Reservoir Oil and Gas Content Analysis Method, Device, Storage Medium and Electronic Equipment

Abstract

This application relates to the technical field of oil exploration and development, and specifically relates to a method, device and electronic equipment for analyzing oil and gas in a reservoir. The method includes: obtaining post-stack seismic data of a target reservoir and preprocessing the post-stack seismic data; obtaining a plurality of intrinsic mode functions according to the preprocessed post-stack seismic data; determining the pseudo energy entropy corresponding to each of the intrinsic mode functions; analyzing the pseudo energy entropy to obtain the oil and gas distribution of the target reservoir. By preprocessing the post-stack seismic data of the target area, the accuracy of the data is ensured. Then, a plurality of intrinsic mode functions are obtained therefrom, and the pseudo energy entropy corresponding to each intrinsic mode function is determined, so as to ensure that the oil and gas distribution of the target reservoir can be accurately analyzed according to the pseudo energy entropy. The accuracy of seismic oil and gas detection in thin sandstone reservoirs is improved, thereby providing reliable information for well placement and reducing the risk of oil and gas drilling.

Description

Technical Field

[0001] The present application relates to the technical field of oil and gas exploration and development, and particularly to a method, device, storage medium and electronic device for analyzing oil and gas in a reservoir. Background Art

[0002] The progress of seismic technology has greatly promoted the development of oil and gas exploration and development technology, and is one of the core technologies that currently reduce the risks of oil and gas exploration and development. Seismic signals not only contain the structural information of underground geology, but also contain richer reservoir and oil and gas information. At present, the post-stack oil and gas detection technology for reservoirs is one of the commonly used technologies in reservoir description and has great application value.

[0003] Currently, time-frequency analysis methods are often used to analyze seismic signals. The main methods of time-frequency analysis include short-time Fourier transform, continuous wavelet transform, Wigner-Ville distribution transform, S transform, and Hilbert-Huang transform with eigenfunctions as the core. Among them, the time window length of the short-time Fourier transform is fixed, and the time and frequency resolutions cannot be adjusted after the time window length is determined, resulting in inaccurate calculation results. The continuous wavelet transform overcomes the limitation of the fixed time window of the short-time Fourier transform and has multi-resolution characteristics, and the signal feature characterization effect is good. However, affected by the Heisenberg principle, its time-frequency resolution is limited, and it is also prone to inaccurate calculation results. Although the Wigner-Ville distribution transform method can well characterize the signal of a single frequency component in the time-frequency domain, complex signals will produce serious cross-interference, reducing the accuracy of the local characteristics of the time-frequency analysis of the signal. Summary of the Invention

[0004] In view of the above problems, the present application provides a method, device, storage medium and electronic device for analyzing oil and gas in a reservoir.

[0005] In a first aspect, the present application provides a method for analyzing oil and gas in a reservoir, the method comprising:

[0006] Obtaining post-stack seismic data of a target reservoir and preprocessing the post-stack seismic data;

[0007] Obtaining a plurality of intrinsic mode functions according to the preprocessed post-stack seismic data;

[0008] Determining the quasi-energy entropy corresponding to each of the intrinsic mode functions;

[0009] Analyzing the quasi-energy entropy to obtain the oil and gas distribution of the target reservoir.

[0010] In the above implementation process, by obtaining the post-stack seismic data of the target area and preprocessing the post-stack seismic data, the accuracy of the data is ensured. Then, multiple intrinsic mode functions are obtained based on the preprocessed post-stack seismic data, thereby avoiding inaccuracies caused by directly processing the post-stack seismic data. Next, the pseudo energy entropy corresponding to each intrinsic mode function is determined to ensure that the oil and gas distribution of the target reservoir can be analyzed more accurately based on the pseudo energy entropy.

[0011] According to an embodiment of the present application, optionally, in the above reservoir oil and gas analysis method, the preprocessing of the post-stack seismic data includes:

[0012] Resampling the post-stack seismic data.

[0013] In the above implementation process, resampling the post-stack seismic data can increase the resampling rate, making the post-stack seismic data more accurate.

[0014] According to an embodiment of the present application, optionally, in the above reservoir oil and gas analysis method, the obtaining of multiple intrinsic mode functions based on the preprocessed post-stack seismic data includes:

[0015] Adding a preset white noise to the preprocessed post-stack seismic data to obtain multiple noisy signals, and generating a set of noisy signals;

[0016] Performing empirical mode decomposition on the set of noisy signals to determine the initial intrinsic mode functions;

[0017] Determining the final residual based on the initial intrinsic mode functions;

[0018] Determining multiple intrinsic mode functions of the post-stack seismic data based on the final residual.

[0019] In the above implementation process, by introducing white noise to form a noise-assisted signal, and then obtaining the eigenfunction of the post-stack seismic data. That is to say, by adding multiple groups of independent and identically distributed adaptive white noises with finite variance constraints to the post-stack seismic data, a set of noisy signals is obtained. On this basis, the empirical mode decomposition method is applied to obtain the eigenfunction of the post-stack seismic data. This method can further reduce the number of iterations, compress the frequency aliasing region, improve the convergence performance, and has higher resolution ability for different frequency components of non-stationary signals.

[0020] According to an embodiment of the present application, optionally, in the above reservoir oil and gas analysis method, the determining of the pseudo energy entropy corresponding to each intrinsic mode function includes:

[0021] Performing Hilbert transform on each intrinsic mode function to obtain the energy intensity corresponding to each intrinsic mode function;

[0022] Determine the pseudo - energy entropy of each of the intrinsic mode functions according to the energy intensity.

[0023] In the above implementation process, the pseudo - energy entropy can reflect the clutter degree of the signal, and it is very sensitive to the changes of the signal. It can quantitatively describe and amplify the characteristics of the signal, so as to effectively reflect the changes in the oil - gas content of each part of the target reservoir corresponding to each intrinsic mode function.

[0024] According to an embodiment of the present application, optionally, in the above - mentioned reservoir oil - gas analysis method, the analyzing the pseudo - energy entropy to obtain the oil - gas distribution of the target reservoir includes:

[0025] Determine the target pseudo - energy entropy from a plurality of the pseudo - energy entropies according to the oil - gas characteristics of the target reservoir;

[0026] Analyze the oil - gas distribution of the target reservoir according to the target pseudo - energy entropy.

[0027] In the above implementation process, since the pseudo - energy entropy can effectively reflect the changes in the oil - gas content of each part of the target reservoir corresponding to each intrinsic mode function, therefore, analysis can be carried out according to the pseudo - energy entropy, and the oil - gas distribution of the target reservoir can be accurately obtained.

