] Because the latest nuclear magnetic resonance (NMR) logging technology uses an echo interval (TE) of 0.06 ms, it can detect pores with a relaxation time as small as 0.01 ms (approximately 8 nm). Therefore, this latest NMR logging technology significantly improves the ability to identify pores such as kerogen nanopores, intergranular nanopores, mineral intercrystalline nanopores, and dissolution nanopores. Although the latest NMR logging technology is currently an important means of accurately, rapidly, and quantitatively evaluating shale reservoirs, in the process of developing this invention, the inventors discovered that the accompanying measurement method still cannot effectively eliminate the influence of solid organic sediments such as kerogen on the measurement results.

[0006] Therefore, accurately assessing the fluid-bearing pore volume of shale reservoirs is one of the most prominent and fundamental problems currently facing us. Summary of the Invention

[0007] One of the technical problems to be solved by this invention is to provide a method for calculating the fluid-bearing porosity of shale reservoir samples, comprising: acquiring the current rock sample to be analyzed and determining the sample volume; conducting nuclear magnetic resonance (NMR) logging experiments on the rock sample to be analyzed to obtain a first NMR spectrum; grinding the current rock sample to be analyzed into powder and immersing the powder in an organic solvent, and then conducting NMR logging experiments on the mixture to obtain a second NMR spectrum and identifying the spectrum of solid organic precipitates therefrom; comparing the first NMR spectrum and the spectrum of solid organic precipitates to obtain a third NMR spectrum characterizing the removal of solid organic precipitate features; and calculating the fluid-bearing porosity of the rock sample to be analyzed based on the third NMR spectrum and the sample volume.

[0008] Preferably, in the method for calculating the fluid porosity of shale reservoir samples provided in this embodiment of the invention, the particle size of the ground powder is less than 200 mesh; the powder is soaked in an organic solvent for no less than 10 minutes; the organic solvent is preferably selected from chloroform and carbon tetrachloride.

[0009] Preferably, the sample volume is calculated based on the skeleton density method in the standard specifications of nuclear magnetic resonance logging technology.

[0010] Preferably, the process of identifying the solid organic precipitate spectrum from the second nuclear magnetic resonance spectrum includes: identifying features in the second nuclear magnetic resonance spectrum that have not changed compared to the first nuclear magnetic resonance spectrum, and marking the currently unchanged features as the solid organic precipitate spectrum, so that the solid organic precipitate spectrum can be used to characterize an image in which the nuclear magnetic resonance properties have not changed in a specific short relaxation time region.

[0011] Preferably, the step of comparing the first NMR spectrum and the spectrum of the solid organic precipitate to obtain a third NMR spectrum characterizing the removal of the organic precipitate includes: performing a difference calculation on the NMR signal quantity corresponding to each relaxation time in the first NMR spectrum and the spectrum of the solid organic precipitate, and forming the third NMR spectrum based on the signal quantity difference at each relaxation time.

[0012] Preferably, the step of calculating the fluid-bearing porosity of the rock sample to be analyzed based on the third nuclear magnetic resonance spectrum and the sample volume includes: summing the signal quantities corresponding to each relaxation time in the third nuclear magnetic resonance spectrum to obtain the total signal quantity to be analyzed; and calculating the fluid-bearing porosity based on the porosity calibration formed by the nuclear magnetic resonance logging technology standard and specifications, according to the total signal quantity to be analyzed and the sample volume.

[0013] On the other hand, the present invention also provides a system for calculating the fluid porosity of shale reservoir samples. The system includes the following modules: a sample generation module for acquiring the current rock sample to be analyzed and determining its volume; a raw spectrum generation module for conducting nuclear magnetic resonance (NMR) logging experiments on the rock sample to be analyzed to obtain a first NMR spectrum; an organic precipitate extraction module for grinding the current rock sample to be analyzed into powder and immersing the powder in an organic solvent, then conducting NMR logging experiments on the mixture to obtain a second NMR spectrum and identifying the solid organic precipitate spectrum; a spectrum processing module for comparing the first NMR spectrum and the solid organic precipitate spectrum to obtain a third NMR spectrum characterizing the solid organic precipitate; and a fluid porosity calculation module for calculating the fluid porosity of the rock sample to be analyzed based on the third NMR spectrum and the sample volume.

