Component elimination method, device, equipment and product of NMR (nuclear magnetic resonance) spectrum
By generating mask spectra in NMR spectra and iteratively subtracting them, the problem of erroneous elimination of adjacent components during the elimination of high-peak and high-intensity components is solved, achieving higher accuracy and stability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-14
- Publication Date
- 2026-04-07
AI Technical Summary
Existing techniques for eliminating high-peak, high-intensity components in NMR spectra can easily lead to the accidental elimination of adjacent components, resulting in decreased accuracy of the results.
By acquiring the original echo train signal from the well side, the original NMR spectrum is obtained through inversion. The component elimination region is determined to generate a mask spectrum. Component elimination is then performed by combining the mask spectrum and the echo train through iterative subtraction until the iteration stop condition is met.
It improves the accuracy and stability of component elimination, reduces the impact of erroneous elimination of other components when peaks overlap, and reduces traces of manual processing.
Smart Images
Figure CN121806124A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The application belongs to the technical field of nuclear magnetic resonance, and particularly relates to a component elimination method, device, equipment and product of NMR spectrum. BACKGROUND
[0002] The final actual observation result of well measurement two-dimensional data is an NMR spectrum obtained through echo string inversion, which is usually displayed in the form of a thermodynamic map; in some scenarios, local processing of the final presented spectrum may be required to facilitate data analysis; however, in actual application, there may be a case where the intensity of some local components in the inverted spectrum is extremely high, which makes it difficult to observe signals (such as small pore and bound fluid signals) with lower amplitude but possibly more geological significance, and therefore, it is necessary to eliminate the components with high intensity in the spectrum to obtain a more accurate NMR spectrum.
[0003] At present, the conventional component elimination method is to directly perform mask difference on the selected region, which does not have a smooth transition, resulting in unnatural image transformation; meanwhile, in data where the peak component overlap is more obvious, since the selected region cannot be completely accurate, the traditional technology may divide a part of other components into the selected region, resulting in mis-elimination of adjacent components and thus causing a decrease in result accuracy; therefore, based on the foregoing deficiencies, it is necessary to develop a controllable component elimination method for local spectrum with high peak value and high intensity to meet the analysis needs. SUMMARY
[0004] The application aims to provide a component elimination method, device, equipment and product of NMR spectrum, to solve the problem of mis-elimination of adjacent components and thus causing a decrease in result accuracy existing in the prior art.
[0005] To achieve the above-mentioned purpose, the application adopts the following technical solutions: In a first aspect, a component elimination method of NMR spectrum is provided, comprising: obtaining a well-side original echo string signal and performing inversion on the well-side original echo string signal to obtain an original NMR spectrum; determining a component elimination region in the original NMR spectrum and generating a mask spectrum according to the component elimination region; obtaining an NMR spectrum at the i-th iteration, wherein the initial value of i is 1, and when i is 1, the NMR spectrum at the i-th iteration is the original NMR spectrum; generating a high-peak signal echo string at the i-th iteration based on the mask spectrum and the NMR spectrum at the i-th iteration; The original wellside echo train signal is subtracted from the peak signal echo train to obtain the wellside echo train signal after the i-th component elimination, and the wellside echo train signal is inverted to obtain the new NMR spectrum. Based on the new NMR spectrum, determine whether the iteration stopping condition is met; If not, then the new NMR spectrum is taken as the NMR spectrum at the (i+1)th iteration; Increment i by 1 and reacquire the NMR spectrum at the i-th iteration until the iteration stop condition is met. Then, take the new NMR spectrum at the iteration stop condition as the optimal NMR spectrum corresponding to the original echo train signal on the well side.
