Coal seam seismic exploration data analysis method and system

Abstract

The invention is suitable for the technical field of coal seam exploration, and provides a coal seam seismic exploration data analysis method and system, and the method comprises the steps: analyzing the historical seismic exploration data and historical record data of a micro-logging, obtaining the interference data related to the micro-logging, and obtaining the excitation preparation data of the micro-logging, the interference data is used for representing interference of a first target on seismic exploration, and the first target comprises a predictive interference target and / or a dynamic interference target; and determining a first time period when the dynamic interference target passes through an interference range based on the interference data and the excitation position, and determining a future interference time period of the predictive interference target on the micro-logging based on the interference data in a second time period. The data interpretation and analysis difficulty is greatly reduced in the whole interpretation process, so that a powerful geological basis is provided for safe production of mining areas such as large-dip-angle coal seams.

Description

Technical Field

[0001] The present invention belongs to the technical field of coal seam exploration, and in particular relates to a coal seam seismic exploration data analysis method and system. Background Art

[0002] Seismic exploration can provide technical support for the formulation of coal mining designs. Seismic exploration is the artificial excitation of seismic waves underground (or in wells), and the recording of reflected seismic waves from underground by instruments and equipment on the surface or in strata. The obtained seismic records are processed through a series of processes to finally obtain a seismic profile.

[0003] Obtaining geological information of coal seams through seismic exploration is particularly important for mine mining, especially for steeply inclined coal seams. In related technologies, coal seam geological exploration data is analyzed to analyze the distribution of coal seams. However, the analysis ability of related technologies for seismic exploration data is limited, and ideal analysis results cannot be obtained, thus affecting the quality of geological data. Summary of the Invention

[0004] The purpose of the embodiments of the present invention is to provide a coal seam seismic exploration data analysis method and system, aiming to solve the problems raised in the above background technology.

[0005] The embodiment of the present invention is implemented as follows: in a first aspect, a method for analyzing coal seam seismic exploration data includes:

[0006] parsing historical seismic exploration data and historical record data of the micro-logging to obtain interference data related to the micro-logging and acquiring excitation preparation data of the micro-logging, wherein the excitation preparation data includes an excitation position, an excitation period, and an excitation charge amount, and the interference data is used to characterize the interference of a first target on the seismic exploration, wherein the first target includes a predictive interference target and / or a dynamic interference target;

[0007] Determining, based on the interference data and the excitation position, a first time period during which the dynamic interference target passes through an interference range, and determining, within a second time period, based on the interference data, a future interference period of the predictive interference target on the micro-well logging, wherein the interference range is determined based on the micro-well logging, and the second time period covers the excitation period and is at least a preset time period in advance;

[0008] updating target items of the excitation preparation data according to the first time period, the future interference period, and the historical seismic exploration data to obtain first excitation data, and acquiring first seismic exploration data collected according to the first excitation data, wherein the target items include the excitation period and the excitation charge;

[0009] The first seismic exploration data is parsed using a preset denoising scheme, wherein the preset denoising scheme is used to remove interference caused by objects other than the first target.

[0010] In a second aspect, the present invention further provides a coal seam seismic exploration data analysis system, which applies the above-mentioned coal seam seismic exploration data analysis method, including: a first analysis module, which is used to analyze historical seismic exploration data and historical record data of micro-logging, obtain interference data related to the micro-logging and obtain excitation preparation data of the micro-logging, wherein the excitation preparation data includes an excitation position, an excitation period, and an excitation charge, and the interference data is used to characterize the interference of a first target on the seismic exploration, wherein the first target includes a predictive interference target and / or a dynamic interference target;

[0011] a time period determination module, configured to determine, based on the interference data and the excitation position, a first time period during which the dynamic interference target passes through an interference range, and, within a second time period, determine, based on the interference data, a future interference period of the predictive interference target on the micro-logging, wherein the interference range is determined based on the micro-logging, and the second time period covers the excitation period and is at least a preset time period in advance;

[0012] an excitation data updating module, configured to update target items of the excitation preparation data according to the first time period, the future interference period, and the historical seismic exploration data, to obtain first excitation data, and acquire first seismic exploration data collected according to the first excitation data, wherein the target items include the excitation period and the excitation charge;

[0013] The second parsing module is configured to parse the first seismic exploration data using a preset denoising scheme, wherein the preset denoising scheme is configured to remove interference caused by targets other than the first target.