[0014] Preferably, the sample generation module is further used to calculate the sample volume based on the skeleton density method in the standard specifications of nuclear magnetic resonance logging technology.

[0015] Preferably, the organic precipitate extraction module is further configured to identify features in the second nuclear magnetic resonance spectrum that have not changed compared to the first nuclear magnetic resonance spectrum, and to mark the currently unchanged features as the solid organic precipitate spectrum, so that the solid organic precipitate spectrum can be used to characterize an image in which the nuclear magnetic resonance characteristics have not changed in a specific short relaxation time region.

[0016] Preferably, the spectrum processing module is further configured to perform a difference calculation on the nuclear magnetic resonance signal quantity corresponding to each relaxation time in the first nuclear magnetic resonance spectrum and the spectrum of the solid organic precipitate, and form the third nuclear magnetic resonance spectrum based on the signal quantity difference at each relaxation time.

[0017] Compared with the prior art, one or more embodiments of the above solutions may have the following advantages or beneficial effects:

[0018] This invention proposes a method and system for calculating the fluid porosity of shale reservoir samples. The method and system acquire the NMR spectrum of the sample to be analyzed using nuclear magnetic resonance (NMR) logging technology, identify and remove portions of the image containing solid organic precipitates such as kerogen, obtaining an NMR spectrum characterizing the removed kerogen and other solid organic precipitates. Finally, based on this NMR spectrum characterizing the removed kerogen and other solid organic precipitates, the fluid porosity of the sample is calculated. This invention effectively eliminates the influence of solid organic precipitates such as kerogen on the measurement results when using NMR technology to measure the fluid porosity of shale reservoirs, improving the accuracy and rationality of the measurement results for the fluid porosity of shale reservoir samples, and providing stronger technical support for the exploration and development of unconventional shale oil and gas.

[0019] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0020] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0021] Figure 1 This is a step diagram illustrating the method for calculating the fluid-bearing porosity of shale reservoir rock samples according to an embodiment of this application.

[0022] Figure 2 This is an example of a first nuclear magnetic resonance spectrum in the method for calculating the fluid-bearing porosity of shale reservoir rock samples according to an embodiment of this application.

[0023] Figure 3 This is an example of a second nuclear magnetic resonance spectrum in the method for calculating the fluid-bearing porosity of shale reservoir rock samples according to an embodiment of this application.

[0024] Figure 4 This is an example of a solid organic precipitate spectrum in the method for calculating the fluid porosity of shale reservoir rock samples according to an embodiment of this application.

[0025] Figure 5 This is an example of a third nuclear magnetic resonance spectrum in the method for calculating the fluid-bearing porosity of shale reservoir rock samples in this application embodiment.

[0026] Figure 6 This is an example of a porosity gauging curve in the method for calculating fluid-bearing porosity of shale reservoir samples according to an embodiment of this application.

[0027] Figure 7 This is a block diagram of a system for calculating the fluid-bearing porosity of shale reservoir samples, according to an embodiment of this application. Detailed Implementation

[0028] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples, so that the process of how the present invention uses technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly. It should be noted that, as long as there is no conflict, the various embodiments and features in the various embodiments of the present invention can be combined with each other, and the resulting technical solutions are all within the protection scope of the present invention.

[0029] Furthermore, the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0030] Shale oil and gas falls under the category of nano-oil and gas, encompassing source rock formations and the closely adjacent, near-source tight reservoir systems in extensive contact with them. Shale oil and gas development, as a significant direction and breakthrough in oil and gas exploration in recent years, is both a hot topic and a challenging area. Unlike conventional reservoirs, shale oil and gas reservoirs primarily consist of micron- to nanometer-scale pores and fractures, characterized by complex pore shapes and diverse pore and fracture types. Shale oil and gas reservoirs are classified as ultra-low porosity and ultra-low permeability reservoirs.

[0031] Currently, nuclear magnetic resonance (NMR) logging technology is widely used in shale oil and gas reservoir evaluation, oil and gas development testing, and other fields. As an effective means of evaluating the physical properties and hydrocarbon properties of shale reservoirs, NMR logging technology has advantages such as fast analysis speed and high quantification. In addition, NMR logging technology can also be used to measure shale reservoir samples of various shapes without damaging the samples being measured.