[0006] Based on the above disclosure, after obtaining the original wellside echo train signal, this invention first inverts it to obtain the original NMR spectrum; then, it determines the component elimination region in the original NMR spectrum and generates a mask spectrum based on this; then, iterative component elimination is performed on the original NMR spectrum, that is, the peak signal echo train at the i-th iteration is generated based on the mask spectrum and the NMR spectrum at the i-th iteration; next, the original echo train signal is subtracted from the peak signal echo train to obtain the wellside echo train signal after the i-th component elimination; thus, after completing one component elimination, the wellside echo train signal can be inverted to obtain a new NMR spectrum; finally, it is determined whether the obtained new NMR spectrum meets the iteration stopping condition; if it does not meet the condition, it is necessary to continue the iteration, that is, the new NMR spectrum is used as the NMR spectrum at the (i+1)-th iteration, and the aforementioned component elimination operation is re-executed until the iteration stopping condition is met, thus obtaining the optimal NMR spectrum.
[0007] Through the above design, this invention generates a mask spectrum by selecting a component elimination region; then, it combines the mask spectrum with an echo train for subtraction to perform component elimination, and finally iteratively inverts to obtain a new spectrum. This method can more accurately target specific signals that need to be removed, and its signal-to-noise ratio and stability are generally superior to those of direct spectrum subtraction. It not only effectively reduces the impact of erroneous elimination of other components when peaks overlap, but also reduces traces of manual processing, thus improving the stability and accuracy of the processing results. Therefore, this invention provides a localized, controllable component elimination method for high-peak-intensity spectra, making it highly suitable for large-scale application and promotion.
[0008] In one possible design, based on the mask spectrum and the NMR spectrum at the i-th iteration, the peak signal echo train at the i-th iteration is generated, including: The mask spectrum is multiplied by the NMR spectrum at the i-th iteration to obtain the processed NMR spectrum. Subtracting the original NMR spectrum from the processed NMR spectrum yields the first differential NMR spectrum. The first differential NMR spectrum is forward modeled to obtain the peak signal echo train at the i-th iteration.
[0009] In one possible design, the first differential NMR spectrum is forward modeled to obtain the peak signal echo train at the i-th iteration, including: The first forward modeling parameters of the first differential NMR spectrum are determined, wherein the first forward modeling parameters include longitudinal relaxation time, transverse relaxation time, echo time, and reversal time; Based on the echo time and the transverse relaxation time in the first forward modeling parameters, a T2 attenuation kernel matrix is constructed, and based on the longitudinal relaxation time and the reversal time in the first forward modeling parameters, a T1 recovery kernel matrix is constructed. Based on the T2 attenuation kernel matrix and the T1 recovery kernel matrix, the first differential NMR spectrum is forward modeled to obtain the peak signal echo train.
[0010] In one possible design, the first differential NMR spectrum is forward modeled based on the T2 attenuation kernel matrix and the T1 recovery kernel matrix to obtain the peak signal echo train, including: The peak signal echo train is obtained by performing forward modeling on the first differential NMR spectrum according to the following formula; ; In the formula, This refers to the peak signal echo train. This represents the T2 decay kernel matrix. This represents the T1 recovery kernel matrix. This represents the first differential NMR spectrum. These represent the echo time and the reversal time, respectively. These represent the longitudinal relaxation time and the transverse relaxation time, respectively. Here, are the second forward parameters, ,and The pulse angle is the first differential NMR spectrum.
[0011] In one possible design, based on the new NMR spectrum, it is determined whether the iteration stopping condition is met, including: Subtract the new NMR spectrum from the NMR spectrum at the i-th iteration to obtain the second difference NMR spectrum; Calculate the modulus of the second differential NMR spectrum; Determine whether the modulus value is less than a preset threshold; If so, the iteration stopping condition is met; otherwise, the new NMR spectrum is used as the NMR spectrum for the (i+1)th iteration.
[0012] In one possible design, the T1T2 two-dimensional relaxation spectrum algorithm based on ADMM is used to invert the original echo train signal from the well side to obtain the original NMR spectrum.
[0013] In one possible design, the inversion parameters when the wellside echo train signal is inverted are the same as the inversion parameters when the original wellside echo train signal is inverted.