[0028] In a second aspect, the present application provides a reservoir oil - gas analysis device, and the device includes:

[0029] A data acquisition module, configured to acquire post - stack seismic data of a target reservoir and pre - process the post - stack seismic data;

[0030] An intrinsic mode function acquisition module, configured to acquire a plurality of intrinsic mode functions according to the pre - processed post - stack seismic data;

[0031] A pseudo - energy entropy determination module, configured to determine the pseudo - energy entropy corresponding to each of the intrinsic mode functions;

[0032] An oil - gas distribution analysis module, configured to analyze the pseudo - energy entropy to obtain the oil - gas distribution of the target reservoir.

[0033] According to an embodiment of the present application, optionally, in the above - mentioned reservoir oil - gas analysis device, the data acquisition module includes:

[0034] A resampling unit, configured to resample the post - stack seismic data.

[0035] According to an embodiment of the present application, optionally, in the above - mentioned reservoir oil - gas analysis device, the intrinsic mode function acquisition module includes:

[0036] A noise addition processing unit, configured to add preset white noise to the post-stack seismic data after preprocessing to obtain a plurality of noisy signals, and generate a set of noisy signals;

[0037] An initial intrinsic mode function acquisition unit, configured to perform empirical mode decomposition on the set of noisy signals to determine an initial intrinsic mode function;

[0038] A final residual determination unit, configured to determine a final residual according to the initial intrinsic mode function;

[0039] An intrinsic mode function determination unit, configured to determine a plurality of intrinsic mode functions of the post-stack seismic data according to the final residual.

[0040] According to an embodiment of the present application, optionally, in the above reservoir oil and gas analysis device, the pseudo energy entropy determination module includes:

[0041] An energy intensity acquisition unit, configured to perform Hilbert transform on each of the intrinsic mode functions to obtain the energy intensity corresponding to each of the intrinsic mode functions;

[0042] A pseudo energy entropy determination unit, configured to determine the pseudo energy entropy of each of the intrinsic mode functions according to the energy intensity.

[0043] According to an embodiment of the present application, optionally, in the above reservoir oil and gas analysis device, the oil and gas distribution analysis module includes:

[0044] A target pseudo energy entropy determination unit, configured to determine a target pseudo energy entropy from a plurality of the pseudo energy entropies according to the oil and gas characteristics of the target reservoir;

[0045] An oil and gas analysis unit, configured to analyze the oil and gas distribution of the target reservoir according to the target pseudo energy entropy.

[0046] In a third aspect, the present application provides a storage medium, and a computer program stored in the storage medium can be executed by one or more processors and can be used to implement the reservoir oil and gas analysis method as described above.

[0047] In a fourth aspect, the present application provides an electronic device, including a memory and a processor, where a computer program is stored on the memory, and when the computer program is executed by the processor, the above reservoir oil and gas analysis method is executed.

[0048] Compared with the prior art, one or more embodiments in the above solution may have the following advantages or beneficial effects:

[0049] A reservoir oil and gas content analysis method, device, storage medium and electronic device provided by the present application. The reservoir oil and gas content analysis method includes: obtaining post-stack seismic data of a target reservoir and preprocessing the post-stack seismic data; obtaining a plurality of intrinsic mode functions according to the preprocessed post-stack seismic data; determining the pseudo energy entropy corresponding to each intrinsic mode function; analyzing the pseudo energy entropy to obtain the oil and gas distribution of the target reservoir. This method ensures the accuracy of data by obtaining the post-stack seismic data of the target area and preprocessing the post-stack seismic data. Then, a plurality of intrinsic mode functions are obtained according to the preprocessed post-stack seismic data, thereby avoiding inaccuracies caused by directly processing the post-stack seismic data. Furthermore, the pseudo energy entropy corresponding to each intrinsic mode function is determined to ensure that the oil and gas distribution of the target reservoir can be analyzed more accurately based on the pseudo energy entropy. In addition, this method can improve the accuracy of seismic oil and gas detection in thin sandstone reservoirs without well information constraints, provide reliable information for well placement, and reduce the risk of oil and gas drilling. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Hereinafter, the present application will be described in more detail based on embodiments with reference to the drawings.

[0051] Figure 1 It is a schematic flowchart of a reservoir oil and gas content analysis method provided by Embodiment 1 of the present application.

[0052] Figure 2 It is another schematic flowchart of a reservoir oil and gas content analysis method provided by Embodiment 7 of the present application.

[0053] Figure 3 It is an original seismic reflection profile of a target reservoir provided by Embodiment 7 of the present application.

[0054] Figure 4 It is a corresponding spectral feature diagram of seismic reflection data provided by Embodiment 7 of the present application.

[0055] Figure 5 It is a schematic diagram of the oil and gas content analysis result of the energy entropy directly obtained by empirical mode decomposition provided by Embodiment 7 of the present application.

[0056] Figure 6 It is a schematic diagram of the reservoir oil and gas content analysis result provided by Embodiment 7 of the present application.

[0057] Figure 7 It is a schematic structural diagram of a reservoir oil and gas content analysis device provided by Embodiment 8 of the present application.

[0058] Figure 8 It is a connection block diagram of an electronic device provided by Embodiment 10 of the present application.

[0059] In the accompanying drawings, like reference numerals are used for like components, and the drawings are not drawn to actual scale. Detailed implementation manners

[0060] The following will describe in detail the implementation manners of the present application in conjunction with the accompanying drawings and embodiments, so as to fully understand how the present application uses technical means to solve technical problems and achieve the implementation process of corresponding technical effects and implement accordingly. Each feature in the embodiments of the present application and the embodiments can be combined with each other on the premise of not conflicting, and the formed technical solutions are all within the protection scope of the present application.

[0061] Example 1

[0062] Please refer to Figure 1 , Figure 1 , which is a schematic flowchart of a reservoir oil and gas content analysis method provided in Embodiment 1 of the present application. The present application provides a reservoir oil and gas content analysis method that can be applied to electronic devices such as mobile phones, computers, or tablet computers. The method includes the following steps:

[0063] Step S110: Obtain the post-stack seismic data of the target reservoir and preprocess the post-stack seismic data.