[0032] The basic principle of nuclear magnetic resonance (NMR) logging technology is to indirectly obtain reservoir physical parameters by detecting the 1H NMR signal in the reservoir fluid. In developing this invention, the inventors discovered that shale reservoirs are rich in solid organic precipitates such as kerogen. When using NMR logging technology to assess the fluid-bearing pore volume of shale reservoirs, the 1H NMR signal contained in these solid organic precipitates is also detected. In other words, if existing methods are used to directly measure the fluid-bearing pore volume of shale reservoir samples, the volume occupied by solid organic precipitates such as kerogen will also be included in the fluid-bearing pore volume, resulting in a measured porosity that is much larger than the actual porosity. Using the measured porosity to evaluate shale oil and gas reservoirs severely affects the accuracy of the evaluation results, posing a significant challenge to the evaluation of the corresponding oil and gas reservoirs.

[0033] Because the latest nuclear magnetic resonance (NMR) logging technology uses an echo interval (TE) of 0.06 ms, it can detect pores with a relaxation time as small as 0.01 ms (approximately 8 nm). Therefore, this latest NMR logging technology significantly improves the ability to identify pores such as kerogen nanopores, intergranular nanopores, mineral intercrystalline nanopores, and dissolution nanopores. Although the latest NMR logging technology is currently an important means of accurately, rapidly, and quantitatively evaluating shale reservoirs, in the process of developing this invention, the inventors discovered that the accompanying measurement method still cannot effectively eliminate the influence of solid organic sediments such as kerogen on the measurement results.

[0034] Therefore, accurately assessing the fluid-bearing pore volume of shale reservoirs is one of the most prominent and fundamental problems currently facing us.

[0035] Therefore, to address the aforementioned problems, this invention proposes a method and system for calculating the fluid-bearing porosity of shale reservoir samples. This method and system utilize nuclear magnetic resonance (NMR) logging technology to obtain the NMR spectrum of the sample to be analyzed. It identifies and removes the portion of the spectrum belonging to solid organic precipitates such as kerogen, resulting in an NMR spectrum characterized by the removal of kerogen and other solid organic precipitates. Finally, based on this NMR spectrum characterized by the removal of kerogen and other solid organic precipitates, the fluid-bearing porosity of the sample to be analyzed is calculated. This invention effectively eliminates the influence of solid organic precipitates such as kerogen on the measurement results when using NMR technology to measure the fluid-bearing porosity of shale reservoirs, improving the accuracy and rationality of the measurement results for the fluid-bearing porosity of shale reservoir samples, and providing stronger technical support for the exploration and development of unconventional shale oil and gas.

[0036] Example 1

[0037] Figure 1This is a step-by-step diagram illustrating a method for calculating the fluid-bearing porosity of shale reservoir samples according to an embodiment of this application. See below for reference. Figure 1 This will explain each step of the method.

[0038] like Figure 1 As shown, in step S110, the current rock sample to be analyzed is acquired and its sample volume is determined. Specifically, the current rock sample to be analyzed is first acquired from the oil and gas well using methods such as drilling core sampling or wellbore core sampling. Then, the sample volume of the rock sample to be analyzed is calculated based on the methods required by the nuclear magnetic resonance logging technology standard specifications. The methods for measuring rock sample volume required by the nuclear magnetic resonance logging technology standard specifications include: weighing method, displacement method, and skeleton density method. In this embodiment of the invention, the skeleton density method is preferably used to measure the sample volume of the rock sample to be analyzed.

[0039] It should be noted that the embodiments of the present invention do not specifically limit the method for measuring the volume of rock samples, and those skilled in the art can choose according to actual needs.

[0040] In one specific embodiment of this application, a rock sample to be analyzed was collected from well NX55 using a core drilling method. The sample was taken from a shale reservoir with a lithology of mudstone and shale at a depth of 3784m. Furthermore, the skeleton density of the rock sample was measured to be 2.64 g / cm³. 3 The mass is 10.32g. Based on the measured skeleton density and mass, the volume of the rock sample to be analyzed is calculated to be 3.9ml using the skeleton density method.

