Shale oil nuclear magnetic resonance forward inversion simulation method and device

Abstract

The application provides a shale oil nuclear magnetic resonance forward and inverse simulation method and device, and relates to the technical field of petroleum engineering and rock physics. The method comprises the following steps: obtaining a simulated nuclear magnetic resonance T2 spectrum of a shale core in a water-saturated state according to first attribute data of the shale core and a T2 spectrum converted from a pore size distribution; obtaining shale core nuclear magnetic resonance T2 spectra of different viscosity crude oils according to the simulated nuclear magnetic resonance T2 spectrum of the water-saturated state by using the viscosity difference of the crude oils at different temperatures and the nuclear magnetic resonance relaxation characteristics of oil and water; performing forward simulation on the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal, adding noise to the echo train signal to obtain echo train attenuation data; and performing inverse simulation on the echo train attenuation data to obtain shale core nuclear magnetic resonance simulation T2 spectra of different crude oil viscosities containing noise and data processing errors. The device executes the above method. The method and device provided in the application can obtain more real data.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of petroleum engineering and rock physics, and particularly relates to a shale oil nuclear magnetic resonance forward inversion simulation method and device. BACKGROUND

[0002] With the increasing demand for oil and gas resources in society, and the increasing depletion of conventional reservoir oil and gas resources, improving oil and gas recovery efficiency, reducing labor costs and reducing costs have become the inevitable choice of each oil company. Under this background, artificial intelligence technology has been widely used in many aspects of oil exploration and development. However, the combination of artificial intelligence and the oil industry still faces many problems and challenges. Many artificial intelligence algorithms are limited by data sets and cannot play a greater role in the industry. High-quality data sets can greatly improve the prediction accuracy of artificial intelligence algorithms.

[0003] Nuclear magnetic resonance logging uses the resonance phenomenon of hydrogen atoms interacting with the magnetic field to detect hidden physical properties. It can directly reflect the relaxation and diffusion information of hydrogen nuclei in the pore fluid of the formation, and obtain rock physical parameters such as porosity, permeability and saturation. However, there is always some noise interference in the measurement process of downhole nuclear magnetic resonance logging, which makes the correlation between data worse. The nuclear magnetic resonance data obtained by numerical simulation theoretically does not contain any noise and can adapt to any underground conditions.

[0004] Many current nuclear magnetic resonance forward methods are based on some rule-based model exploration, nuclear magnetic resonance theoretical research, and Gaussian distribution random signal superposition. They have little significance in actual production and cannot simulate real underground or measurement conditions. SUMMARY

[0005] To solve the problems in the prior art, the embodiments of the present application provide a shale oil nuclear magnetic resonance forward inversion simulation method and device, which can at least partially solve the problems in the prior art.

[0006] In one aspect, the present application provides a shale oil nuclear magnetic resonance forward inversion simulation method, comprising:

[0007] According to the first attribute data of the shale core and the T2 spectrum converted by the pore size distribution, the simulated nuclear magnetic resonance T2 spectrum of the saturated water state of the shale core is obtained;

[0008] According to the simulated nuclear magnetic resonance T2 spectrum of the saturated water state, the shale core nuclear magnetic resonance T2 spectrum of different viscosity crude oils is obtained by using the viscosity difference of crude oils at different temperatures and the nuclear magnetic resonance relaxation characteristics of oil and water;

[0009] forward the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal, and add noise to the echo train signal to obtain echo train decay data;

[0010] inverting the echo train decay data to obtain shale core nuclear magnetic resonance simulation T2 spectrum of different crude oil viscosities containing noise and data processing errors.

[0011] wherein, the simulated nuclear magnetic resonance T2 spectrum of the shale core in the saturated water state is obtained according to the T2 spectrum converted from the first attribute data and the pore size distribution of the shale core, comprising:

[0012] According to the T2 spectrum converted from the first attribute data and the pore size distribution of the shale core, Gaussian fitting is carried out to obtain the simulated nuclear magnetic resonance T2 spectrum in the saturated water state;

[0013] wherein, the mean value in the Gaussian function used for Gaussian fitting corresponds to the main peak position of the relaxation signal peak to be simulated, and the variance in the Gaussian function corresponds to the spectral peak width of the relaxation signal peak to be simulated.

[0014] wherein, the shale core nuclear magnetic resonance T2 spectrum of different viscosity crude oils is obtained according to the simulated nuclear magnetic resonance T2 spectrum in the saturated water state, using the viscosity difference of crude oil at different temperatures and the nuclear magnetic resonance relaxation characteristics of oil and water.

[0015] determining the logarithmic average of transverse relaxation time according to the preset absolute temperature, the preset viscosity and the preset coefficient;

[0016] According to the logarithmic average of transverse relaxation time, each transverse relaxation time of the simulated nuclear magnetic resonance T2 spectrum in the saturated water state and the signal amplitude corresponding to each transverse relaxation time, the shale core nuclear magnetic resonance T2 spectrum of different viscosity crude oils is obtained.

[0017] wherein, the forward of the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal comprises:

[0018] Based on the nuclear magnetic resonance forward model, the shale core nuclear magnetic resonance T2 spectrum is forward to obtain an echo train signal.

[0019] wherein, the adding noise to the echo train signal to obtain echo train decay data comprises:

[0020] A random number is generated from a normal distribution, and the random number is added to each echo acquisition data to obtain echo train decay data.