[0064] The strata have a layered structure. When seismic waves propagate underground and encounter a reflection interface, reflection and transmission phenomena will occur, forming multiple waves. In addition, there are surface waves and random noise propagating along the ground in seismic waves. Eliminating the noise in the seismic data collected in the field is one of the main tasks of seismic data processing. Suppressing multiple waves, especially interlayer multiple waves, has always been a worldwide problem in seismic data processing. In the seismic data processing stage, after processing through static and dynamic correction, horizontal stacking, migration processing, and some noise removal methods, the post-stack seismic data is obtained for seismic interpreters to analyze and interpret. The post-stack seismic data has a relatively high signal-to-noise ratio and a small data volume. Therefore, obtaining the post-stack seismic data of the target reservoir can ensure the accuracy of reservoir oil and gas content analysis. Although the signal-to-noise ratio of the post-stack seismic data is relatively high, there is still a certain amount of noise in the actual post-stack seismic data. Therefore, the post-stack seismic data can be preprocessed to remove the noise and ensure the accuracy of reservoir oil and gas content analysis using the post-stack seismic data. Among them, when obtaining the post-stack seismic data of the target reservoir, it can be obtained in real time through seismic data acquisition, or it can be obtained through historical seismic data.

[0065] Step S120: Obtain a plurality of intrinsic mode functions according to the preprocessed post-stack seismic data.

[0066] The empirical mode decomposition method can be used to obtain the intrinsic mode function. In the time-frequency analysis of conventional seismic signals, non-linear and non-stationary seismic signals cannot meet the generalized integrability condition in the Fourier transform, resulting in signal energy leakage; while in wavelet transform, due to signal energy leakage at the edges of the frequency domain part, serious aliasing occurs between frequency bands, and the analysis characteristics are determined by the wavelet basis, without good self-adaptability. The intrinsic mode function method can improve the above problems and is especially suitable for the analysis and processing of non-linear and non-stationary signals. The intrinsic mode function of a signal characterizes the inherent vibration mode of the signal. Therefore, it can be considered that any signal is composed of several intrinsic mode functions, and at any time, a signal can contain several intrinsic mode functions. That is to say, the intrinsic mode function method of a signal is to decompose the original signal into a finite number of intrinsic mode functions, and each decomposed intrinsic mode function contains the local characteristic signals of different time scales of the original signal, with good self-applicability.

[0067] An intrinsic mode function of a signal must satisfy the following two conditions: First, within the entire time range of the function, the number of local extreme points and zero-crossing points must be equal, or at most differ by one. Second, at any time point, the average of the envelopes of the local maximum (upper envelope line) and the local minimum (lower envelope line) must be zero, that is, the upper and lower envelope lines are locally symmetric with respect to the time axis.

[0068] The first condition is obvious and is similar to the narrowband requirement of traditional stationary Gaussian signals. For the second condition, the classical global requirement is modified to a local requirement, so that the instantaneous frequency is no longer affected by the unnecessary fluctuations formed by asymmetric waveforms.

[0069] According to the definition of the intrinsic mode function, each vibration period of the intrinsic mode function defined by the zero-crossing point has only one vibration mode without other complex odd waves; an intrinsic mode function is not restricted to be a narrowband signal and can be frequency and amplitude modulation, and can also be non-steady-state; signals modulated by single frequency or single amplitude can also become intrinsic mode functions.

[0070] Step S130: Determine the pseudo energy entropy corresponding to each intrinsic mode function.

[0071] The pseudo energy entropy can reflect the clutter degree of the signal, and the pseudo energy entropy is very sensitive to the changes of the signal, can quantitatively describe and amplify the characteristics of the signal, so as to effectively reflect the changes of the oil and gas content in each part of the target reservoir corresponding to each intrinsic mode function.

[0072] When obtaining the pseudo energy entropy, it can be obtained through the pseudo energy entropy function.

[0073] Step S140: Analyze the pseudo energy entropy to obtain the oil and gas distribution in the target reservoir.

[0074] Since the pseudo energy entropy can effectively reflect the change of the oil and gas content in each part of the target reservoir corresponding to each intrinsic mode function, therefore, it can be analyzed according to the pseudo energy entropy to obtain the oil and gas distribution in the target reservoir.

[0075] By obtaining the post-stack seismic data of the target area and preprocessing the post-stack seismic data to ensure the accuracy of the data. Then, multiple intrinsic mode functions are obtained according to the preprocessed post-stack seismic data, thus avoiding the inaccuracy caused by directly processing the post-stack seismic data. Then, the pseudo energy entropy corresponding to each intrinsic mode function is determined to ensure that the oil and gas distribution in the target reservoir can be analyzed more accurately according to the pseudo energy entropy.

[0076] Example 2

[0077] On the basis of Embodiment 1, this embodiment illustrates the method in Embodiment 1 through a specific implementation case.

[0078] The method for analyzing the oil and gas in the reservoir includes the following steps:

[0079] Obtain the post-stack seismic data of the target reservoir and preprocess the post-stack seismic data;

[0080] Obtain multiple intrinsic mode functions according to the preprocessed post-stack seismic data;

[0081] Determine the pseudo energy entropy corresponding to each intrinsic mode function;

[0082] Analyze the pseudo energy entropy to obtain the oil and gas distribution in the target reservoir.

[0083] Among them, preprocessing the post-stack seismic data includes: resampling the post-stack seismic data.

[0084] Obtaining the post-stack seismic data of the target reservoir and preprocessing the post-stack seismic data can also include the following methods.

[0085] First, the quality of the obtained post-stack seismic data can be evaluated, and then data filtering processing can be carried out according to the evaluation results.

[0086] When performing quality evaluation, it can be evaluated based on the signal-to-noise ratio and spectral analysis results to determine the effective seismic frequency band range of the target reservoir, so as to obtain the preprocessed post-stack seismic data, so as to ensure that the oil and gas in the target reservoir can be accurately analyzed according to the post-stack seismic data, provide reliable information for oil and gas drilling deployment, and reduce the risk of oil and gas drilling at the same time.

[0087] Specifically, first, it is necessary to determine the geological sedimentary characteristics of the target reservoir and the petrophysical characteristics of the target reservoir, etc. Then, based on the above analysis results, a feasibility analysis is carried out on the post-stack seismic data in the work area to determine the effective seismic frequency band range of the target reservoir, so as to ensure that the oil and gas analysis method for this reservoir can be analyzed within the effective frequency band, and then ensure the accuracy of the analysis results.

[0088] In addition, for the preprocessing of the post-stack seismic data, resampling can also be performed on the post-stack seismic data to increase the resampling rate and make the post-stack seismic data more accurate. Specifically, resampling can be carried out in the way of encrypted resampling, so as to ensure that the resampling rate is increased by at least one time, and then improve the accuracy of the post-stack seismic data.