[0014] Secondly, a component elimination device for NMR spectra is provided, comprising: The inversion unit is used to acquire the original echo train signal from the well side and invert the original echo train signal from the well side to obtain the original NMR spectrum. A mask generation unit is used to determine the component elimination region in the original NMR spectrum and generate a mask spectrum based on the component elimination region. A component elimination unit is used to obtain the NMR spectrum at the i-th iteration, where the initial value of i is 1, and when i is 1, the NMR spectrum at the i-th iteration is the original NMR spectrum; The component elimination unit is used to generate the peak signal echo train at the i-th iteration based on the mask spectrum and the NMR spectrum at the i-th iteration. The component elimination unit is used to subtract the original wellside echo train signal from the peak signal echo train to obtain the wellside echo train signal after the i-th component elimination, and to invert the wellside echo train signal to obtain a new NMR spectrum. The component elimination unit is used to determine whether the iteration stopping condition is met based on the new NMR spectrum; The component elimination unit is used to use the new NMR spectrum as the NMR spectrum of the (i+1)th iteration when it is determined that the iteration stopping condition is not met. The component elimination unit is also used to increment i by 1 and reacquire the NMR spectrum at the i-th iteration until the iteration stop condition is met. The new NMR spectrum at the iteration stop condition is then used as the optimal NMR spectrum corresponding to the original echo train signal on the well side.
[0015] Thirdly, another component elimination device for NMR spectra is provided. Taking the device as an electronic device as an example, it includes a memory, a processor, and a transceiver that are connected in sequence. The memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the component elimination method for NMR spectra as described in the first aspect or any possible design of the first aspect.
[0016] Fourthly, a storage medium is provided, on which instructions are stored, which, when executed on a computer, perform the component elimination method of the NMR spectrum as described in the first aspect or any possible design of the first aspect.
[0017] Fifthly, a computer program product containing instructions is provided, which, when executed on a computer, cause the computer to perform the component elimination method of the NMR spectrum as described in the first aspect or any possible design of the first aspect.
[0018] Beneficial effects: (1) This invention generates a mask spectrum by selecting a component elimination region; then, it combines the mask spectrum and uses the method of converting the spectrum into an echo train for subtraction to perform component elimination, and finally iterates and inverts to obtain a new spectrum; thus, this method can more accurately target the specific signal that needs to be removed, and its signal-to-noise ratio and stability are usually better than the result of direct spectrum subtraction. It not only effectively reduces the influence of erroneous elimination of other components when peaks overlap, but also reduces the traces of manual processing. Therefore, it improves the stability and accuracy of the processing results; thus, this invention provides a localized and controllable component elimination method for high peak and high intensity spectra, which is very suitable for large-scale application and promotion. Attached Figure Description
[0019] Figure 1 A schematic flowchart illustrating the steps of the NMR spectrum component elimination method provided in this embodiment of the invention; Figure 2 A structural diagram of the component elimination device for NMR spectra provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation
[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in conjunction with the accompanying drawings and descriptions of the embodiments or the prior art. Obviously, the following description of the structure of the accompanying drawings is only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. It should be noted that the description of these embodiments is for the purpose of helping to understand the present invention, but does not constitute a limitation of the present invention.
[0021] It should be understood that although the terms first, second, etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit, without departing from the scope of the exemplary embodiments of the invention.
[0022] It should be understood that the term "and / or" that may appear in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist simultaneously. The term " / and" that may appear in this document describes another relationship between related objects, indicating that two relationships can exist. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " that may appear in this document generally indicates that the related objects before and after it are in an "or" relationship.
[0023] Example: See Figure 1 As shown, the NMR spectrum component elimination method provided in this embodiment selects a region on the NMR spectrum, converts it into an echo train signal for differential processing, and performs component elimination in an iterative manner to finally convert it into a new spectrum. In this way, compared with traditional technology, this method can effectively reduce the influence of erroneous elimination of other components when peaks overlap, and can reduce the traces of manual processing, thus improving the stability and accuracy of the processing results. For example, this method can be run on the component elimination end side. Optionally, the component elimination end can be, but is not limited to, a personal computer (PC) or a server. It is understood that the aforementioned execution subject does not constitute a limitation on the embodiments of this application. Accordingly, the operation steps of this method can be, but are not limited to, the steps S1 to S8 below.