[0021] wherein, before the step of obtaining the simulated nuclear magnetic resonance T2 spectrum in the saturated water state of the shale core according to the T2 spectrum converted from the first attribute data and the pore size distribution of the shale core, the shale oil nuclear magnetic resonance forward and inversion simulation method further comprises:

[0022] determine a pore size distribution curve of the shale core according to second attribute data of the shale core;

[0023] transform the pore size distribution curve to obtain a pore size distribution converted T2 spectrum.

[0024] The shale oil nuclear magnetic resonance forward-inversion simulation method further comprises, after the step of obtaining the shale core nuclear magnetic resonance simulation T2 spectrum of different crude oil viscosities containing noise and data processing errors:

[0025] obtaining shale core samples under preset simulation conditions by applying the echo train signal obtained by the forward modeling and the shale core nuclear magnetic resonance simulation T2 spectrum obtained by the inversion, and obtaining fluid types and fluid saturations according to the shale core samples.

[0026] In one aspect, the present application provides a shale oil nuclear magnetic resonance forward-inversion simulation device, comprising:

[0027] The first obtaining unit is configured to obtain a simulated nuclear magnetic resonance T2 spectrum of a water-saturated state of the shale core according to the first attribute data of the shale core and the pore size distribution converted T2 spectrum;

[0028] The second obtaining unit is configured to obtain shale core nuclear magnetic resonance T2 spectrums of different viscosities of crude oil by utilizing viscosity differences of the crude oil at different temperatures and nuclear magnetic resonance relaxation characteristics of oil and water according to the simulated nuclear magnetic resonance T2 spectrum of the water-saturated state.

[0029] The forward modeling unit is configured to perform forward modeling on the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal, and add noise to the echo train signal to obtain echo train attenuation data.

[0030] The inversion unit is configured to perform inversion on the echo train attenuation data to obtain shale core nuclear magnetic resonance simulation T2 spectrums of different viscosities of crude oil containing noise and data processing errors.

[0031] In still another aspect, the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following method when executing the computer program:

[0032] obtaining a simulated nuclear magnetic resonance T2 spectrum of a water-saturated state of the shale core according to the first attribute data of the shale core and the pore size distribution converted T2 spectrum;

[0033] obtaining shale core nuclear magnetic resonance T2 spectrums of different viscosities of crude oil by utilizing viscosity differences of the crude oil at different temperatures and nuclear magnetic resonance relaxation characteristics of oil and water according to the simulated nuclear magnetic resonance T2 spectrum of the water-saturated state.

[0034] forward the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal, and add noise to the echo train signal to obtain echo train attenuation data;

[0035] inversion is performed on the echo train attenuation data to obtain shale core nuclear magnetic resonance simulation T2 spectra of different crude oil viscosities containing noise and data processing errors.

[0036] The embodiment of the present application provides a computer readable storage medium, comprising:

[0037] The computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the following method:

[0038] According to the first attribute data of the shale core and the T2 spectrum converted by the pore size distribution, a simulated nuclear magnetic resonance T2 spectrum of the shale core in a water-saturated state is obtained;

[0039] According to the simulated nuclear magnetic resonance T2 spectrum in the water-saturated state, the shale core nuclear magnetic resonance T2 spectra of different crude oil viscosities are obtained by using the viscosity difference of the crude oil at different temperatures and the nuclear magnetic resonance relaxation characteristics of oil and water;

[0040] Forward the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal, and add noise to the echo train signal to obtain echo train attenuation data;

[0041] Inversion is performed on the echo train attenuation data to obtain shale core nuclear magnetic resonance simulation T2 spectra of different crude oil viscosities containing noise and data processing errors.

[0042] The shale oil nuclear magnetic resonance forward and inversion simulation method and device provided by the embodiment of the present application can obtain shale core nuclear magnetic resonance simulation T2 spectra that are closer to the real measurement results by obtaining a simulated nuclear magnetic resonance T2 spectrum of a shale core in a water-saturated state according to the first attribute data of the shale core and the T2 spectrum converted by the pore size distribution, obtaining shale core nuclear magnetic resonance T2 spectra of different crude oil viscosities by using the viscosity difference of the crude oil at different temperatures and the nuclear magnetic resonance relaxation characteristics of oil and water according to the simulated nuclear magnetic resonance T2 spectrum in the water-saturated state, performing forward on the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal, adding noise to the echo train signal to obtain echo train attenuation data, and performing inversion on the echo train attenuation data to obtain shale core nuclear magnetic resonance simulation T2 spectra of different crude oil viscosities containing noise and data processing errors. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to make the technical solutions in the embodiments of the present application or the prior art clearer, the accompanying drawings needed in the embodiments or prior art description will be briefly introduced below. Obviously, the accompanying drawings in the following description only aim to explain some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative effort. In the drawings:

[0044] Figure 1 Fig. 1 is a flowchart of a shale oil NMR forward inversion simulation method provided by an embodiment of the present application;

[0045] Fig. 2(a) is a pore size distribution diagram of organic pores;

[0046] Fig. 2(b) is a pore size distribution diagram of inorganic pores;

[0047] Fig. 2(c) is a pore size distribution diagram of organic fractures;

[0048] Fig. 2(d) is a pore size distribution diagram of inorganic fractures;

[0049] Fig. 2(e) is a pore size distribution diagram based on digital core data of an actual shale core;

[0050] Figure 3 Fig. 3 is an illustrative diagram of a NMR T2 spectrum obtained by superimposing Gaussian distribution simulation curves based on pore size distribution provided by an embodiment of the present application;

[0051] Fig. 4(a) is an echo train decay diagram plotted by taking the time distribution as logarithmic coordinates provided by an embodiment of the present application;

[0052] Fig. 4(b) is an illustrative diagram of a NMR T2 spectrum obtained by inversion provided by an embodiment of the present application;