[0089] Example 3

[0090] On the basis of Embodiment 1, this embodiment illustrates the method in Embodiment 1 through specific implementation cases.

[0091] The oil and gas analysis method for the reservoir includes:

[0092] Obtain the post-stack seismic data of the target reservoir and preprocess the post-stack seismic data;

[0093] Obtain a plurality of intrinsic mode functions according to the preprocessed post-stack seismic data;

[0094] Determine the quasi-energy entropy corresponding to each intrinsic mode function;

[0095] Analyze the quasi-energy entropy to obtain the oil and gas distribution of the target reservoir.

[0096] Among them, obtaining a plurality of intrinsic mode functions according to the preprocessed post-stack seismic data includes:

[0097] Add preset white noise to the preprocessed post-stack seismic data to obtain a plurality of noisy signals and generate a noisy signal set;

[0098] Perform empirical mode decomposition according to the noisy signal set to determine the initial intrinsic mode functions;

[0099] Determine the final residual according to the initial intrinsic mode functions;

[0100] Determine a plurality of intrinsic mode functions of the post-stack seismic data according to the final residual.

[0101] At any time, a signal can contain several intrinsic mode functions. That is to say, the intrinsic mode function method of the signal is to decompose the original signal into a finite number of intrinsic mode functions. Each of the decomposed intrinsic mode functions contains the local characteristic signals of different time scales of the original signal and has good self-applicability.

[0102] In step S120 of obtaining multiple intrinsic mode functions based on the preprocessed post-stack seismic data as described above, the following process may further be included.

[0103] First, a preset white noise is added to the preprocessed post-stack seismic data to obtain multiple noisy signals, generating a set of noisy signals.

[0104] The preset white noise may be white noise with a normal distribution.

[0105] Then, empirical mode decomposition is performed according to the set of noisy signals to determine the initial intrinsic mode functions.

[0106] Next, the final residual is determined according to the initial intrinsic mode functions.

[0107] Finally, multiple intrinsic mode functions of the post-stack seismic data are determined according to the final residual.

[0108] By introducing white noise to form a noise-assisted signal, and then obtaining the eigenfunctions of the post-stack seismic data. That is to say, by adding multiple groups of independent and identically distributed adaptive white noises with finite variance constraints to the post-stack seismic data, a set of noisy signals is obtained. On this basis, the empirical mode decomposition method (EMD) is applied to obtain the eigenfunctions of the post-stack seismic data. This method can further reduce the number of iterations, compress the frequency aliasing region, improve the convergence performance, and has a higher resolution ability for different frequency components of non-stationary signals.

[0109] Specifically, different white noises may first be added to the to-be-processed post-stack seismic data obtained after preprocessing to obtain multiple noisy signals, generating a set of noisy signals.

[0110] Then, multiple initial first intrinsic mode functions are determined according to each noisy signal in the set of noisy signals. Then, the first intrinsic mode function of the to-be-processed post-stack seismic data is determined according to the multiple initial first intrinsic mode functions.

[0111] Next, the residual amount is determined according to the first intrinsic mode function, and the first intrinsic mode function is used as the operator function.

[0112] The second intrinsic mode function is determined according to the residual amount and the operator function.

[0113] Then, the second intrinsic mode function is used as the new first intrinsic mode function, and the steps of determining the residual amount according to the first intrinsic mode function, using the first intrinsic mode function as the operator function, and determining the second intrinsic mode function according to the residual amount and the current operator function are repeatedly executed until the order of the second intrinsic mode function is greater than or equal to the preset order.

[0114] Finally, the post-stack seismic data to be processed can be expressed as the sum of each order of the obtained intrinsic mode function, i.e., the final residual.

[0115] Example 4

[0116] Based on Embodiment 3, this embodiment illustrates the method in Embodiment 3 through specific implementation cases.

[0117] Take the preprocessed post-stack seismic data as the signal function x(t) to be processed, and add a preset white noise to the signal function x(t) to be processed to obtain multiple noisy signals, as follows:

[0118] x i (t) = x(t) + (-1) I ·ω i (t)

[0119] Among them, x i (t) represents the set of noisy signals, x(t) represents the signal function to be processed, ω i (t) represents Gaussian white noise, i = 0, 1, 2,..., I, and i represents the number of samples in the set.

[0120] Then, perform empirical mode decomposition on each noisy signal in the set of noisy signals to obtain the first-order intrinsic mode function Then calculate the mean of all the first-order intrinsic mode functions as the first-order intrinsic mode function of the signal function x(t) to be processed as follows:

[0121]

[0122] Then, according to this first-order intrinsic mode function calculate the first-order residual, as follows:

[0123]

[0124] Among them, r 1 represents the first-order residual.

[0125] At this time, define the operator E J (·) as the operator function for the signal function x(t) to be processed to obtain the jth-order intrinsic mode function through empirical mode decomposition, and then calculate the second-order intrinsic mode function according to the first-order residual and the operator function as follows:

[0126]

[0127] Among them, represents the second-order intrinsic mode function, E J(·) represents the J-th order operator function, r 1 (t) represents the first-order residual, ε k represents the signal-to-noise ratio corresponding to each intrinsic mode function, k = 1, 2, …, K, where K is the highest order set for obtaining the intrinsic mode functions, ω i (t) represents Gaussian white noise, i = 0, 1, 2, ……, I, and i represents the number of samples in the set.

[0128] For k, k = 1, 2, … K, calculate the k-th order residual successively according to the above steps as follows:

[0129]

[0130] Then, calculate the (k + 1)-th order intrinsic mode function as follows:

[0131]

[0132] Among them, represents the second-order intrinsic mode function, E k (·) represents the k-th order operator function, r k (t) represents the k-th order residual, ε k represents the signal-to-noise ratio corresponding to each intrinsic mode function, k = 1, 2, …, K, and K is the highest order set for obtaining the intrinsic mode functions, ω i (t) represents Gaussian white noise, i = 0, 1, 2, ……, I, and i represents the number of samples in the set.

[0133] Repeat the steps of calculating the k-th order residual and calculating the (k + 1)-th order intrinsic mode function based on the k-th order residual until the k-th order residual cannot be decomposed further or reaches the highest order K of the intrinsic mode functions. Obtain the final residual R(t) as follows:

[0134]

[0135] Among them, R(t) represents the final residual, and x(t) represents the signal function to be processed, represents the k-th order intrinsic mode function, k k = 1, 2, …, K, and K is the highest order set for obtaining the intrinsic mode functions.