[0014] A coal seam seismic exploration data analysis method and system provided by an embodiment of the present invention starts from the interpretation of historical seismic survey data, obtains interference data and determines relevant time information, and then updates the excitation preparation data in combination with the historical seismic exploration data to obtain the first excitation data. In theory, it is possible to obtain first seismic exploration data of higher quality, and uses the near-path resection and other means in the preset denoising scheme to process the first seismic exploration data, thereby further improving the interpretation quality of the coal seam seismic data to obtain geological information with high precision and high signal-to-noise ratio. The entire interpretation process greatly reduces the difficulty of data interpretation and analysis, thereby providing a strong geological basis for safe production in mining areas such as high-angle coal seams, and providing technical support for coal mine mining design. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1The present invention is a main flow chart of a coal seam seismic exploration data analysis method.

[0016] Figure 2 The present invention is a flow chart of obtaining interference data related to micro-logging in a coal seam seismic exploration data analysis method.

[0017] Figure 3 The invention discloses a flow chart for determining a first time period in a coal seam seismic exploration data analysis method.

[0018] Figure 4 It is a diagram showing the types and development of interference waves in coal seam seismic exploration data analysis methods.

[0019] Figure 5 It is a main structural diagram of a coal seam seismic exploration data analysis system. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0021] The specific implementation of the present invention is described in detail below with reference to specific embodiments.

[0022] The present invention provides a coal seam seismic exploration data analysis method and system, which solve the technical problems in the background technology.

[0023] like Figure 1 FIG. 1 is a main flow chart of a coal seam seismic exploration data analysis method provided by an embodiment of the present invention. The coal seam seismic exploration data analysis method includes:

[0024] Step S10: parsing historical seismic exploration data and historical record data of the micro-logging, obtaining interference data related to the micro-logging and acquiring excitation preparation data of the micro-logging, wherein the excitation preparation data includes an excitation position, an excitation period, and an excitation charge amount, and the interference data is used to characterize the interference of a first target on the seismic exploration, wherein the first target includes a predictive interference target and / or a dynamic interference target;

[0025] Specifically, historical seismic exploration data records the characteristic information of interference targets, such as predictive interference targets: all detectors within the coverage have a global array response; historical record data records the interference process. Based on the analysis of the two, the first target can be determined, that is, including predictive interference targets and / or dynamic interference targets. Predictive interference targets generally refer to interference sources with fixed patterns or that can be predicted in advance. Their occurrence time, frequency, intensity or spatial location can be predicted based on historical data or external information, such as meteorological events such as rainfall, strong winds, thunderstorms, and vehicle vibration on roads around the mining area (such as 7:00-9:00 every day). :00 commuting period), which has seasonal / periodic patterns; dynamic interference targets refer to interference sources that appear randomly and cannot be predicted in advance. Their time, space or spectrum characteristics have no fixed patterns and need to be monitored in real time or identified through post-analysis. For example, random operations such as excavators and drilling rigs generate broadband impact vibrations, both of which may interfere with seismic exploration; after determining the first target, interference data can be obtained based on the characteristics of the first target, and excitation preparation data for micro-logging can be obtained. Analyzing the interference patterns through historical data can help to accurately and quickly obtain interference data, and facilitate the subsequent effective updating and optimization of excitation preparation data.

[0026] Step S11: Based on the interference data and the excitation position, determining a first time period during which the dynamic interference target passes through an interference range, and within a second time period, determining a future interference period of the predictive interference target on the micro-logging based on the interference data, wherein the interference range is determined based on the micro-logging, and the second time period covers the excitation period and is at least a preset time period in advance;

[0027] Specifically, the interference data is used to record the interference process or interference trend of the first target on the micro-logging. Based on the interference data of the dynamic interference target and the excitation position, the time when the dynamic interference target enters the interference range, that is, the first time period, can be predicted. The dynamic interference target needs to be monitored when it appears at a farther position; for the predictive target, there is a certain regularity, and monitoring can be started based on a preset time in advance of the excitation period. The preset time is at least the preparation time for the excitation, and based on the interference data of the predictive interference target, the future interference time period of the predictive interference target on the micro-logging can be determined. The determination of the first time period and the future interference time period can be directly used for the subsequent update and optimization of the excitation preparation data.

[0028] Step S12: updating target items of the excitation preparation data according to the first time period, the future interference period, and the historical seismic exploration data to obtain first excitation data, and acquiring first seismic exploration data collected according to the first excitation data, wherein the target items include the excitation period and the excitation charge;

[0029] Specifically, the first target may interfere with the excitation process of the micro-log under the excitation preparation data. Through the first time period, the future interference period and the historical seismic exploration data, the target item can be updated, such as the excitation period, to avoid or reduce the interference of the first target, and realize the preset avoidance strategy in combination with the historical seismic exploration data. If necessary, the excitation amount in the target micro-log is changed in combination with other micro-logs under the same or similar conditions corresponding to the seismic exploration data with better interpretation effects, so as to combine the target item, update the excitation preparation data, and obtain reasonable first excitation data for execution, and then obtain the first seismic exploration data collected according to the first excitation data, which helps to improve the quality of coal seam seismic data.