[0053] Fig. 5(a) is an illustrative diagram of NMR T2 spectra of crude oil at different temperatures in a free state;

[0054] Fig. 5(b) is an illustrative diagram of NMR T2 spectra of an actual shale oil sample obtained by a variable-temperature NMR experiment;

[0055] Fig. 5(c) is an illustrative diagram of NMR T2 spectra of an actual shale oil sample obtained by a numerical simulation experiment;

[0056] Figure 6 Fig. 6 is a structural diagram of a shale oil NMR forward inversion simulation device provided by an embodiment of the present application;

[0057] Figure 7 Fig. 7 is a computer device physical structure diagram provided by an embodiment of the present application. DETAILED DESCRIPTION

[0058] To make the purposes, technical solutions and advantages of the embodiments of the present application clearer, further detailed descriptions of the embodiments of the present application will be given below with reference to the drawings. Here, the illustrative embodiments of the present application and their descriptions are used to explain the present application but are not used as limitations of the present application. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other at will without conflicts.

[0059] Figure 1 is a flowchart of a shale oil nuclear magnetic resonance forward inversion simulation method provided by an embodiment of the present application, as shown in Figure 1 The shale oil nuclear magnetic resonance forward inversion simulation method provided by the embodiment of the present application comprises the following steps.

[0060] Step S1: obtaining a simulated nuclear magnetic resonance T2 spectrum of a shale core in a water-saturated state according to first attribute data of the shale core and a T2 spectrum converted from a pore size distribution.

[0061] Step S2: obtaining a shale core nuclear magnetic resonance T2 spectrum of different viscosity crude oils according to the simulated nuclear magnetic resonance T2 spectrum of the shale core in the water-saturated state and by using viscosity differences of the crude oils at different temperatures and nuclear magnetic resonance relaxation characteristics of oil and water.

[0062] Step S3: performing forward inversion on the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal, adding noise to the echo train signal to obtain echo train attenuation data.

[0063] Step S4: performing inversion on the echo train attenuation data to obtain shale core nuclear magnetic resonance simulation T2 spectra of different crude oil viscosities containing noise and data processing errors.

[0064] In the above step S1, the device obtains the simulated nuclear magnetic resonance T2 spectrum of the shale core in the water-saturated state according to the first attribute data of the shale core and the T2 spectrum converted from the pore size distribution. The device can be a computer device or the like that executes the method, for example, a server. The acquisition, storage, use, processing and the like of data in the technical solution of the present application all conform to relevant regulations. The first attribute data can include pore distribution of the shale core, sizes of mineral particles and cracks, proportions of organic pores and inorganic pores, water film thickness, and nuclear magnetic resonance T2 spectrum of the shale core.

[0065] The shale core can be measured by using a nuclear magnetic resonance core analyzer, nuclear magnetic resonance echo data of shale oil can be collected, and the nuclear magnetic resonance T2 spectrum of the shale core can be obtained by inversion.

[0066] The FIB-SEM three-dimensional analysis can be used to detect the internal mineral and pore structure (corresponding to the mineral particle size and crack size) of the shale core, and the distribution characteristics including the pore (corresponding to the pore distribution), throat and mineral, and the proportion and pore size distribution of the organic pore, inorganic pore, organic crack and inorganic crack of the shale core.

[0067] The shale core of the reservoir is collected, and the collected shale core is subjected to nuclear magnetic resonance test to obtain one-dimensional T2 spectrum of saturated formation water and one-dimensional T2 spectrum of saturated formation crude oil, and one-dimensional T2 spectrum of the state of the saturated formation crude oil of the shale core at different temperatures. The water film thickness can be obtained according to the above one-dimensional T2 spectrum.

[0068] The T2 spectrum converted from the first attribute data and the pore size distribution of the shale core is used to obtain the simulated nuclear magnetic resonance T2 spectrum of the saturated water state of the shale core, which comprises:

[0069] The T2 spectrum converted from the first attribute data and the pore size distribution of the shale core is subjected to Gaussian fitting to obtain the simulated nuclear magnetic resonance T2 spectrum of the saturated water state;

[0070] The mean value in the Gaussian function used for Gaussian fitting corresponds to the main peak position of the relaxation signal peak to be simulated, and the variance in the Gaussian function corresponds to the spectral peak width of the relaxation signal peak to be simulated. The expression of the Gaussian function is as follows:

[0071]

[0072] First, the characteristics of the relaxation signal peak to be simulated are determined. Each T2 spectrum component corresponds to different signal intensity and relaxation time, which is manifested as different mean value and variance of the Gaussian function, wherein the mean value determines the main peak position of the relaxation signal peak, and the variance determines the spectral peak width of the relaxation signal peak.

[0073] Further, the T2 distribution curve of each T2 spectrum component is determined by the Gaussian function, and a weight parameter is set to avoid the condition that each component has the same saturation degree. The expression of each component is as follows:

[0074]

[0075] Wherein, f is the frequency at a certain moment; w is the weight of the component in the T2 distribution; σ 2 is the variance of the Gaussian function; and μ is the mean value of the Gaussian function.

[0076] Wherein, the weight of each component is determined according to the proportion of the component in the expected result, and σ 2 and μ are obtained from the empirical distribution characteristics of the component.