[0136] Finally, the signal function x(t) to be processed can be expressed as:

[0137]

[0138] According to the above method, by introducing white noise, a noise-assisted signal is formed. Then, the eigenfunction of the post-stack seismic data is obtained. That is to say, by adding multiple groups of independent and identically distributed adaptive white noise with finite variance constraints to the post-stack seismic data, a set of noisy signals is obtained. On this basis, the empirical mode decomposition method is applied to obtain the eigenfunction of the post-stack seismic data. This method can further reduce the number of iterations, compress the frequency aliasing region, improve the convergence performance, and has higher resolution ability for different frequency components of non-stationary signals.

[0139] Example 5

[0140] On the basis of Embodiment 3, this embodiment illustrates the method in Embodiment 3 through specific implementation cases.

[0141] First, an intrinsic mode function of a signal must satisfy the following two conditions: First, within the entire time range of the function, the number of local extreme points and zero-crossing points must be equal, or at most differ by one. Second, at any time point, the envelopes of the local maximum (upper envelope line) and the local minimum (lower envelope line) must average to zero, that is, the upper and lower envelope lines are locally symmetric with respect to the time axis.

[0142] The first condition is obvious and is similar to the narrowband requirement of traditional stationary Gaussian signals. For the second condition, the classical global requirement is modified to a local requirement, so that the instantaneous frequency is no longer affected by unnecessary fluctuations formed by asymmetric waveforms.

[0143] According to the definition of the intrinsic mode function, for each vibration period of the intrinsic mode function defined by zero-crossing points, there is only one vibration mode and no other complex odd waves; an intrinsic mode function is not restricted to be a narrowband signal and can be frequency and amplitude modulated, and can also be non-steady; signals modulated by single frequency or single amplitude can also become intrinsic mode functions.

[0144] In the step of performing empirical mode decomposition on the set of noisy signals to determine the initial intrinsic mode functions, the empirical mode decomposition method is as follows:

[0145] Taking the preprocessed post-stack seismic data as the signal function x(t) to be processed, first, determine all local maximum and local minimum points of the signal function x(t) to be processed. Then, use cubic spline functions to fit all local maximums into the upper envelope line e max (t), and fit all local minimums into the lower envelope line e min (t). Calculate the mean value of the upper and lower envelope lines:

[0146] m(t) = [e max (t) + e min (t)] / 2

[0147] Then, subtract the mean value m(t) from the signal function x(t) to be processed to obtain a preliminary intrinsic mode function:

[0148] c i (t) = x(t) - m(t)

[0149] Judge whether c i (t) satisfies the two conditions of the intrinsic function IMF.

[0150] If it does not satisfy, take c i (t) as the new signal function to be processed and loop to execute the above steps.

[0151] If c i (t) can satisfy the two conditions of the intrinsic function IMF, then c i (t) is an intrinsic function IMF of the original signal i , and the remainder r i (t) = x(t) - c i (t). Continue to decompose the remainder r i (t) in a loop. When the remainder r i (t) is less than a pre-determined valve value or is a monotonic function, the decomposition process of the signal function x(t) to be processed ends.

[0152] Finally, the signal function x(t) to be processed can be expressed as:

[0153]

[0154] where c i (t) is the intrinsic function component, r n (t) is the remainder, and the remainder is the trend term of the signal function to be processed.

[0155] Example 6

[0156] Based on Embodiment 1 and Embodiment 4, this embodiment illustrates the method in Embodiment 1 through a specific implementation case.

[0157] The reservoir oil and gas analysis method includes:

[0158] Obtain the post-stack seismic data of the target reservoir and preprocess the post-stack seismic data;

[0159] Obtain multiple intrinsic mode functions according to the preprocessed post-stack seismic data;

[0160] Determine the quasi-energy entropy corresponding to each intrinsic mode function;

[0161] Analyze the pseudo energy entropy to obtain the oil and gas distribution in the target reservoir.

[0162] Among them, the steps to determine the pseudo energy entropy corresponding to each intrinsic mode function include the following process:

[0163] First, perform Hilbert transform on each intrinsic mode function to obtain the energy intensity corresponding to each intrinsic mode function.

[0164] Then, determine the pseudo energy entropy of each intrinsic mode function according to the energy intensity.

[0165] First, the post-stack seismic data after preprocessing is the signal function x(t) to be processed. According to the solution in Embodiment 3, it can be known that the respective intrinsic mode functions have been obtained according to the signal function x(t) to be processed as For each intrinsic mode function Do the Hibert transform as follows:

[0166]

[0167] Among them, And Are conjugate complex number pairs.

[0168] Then the constructed analytic intrinsic mode function can be expressed as:

[0169]

[0170] Among them, E i (t) represents the energy intensity of the i-th intrinsic mode function, Represents the phase.

[0171] According to the above steps, the energy intensity E Of the i-th intrinsic mode function of the signal function x(t) to be processed is calculated. Then the pseudo energy entropy of the intrinsic mode function is defined as S i (t), as follows: i (t), as follows:

[0172] S i (t) = E i (t) · lnE i (t)

[0173] After obtaining the pseudo energy entropy, the pseudo energy entropy can be analyzed to obtain the oil and gas distribution in the target reservoir. Specifically as follows:

[0174] Determine the target pseudo energy entropy from multiple pseudo energy entropies according to the oil and gas characteristics of the target reservoir.

[0175] Analyze the oil and gas distribution in the target reservoir according to the target pseudo energy entropy.

[0176] When determining the target pseudo energy entropy from multiple pseudo energy entropies according to the oil and gas characteristics of the target reservoir, the pseudo energy entropy of the intrinsic mode function sensitive to the oil and gas in the reservoir can be selected as the target pseudo energy entropy based on the oil and gas characteristics of the target reservoir.

[0177] Example 7

[0178] Please refer to Figure 2 , the oil and gas analysis method for this reservoir specifically includes the following process. First, it is necessary to clarify the geological sedimentary characteristics of the target reservoir and the petrophysical characteristics of the reservoir, and conduct a feasibility analysis on the post-stack seismic data in the work area where the target reservoir is located to determine the effective seismic frequency band range of the target reservoir. Then, perform encrypted resampling on the original post-stack seismic data to ensure that the sampling rate of the seismic data does not exceed 1 ms (millisecond) to ensure the accuracy of the post-stack seismic data.