[0041] Then, in step S120, a nuclear magnetic resonance (NMR) logging experiment is performed on the rock sample to be analyzed to obtain the first NMR spectrum. After calculating the volume of the current rock sample to be analyzed in step S110, the first NMR logging experiment is then performed on the current rock sample and analyzed to obtain data on each relaxation time in the current rock sample and all 1H NMR signals corresponding to each relaxation time, and the first NMR spectrum is determined accordingly. Since shale reservoirs are rich in solid organic precipitates such as kerogen, and these solid organic precipitates also have 1H characteristics, the first NMR spectrum includes the NMR data of solid organic precipitates such as kerogen. It should be noted that in the NMR spectrum, the "peak-like" curves at different positions represent the distribution of hydrogen-containing substances with different NMR characteristics in the rock sample to be analyzed.

[0042] Figure 2 This is an example of a first nuclear magnetic resonance (NMR) spectrum in the method for calculating the fluid-bearing porosity of shale reservoir samples according to an embodiment of this application. The first NMR spectrum is analyzed based on the distribution of NMR signal data corresponding to each relaxation time, as follows: Figure 2As shown, in the first NMR spectrum, both the first half (first part) of the abscissa representing the short relaxation time region and the second half (second part) of the abscissa representing the long relaxation time region exhibit two consecutive peak values ​​of NMR signal data variation (having a double "overlapping peak" characteristic); furthermore, the number of "overlapping peak" NMR signal data in the short relaxation time region is far greater than that in the long relaxation time region. In a specific embodiment of this application, based on the readings of the first NMR spectrum, all NMR signal data in the first NMR spectrum are accumulated, resulting in a total of 4308 NMR signal data points. Among these 4308 NMR signal data points, NMR signal data from the generation of solid organic precipitates such as kerogen are included.

[0043] To eliminate the influence of solid organic precipitates such as kerogen on the porosity measurement results of the fluid, in step S130, the rock sample to be analyzed is ground into powder and the powder is soaked in an organic solvent. Then, a nuclear magnetic resonance (NMR) logging experiment is performed on the mixture to obtain a second NMR spectrum and identify the solid organic precipitate spectrum. After completing steps S110 and S120, step S130 involves grinding the rock sample to be analyzed and soaking the resulting powder in an organic solvent. At this point, the ground powder partially dissolves in the organic solvent, resulting in a mixture containing powdered rock. A second NMR logging experiment is then performed on the mixture containing the powdered rock, and the results are analyzed to obtain data on each relaxation time in the mixture and all corresponding 1H NMR signals, thereby determining the second NMR spectrum. Finally, the solid organic precipitate spectrum is identified from the second NMR spectrum.

[0044] Specifically, the rock sample under study is ground using a grinding tool until a fine powder with a particle size of less than 200 mesh is obtained. Next, the powder is immersed in an organic solvent, and to ensure complete dissolution, the immersion time should be no less than 10 minutes, thus obtaining a mixture containing powdered rock sample. The undissolved powdered rock sample portion in the mixture is kerogen and other solid organic precipitates. In this embodiment, the organic solvent used has the following characteristics: it can dissolve crude oil under normal surface temperature and pressure conditions, but cannot dissolve solid organic precipitates such as kerogen in the formation rocks. Preferably, the organic solvent is selected from chloroform and carbon tetrachloride.

[0045] It should be noted that the embodiments of the present invention do not specifically limit the types of organic solvents mentioned above. Those skilled in the art can choose according to the actual situation, as long as the characteristics of the organic solvents mentioned above are met.

[0046] In the mixture of step S130, the crude oil in the pores of the rock sample to be analyzed is dissolved in organic solvents such as chloroform or carbon tetrachloride. As a result, the generation of the NMR signal from the dissolved portion is no longer affected by the micro- and nano-sized pores. The relaxation time of the solution portion becomes longer, which is reflected in the second NMR spectrum as the NMR signal data belonging to the solution portion appearing in the long relaxation time region. Furthermore, since solid organic precipitates such as kerogen are not dissolved in the organic solvent, their NMR characteristics remain unchanged. Therefore, in the second NMR spectrum, the solid organic precipitate characteristics are represented by the NMR signal data belonging to the kerogen portion, which remains unchanged within the original relaxation time region.

[0047] Then, in step S130, a nuclear magnetic resonance (NMR) logging experiment is performed on the current rock sample to be analyzed (the current rock sample to be analyzed is a mixture containing powdery rock samples) to obtain a second NMR spectrum. At this time, a second NMR logging experiment is performed on the current rock sample to be analyzed to obtain data on each relaxation time in the current rock sample and all 1H NMR signal data corresponding to each relaxation time, and the second NMR spectrum is determined accordingly.