[0030] Step S13: parsing the first seismic exploration data using a preset denoising scheme, wherein the preset denoising scheme is used to remove interference caused by non-first targets.

[0031] Specifically, starting from the interpretation of historical seismic survey data, interference data is obtained and relevant time information is determined. Then, the excitation preparation data is updated in combination with the historical seismic exploration data to obtain the first excitation data. In theory, higher-quality first seismic survey data can be obtained. Furthermore, the near-path resection and other means in the preset denoising scheme can be used to parse the latest first seismic exploration data, thereby further improving the interpretation quality of coal seam seismic data to obtain high-precision and high signal-to-noise ratio geological information, greatly reducing the difficulty of data interpretation and analysis, and providing technical support for the formulation of coal mining design.

[0032] When this embodiment is applied, by parsing the historical seismic exploration data of the micro-logging and the historical record data, interference data related to the micro-logging and the excitation preparation data of the micro-logging are obtained. Analyzing the interference pattern through the historical data helps to accurately and quickly obtain the interference data, and helps to effectively update and optimize the subsequent excitation preparation data. Based on the interference data and the excitation position, a first time period in which the dynamic interference target passes through the interference range is determined. Within a second time period, based on the interference data, the future interference period of the predictive interference target on the micro-logging is determined. The determination of the first time period and the future interference period can be directly used for the subsequent update and optimization of the excitation preparation data. According to the first time period, the future interference period and the historical seismic exploration data, the target item of the excitation preparation data is updated to obtain the first excitation data, and the first seismic exploration data collected according to the first excitation data is obtained. The preset avoidance strategy can be implemented in combination with the historical seismic exploration data, and when necessary, the same or similar conditions corresponding to the seismic exploration data with better interpretation effects can be combined. Other micro-logging is then performed, and then, in combination with the target item, the excitation preparation data is updated, thereby obtaining reasonable first excitation data to execute and obtain first seismic exploration data collected according to the first excitation data, which helps to improve the quality of coal seam seismic data; by analyzing the first seismic exploration data through a preset denoising scheme, it is possible to suppress limited noise interference while retaining the effective signal of the coal seam to the maximum extent, thereby ensuring the reliability of structural interpretation; the present invention starts from the interpretation of historical seismic survey data, obtains interference data and determines relevant time information, and then updates the excitation preparation data in combination with the historical seismic exploration data to obtain first excitation data, so that theoretically higher-quality first seismic exploration data can be obtained, and the first seismic exploration data is processed by means such as near-path resection in the preset denoising scheme, thereby further improving the interpretation quality of the coal seam seismic data to obtain geological information with high precision and high signal-to-noise ratio. The entire interpretation process greatly reduces the difficulty of data interpretation and analysis, thereby providing a strong geological basis for safe production in mining areas such as high-angle coal seams, and providing technical support for coal mining design.

[0033] like Figure 2 As shown in FIG. 1 , as a preferred embodiment of the present invention, the analyzing of historical seismic exploration data and historical record data of micro-logging to obtain interference data related to micro-logging includes:

[0034] Step S101: performing spectrum feature recognition and detector array analysis on historical seismic exploration data to determine a period of suspicious interference caused by suspicious factors, including environmental vibrations and weather changes;

[0035] Specifically, dynamic interference (such as vehicles and construction machinery), unpredictable occurrence time and location (such as temporary construction vehicles and moving drilling rigs), low-frequency vibration (vehicle engine), and high-frequency impact (mechanical collision) have a spectrum that manifests as sudden spikes or broadband noise. The interference energy decays with distance and may only affect local detectors; it manifests as a sudden increase in the spectrum + a local array response.

[0036] Predictable interference (such as weather) is periodic or predictable, such as thunderstorms (broadband electromagnetic pulses), strong winds (low-frequency environmental vibrations), and rainfall (surface wave attenuation). Thunderstorms: instantaneous high-frequency electromagnetic interference (sudden increase in spectrum energy); strong winds: continuous low-frequency environmental noise (0.1-10Hz); rainfall: changes in surface media lead to distortion of reflected signals. Global impact: weather interference usually covers the entire exploration area, and all detectors may be affected simultaneously. The characteristics of predictable interference are: periodic spectrum characteristics + global array response. When the corresponding combined characteristics are identified based on historical seismic exploration data, the corresponding suspected interference period is determined.