[0179] Based on the post-stack seismic data after encrypted resampling, then apply a robust adaptive method to obtain the post-stack seismic data, that is, a finite number of intrinsic mode functions of the signal function x(t) to be processed Among them, the number of intrinsic mode functions can not exceed 8.

[0180] Then, for each intrinsic mode function of the signal function x(t) to be processed, apply the Hilbert transform to obtain the energy intensity E i (t). Then, obtain the pseudo energy entropy S i of the energy intensity E i (t) of each intrinsic mode function of the signal function to be processed

[0181] Finally, based on the low-frequency oil and gas characteristics of the reservoir containing oil and gas, select the pseudo energy entropy of the intrinsic mode function sensitive to the oil and gas characteristics, analyze the spatial distribution characteristics of the reservoir containing oil and gas, and determine the drilling target of the reservoir containing oil and gas.

[0182] Taking the actual seismic data of a deep-water turbidite sandstone oil reservoir as an example, according to the Figure 2 shown process, conduct an oil and gas analysis on this deep-water turbidite sandstone oil reservoir. First, conduct a feasibility analysis on its post-stack seismic data and implement encrypted resampling of the post-stack seismic data; complete the acquisition of the adaptive intrinsic mode function, the energy intensity of the intrinsic mode function, and the pseudo energy entropy of the energy intensity of the intrinsic mode function of the post-stack seismic data; determine the drilling target of the sandstone reservoir containing oil and gas based on the pseudo energy entropy of the intrinsic mode function sensitive to the oil and gas characteristics, reducing the risk of oil and gas drilling.

[0183] To better illustrate the advantages of the present invention, please refer to Figure 3 , Figure 3This is the original seismic reflection profile of a target reservoir provided in the seventh embodiment of the present application. The water depth of the research target area where this deep-water turbidite sandstone reservoir is located is about 2,000 meters. The turbidite sand bodies in the target reservoir intersect and overlap with complex relationships. Due to the loose structure of the turbidite sandstone, the difference in rock physical characteristics from the surrounding rock is small, making it difficult to accurately describe the reservoir in detail and detect fluids, and the results are inaccurate. In addition, the actual 3D seismic data of the target reservoir has problems such as a narrow effective frequency band and low resolution. Using traditional methods, it is impossible to accurately identify and analyze the presence of oil and gas, and there is a large uncertainty in the identification of oil and gas fluids, which also brings great risks to oilfield development.

[0184] The method for analyzing the oil and gas content of the reservoir includes:

[0185] Obtain the post-stack seismic data of the target reservoir and preprocess the post-stack seismic data;

[0186] Obtain a plurality of intrinsic mode functions based on the preprocessed post-stack seismic data;

[0187] Determine the quasi-energy entropy corresponding to each intrinsic mode function;

[0188] Analyze the quasi-energy entropy to obtain the oil and gas distribution of the target reservoir.

[0189] Among them, when obtaining a plurality of intrinsic mode functions based on the preprocessed post-stack seismic data, obtaining the intrinsic mode functions in the manner as in Embodiment 3 can more accurately obtain the analysis results of the oil and gas content of the reservoir.

[0190] Please refer to Figure 4 , Figure 4 This is a schematic diagram of the corresponding spectral characteristics of seismic reflection data provided in the seventh embodiment of the present application. According to Figure 4 it can be seen that the original 3D post-stack seismic data corresponding to the target reservoir has a narrow effective frequency band and low resolution. The target layer section has the characteristics of a strong reflection seismic wave group. The main frequency of the seismic reflection of the reservoir is about 15 Hz, and the effective frequency bandwidth is about 30 Hz.

[0191] Please refer to Figure 5 and Figure 6 , Figure 5 This is a schematic diagram of the analysis result of the oil and gas content obtained by directly calculating the energy entropy through empirical mode decomposition provided in the seventh embodiment of the present application.

[0192] Figure 5 In the energy entropy oil and gas identification profile obtained by the empirical mode decomposition method in

[0193] Figure 6 , it can be seen that its resolution is not high, and the identification ability of thin reservoirs is not strong, which affects the accuracy of reservoir oil and gas identification and brings difficulties to the deployment of drilling well positions and the formulation of oil reservoir development plans.A schematic diagram of the analysis results of hydrocarbon-bearing reservoirs provided in the seventh embodiment of this application. The results are obtained through the following steps: First, the post-stack seismic data of the target reservoir is acquired and preprocessed. Then, a preset white noise is added to the preprocessed post-stack seismic data to obtain multiple noisy signals, generating a set of noisy signals. Next, empirical mode decomposition is performed on the set of noisy signals to determine the initial intrinsic mode functions. Then, the final residue is determined based on the initial intrinsic mode functions. Finally, multiple intrinsic mode functions of the post-stack seismic data are determined based on the final residue.

[0194] By introducing white noise to form noise-assisted signals, and then obtaining the eigenfunctions of the post-stack seismic data. That is to say, by adding multiple groups of independent and identically distributed adaptive white noises with finite variance constraints to the post-stack seismic data, a set of noisy signals is obtained. On this basis, the empirical mode decomposition method is applied to obtain the eigenfunctions of the post-stack seismic data. This method can further reduce the number of iterations, compress the frequency aliasing region, improve the convergence performance, and has higher resolution ability for different frequency components of non-stationary signals.

[0195] After obtaining the mode functions using this method, the pseudo energy entropy is calculated for analysis to obtain the hydrocarbon-bearing identification profile. Figure 3 Compared with the original seismic reflection profile in Figure 5 and the hydrocarbon-bearing identification profile of energy entropy obtained by using the empirical mode decomposition method in Figure 6 the hydrocarbon-bearing targets of deep-water turbidite sandstones in

[0196] Example 8

[0197] This application also provides a reservoir hydrocarbon-bearing analysis device. Please refer to Figure 7 The reservoir hydrocarbon-bearing analysis device 700 includes:

[0198] A data acquisition module 710, configured to acquire the post-stack seismic data of the target reservoir and preprocess the post-stack seismic data;

[0199] An intrinsic mode function acquisition module 720, configured to obtain multiple intrinsic mode functions according to the preprocessed post-stack seismic data;

[0200] A pseudo energy entropy determination module 730, configured to determine the pseudo energy entropy corresponding to each intrinsic mode function;

[0201] A hydrocarbon-bearing distribution analysis module 740, configured to analyze the pseudo energy entropy to obtain the hydrocarbon-bearing distribution of the target reservoir.

[0202] According to an embodiment of the present application, optionally, in the above reservoir oil and gas analysis device, the data acquisition module includes:

[0203] A resampling unit for resampling the post-stack seismic data.