[0024] S1. Acquire the original echo train signal from the well side and invert the original echo train signal from the well side to obtain the original NMR spectrum. In specific implementation, for example, but not limited to, the T1T2 two-dimensional relaxation spectrum algorithm based on ADMM (alternating direction multiplier method) can be used to invert the aforementioned original echo train signal from the well side to obtain the original NMR spectrum. The aforementioned T1T2 two-dimensional relaxation spectrum algorithm based on ADMM is a commonly used technique for signal inversion, and its inversion process will not be described in detail.
[0025] After inverting the original echo train signal from the well side to obtain the original NMR spectrum, a mask spectrum for eliminating high-peak components can be determined so that component elimination can be performed based on the mask spectrum. The process of constructing the mask spectrum can be, but is not limited to, the steps shown in step S2 below.
[0026] S2. Determine the component elimination region in the original NMR spectrum and generate a mask spectrum based on the component elimination region. In specific implementation, the original NMR spectrum is essentially a two-dimensional array. To build a mask spectrum with a defined shape (e.g., a rectangle), it is necessary to first determine the component elimination region (i.e., the selected area). This can be achieved, but is not limited to, first obtaining the endpoint coordinates of the component elimination region (obtained in response to human-computer interaction). Then, based on the endpoint coordinates, the component elimination region is determined in the original NMR spectrum. Next, an initial mask spectrum with the same length and width as the original NMR spectrum is created. Finally, the values of the elements in the region corresponding to the component elimination region in the initial mask spectrum are set to 1, and the values of the elements in the remaining regions that do not need to be eliminated are set to 0, thus generating the aforementioned mask spectrum.
[0027] After generating the mask spectrum for component elimination, iterative component elimination can be performed based on the mask spectrum. The process can be, but is not limited to, the steps S3 to S8 below.
[0028] S3. Obtain the NMR spectrum at the i-th iteration, where the initial value of i is 1, and when i is 1, the NMR spectrum at the i-th iteration is the original NMR spectrum.
[0029] After obtaining the NMR spectrum at the i-th iteration, the peak signal echo train at the current iteration can be generated by combining it with the mask spectrum, as shown in step S4 below.
[0030] S4. Based on the mask spectrum and the NMR spectrum at the i-th iteration, generate the peak signal echo train at the i-th iteration; in specific implementation, the mask spectrum is multiplied by the NMR spectrum at the i-th iteration, then the difference is performed with the original NMR spectrum, and finally the peak signal echo train at the current iteration is obtained through forward modeling.
[0031] The aforementioned processing procedure may be, but is not limited to, the following steps S41 to S43.
[0032] S41. Multiply the mask spectrum with the NMR spectrum at the i-th iteration to obtain the processed NMR spectrum. In this embodiment, multiplying the mask spectrum with the NMR spectrum at the i-th iteration preserves the component elimination region in the NMR spectrum at the i-th iteration. Then, it can be differentially divided with the original NMR spectrum to perform elemental difference of the component elimination region in the spectrum, thereby achieving the purpose of one-time component elimination in the spectrum. The process is shown in step S42 below.
[0033] S42. Subtract the original NMR spectrum from the processed NMR spectrum to obtain the first differential NMR spectrum.
[0034] After the difference operation between the original NMR spectrum and the processed NMR spectrum is completed, the forward modeling of the first difference NMR spectrum can be performed to convert the spectrum into an echo train for component elimination, as shown in step S43 below.