[0077] Before the step of converting the T2 spectrum of the shale core according to the first attribute data of the shale core and the pore size distribution, the shale oil nuclear magnetic resonance forward inversion simulation method further comprises:

[0078] According to the second attribute data of the shale core, a pore size distribution curve of the shale core is determined; the second attribute data can include parameters such as mineral and pore structure, distribution characteristics including pores, throats and minerals inside the shale core; the proportions of organic pores, inorganic pores, organic fractures and inorganic fractures of the shale core and the pore size distribution are shown in Figures 2(a), 2(b), 2(c) and 2(d) respectively, and the pore size distribution graph based on the digital core data of the actual shale core is shown in Figure 2(e). From the shale oil pore size distribution and the proportions of organic pores and inorganic pores, it can be seen that the nano-pores are mainly in the nano-pores, and the vast majority of micropores and meso / macropores with a pore size of 40-60 nm make a major contribution to the porosity. There are peaks at pore sizes of <1 nm, 5.5-6.5 nm and 40-60 nm, and the pore size distribution is relatively uniform, and the mesopores are mainly in the whole.

[0079] The existing prior art can obtain the pore size distribution of the shale core, and based on this, the pore size distribution curve of the shale core can be drawn.

[0080] The pore size distribution curve is converted to obtain a pore size distribution converted T2 spectrum. The existing prior art converts the pore size distribution through the core nuclear magnetic resonance t2 spectrum, and based on this prior art, inverse transformation can be performed to convert the pore size distribution curve to obtain a pore size distribution converted T2 spectrum. The related technical principles are described as follows:

[0081]

[0082] wherein, T 2B is the T2 relaxation time of the pore fluid measured in a large enough container (large enough that the effect of the container can be ignored);

[0083] ρ2 is the surface relaxation strength;

[0084] is the specific surface area;

[0085] γ is the gyromagnetic ratio, rad / (s·T);

[0086] G is the field strength gradient, T / cm;

[0087] TE is the echo interval, s;

[0088] Dt is the diffusion coefficient.

[0089] In the absence of a gradient magnetic field, or when the value of GTE is very small, the diffusion term can be neglected, and in rocks, generally the bulk relaxation is much slower than the surface relaxation, so in the case of saturated water, only the effect of surface relaxation can be considered, by which the pore size conversion is carried out:

[0090]

[0091] Wherein, T 2S is the surface relaxation time, r is the pore size distribution, F s is the shape factor.

[0092] In the above step S2, the device obtains shale core nuclear magnetic resonance T2 spectrum of crude oil with different viscosities according to the simulated nuclear magnetic resonance T2 spectrum of the saturated water state, by using the viscosity difference of crude oil at different temperatures and the nuclear magnetic resonance relaxation characteristics of oil and water. As shown in the figure, Figure 3 The abscissa is the relaxation time, and the ordinate is the porosity component. The porosity of the shale oil core is set to 5%, and the saturated fluid is formation water. By comparing the shale pore size distribution obtained by the digital core data, the nuclear magnetic T2 spectrum is simulated by a Gaussian function.

[0093] The shale core nuclear magnetic resonance T2 spectrum of crude oil with different viscosities is obtained according to the simulated nuclear magnetic resonance T2 spectrum of the saturated water state, by using the viscosity difference of crude oil at different temperatures and the nuclear magnetic resonance relaxation characteristics of oil and water, including:

[0094] Determine the logarithmic average value of the transverse relaxation time according to the preset absolute temperature, the preset viscosity and the preset coefficient;

[0095] According to the logarithmic average value of the transverse relaxation time, the transverse relaxation time of the simulated nuclear magnetic resonance T2 spectrum of the saturated water state, and the signal amplitude corresponding to each transverse relaxation time, the shale core nuclear magnetic resonance T2 spectrum of crude oil with different viscosities is obtained. The shale core nuclear magnetic resonance T2 spectrum of crude oil with different viscosities is obtained by the following expression:

[0096]

[0097]

[0098] Wherein, T 2,LM is the logarithmic average value of the transverse relaxation time, the unit is ms; f j is the signal amplitude obtained when the transverse relaxation time is T j ; T k is the preset absolute temperature, the unit is K; η is the preset viscosity, the unit is cP or mPa.s. The preset coefficient is 4.03.

[0099] In step S3, the device performs forward modeling on the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal, and adds noise to the echo train signal to obtain echo train decay data. The forward modeling on the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal includes:

[0100] The echo train signal is obtained by performing forward modeling on the shale core nuclear magnetic resonance T2 spectrum based on a nuclear magnetic resonance forward modeling model. The implementation process of the nuclear magnetic resonance forward modeling is as follows. After complete polarization, the decay of the normalized magnetization M(t) of the pore fluid with time can be expressed as:

[0101]

[0102] The three parts in the formula are the transverse bulk relaxation magnetization, the surface relaxation magnetization and the diffusion relaxation magnetization of the fluid at time t, T 2B , T 2S is the transverse bulk relaxation time and the surface relaxation time, Dt is the diffusion coefficient, γ is the gyromagnetic ratio, and G is the magnetic field gradient constant. The bulk relaxation is only related to T 2B , and the type of the fluid determines the bulk relaxation time. The echo train signal reflecting different fluids can be calculated from the T2 signal amplitude by an exponential model:

[0103]

[0104] The echo train decay data is obtained by adding noise to the echo train signal, including:

[0105] A random number is generated from a normal distribution, and the random number is added to each echo acquisition data to obtain the echo train decay data. In order to be more close to the actual instrument acquisition data, a random noise is added, a random number is generated from a normal distribution, and added to each echo acquisition data, with a mean of 0 and a standard deviation of 0.1.

[0106] Further, the signal-to-noise ratio is expressed as follows:

[0107] SNR = 10 x log 10 G(1) / Noise(1)

[0108] Where G(1) is the amplitude of the first wave of the echo train after adding noise, and Noise(1) is the Gaussian noise corresponding to the first wave.