[0204] Optionally, in the above reservoir oil and gas analysis device 700, the intrinsic mode function acquisition module 720 includes:

[0205] A noise adding processing unit for adding a preset white noise to the preprocessed post-stack seismic data to obtain a plurality of noisy signals and generating a noisy signal set;

[0206] An initial intrinsic mode function acquisition unit for performing empirical mode decomposition on the noisy signal set to determine an initial intrinsic mode function;

[0207] A final residual determination unit for determining a final residual according to the initial intrinsic mode function;

[0208] An intrinsic mode function determination unit for determining a plurality of intrinsic mode functions of the post-stack seismic data according to the final residual.

[0209] Optionally, in the above reservoir oil and gas analysis device 700, the pseudo energy entropy determination module 730 includes:

[0210] An energy intensity acquisition unit for performing Hilbert transform on each intrinsic mode function to obtain the energy intensity corresponding to each intrinsic mode function;

[0211] A pseudo energy entropy determination unit for determining the pseudo energy entropy of each intrinsic mode function according to the energy intensity.

[0212] Optionally, in the above reservoir oil and gas analysis device 700, the oil and gas distribution analysis module 740 includes:

[0213] A target pseudo energy entropy determination unit for determining a target pseudo energy entropy from a plurality of pseudo energy entropies according to the oil and gas characteristics of the target reservoir;

[0214] An oil and gas analysis unit for analyzing the oil and gas distribution of the target reservoir according to the target pseudo energy entropy.

[0215] In summary, the embodiment of the present application discloses a reservoir oil and gas analysis device 700, which includes: a data acquisition module 710 for acquiring post-stack seismic data of a target reservoir and preprocessing the post-stack seismic data; an intrinsic mode function acquisition module 720 for obtaining a plurality of intrinsic mode functions according to the preprocessed post-stack seismic data; a pseudo energy entropy determination module 730 for determining the pseudo energy entropy corresponding to each intrinsic mode function; and an oil and gas distribution analysis module 740 for analyzing the pseudo energy entropy to obtain the oil and gas distribution of the target reservoir. By acquiring the post-stack seismic data of the target area and preprocessing the post-stack seismic data, the accuracy of the data is ensured. Then, a plurality of intrinsic mode functions are obtained according to the preprocessed post-stack seismic data, thereby avoiding inaccuracies caused by directly processing the post-stack seismic data. Next, the pseudo energy entropy corresponding to each intrinsic mode function is determined to ensure that the oil and gas distribution of the target reservoir can be more accurately analyzed based on the pseudo energy entropy. In addition, the device can improve the accuracy of seismic oil and gas detection in thin sandstone reservoirs without well information constraints, provide reliable information for well placement, and reduce the risk of oil and gas drilling.

[0216] Example 9

[0217] This embodiment also provides a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application store, etc., on which a computer program is stored. When the computer program is executed by a processor, the following method steps can be implemented:

[0218] Step S110: Acquire post-stack seismic data of a target reservoir and preprocess the post-stack seismic data;

[0219] Step S120: Obtain a plurality of intrinsic mode functions according to the preprocessed post-stack seismic data;

[0220] Step S130: Determine the pseudo energy entropy corresponding to each of the intrinsic mode functions;

[0221] Step S140: Analyze the pseudo energy entropy to obtain the oil and gas distribution of the target reservoir.

[0222] Optionally, in the above reservoir oil and gas analysis method, the preprocessing of the post-stack seismic data includes:

[0223] Resample the post-stack seismic data.

[0224] In the above implementation process, resampling the post-stack seismic data can increase the resampling rate and make the post-stack seismic data more accurate.

[0225] Optionally, in the above reservoir oil and gas analysis method, the obtaining of multiple intrinsic mode functions based on the preprocessed post-stack seismic data includes:

[0226] Adding a preset white noise to the preprocessed post-stack seismic data to obtain multiple noisy signals and generating a set of noisy signals;

[0227] Performing empirical mode decomposition on the set of noisy signals to determine the initial intrinsic mode functions;

[0228] Determining the final residual based on the initial intrinsic mode functions;

[0229] Determining multiple intrinsic mode functions of the post-stack seismic data based on the final residual.

[0230] Optionally, in the above reservoir oil and gas analysis method, the determining of the pseudo energy entropy corresponding to each of the intrinsic mode functions includes:

[0231] Performing Hilbert transform on each of the intrinsic mode functions to obtain the energy intensity corresponding to each of the intrinsic mode functions;

[0232] Determining the pseudo energy entropy of each of the intrinsic mode functions based on the energy intensity.

[0233] Optionally, in the above reservoir oil and gas analysis method, the analyzing of the pseudo energy entropy to obtain the oil and gas distribution of the target reservoir includes:

[0234] Determining a target pseudo energy entropy from multiple pseudo energy entropies according to the oil and gas characteristics of the target reservoir;

[0235] Analyzing the oil and gas distribution of the target reservoir based on the target pseudo energy entropy.

[0236] For the specific implementation process of the above method steps, reference can be made to the above embodiments, and this embodiment will not be repeated here.

[0237] Example 10

[0238] An embodiment of the present application provides an electronic device, which can be a mobile phone, a computer, a tablet computer, etc., including a memory and a processor. A calculator program is stored on the memory, and when the computer program is executed by the processor, it implements the reservoir oil and gas analysis method in the first embodiment. It can be understood, please refer to Figure 8, the electronic device 800 may further include a processor 801, a memory 802, a multimedia component 803, an input / output (I / O) interface 804, and a communication component 805.

[0239] Among them, the processor 801 is configured to execute all or part of the steps in the reservoir hydrocarbon-bearing analysis method in the first embodiment. The memory 802 is used to store various types of data, which may include, for example, instructions of any application or method in the electronic device, as well as application-related data.

[0240] The processor 801 may be implemented by an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components, and is used to execute the reservoir hydrocarbon-bearing analysis method in the first embodiment above.

[0241] The memory 802 may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic memory, a flash memory, a magnetic disk, or an optical disk.

[0242] The multimedia component 803 may include a screen and an audio component. The screen may be a touch screen. The audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in the memory or transmitted through the communication component. The audio component further includes at least one speaker for outputting audio signals.

[0243] The I / O interface 804 provides an interface between the processor 801 and other interface modules, and the other interface modules may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons.

[0244] The communication component 805 is used for wired or wireless communication between the electronic device 800 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them. Accordingly, the communication component 805 may include: a Wi-Fi module, a Bluetooth module, and an NFC module.