[0035] S43. Perform forward modeling on the first differential NMR spectrum to obtain the peak signal echo train at the i-th iteration; in specific implementation, the peak signal echo train at the i-th iteration can be expressed as: Si = g(f(S0) - M · Xi), where f(S0) represents the original NMR spectrum, M represents the mask spectrum, Xi represents the NMR spectrum at the i-th iteration, and g() represents the forward modeling function; specifically, the forward modeling process is described in detail below, and may be, but is not limited to, the steps S43a to S43c below.
[0036] S43a. Determine the first forward modeling parameters of the first differential NMR spectrum, wherein the first forward modeling parameters include longitudinal relaxation time, transverse relaxation time, echo time, and reversal time; in this embodiment, the aforementioned longitudinal relaxation time, transverse relaxation time, echo time, and reversal time can be preset; thus, after obtaining the aforementioned first forward modeling parameters, a T2 attenuation kernel matrix and a T1 recovery kernel matrix can be constructed based on them, so that the forward modeling of the first differential NMR spectrum can be performed by using the dual integration method of the T2 attenuation kernel matrix and the T1 recovery kernel matrix, thereby obtaining an echo train composed purely of peak signals.
[0037] The construction process of the T2 decay kernel matrix and the T1 recovery kernel matrix is shown in step S43b below.
[0038] S43b. Based on the echo time and the transverse relaxation time in the first forward modeling parameters, construct the T2 attenuation kernel matrix, and based on the longitudinal relaxation time and the reversal time in the first forward modeling parameters, construct the T1 recovery kernel matrix; in specific implementation, the T2 attenuation kernel matrix is: The T1 recovery kernel matrix is: ;in, These represent the echo time and the reversal time, respectively. These represent the longitudinal relaxation time and the transverse relaxation time, respectively. These are the second forward parameters; specifically, ,and The pulse angle is the first differential NMR spectrum.
[0039] Thus, after constructing the T2 decay kernel matrix and the T1 recovery kernel matrix in the aforementioned manner, the first differential NMR spectrum can be forward modeled based on these matrices, as shown in step S43c below.
[0040] S43c. Based on the T2 attenuation kernel matrix and the T1 recovery kernel matrix, perform forward modeling on the first differential NMR spectrum to obtain the peak signal echo train; in specific implementation, for example, but not limited to, performing forward modeling on the first differential NMR spectrum according to the following formula to obtain the peak signal echo train.
[0041] ; In the formula, This refers to the peak signal echo train (which is essentially Si). This represents the T2 decay kernel matrix. This represents the T1 recovery kernel matrix. This refers to the first differential NMR spectrum (i.e., the two-dimensional NMR spectrum, which is the joint relaxation time distribution). These represent the echo time and the reversal time, respectively. These represent the longitudinal relaxation time and the transverse relaxation time, respectively. Here, are the second forward parameters, ,and The pulse angle is the first differential NMR spectrum.
[0042] Thus, based on the aforementioned steps S41 to S43 and their sub-steps, after obtaining the peak signal echo train through forward modeling, it can be differentially processed with the original echo train signal to obtain a new echo train after the first component elimination (i.e., the wellside echo train signal after the i-th component elimination below), as shown in step S5 below.
[0043] S5. Subtract the original well-side echo train signal from the peak signal echo train to obtain the well-side echo train signal after the i-th component elimination, and invert the well-side echo train signal to obtain a new NMR spectrum. In specific applications, the inversion method of the well-side echo train signal is the same as the inversion method of the original well-side echo train signal, and the inversion parameters when inverting the well-side echo train signal are the same as the inversion parameters when inverting the original well-side echo train signal. In this way, it is possible to avoid a large difference between the generated new NMR spectrum and the NMR spectrum obtained by inverting the original echo train. Optionally, for example, the aforementioned inversion parameters are the regularization coefficients in the inversion function corresponding to the two-dimensional relaxation spectrum algorithm.
[0044] Thus, after completing one component elimination based on the aforementioned steps and obtaining a new NMR spectrum, it can be determined whether the iteration can be stopped, as shown in step S6 below.