[0109] Further, the time distribution is determined, and the time step is preset as T E = 0.1 ms, and the time distribution is T E x the number of echoes.

[0110] Further, the time distribution is plotted in logarithmic coordinates to obtain an echo train decay graph as shown in Fig. 4(a), and a nuclear magnetic T2 spectrum is obtained by inversion as shown in Fig. 4(b).

[0111] In the step S4, the device inverts the echo train decay data to obtain a shale core nuclear magnetic simulation T2 spectrum of different crude oil viscosities containing noise and data processing errors. After the step of obtaining the shale core nuclear magnetic simulation T2 spectrum of different crude oil viscosities containing noise and data processing errors, the shale oil nuclear magnetic forward and inverse simulation method further comprises:

[0112] The echo train signal obtained by the forward simulation and the shale core nuclear magnetic simulation T2 spectrum obtained by the inversion are applied to obtain a shale core sample under a preset simulation condition, and fluid type and fluid saturation are obtained according to the shale core sample. The shale nuclear magnetic T2 spectrum distribution characteristics of different porosities, fluid types, fluid saturations, temperatures and viscosity states can be used to simulate a shale core sample under a certain porosity, temperature, viscosity and saturation condition, and fluid type and fluid saturation are obtained by analyzing the T2 spectrum of the shale core sample.

[0113] The shale core nuclear magnetic experimental analysis of crude oil viscosities at different temperatures can obtain Figs. 5(a), 5(b) and 5(c), and it can be seen that the shale core nuclear magnetic T2 spectrum at different temperatures and viscosities is simulated by the method.

[0114] The shale oil nuclear magnetic forward and inverse simulation method provided by the embodiment of the application obtains a simulated nuclear magnetic T2 spectrum of a saturated water state of a shale core according to first attribute data of the shale core and a T2 spectrum converted from a pore size distribution; obtains shale core nuclear magnetic T2 spectra of different crude oil viscosities according to the simulated nuclear magnetic T2 spectrum of the saturated water state of the shale core, by using viscosity differences of the crude oil at different temperatures and nuclear magnetic relaxation characteristics of oil and water; performs forward simulation on the shale core nuclear magnetic T2 spectra to obtain echo train signals, adds noise to the echo train signals to obtain echo train decay data, and performs inversion on the echo train decay data to obtain shale core nuclear magnetic simulation T2 spectra of different crude oil viscosities containing noise and data processing errors. The shale core nuclear magnetic simulation T2 spectra obtained by the method are closer to real measurement results, and the method provides strong support for data application.

[0115] Further, the obtaining of the simulated nuclear magnetic T2 spectrum of the saturated water state of the shale core according to the first attribute data of the shale core and the T2 spectrum converted from the pore size distribution comprises:

[0116] Gaussian fitting is performed on the first attribute data of the shale core and the T2 spectrum converted from the pore size distribution to obtain the simulated nuclear magnetic T2 spectrum of the saturated water state of the shale core. The Gaussian fitting can be understood with reference to the above embodiment, and will not be described herein again.

[0117] wherein the mean in the Gaussian function used for the Gaussian fitting corresponds to the main peak position of the relaxation signal peak to be simulated, and the variance in the Gaussian function corresponds to the spectral peak width of the relaxation signal peak to be simulated. Refer to the above embodiments for illustration, which will not be repeated here.

[0118] Further, the shale oil NMR forward and inverse simulation method further comprises:

[0119] According to the preset absolute temperature, the preset viscosity and the preset coefficient, the logarithmic mean value of the transverse relaxation time is determined; refer to the above embodiments for illustration, which will not be repeated here.

[0120] According to the logarithmic mean value of the transverse relaxation time, each transverse relaxation time of the simulated NMR T2 spectrum of the saturated water state, and the signal amplitude corresponding to each transverse relaxation time, the shale core NMR T2 spectrum of the crude oil with different viscosities is obtained. Refer to the above embodiments for illustration, which will not be repeated here.

[0121] Further, the forward modeling of the shale core NMR T2 spectrum to obtain the echo train signal comprises:

[0122] Based on the NMR forward modeling model, the shale core NMR T2 spectrum is forward modeled to obtain the echo train signal. Refer to the above embodiments for illustration, which will not be repeated here.

[0123] Further, the shale oil NMR forward and inverse simulation method further comprises:

[0124] A random number is generated from a normal distribution, and the random number is added to each echo acquisition data to obtain the echo train decay data. Refer to the above embodiments for illustration, which will not be repeated here.

[0125] Further, before the step of converting the T2 spectrum according to the first attribute data of the shale core and the pore size distribution, the shale oil NMR forward and inverse simulation method further comprises:

[0126] According to the second attribute data of the shale core, the pore size distribution curve of the shale core is determined; refer to the above embodiments for illustration, which will not be repeated here.

[0127] The pore size distribution curve is converted to obtain the T2 spectrum converted from the pore size distribution. Refer to the above embodiments for illustration, which will not be repeated here.

[0128] Further, after the step of obtaining shale core nuclear magnetic resonance simulation T2 spectrum of different crude oil viscosity containing noise and data processing error, the shale oil nuclear magnetic resonance forward and inverse simulation method further comprises:

[0129] The echo train signal obtained by the forward simulation and the shale core nuclear magnetic resonance simulation T2 spectrum obtained by the inverse simulation are used to obtain shale core samples under preset simulation conditions, and fluid type and fluid saturation are obtained according to the shale core samples. Refer to the above embodiment description, which will not be repeated here.