[0245] In summary, a reservoir oil and gas content analysis method, device, storage medium and electronic device provided by the present application. The reservoir oil and gas content analysis method includes: acquiring post-stack seismic data of a target reservoir and preprocessing the post-stack seismic data; acquiring a plurality of intrinsic mode functions according to the preprocessed post-stack seismic data; determining a quasi-energy entropy corresponding to each intrinsic mode function; analyzing the quasi-energy entropy to obtain the oil and gas distribution of the target reservoir. This method ensures the accuracy of the data by acquiring the post-stack seismic data of the target area and preprocessing the post-stack seismic data. Then, a plurality of intrinsic mode functions are acquired according to the preprocessed post-stack seismic data, thereby avoiding inaccuracies caused by directly processing the post-stack seismic data. Furthermore, the quasi-energy entropy corresponding to each intrinsic mode function is determined to ensure that the oil and gas distribution of the target reservoir can be more accurately analyzed based on the quasi-energy entropy. In addition, this method can improve the accuracy of seismic oil and gas detection in thin sandstone reservoirs without well information constraints, provide reliable information for well location deployment, and thus reduce the risk of oil and gas drilling.

[0246] In several embodiments provided by the embodiments of the present application, it should be understood that the disclosed systems and methods can also be implemented in other ways. The system and method embodiments described above are merely illustrative.

[0247] It should be noted that in this article, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.

[0248] Although the embodiments disclosed in this application are as above, the content described is only an embodiment adopted for the convenience of understanding this application and is not intended to limit this application. Any person skilled in the art within the technical field to which this application pertains may make any modifications and changes in the form of implementation and details without departing from the spirit and scope disclosed in this application. However, the scope of patent protection of this application shall still be subject to the scope defined by the appended claims.

Claims

1. A method for analyzing oil and gas in a reservoir, characterized in that, the method includes: Obtain the post-stack seismic data of the target reservoir, and perform encrypted resampling preprocessing on the post-stack seismic data; According to the post-stack seismic data after encrypted resampling preprocessing, add adaptive white noise to obtain multiple noisy signals, and obtain multiple adaptive intrinsic mode functions; Determine the pseudo energy entropy corresponding to each of the adaptive intrinsic mode functions; Analyze the pseudo energy entropy to obtain the oil and gas distribution of the target reservoir; The step of obtaining multiple adaptive intrinsic mode functions according to the post-stack seismic data after encrypted resampling preprocessing includes: Add preset adaptive white noise to the post-stack seismic data after encrypted resampling preprocessing to obtain multiple noisy signals, and generate a set of noisy signals; Perform empirical mode decomposition according to the set of noisy signals to determine the initial intrinsic mode functions; Determine the final residual according to the initial intrinsic mode functions; Determine multiple adaptive intrinsic mode functions of the post-stack seismic data according to the final residual; The step of determining the pseudo energy entropy corresponding to each of the intrinsic mode functions includes: Perform Hilbert transform on each of the intrinsic mode functions to obtain the energy intensity corresponding to each of the adaptive intrinsic mode functions; Determine the pseudo energy entropy of each of the intrinsic mode functions according to the energy intensity; Among them, the step of adding preset adaptive white noise to the post-stack seismic data after encrypted resampling preprocessing to obtain multiple noisy signals and generate a set of noisy signals includes: taking the post-stack seismic data after encrypted resampling preprocessing as the signal function to be processed x(t), and adding preset adaptive white noise to the signal function to be processed x(t) to obtain multiple noisy signals as follows: x i (t) = x(t) + (-1) I ·ω i (t) where x i (t) represents the noisy signal set, x(t) represents the signal function to be processed, ω i (t) represents the adaptive Gaussian white noise, i = 0, 1, 2, ……, I, and i represents the number of samples in the set.

2. The method according to claim 1, characterized in that, the step of analyzing the pseudo energy entropy to obtain the oil and gas distribution of the target reservoir includes: Determine the target pseudo energy entropy from multiple pseudo energy entropies according to the oil and gas characteristics of the target reservoir; Analyze the oil and gas distribution of the target reservoir according to the target pseudo energy entropy.

3. A device for analyzing oil and gas in a reservoir, characterized in that, the device includes: A data acquisition module for acquiring the post-stack seismic data of the target reservoir and performing encrypted resampling preprocessing on the post-stack seismic data; An intrinsic mode function acquisition module for adding adaptive white noise to the post-stack seismic data after encrypted resampling preprocessing to obtain multiple noisy signals and acquiring multiple adaptive intrinsic mode functions; A pseudo energy entropy determination module for determining the pseudo energy entropy corresponding to each of the adaptive intrinsic mode functions; An oil and gas distribution analysis module for analyzing the pseudo energy entropy to obtain the oil and gas distribution of the target reservoir; The intrinsic mode function acquisition module includes: A noise addition adaptive processing unit for adding preset adaptive white noise to the post-stack seismic data after encrypted resampling preprocessing to obtain multiple noisy signals and generating a set of noisy signals; An initial intrinsic mode function acquisition unit for performing empirical mode decomposition according to the set of noisy signals to determine the initial intrinsic mode functions; A final residual determination unit, configured to determine a final residual according to the initial intrinsic mode function; An intrinsic mode function determination unit, configured to determine a plurality of adaptive intrinsic mode functions of the post-stack seismic data according to the final residual; The pseudo energy entropy determination module includes: An energy intensity acquisition unit, configured to perform Hilbert transform on each intrinsic mode function to obtain the energy intensity corresponding to each adaptive intrinsic mode function; A pseudo energy entropy determination unit, configured to determine the pseudo energy entropy of each intrinsic mode function according to the energy intensity; A noise addition processing unit is further configured to use the post-stack seismic data after encrypted resampling preprocessing as a signal function x(t) to be processed, and add a preset adaptive white noise to the signal function x(t) to be processed to obtain a plurality of noisy signals, as follows: x i (t) = x(t) + (-1) I ·ω i (t) where x i (t) represents the noisy signal set, x(t) represents the signal function to be processed, ω i (t) represents the adaptive Gaussian white noise, i = 0, 1, 2, ……, I, and i represents the number of samples in the set.

4. A storage medium, characterized in that the computer program stored in the storage medium, when executed by one or more processors, is used to implement the method according to any one of claims 1-2.

5. An electronic device, characterized in that it includes a memory and a processor, and a computer program is stored on the memory. When the computer program is executed by the processor, the method according to any one of claims 1-2 is executed.

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