Deep coal bed gas containing heterogeneity detection method, storage medium and equipment

Abstract

The invention discloses a deep coal bed gas containing heterogeneity detection method, a storage medium and equipment. The method comprises the following steps: 1, acquiring post-stack seismic data of a corresponding coal bed gas work area; 2, according to the post-stack seismic data, obtaining a seismic interpretation horizon of a coal seam, and marking the seismic interpretation horizon as T; 3, extracting a plurality of position pairs of post-stack seismic data to obtain a plurality of seismic traces; 4, performing time-frequency analysis on the extracted seismic traces by adopting synchronous extrusion S transformation to obtain a time-frequency distribution diagram; according to the method, the coal seam seismic data is analyzed through synchronous extrusion S transformation, compared with a traditional time-frequency analysis method, the obtained time-frequency analysis result has higher time-frequency resolution and better time-frequency energy focusing performance, in the application of actual seismic data, instantaneous spectrum anomaly characteristics such as high-frequency attenuation related to deep coal reservoirs can be effectively detected, and the method has the advantages of being high in accuracy and high in reliability. The prediction precision of the deep coal reservoir is improved, and the gas-bearing heterogeneity of the deep coal reservoir can be accurately described.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration and development technology, specifically to a method, storage medium, and equipment for detecting the heterogeneity of gas content in deep coalbed methane. Background Technology

[0002] Coalbed methane (CBM) is a clean energy source found in unconventional oil and gas reservoirs. my country possesses abundant CBM resources, but the overall exploration and development level, as well as the understanding of CBM enrichment mechanisms and key factors controlling production capacity, remain low. Domestic CBM resource evaluation targets are mostly limited to strata shallower than 2000m. As domestic unconventional exploration shifts from shallow to deep burial depths, it is necessary to strengthen research on deep CBM. Existing deep CBM development practices often encounter the problem that production wells at different locations within the same coal reservoir can exhibit significant differences in production capacity, indicating strong heterogeneity in reservoir gas content across the plane. Predicting these local variations before drilling necessitates the emergence and development of targeted seismic prediction technologies for deep CBM reservoirs.

[0003] In the prior art, a Chinese patent with publication number CN103412326A discloses a method and system for predicting coalbed methane using the inversion of elastic modulus parameters. This method, based on pre-stack seismic data, utilizes the Zoeppritz equations' approximation of the elastic modulus to simultaneously invert the relative changes in the Lamé constant, shear modulus, and density. Coalbed methane prediction is then performed based on the inversion results, allowing for the evaluation of reservoir differences at different lateral locations. However, in practical applications, especially when evaluating deep reservoirs, this method requires seismic data with a wide incident angle and is not suitable for older data acquired by some small-offset observation systems.

[0004] In conventional oil and gas exploration and development, seismic waves undergo energy attenuation after passing through oil and gas-bearing reservoirs. This attenuation is characterized by faster attenuation of high-frequency energy and slower attenuation of low-frequency energy. This anomaly can be used to indicate the enrichment of oil and gas in the reservoir. Unlike conventional oil and gas, coalbed methane exists in coal seams in two forms: free gas and adsorbed gas. Deep coal seams are controlled by both temperature and pressure, and a considerable amount of free gas is still preserved within the coal seam traps. Therefore, the prediction mechanism for conventional oil and gas can also be applied here.

[0005] People typically use various computational tools to perform time-frequency analysis on post-stack seismic data. The resulting time-frequency plots reflect the changes in frequency components over time and can detect the existence of the aforementioned high-frequency attenuation anomalies. Several commonly used time-frequency analysis tools, such as the S-transform (ST), Short-Time Fourier Transform (STFT), and Continuous Wavelet Transform (CWT), suffer from insufficient time-frequency resolution. These tools generally use specific types of wavelet mother functions and estimate the time-frequency energy of the signal within the effective region of these functions. This results in the time-frequency energy obtained at a given moment always diverging within a certain time and frequency range near the true instantaneous frequency of the signal. Therefore, the instantaneous frequency energy distribution obtained by conventional time-frequency transforms is ambiguous, containing spurious frequency components, which can lead to incorrect interpretations and thus hinder reservoir gas-bearing analysis. For reservoir prediction of deep coalbed methane, especially for the analysis of coal seam gas heterogeneity, high time-frequency resolution time-frequency analysis tools are urgently needed. Summary of the Invention

[0006] The purpose of this invention is to provide a method, storage medium, and equipment for detecting the gas heterogeneity of deep coalbed methane, aiming to improve the problems mentioned in the background art.