[0048] Figure 3 This is an example of a second nuclear magnetic resonance (NMR) spectrum in the method for calculating fluid-bearing porosity of shale reservoir samples according to an embodiment of this application. The second NMR spectrum is analyzed based on the distribution of NMR signal data corresponding to each relaxation time, such as... Figure 3 As shown, in the second NMR spectrum, the first half (first part) of the abscissa representing the short relaxation time region and the second half (second part) of the abscissa representing the long relaxation time region, that is, the entire relaxation time region, have three peak values ​​of NMR signal data variation (with "single-peak" characteristics); and the "single-peak" NMR signal data in the short relaxation time region is much less than the "single-peak" NMR signal data in the long relaxation time region.

[0049] Figure 4 This is an example of a solid organic precipitate spectrum in the method for calculating the fluid-bearing porosity of shale reservoir samples according to embodiments of this application. By identifying... Figure 2 and Figure 3 Compared to features that have not changed, determine Figure 3 The unchanged characteristic portion is the spectral part located in the leftmost short relaxation time region. This part of the image represents the NMR signal information belonging to organic precipitates such as kerogen. Figure 4 As shown, this portion of the image was extracted to obtain the spectrum of solid organic precipitates.

[0050] In step S130, this embodiment of the invention further identifies features in the second NMR spectrum that have not changed compared to the first NMR spectrum. These features represent the portion of the NMR signal data that has not changed within the original relaxation time region compared to the first NMR spectrum. The currently unchanged features (representing the portion of the NMR signal data that has not changed within the original relaxation time region) are then marked as solid organic precipitate spectra. This allows the solid organic precipitate spectra to be used to characterize an image in which the NMR properties have not changed within a specific short relaxation time region.

[0051] Next, in step S140, the first NMR spectrum and the solid organic precipitate spectrum are compared to obtain a third NMR spectrum characterizing the removal of solid organic precipitate features. The first NMR spectrum obtained in step S120 and the solid organic precipitate spectrum obtained in step S130 are compared. NMR signal data belonging to the solid organic precipitate are identified from the first NMR spectrum, and the solid organic precipitate is removed from the first NMR spectrum to create a new NMR spectrum, forming the third NMR spectrum characterizing the removal of solid organic precipitate features.

[0052] Further, in step S140, the NMR signal quantities corresponding to each relaxation time in the first NMR spectrum and the solid organic precipitate spectrum are calculated by difference, and a third NMR spectrum is formed based on the signal quantity difference corresponding to each relaxation time. Specifically, the NMR signal data corresponding to each relaxation time in the first NMR spectrum of step S120 and the NMR signal data corresponding to each relaxation time in the solid organic precipitate spectrum of step S130 are read respectively. Using the relaxation time as a reference, the difference of the NMR signal data corresponding to each relaxation time is calculated to obtain the combination of differences of the NMR signal data. Then, the signal quantity differences corresponding to each relaxation time are integrated to obtain the third NMR spectrum with the NMR information of solid organic precipitates such as kerogen removed.

[0053] Figure 5 This is an example of the third nuclear magnetic resonance (NMR) spectrum in the method for calculating fluid-bearing porosity of shale reservoir samples according to embodiments of this application. Based on the distribution of NMR signal data corresponding to each relaxation time, the... Figure 2 The first nuclear magnetic resonance spectrum shown is... Figure 4 The solid organic precipitate spectra shown were compared and analyzed. Using relaxation time as a baseline, the corresponding NMR signal data of the solid organic precipitate spectrum was subtracted from the NMR signal data of each relaxation time in the first NMR spectrum. This yielded a combination of differences in the NMR signal data. These differences were then integrated according to their correspondence with relaxation time, resulting in the following... Figure 5The third nuclear magnetic resonance spectrum is shown.

[0054] Next, based on the distribution of NMR signal data corresponding to each relaxation time, the third NMR spectrum is analyzed. For example... Figure 5 As shown, in the third NMR spectrum, the peaks in the first half (first part) of the abscissa representing the short relaxation time region become smaller and change from double peaks to single peaks, while the peaks in the second half (second part) of the abscissa representing the long relaxation time region remain unchanged. Furthermore, based on the readings from the third NMR spectrum, the total number of NMR signal data points obtained by summing all NMR signal data in the third NMR spectrum is 832. These 832 NMR signal data points represent the NMR signals generated by solid organic precipitates such as kerogen.