[0045] S6. Determine whether the iterative stop condition is satisfied based on the new NMR spectrum; in specific implementation, for example but not limited to, first subtract the new NMR spectrum from the NMR spectrum at the i-th iteration to obtain a second differential NMR spectrum; then, calculate the modulus value of the second differential NMR spectrum; next, determine whether the modulus value is less than a preset threshold, where if so, it is determined that the iterative stop condition is satisfied, and the new NMR spectrum can be directly used as the optimal NMR spectrum; where the aforementioned iterative stop condition can be summarized as: |X’ - Xi| < k, where X’ represents the new NMR spectrum, k is the preset threshold, and || represents the modulus of the signal.
[0046] Further, when the modulus value is greater than or equal to the preset threshold, iteration needs to continue, that is, use the new NMR spectrum as the NMR spectrum for the next iteration, and then start from the aforementioned step S3 again until the iterative stop condition is satisfied, and the optimal NMR spectrum can be obtained; where the loop iteration steps are shown in the following steps S7 and S8.
[0047] S7. If not, then use the new NMR spectrum as the NMR spectrum for the (i + 1)-th iteration; S8. Increment i by 1, and re-obtain the NMR spectrum at the i-th iteration until the iterative stop condition is satisfied, and use the new NMR spectrum when the iterative stop condition is satisfied as the optimal NMR spectrum corresponding to the original echo train signal on the well side; in this embodiment, when the iterative stop condition is satisfied, the final NMR spectrum can be obtained. At this time, the high peak value on the original NMR spectrum is effectively suppressed, and the signals with lower amplitude but possibly more geological significance that were originally masked by it are clearly shown.
[0048] Thus, through the NMR spectrum component elimination method detailed in the aforementioned steps S1 - S8, the present invention generates a mask spectrum by selecting a component elimination region; then, in combination with the mask spectrum and using the method of converting the spectrum into echo trains for subtraction to perform component elimination, and finally iteratively invert to obtain a new spectrum; in this way, this method can more accurately target specific signals to be removed, and its signal-to-noise ratio and stability are usually better than the results of direct spectrum subtraction. It not only effectively reduces the influence of erroneously eliminating other components when the wave peaks overlap, but also can reduce the traces of manual processing. Therefore, the stability and accuracy of the processing results are improved; thus, the present invention provides a local and controllable component elimination method for spectra with high peak values and high intensities, which is very suitable for large-scale application and promotion.
[0049] As Figure 2 shown, in the second aspect of this embodiment, a hardware device for implementing the NMR spectrum component elimination method described in the first aspect of the embodiment is provided, including: The inversion unit is used to acquire the original echo train signal from the well side and invert the original echo train signal from the well side to obtain the original NMR spectrum.
[0050] A mask generation unit is used to determine the component elimination region in the original NMR spectrum and generate a mask spectrum based on the component elimination region.
[0051] The component elimination unit is used to obtain the NMR spectrum at the i-th iteration, where the initial value of i is 1, and when i is 1, the NMR spectrum at the i-th iteration is the original NMR spectrum.
[0052] The component elimination unit is used to generate the peak signal echo train at the i-th iteration based on the mask spectrum and the NMR spectrum at the i-th iteration.
[0053] The component elimination unit is used to subtract the original wellside echo train signal from the peak signal echo train to obtain the wellside echo train signal after the i-th component elimination, and to invert the wellside echo train signal to obtain a new NMR spectrum.
[0054] The component elimination unit is used to determine whether the iteration stopping condition is met based on the new NMR spectrum.
[0055] The component elimination unit is used to use the new NMR spectrum as the NMR spectrum for the (i+1)th iteration when it is determined that the iteration stopping condition has not been met.
[0056] The component elimination unit is also used to increment i by 1 and reacquire the NMR spectrum at the i-th iteration until the iteration stop condition is met. The new NMR spectrum at the iteration stop condition is then used as the optimal NMR spectrum corresponding to the original echo train signal on the well side.
[0057] The working process, working details and technical effects of the device provided in this embodiment can be found in the first aspect of the embodiment, and will not be repeated here.