[0007] This invention is implemented as follows:

[0008] According to one aspect of the present invention, the present invention provides a method for detecting the gas-bearing heterogeneity of deep coalbed methane, including...

[0009] Step 1: Obtain post-stack seismic data for the corresponding coalbed methane work area;

[0010] Step 2: Based on the post-stack seismic data, obtain the seismic interpretation horizon of the coal seam and mark it as T;

[0011] Step 3: Extract post-stack seismic data from several locations to obtain several seismic traces;

[0012] Step 4: Perform time-frequency analysis on the extracted seismic traces using synchronous compression S-transform to obtain a time-frequency distribution map;

[0013] Step 5: Analyze the time-frequency distribution results below the time depth corresponding to the seismic interpretation layer T on each seismic trace, and obtain the gas content differences of the coal seam under study at different locations in the work area.

[0014] Preferably, in step four, the seismic signal is synchronously squeezed during S-transformation. The S-transform in the time domain is defined as b represents the time of the time-frequency transformation, and f represents the frequency.

[0015] Preferably, according to Parseval's theorem, its frequency domain expression is:

[0016]

[0017] Preferably, among which It is the Fourier transform of x(t). yes Fourier transform.

[0018] Preferably, because There is a support range within the frequency domain, ST x (f, b) exhibits energy divergence compared to the true time-frequency distribution of the signal.

[0019] Preferably, instantaneous frequency needs to be utilized. The diffused energy is squeezed back to the corresponding true instantaneous frequency.

[0020] Preferred, in

[0021] Preferably, equation (3) allows the extraction of the signal's true frequency at time b from information at any time-frequency point (f, b). This allows the energy of (f, b) to be "rearranged and squeezed" to At this point, the time-frequency distribution map is obtained.

[0022] Preferably, the energy is rearranged and squeezed in the time-frequency domain to obtain a synchronous squeezed S-transform.

[0023]

[0024] Where δ is the unit impulse function, according to This yields the time-frequency distribution diagram.

[0025] Preferably, the analysis of the time-frequency distribution results below the time depth corresponding to the seismic interpretation layer T in step five is to detect the high-frequency attenuation phenomenon below the coal seam location in each seismic trace. The location of the seismic trace with large high-frequency attenuation corresponds to the favorable gas-bearing zone of coalbed methane.

[0026] According to a second aspect of the present invention, the present invention provides a computer-readable storage medium storing computer program instructions, wherein the computer program instructions, when executed by a processor, are used to implement the steps of the above-described method for detecting the gas-bearing heterogeneity of deep coalbed methane.

[0027] According to a third aspect of the present invention, the present invention provides an electronic device, including a memory and a processor, and computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, complete the steps of the above-described method for detecting the heterogeneity of gas content in deep coalbed methane.

[0028] Compared with existing technologies, the beneficial effects of this invention are: by analyzing coal seam seismic data through synchronous compression S-transform, compared with traditional time-frequency analysis methods such as S-transform and short-time Fourier transform, the obtained time-frequency analysis results have higher time-frequency resolution and better time-frequency energy focusing. In the application of actual seismic data, it can effectively detect instantaneous spectral anomalies such as "high-frequency attenuation" related to deep coal reservoirs, improve the accuracy of deep coal reservoir prediction, and help to accurately characterize the gas-bearing heterogeneity of deep coal reservoirs. Attached Figure Description

[0029] Figure 1 A flowchart of a method for detecting gas heterogeneity in deep coalbed methane;

[0030] Figure 2 Inversion diagram of the thickness of coal seam in section 1 of Taiyuan Formation;

[0031] Figure 3 Post-stack seismic data profiles of the well points to be studied;

[0032] Figure 4 The study investigated the time-frequency diagrams of conventional S-transform and synchronous compression S-transform of the seismic traces at the location. Detailed Implementation

[0033] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0034] The following description, in conjunction with the accompanying drawings and specific embodiments, provides further details:

[0035] Example 1

[0036] This invention provides a method for detecting the heterogeneity of gas content in deep coalbed methane, comprising the following steps:

[0037] Acquire post-stack seismic data for the coalbed methane working area under study;

[0038] Obtain the seismic interpretation horizon of the coal seam under study on the post-stack seismic data, denoted as T;

[0039] Here, the seismic interpretation horizons are obtained through well-seismic calibration and horizon tracking.