[0055] Finally, in step S150, the fluid-bearing porosity of the rock sample to be analyzed is calculated based on the third nuclear magnetic resonance (NMR) spectrum and the sample volume. Specifically, firstly, the NMR signal data corresponding to each relaxation time in the third NMR spectrum obtained in step S140 is read, thus obtaining the effective NMR signal data of the current rock sample to be analyzed after removing solid organic precipitates such as kerogen. Then, using the porosity datum and the volume of the rock sample to be analyzed calculated in step S110, the actual fluid-bearing porosity of the rock sample to be analyzed is calculated.

[0056] Furthermore, in the step of calculating the fluid-bearing porosity of the rock sample to be analyzed, the signal quantities corresponding to each relaxation time in the third nuclear magnetic resonance spectrum are first summed to obtain the total signal quantity to be analyzed. Then, based on the porosity calibration formed by the standard specifications of nuclear magnetic resonance logging technology, the fluid-bearing porosity is calculated according to the total signal quantity to be analyzed and the sample volume.

[0057] Figure 6 This is an example of a porosity gauging curve in the method for calculating the fluid-bearing porosity of shale reservoir samples according to an embodiment of this application. For example... Figure 6 As shown, when calculating the fluid-bearing porosity of the rock sample to be analyzed, the total amount of effective NMR signal data of the rock sample is directly related to the actual fluid-bearing porosity of the current rock sample. Therefore, firstly, the NMR signal data corresponding to each relaxation time in the third NMR spectrum are summed to obtain the total amount of effective NMR signal data of the current rock sample to be analyzed. Then, based on the porosity calibration curve formed according to the NMR logging technical standard, combined with the total amount of effective NMR signal data of the current rock sample and the sample volume of the rock sample, the calculated result of the fluid-bearing porosity of the current rock sample is obtained. The porosity calibration curve is a calibration curve formed according to the NMR logging technical standard.

[0058] In one specific embodiment of this application, the nuclear magnetic resonance signal data corresponding to each relaxation time in the third nuclear magnetic resonance spectrum are first accumulated, such as... Figure 3 As shown, the total number of valid NMR signal data points obtained for the rock sample to be analyzed is 3470. Then, the volume of the rock sample to be analyzed is calculated to be 3.91 ml. Next, based on the porosity calibration formed by the standard specifications for NMR logging technology, the actual fluid-bearing porosity of the rock sample to be analyzed is calculated. The final calculated fluid-bearing porosity of the rock sample to be analyzed is 5.95%. Similarly, the fluid-bearing porosity of the rock sample to be analyzed is calculated without excluding the influence of solid organic precipitates such as kerogen. The final original fluid-bearing porosity of the rock sample to be analyzed was 7.47%. Comparing the two analytical results, it can be seen that the fluid-bearing porosity obtained without excluding the influence of solid organic precipitates such as kerogen differs from the actual fluid-bearing porosity by 1.52%, meaning the original measurement result is 25.45% larger than the actual measurement result. Therefore, this invention can effectively eliminate the influence of solid organic precipitates such as kerogen in the process of measuring fluid-bearing porosity, and accurately measure the actual fluid-bearing porosity of shale reservoirs.

[0059] Example 2

[0060] Based on the method for calculating the fluid-bearing porosity of shale reservoir samples described in Embodiment 1 above, this embodiment of the invention also provides a system for calculating the fluid-bearing porosity of shale reservoir samples (hereinafter referred to as the "fluid-bearing porosity calculation system"). Figure 7 This is a block diagram of a system for calculating the fluid-bearing porosity of shale reservoir samples, according to an embodiment of this application.