[0058] like Figure 3 As shown, the third aspect of this embodiment provides another component elimination device for NMR spectra. Taking the device as an electronic device as an example, it includes: a memory, a processor, and a transceiver that are connected in sequence. The memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the component elimination method for NMR spectra as described in the first aspect of the embodiment.
[0059] For specific examples, the memory may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, first-in-first-out (FIFO) memory, and / or first-in-last-out (FILO) memory, etc.; specifically, the processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor may be implemented using at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), PLA (Programmable Logic Array). The processor may also include a main processor and a coprocessor. The main processor, also known as the CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state.
[0060] In some embodiments, the processor may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. For example, the processor may not be limited to microprocessors of the STM32F105 series, reduced instruction set computer (RISC) microprocessors, x86 architecture processors, or processors with integrated neural network processing units (NPUs). The transceiver may be, but is not limited to, a Wi-Fi transceiver, a Bluetooth transceiver, a General Packet Radio Service (GPRS) transceiver, a ZigBee (a low-power LAN protocol based on the IEEE 802.15.4 standard) transceiver, a 3G transceiver, a 4G transceiver, and / or a 5G transceiver. Furthermore, the device may also include, but is not limited to, a power module, a display screen, and other necessary components.
[0061] The working process, working details and technical effects of the electronic device provided in this embodiment can be found in the first aspect of the embodiment, and will not be repeated here.
[0062] The fourth aspect of this embodiment provides a storage medium storing instructions for a component elimination method for NMR spectra as described in the first aspect of the embodiment. That is, the storage medium stores instructions that, when executed on a computer, perform the component elimination method for NMR spectra as described in the first aspect of the embodiment.
[0063] The storage medium refers to a carrier for storing data, which may include, but is not limited to, floppy disks, optical disks, hard disks, flash memory, USB flash drives, and / or memory sticks. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.
[0064] The working process, working details and technical effects of the storage medium provided in this embodiment can be found in the first aspect of the embodiment, and will not be repeated here.
[0065] The fifth aspect of this embodiment provides a computer program product containing instructions that, when executed on a computer, cause the computer to perform the NMR spectrum component elimination method as described in the first aspect of the embodiment, wherein the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.
[0066] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.
Claims
1. A method for component elimination in NMR spectra, characterized in that, include: The original echo train signal from the well side is acquired, and the original NMR spectrum is obtained by inversion of the original echo train signal from the well side. The component elimination regions in the original NMR spectrum are determined, and a mask spectrum is generated based on the component elimination regions; Obtain the NMR spectrum at the i-th iteration, where the initial value of i is 1, and when i is 1, the NMR spectrum at the i-th iteration is the original NMR spectrum; Based on the mask spectrum and the NMR spectrum at the i-th iteration, a peak signal echo train at the i-th iteration is generated; The original wellside echo train signal is subtracted from the peak signal echo train to obtain the wellside echo train signal after the i-th component elimination, and the wellside echo train signal is inverted to obtain the new NMR spectrum. Based on the new NMR spectrum, determine whether the iteration stopping condition is met; If not, then the new NMR spectrum is taken as the NMR spectrum at the (i+1)th iteration; Increment i by 1 and reacquire the NMR spectrum at the i-th iteration until the iteration stop condition is met. Then, take the new NMR spectrum at the iteration stop condition as the optimal NMR spectrum corresponding to the original echo train signal on the well side.
2. The method according to claim 1, characterized in that, Based on the mask spectrum and the NMR spectrum at the i-th iteration, a peak signal echo train at the i-th iteration is generated, including: The mask spectrum is multiplied by the NMR spectrum at the i-th iteration to obtain the processed NMR spectrum. Subtracting the original NMR spectrum from the processed NMR spectrum yields the first differential NMR spectrum. The first differential NMR spectrum is forward modeled to obtain the peak signal echo train at the i-th iteration.