[0040] (3) Extract post-stack seismic data from several locations to be studied to obtain several seismic traces;

[0041] (4) The time-frequency distribution map is obtained by performing time-frequency analysis on the extracted seismic traces using synchronous compression S-transform;

[0042] (5) Analyze the time-frequency distribution results below the time depth corresponding to the seismic interpretation layer T on each seismic trace, and obtain the gas content difference of the coal seam to be studied at different locations in the work area.

[0043] Here, the synchronous extrusion S-transformation in step (4) includes the following steps:

[0044] Step a: Seismic signal The S-transform in the time domain is defined as

[0045]

[0046] In the formula, b represents the time of the time-frequency transformation, and f is the frequency. According to Parseval's theorem, its frequency domain expression is:

[0047]

[0048] in It is the Fourier transform of x(t). yes Fourier transform.

[0049] because In the frequency domain, there is always a certain support range, which means that the time-frequency distribution ST x (f, b) exhibits energy divergence compared to the true time-frequency distribution of the signal. To obtain a more accurate and localized time-frequency distribution, the diffused energy needs to be squeezed back to the corresponding true instantaneous frequency.

[0050] Step b: Calculate the instantaneous frequency

[0051]

[0052] in

[0053]

[0054] The significance of equation (3) lies in the ability to extract the true frequency of the signal at time b using information from any time-frequency point (f, b). This allows the energy of (f, b) to be "rearranged and squeezed" to At this point, a sharpened time-frequency distribution map that reflects the true physical characteristics of the signal is obtained.

[0055] Step c: Rearrange and squeeze the energy in the time-frequency domain to obtain the synchronous squeezed S-transform;

[0056]

[0057] Where δ is the unit impulse function, according to Then you can get the time-frequency distribution map.

[0058] Here, the analysis of the time-frequency distribution results below the time depth corresponding to the seismic interpretation layer T in step five is to detect the high-frequency attenuation phenomenon below the coal seam location in each seismic trace. The location of the seismic trace with large high-frequency attenuation corresponds to the favorable gas-bearing zone of coalbed methane.

[0059] Specifically, this embodiment uses actual data from a work area in the Ordos Basin to verify the effectiveness of the method. Deep coal seams are more conducive to desorption under high temperatures. Core sampling shows that the No. 8 coal seam in the deep section of the Taiyuan Formation 1 still retains 34% free gas content. Figure 2 This is a coal seam thickness map obtained using sparse pulse inversion. Points A and B in the map are two old wells in the He 1 section of the Xiashihezi Formation, designed to be used for production by returning to the deep No. 8 coal seam of the Taiyuan Formation 1 section. Figure 2 The inversion results show that the No. 8 coal seam in the deep parts of wells A and B has almost the same thickness. Structurally, well A is located in the thick core of the coal seam, while well B is located near the transition zone where the coal seam thins. Before development, it is necessary to understand whether this structural difference has a controlling effect on the gas content of the coal reservoir, so as to provide a basis for the design of reservoir fracturing and stimulation. Figure 3 This is a post-stack seismic data volume containing data from wells under investigation. The seismic traces corresponding to wells A and B are marked. The red line represents the interpretation horizon T9b corresponding to the deep No. 8 coal seam. Due to the large difference in wave impedance between the coal seam and the surrounding rock, T9b is a set of strong reflection axes. Time-frequency distribution maps were obtained by performing time-frequency analysis on the seismic traces corresponding to wells A and B using conventional S-transform and synchronous compression S-transform, as shown in the figure. Figure 4 It can be seen that the synchronous extrusion S-transformation ( Figure 4 c. Figure 4 d) The time-frequency analysis results obtained are better than those obtained by the S-transform ( Figure 4 a, Figure 4 b) It has higher time-frequency resolution and better time-frequency energy focusing. Below 1510ms, the location is below the deep No. 8 coal seam. In this time-frequency zone, well A has a narrower seismic bandwidth and lower high-frequency components compared to well B. Figure 4 c. Figure 4 (Within the white box in d) It was predicted that the deep No. 8 coal seam in Well A, located in the thick core, would have better gas content. In subsequent production, the target section of Well A showed 65% total hydrocarbons, while the target section of Well B showed 20% total hydrocarbons. Well A's daily gas production was 26,000 cubic meters, and Well B's daily gas production was 8,600 cubic meters. The predicted results were consistent with the drilling results. In subsequent production, fracturing was intensified in the deep coal seam of Well B.