[0061] like Figure 7As shown, the fluid-containing porosity calculation system in this embodiment of the invention includes: a sample generation module 71, a raw spectrum generation module 72, an organic precipitate extraction module 73, a spectrum processing module 74, and a fluid-containing porosity calculation module 75. Specifically, the sample generation module 71 is implemented according to the method described in step S110 above, configured to acquire the current rock sample to be analyzed and determine the sample volume of the rock sample; the original spectrum generation module 72 is implemented according to the method described in step S120 above, configured to conduct nuclear magnetic resonance logging experiments on the rock sample to be analyzed to obtain a first nuclear magnetic resonance spectrum; the organic precipitate extraction module 73 is implemented according to the method described in step S130 above, configured to grind the current rock sample to be analyzed into powder and soak the powder in an organic solvent, and then conduct nuclear magnetic resonance logging experiments on the current mixture to obtain a second nuclear magnetic resonance spectrum and identify the solid organic precipitate spectrum therefrom; the spectrum processing module 74 is implemented according to the method described in step S140 above, configured to compare the first nuclear magnetic resonance spectrum and the solid organic precipitate spectrum to obtain a third nuclear magnetic resonance spectrum characterizing the removal of solid organic precipitate features; the fluid porosity calculation module 75 is implemented according to the method described in step S150 above, configured to calculate the fluid porosity of the rock sample to be analyzed based on the third nuclear magnetic resonance spectrum and the sample volume.

[0062] Furthermore, the sample generation module 71 is also configured to calculate the sample volume based on the skeleton density method in the standard specification of nuclear magnetic resonance logging technology.

[0063] Furthermore, the aforementioned organic precipitate extraction module 73 is also configured to identify features in the second nuclear magnetic resonance spectrum that have not changed compared to the first nuclear magnetic resonance spectrum, and to mark the currently unchanged features as solid organic precipitate spectra, so that the solid organic precipitate spectra can be used to characterize images in which the nuclear magnetic resonance characteristics have not changed in a specific short relaxation time region.

[0064] Furthermore, the aforementioned spectrum processing module 74 is also configured to perform a difference calculation on the nuclear magnetic resonance signal quantity corresponding to each relaxation time in the first nuclear magnetic resonance spectrum and the solid organic precipitate spectrum, and to form a third nuclear magnetic resonance spectrum based on the signal quantity difference at each relaxation time.

[0065] This invention discloses a method and system for calculating the fluid porosity of shale reservoir samples. The method and system acquire the NMR spectrum of the sample to be analyzed using nuclear magnetic resonance (NMR) logging technology, identify and remove the portion of the spectrum belonging to solid organic precipitates such as kerogen, obtaining an NMR spectrum characterizing the removal of kerogen and other solid organic precipitates. Finally, based on this NMR spectrum characterizing the removal of kerogen and other solid organic precipitates, the fluid porosity of the sample is calculated. This invention effectively eliminates the influence of solid organic precipitates such as kerogen on the measurement results when using NMR technology to measure the fluid porosity of shale reservoirs. Furthermore, based on the inherent advantages of NMR logging technology—its speed, accuracy, and quantitative analysis—it improves the accuracy and rationality of the measurement results for the fluid porosity of shale reservoir samples. This provides stronger technical support for the exploration and development of unconventional shale oil and gas, and has positive practical significance for improving the ability to accurately interpret and evaluate shale oil and gas through logging.

[0066] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0067] Of course, the present invention may have other various embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art can make various corresponding changes and modifications according to the present invention, but these corresponding changes and modifications should all fall within the protection scope of the claims of the present invention.

[0068] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device, or fabricating them separately as individual integrated circuit modules, or fabricating multiple modules or steps as a single integrated circuit module. Thus, the present invention is not limited to any particular hardware and software combination.

[0069] While the embodiments disclosed in this invention are as described above, the content is merely for the purpose of facilitating understanding of the invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and variations in form and detail of the implementation without departing from the spirit and scope disclosed herein; however, the scope of patent protection for this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A method for calculating the fluid-bearing porosity of shale reservoir samples, comprising: Obtain the current rock sample to be analyzed and determine the sample volume of the rock sample; Nuclear magnetic resonance logging experiments were conducted on the rock sample to be analyzed to obtain the first nuclear magnetic resonance spectrum; The rock sample to be analyzed is ground into powder and then soaked in an organic solvent. Nuclear magnetic resonance logging experiments are then performed on the mixture to obtain a second nuclear magnetic resonance spectrum and identify the spectrum of solid organic precipitates. The selected organic solvent has the characteristic of being able to dissolve crude oil under normal surface temperature and common conditions, but at the same time, it cannot dissolve solid organic precipitates such as kerogen in the formation rocks. By comparing the first nuclear magnetic resonance spectrum and the spectrum of the solid organic precipitate, a third nuclear magnetic resonance spectrum is obtained, which characterizes the solid organic precipitate by removing its features. Based on the third nuclear magnetic resonance spectrum and the sample volume, the fluid porosity of the rock sample to be analyzed is calculated. The process of identifying the spectrum of solid organic precipitates from the second nuclear magnetic resonance spectrum includes: Identify features in the second NMR spectrum that have not changed compared to the first NMR spectrum, and mark the currently unchanged features as the solid organic precipitate spectrum, so that the solid organic precipitate spectrum can be used to characterize an image in which the NMR properties have not changed in a specific short relaxation time region.