3. The method according to claim 2, characterized in that, Perform forward modeling on the first differential NMR spectrum to obtain the peak signal echo train at the i-th iteration, including: The first forward modeling parameters of the first differential NMR spectrum are determined, wherein the first forward modeling parameters include longitudinal relaxation time, transverse relaxation time, echo time, and reversal time; Based on the echo time and the transverse relaxation time in the first forward modeling parameters, a T2 attenuation kernel matrix is constructed, and based on the longitudinal relaxation time and the reversal time in the first forward modeling parameters, a T1 recovery kernel matrix is constructed. Based on the T2 attenuation kernel matrix and the T1 recovery kernel matrix, the first differential NMR spectrum is forward modeled to obtain the peak signal echo train.
4. The method according to claim 3, characterized in that, Based on the T2 attenuation kernel matrix and the T1 recovery kernel matrix, the first differential NMR spectrum is forward modeled to obtain the peak signal echo train, including: The peak signal echo train is obtained by performing forward modeling on the first differential NMR spectrum according to the following formula; ； In the formula, This refers to the peak signal echo train. This represents the T2 decay kernel matrix. This represents the T1 recovery kernel matrix. This represents the first differential NMR spectrum. These represent the echo time and the reversal time, respectively. These represent the longitudinal relaxation time and the transverse relaxation time, respectively. Here, are the second forward parameters, ,and The pulse angle is the first differential NMR spectrum.
5. The method according to claim 1, characterized in that, Based on the new NMR spectrum, determine whether the iteration stopping condition is met, including: Subtract the new NMR spectrum from the NMR spectrum at the i-th iteration to obtain the second difference NMR spectrum; Calculate the modulus of the second differential NMR spectrum; Determine whether the modulus value is less than a preset threshold; If so, the iteration stopping condition is met; otherwise, the new NMR spectrum is used as the NMR spectrum for the (i+1)th iteration.
6. The method according to claim 1, characterized in that, The original wellside echo train signal was inverted using the ADMM-based T1T2 two-dimensional relaxation spectrum algorithm to obtain the original NMR spectrum.
7. The method according to claim 1, characterized in that, The inversion parameters for inverting the wellside echo train signal are the same as the inversion parameters for inverting the original wellside echo train signal.
8. A component elimination device for NMR spectra, characterized in that, include: The inversion unit is used to acquire the original echo train signal from the well side and invert the original echo train signal from the well side to obtain the original NMR spectrum. A mask generation unit is used to determine the component elimination region in the original NMR spectrum and generate a mask spectrum based on the component elimination region. A component elimination unit is used to obtain the NMR spectrum at the i-th iteration, where the initial value of i is 1, and when i is 1, the NMR spectrum at the i-th iteration is the original NMR spectrum; The component elimination unit is used to generate the peak signal echo train at the i-th iteration based on the mask spectrum and the NMR spectrum at the i-th iteration. The component elimination unit is used to subtract the original wellside echo train signal from the peak signal echo train to obtain the wellside echo train signal after the i-th component elimination, and to invert the wellside echo train signal to obtain a new NMR spectrum. The component elimination unit is used to determine whether the iteration stopping condition is met based on the new NMR spectrum; The component elimination unit is used to use the new NMR spectrum as the NMR spectrum of the (i+1)th iteration when it is determined that the iteration stopping condition is not met. The component elimination unit is also used to increment i by 1 and reacquire the NMR spectrum at the i-th iteration until the iteration stop condition is met. The new NMR spectrum at the iteration stop condition is then used as the optimal NMR spectrum corresponding to the original echo train signal on the well side.
9. An electronic device, characterized in that, include: A memory, a processor, and a transceiver are sequentially connected in communication, wherein the memory is used to store computer programs, the transceiver is used to send and receive messages, and the processor is used to read the computer programs and execute the component elimination method of NMR spectrum as described in any one of claims 1 to 7.
10. A computer program product containing instructions, characterized in that, When the instructions are executed on a computer, the computer performs the component elimination method for the NMR spectrum as described in any one of claims 1 to 7.