[0130] Figure 6 FIG. 1 is a structural schematic diagram of a shale oil nuclear magnetic resonance forward and inverse simulation device provided by an embodiment of the present application, as shown in the figure, the shale oil nuclear magnetic resonance forward and inverse simulation device provided by the embodiment of the present application comprises a first obtaining unit 601, a second obtaining unit 602, a forward simulation unit 603 and an inverse simulation unit 604, wherein: Figure 6

[0131] The first obtaining unit 601 is configured to obtain a simulated nuclear magnetic resonance T2 spectrum of a water-saturated state of a shale core according to first attribute data of the shale core and a T2 spectrum converted from a pore size distribution; the second obtaining unit 602 is configured to obtain a shale core nuclear magnetic resonance T2 spectrum of different viscosity crude oils according to the simulated nuclear magnetic resonance T2 spectrum of the water-saturated state by using viscosity differences of the crude oils at different temperatures and nuclear magnetic resonance relaxation characteristics of oil and water; the forward simulation unit 603 is configured to perform forward simulation on the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal, and add noise to the echo train signal to obtain echo train attenuation data; and the inverse simulation unit 604 is configured to perform inverse simulation on the echo train attenuation data to obtain a shale core nuclear magnetic resonance simulation T2 spectrum of different viscosity crude oils containing noise and data processing error.

[0132] Specifically, the first obtaining unit 601 in the device is configured to obtain a simulated nuclear magnetic resonance T2 spectrum of a water-saturated state of a shale core according to first attribute data of the shale core and a T2 spectrum converted from a pore size distribution; the second obtaining unit 602 is configured to obtain a shale core nuclear magnetic resonance T2 spectrum of different viscosity crude oils according to the simulated nuclear magnetic resonance T2 spectrum of the water-saturated state by using viscosity differences of the crude oils at different temperatures and nuclear magnetic resonance relaxation characteristics of oil and water; the forward simulation unit 603 is configured to perform forward simulation on the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal, and add noise to the echo train signal to obtain echo train attenuation data; and the inverse simulation unit 604 is configured to perform inverse simulation on the echo train attenuation data to obtain a shale core nuclear magnetic resonance simulation T2 spectrum of different viscosity crude oils containing noise and data processing error.

[0133] ​The shale oil nuclear magnetic resonance forward inversion simulation device provided by the embodiment of the present application can obtain the shale core nuclear magnetic resonance T2 spectrum of different viscosity crude oils according to the viscosity difference of crude oils at different temperatures and the nuclear magnetic resonance relaxation characteristics of oil and water, perform forward modeling on the shale core nuclear magnetic resonance T2 spectrum, obtain echo train signals, add noise to the echo train signals, and obtain echo train attenuation data; and perform inversion on the echo train attenuation data to obtain shale core nuclear magnetic resonance simulation T2 spectra of different crude oil viscosities containing noise and data processing errors, so that shale core nuclear magnetic resonance simulation T2 spectra closer to real measurement results can be obtained, and strong support is provided for data application.

[0134] Further, the first obtaining unit 601 is specifically configured to:

[0135] perform Gaussian fitting according to the first attribute data of the shale core and the T2 spectrum converted from the pore size distribution to obtain the simulated nuclear magnetic resonance T2 spectrum in the saturated water state.

[0136] The mean value in the Gaussian function used for Gaussian fitting corresponds to the main peak position of the relaxation signal peak to be simulated, and the variance in the Gaussian function corresponds to the spectral peak width of the relaxation signal peak to be simulated.

[0137] Further, the second obtaining unit 602 is specifically configured to:

[0138] determine the logarithmic mean value of the transverse relaxation time according to the preset absolute temperature, the preset viscosity, and the preset coefficient.

[0139] obtain the shale core nuclear magnetic resonance T2 spectrum of different viscosity crude oils according to the logarithmic mean value of the transverse relaxation time, each transverse relaxation time of the simulated nuclear magnetic resonance T2 spectrum in the saturated water state, and the signal amplitude corresponding to each transverse relaxation time.

[0140] Further, the forward modeling unit 603 is specifically configured to:

[0141] perform forward modeling on the shale core nuclear magnetic resonance T2 spectrum based on a nuclear magnetic resonance forward modeling model to obtain echo train signals.

[0142] Further, the forward modeling unit 603 is specifically configured to:

[0143] generate a random number from a normal distribution, and add the random number to each echo acquisition data to obtain echo train attenuation data.

[0144] Further, before the step of converting the T2 spectrum according to the first attribute data of the shale core and the pore size distribution, the shale oil nuclear magnetic resonance forward inversion simulation device is further used for:

[0145] determining a pore size distribution curve of the shale core according to the second attribute data of the shale core;

[0146] transforming the pore size distribution curve to obtain a pore size distribution converted T2 spectrum.

[0147] Further, after the step of obtaining the shale core nuclear magnetic resonance simulation T2 spectrum of different crude oil viscosities containing noise and data processing errors, the shale oil nuclear magnetic resonance forward inversion simulation device is further used for:

[0148] applying the echo train signal obtained by forward modeling and the shale core nuclear magnetic resonance simulation T2 spectrum obtained by inversion to obtain a shale core sample under a preset simulation condition, and obtaining a fluid type and a fluid saturation according to the shale core sample.

[0149] The shale oil nuclear magnetic resonance forward inversion simulation device provided in the embodiments of the present application can be specifically used to execute the processing procedures of the above-mentioned method embodiments, and the functions thereof will not be repeated here, and the detailed description can be referred to the above-mentioned method embodiments.