[0060] Example 2

[0061] An embodiment of the storage medium of the present invention stores program code, which, when executed by a processor, implements the method for detecting the gas heterogeneity of deep coalbed methane as described in Embodiment 1 above.

[0062] Example 3

[0063] An embodiment of the electronic device of the present invention includes a memory and a processor. The memory stores program code that can run on the processor. When the program code is executed by the processor, the method for detecting the gas content heterogeneity of deep coalbed methane as described in Embodiment 1 above is implemented.

[0064] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various modifications and variations. 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 detecting the heterogeneity of gas content in deep coalbed methane, characterized in that, include Step 1: Obtain post-stack seismic data for the corresponding coalbed methane work area; Step 2: Based on the post-stack seismic data, obtain the seismic interpretation horizon of the coal seam and mark it as T; Step 3: Extract post-stack seismic data from several locations to obtain several seismic traces; Step 4: Perform time-frequency analysis on the extracted seismic traces using synchronous compression S-transform to obtain a time-frequency distribution map; Step 5: Analyze the time-frequency distribution results below the time depth corresponding to the seismic interpretation layer T on each seismic trace, and obtain the gas content differences of the coal seam under study at different locations in the work area.

2. The method for detecting the heterogeneity of gas content in deep coalbed methane according to claim 1, characterized in that, Seismic signals in the synchronous compression S-transformation in step four The S-transform in the time domain is defined as b represents the time of the time-frequency transformation, and f represents the frequency.

3. The method for detecting the heterogeneity of gas content in deep coalbed methane according to claim 2, characterized in that, According to Parseval's theorem, its frequency domain expression is:

4. The method for detecting the heterogeneity of gas content in deep coalbed methane according to claim 3, characterized in that, in It is the Fourier transform of x(t). yes Fourier transform.

5. The method for detecting the heterogeneity of gas content in deep coalbed methane according to claim 4, characterized in that, in 6. The method for detecting the heterogeneity of gas content in deep coalbed methane according to claim 5, characterized in that, Equation (3) allows us to extract the true frequency of the signal at time b using information from any time-frequency point (f, b). This allows the energy of (f, b) to be "rearranged and compressed" to At this point, the time-frequency distribution map is obtained.

7. The method for detecting the heterogeneity of gas content in deep coalbed methane as described in claim 6, characterized in that, By rearranging and squeezing energy in the time-frequency domain, a synchronous squeezing S-transform is obtained. Where is the unit impulse function, according to This yields the time-frequency distribution diagram.

8. The method for detecting the heterogeneity of gas content in deep coalbed methane according to claim 7, characterized in that, Step five describes analyzing the time-frequency distribution results below the time depth corresponding to the seismic interpretation layer T on each seismic trace. This involves detecting the high-frequency attenuation phenomenon below the coal seam location on each seismic trace. Seismic traces with large high-frequency attenuation correspond to favorable gas-bearing zones in coalbed methane.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, wherein the computer program instructions, when executed by a processor, are used to implement the steps of the method for detecting the gas-bearing heterogeneity of deep coalbed methane according to any one of claims 1-8.

10. An electronic device, characterized in that, The method includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, which, when executed by the processor, complete the steps of the method for detecting the gas-bearing heterogeneity of deep coalbed methane as described in any one of claims 1-8.

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