2. The method according to claim 1, characterized in that, The particle size of the ground powder is less than 200 mesh; The powder is soaked in an organic solvent for no less than 10 minutes; the organic solvent is selected from chloroform and carbon tetrachloride.

3. The method according to claim 1 or 2, characterized in that, The sample volume was calculated based on the skeleton density method in the standard specifications of nuclear magnetic resonance logging technology.

4. The method according to claim 1, characterized in that, The step of comparing the first NMR spectrum and the spectrum of the solid organic precipitate to obtain a third NMR spectrum characterizing the removal of the organic precipitate includes: The difference between the nuclear magnetic resonance signal quantity corresponding to each relaxation time in the first nuclear magnetic resonance spectrum and the spectrum of the solid organic precipitate is calculated, and the third nuclear magnetic resonance spectrum is formed based on the signal quantity difference at each relaxation time.

5. The method according to any one of claims 1, 2, or 4, characterized in that, The step of calculating the fluid-bearing porosity of the rock sample to be analyzed based on the third nuclear magnetic resonance spectrum and the sample volume includes: The total signal quantity to be analyzed is obtained by summing the signal quantities corresponding to each relaxation time in the third nuclear magnetic resonance spectrum. Based on the porosity datum formed by the standard specifications of nuclear magnetic resonance logging technology, the fluid-containing porosity is calculated according to the total signal quantity to be analyzed and the sample volume.

6. A calculation system for fluid-bearing porosity of shale reservoir rock samples, the calculation system comprising the following modules: a sample generation module, which is used to acquire the current rock sample to be analyzed and determine the sample volume of the rock sample; The original spectrum generation module is used to conduct nuclear magnetic resonance logging experiments on the rock sample to be analyzed to obtain the first nuclear magnetic resonance spectrum. The organic precipitate extraction module is used to grind the rock sample to be analyzed into powder and soak the powder in an organic solvent. Then, a nuclear magnetic resonance logging experiment is carried out on the current mixture to obtain a second nuclear magnetic resonance spectrum and identify the spectrum of solid organic precipitates from it. The selected organic solvent has the characteristics of being able to dissolve crude oil under normal surface temperature and common conditions, but at the same time, it cannot dissolve solid organic precipitates such as kerogen in the formation rocks. The spectrum processing module is used to compare the first nuclear magnetic resonance spectrum and the spectrum of the solid organic precipitate to obtain a third nuclear magnetic resonance spectrum that characterizes the solid organic precipitate after removing its features. The fluid porosity calculation module is used to calculate the fluid porosity of the rock sample to be analyzed based on the third nuclear magnetic resonance spectrum and the sample volume. The organic precipitate extraction module is further used to identify features in the second nuclear magnetic resonance spectrum that have not changed compared to the first nuclear magnetic resonance spectrum, and to mark the currently unchanged features as the solid organic precipitate spectrum, so that the solid organic precipitate spectrum can be used to characterize an image in which the nuclear magnetic resonance characteristics have not changed in a specific short relaxation time region.

7. The system according to claim 6, characterized in that, The sample generation module is further used to calculate the sample volume based on the skeleton density method in the standard specifications of nuclear magnetic resonance logging technology.

8. The system according to any one of claims 6 to 7, characterized in that, The spectrum processing module is further configured to perform a difference calculation on the nuclear magnetic resonance signal quantity corresponding to each relaxation time in the first nuclear magnetic resonance spectrum and the spectrum of the solid organic precipitate, and form the third nuclear magnetic resonance spectrum based on the signal quantity difference at each relaxation time.

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