[0150] Figure 7 The computer device entity structure schematic diagram provided in the embodiments of the present application is shown in FIG. 1, which comprises a memory 701, a processor 702, and a computer program stored in the memory 701 and executable on the processor 702, and the processor 702 implements the following method when executing the computer program. Figure 7

[0151] obtaining a saturated water state simulation nuclear magnetic resonance T2 spectrum of the shale core according to the first attribute data of the shale core and the pore size distribution converted T2 spectrum;

[0152] obtaining a shale core nuclear magnetic resonance T2 spectrum of different viscosities of crude oil according to the saturated water state simulation nuclear magnetic resonance T2 spectrum, the viscosity difference of the crude oil at different temperatures, and the nuclear magnetic resonance relaxation characteristics of oil and water;

[0153] forward modeling the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal, adding noise to the echo train signal to obtain echo train attenuation data;

[0154] inverting the echo train attenuation data to obtain a shale core nuclear magnetic resonance simulation T2 spectrum of different viscosities of crude oil containing noise and data processing errors.

[0155] ​The embodiment discloses a computer program product, which comprises a computer program, and the computer program realizes the following method when executed by a processor.

[0156] According to the first attribute data of the shale core and the T2 spectrum converted from the pore size distribution, a simulated nuclear magnetic resonance T2 spectrum of the shale core in a water-saturated state is obtained.

[0157] According to the simulated nuclear magnetic resonance T2 spectrum of the water-saturated state, the shale core nuclear magnetic resonance T2 spectrum of different viscosity crude oils is obtained by using the viscosity difference of the crude oils at different temperatures and the nuclear magnetic resonance relaxation characteristics of oil and water.

[0158] The forward modeling is performed on the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal, and noise is added to the echo train signal to obtain echo train attenuation data.

[0159] The inversion is performed on the echo train attenuation data to obtain shale core nuclear magnetic resonance simulated T2 spectra of different crude oil viscosities containing noise and data processing errors.

[0160] The embodiment provides a computer readable storage medium, which stores a computer program, and the computer program realizes the following method when executed by a processor.

[0161] According to the first attribute data of the shale core and the T2 spectrum converted from the pore size distribution, a simulated nuclear magnetic resonance T2 spectrum of the shale core in a water-saturated state is obtained.

[0162] According to the simulated nuclear magnetic resonance T2 spectrum of the water-saturated state, the shale core nuclear magnetic resonance T2 spectrum of different viscosity crude oils is obtained by using the viscosity difference of the crude oils at different temperatures and the nuclear magnetic resonance relaxation characteristics of oil and water.

[0163] The forward modeling is performed on the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal, and noise is added to the echo train signal to obtain echo train attenuation data.

[0164] The inversion is performed on the echo train attenuation data to obtain shale core nuclear magnetic resonance simulated T2 spectra of different crude oil viscosities containing noise and data processing errors.

[0165] Compared with the technical solution in the prior art, the shale oil nuclear magnetic resonance forward and inverse simulation method provided by the embodiment of the present application can obtain the simulated nuclear magnetic resonance T2 spectrum of the shale core in a saturated water state according to the first attribute data of the shale core and the T2 spectrum converted from the pore size distribution, obtain the shale core nuclear magnetic resonance T2 spectrum of different viscosity crude oils according to the viscosity difference of the crude oils at different temperatures and the nuclear magnetic resonance relaxation characteristics of oil and water, perform forward simulation on the shale core nuclear magnetic resonance T2 spectrum to obtain an echo train signal, add noise to the echo train signal to obtain echo train attenuation data, and perform inverse simulation on the echo train attenuation data to obtain the shale core nuclear magnetic resonance simulation T2 spectrum of different crude oil viscosities containing noise and data processing errors, so that the shale core nuclear magnetic resonance simulation T2 spectrum closer to the real measurement result can be obtained, and strong support is provided for data application.

[0166] Those skilled in the art will understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0167] The present application is described with reference to flowcharts and / or block diagrams of the method, device (system), and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device that implements the flowcharts and / or block diagrams. Figure 1 The device that implements the function specified in one or more flows or blocks. Figure 1 The device that implements the function specified in one or more flows or blocks.

[0168] These computer program instructions can also be stored in a computer-readable memory capable of guiding the computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including instruction devices that implement the flowcharts and / or block diagrams. Figure 1 The device that implements the function specified in one or more flows or blocks. Figure 1 The device that implements the function specified in one or more flows or blocks.

[0169] These computer program instructions can also be loaded into a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 one or more flowcharts and / or blocks

[0170] In this description, references to "one embodiment", "one example", "some embodiments", "example", "exemplary", or "some examples" mean that the described feature, structure, material, or characteristic is included in at least one embodiment or example of the disclosure. The illustrative appearances of the above- described terms in various places in the specification are not necessarily all referring to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0171] The specific embodiments described above are examples of the present disclosure and are not intended to be limiting. The above description is intended to enable any person skilled in the art to make and use the present disclosure. The various embodiments described above can be modified as necessary. The above description is intended to enable any person skilled in the art to make and use the present disclosure. The various embodiments described above can be modified as necessary. The various examples and features described above can be combined to provide further examples, which fall within the scope of the present disclosure. The above description is intended to enable any person skilled in the art to make and use the present disclosure. The various embodiments described above can be modified as necessary. The various examples and features described above can be combined to provide further examples, which fall within the scope of the present disclosure. The above description is intended to enable any person skilled in the art to make and use the present disclosure. The various embodiments described above can be modified as necessary. The various examples and features described above can be combined to provide further examples, which fall within the scope of the present disclosure.

Claims

1. A method for forward and inverse nuclear magnetic resonance simulation of shale oil, characterized in that, include: Based on the first attribute data and the T2 spectrum of pore size distribution conversion of shale core, the simulated nuclear magnetic resonance T2 spectrum of shale core in saturated water state was obtained; Based on the simulated nuclear magnetic resonance T2 spectrum of the saturated water state, the nuclear magnetic resonance T2 spectra of shale cores of crude oil with different viscosities were obtained by utilizing the viscosity difference of crude oil at different temperatures and the nuclear magnetic resonance relaxation characteristics of oil and water. The T2 nuclear magnetic resonance spectrum of the shale core was forward modeled to obtain the echo train signal, and noise was added to the echo train signal to obtain the echo train attenuation data. The echo train attenuation data was inverted to obtain the simulated T2 spectra of shale core nuclear magnetic resonance for different crude oil viscosities, including noise and data processing errors; The process of obtaining the simulated nuclear magnetic resonance T2 spectrum of the shale core in a saturated water state based on the first attribute data and the T2 spectrum converted from the pore size distribution includes: Gaussian fitting was performed on the first attribute data of the shale core and the T2 spectrum converted by pore size distribution to obtain the simulated nuclear magnetic resonance T2 spectrum of the saturated water state. Wherein, the mean of the Gaussian function used for Gaussian fitting corresponds to the main peak position of the relaxation signal peak to be simulated, and the variance of the Gaussian function corresponds to the spectral peak width of the relaxation signal peak to be simulated. The method of obtaining shale core NMR T2 spectra of crude oil with different viscosities based on the simulated NMR T2 spectrum of the saturated water state, utilizing the viscosity difference of crude oil at different temperatures and the NMR relaxation characteristics of oil and water, includes: The logarithmic average of the transverse relaxation time is determined based on the preset absolute temperature, preset viscosity, and preset coefficient. Based on the logarithmic average of the transverse relaxation time, the transverse relaxation times of the simulated nuclear magnetic resonance T2 spectrum of the saturated water state, and the signal amplitudes corresponding to each transverse relaxation time, nuclear magnetic resonance T2 spectra of shale cores of crude oil with different viscosities are obtained.

2. The shale oil nuclear magnetic resonance forward and inverse simulation method according to claim 1, characterized in that, The forward modeling of the nuclear magnetic resonance T2 spectrum of the shale core to obtain the echo train signal includes: The T2 NMR spectrum of the shale core was modeled using a forward modeling method to obtain the echo train signal.

3. The shale oil nuclear magnetic resonance forward and inverse simulation method according to claim 1, characterized in that, The process of adding noise to the echo train signal to obtain echo train attenuation data includes: A random number is generated from a normal distribution and added to each echo acquisition data to obtain echo train attenuation data.

4. The shale oil nuclear magnetic resonance forward and inverse simulation method according to any one of claims 1 to 3, characterized in that, Prior to the step of converting the T2 spectrum based on the first attribute data and pore size distribution of the shale core, the shale oil nuclear magnetic resonance forward and inverse simulation method further includes: Based on the secondary attribute data of shale cores, the pore size distribution curve of the shale cores was determined; The pore size distribution curve is transformed to obtain the T2 spectrum of the pore size distribution transformation.

5. The shale oil nuclear magnetic resonance forward and inverse simulation method according to any one of claims 1 to 3, characterized in that, Following the step of obtaining the T2 spectra of shale core nuclear magnetic resonance simulations for different crude oil viscosities, which include noise and data processing errors, the shale oil nuclear magnetic resonance forward and inverse simulation method further includes: Using the echo train signal obtained from forward modeling and the T2 spectrum of shale core nuclear magnetic resonance obtained from inversion, shale core samples were obtained downhole under preset simulation conditions, and the fluid type and fluid saturation were obtained based on the shale core samples.

6. A shale oil nuclear magnetic resonance forward and inverse simulation device, characterized in that, include: The first acquisition unit is used to acquire the simulated nuclear magnetic resonance T2 spectrum of the shale core in saturated water state based on the first attribute data and the T2 spectrum converted from the pore size distribution of the shale core. The second acquisition unit is used to acquire the nuclear magnetic resonance T2 spectra of shale cores of crude oil with different viscosities based on the simulated nuclear magnetic resonance T2 spectrum of the saturated water state, utilizing the viscosity difference of crude oil at different temperatures and the nuclear magnetic resonance relaxation characteristics of oil and water. The forward modeling unit is used to perform forward modeling on the nuclear magnetic resonance T2 spectrum of the shale core to obtain the echo train signal, and add noise to the echo train signal to obtain echo train attenuation data; The inversion unit is used to invert the echo train attenuation data to obtain the simulated T2 spectrum of shale core nuclear magnetic resonance for different crude oil viscosities, including noise and data processing errors. The first acquisition unit is specifically used for: Gaussian fitting was performed on the first attribute data of the shale core and the T2 spectrum converted by pore size distribution to obtain the simulated nuclear magnetic resonance T2 spectrum of the saturated water state. Wherein, the mean of the Gaussian function used for Gaussian fitting corresponds to the main peak position of the relaxation signal peak to be simulated, and the variance of the Gaussian function corresponds to the spectral peak width of the relaxation signal peak to be simulated. The second acquisition unit is specifically used for: The logarithmic average of the transverse relaxation time is determined based on the preset absolute temperature, preset viscosity, and preset coefficient. Based on the logarithmic average of the transverse relaxation time, the transverse relaxation times of the simulated nuclear magnetic resonance T2 spectrum of the saturated water state, and the signal amplitudes corresponding to each transverse relaxation time, nuclear magnetic resonance T2 spectra of shale cores of crude oil with different viscosities are obtained.

7. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 5.

Images