[0037] Step S102: performing identification based on historical record data, determining a first target within the suspected interference period and obtaining a characteristic identifier of the first target;

[0038] When the period of future interference has been determined, there is no need to conduct a general identification of the historical record data. Instead, the historical record data within the suspected interference period can be directly identified. For dynamic targets, the historical record data includes image data, and the feature identifiers include standard status photos of dynamic interference targets, numbering information, equipment codes, etc.; for predictable interference targets, the historical record data is the report information recorded by professional departments, such as actual meteorological information. In this case, the feature identifier includes the WMO code given by the World Meteorological Organization, or other defined codes.

[0039] Step S103: Acquire the interference data of the first target according to the feature identifier.

[0040] Specifically, the interference data of dynamic interference targets comes from the latest image data near the micro-well logging and the fixed-point intelligence data set outside the interference range, while the interference data of predictive interference targets comes from local recorded prediction data, or from data provided by professional departments, such as the environmental interference data provided by the meteorological department system.

[0041] It can be understood that by performing spectral feature recognition and detector array analysis on historical seismic exploration data, the suspicious interference period caused by suspicious factors is determined, and then identification is performed based on the historical record data to determine the first target within the suspicious interference period and obtain the characteristic identification of the first target, thereby improving the efficiency of data recognition and ensuring that interference data can be obtained accordingly.

[0042] like Figure 3 As shown, as a preferred embodiment of the present invention, determining, based on the interference data and the excitation position, a first time period during which the dynamic interference target passes through an interference range, and determining, within a second time period, based on the interference data, a future interference period of the predictive interference target on the micro-logging includes:

[0043] Step S111: determining the position and first interference degree of the dynamic interference target according to the characteristic identifier of the dynamic interference target;

[0044] Specifically, the feature identification includes the standard state photo of the dynamic interference target, numbering information, equipment code, etc. According to the feature identification, a single-frame image that meets the preset similarity threshold with the standard state photo can be determined in the image data. The position of the dynamic interference target can be determined according to the shooting position in the single-frame image, or the positioning information of the dynamic interference target can be determined directly according to the equipment code. Dynamic interference targets include trucks, engineering vehicles, agricultural machinery, etc. The first interference degree can be determined by quantitative and qualitative analysis. Quantitative analysis can be achieved through fixed-point monitoring. For example, the proportion of low-frequency (5-15Hz) energy of the vehicle is >40%, which is a significant interference; for engineering machinery, harmonic distortion (THD), THD>15% requires early warning, etc.

[0045] Step S112: reversely determining the interference range centered on the micro-logging according to the first interference degree and the excitation position;

[0046] Specifically, based on the first interference level, the farthest distance that can be propagated to the micro-logging position and the noise can be ignored is calculated in reverse, and this distance is converted into a straight-line distance on the ground. Then, with the micro-logging as the center and this distance as the radius, the interference range of the dynamic interference target can be determined. For example, if the interference source is an excavator, follow the following steps: According to the following formula Where P(r) is the noise amplitude at distance r, P0 is the initial amplitude of the interference source, α is the ground absorption coefficient (related to frequency, unit: dB / m), reverse calculation, when P(r) drops to the threshold value Pth, rmax value, then according to d ground =r max cosθ can be used to calculate the ground projection distance. Assuming a homogeneous medium, θ is the propagation angle. Interference source: excavator (initial amplitude P0 = 1000 μPa, main frequency 30 Hz), absorption coefficient α = 0.05 = 0.05 dB / m (medium-hard clay), noise threshold: Pth = 50 μPa (corresponding to SNR = 10 dB), solving for rmax ≈ 120 m, and ground projection: dground = 120 × cos45° ≈ 85 m, meaning that the interference range is a circular area with a radius of 85 meters centered on the micro-well.

[0047] Step S113: determining the moving direction and moving speed of the dynamic interference target according to the position and movement information of the dynamic interference target;

[0048] Specifically, the average pace is calculated based on the moving path and duration (or when the average pace is too different from the instantaneous pace over a long period of time, the instantaneous pace can be directly used as the moving pace), and the moving direction is determined based on the path.

[0049] Step S114: Determine the distance information of the dynamic interference target from the first position to the nearest edge interference point and the farthest edge interference point in the interference range based on the moving direction, the first position of the dynamic interference target, and the interference range; and determine the first time period in which the dynamic interference target passes through the interference range based on the distance information and the moving pace.

[0050] Specifically, the nearest edge interference point and the farthest edge interference point are the two intersection points of the moving direction and the interference range, such as the two intersection points of a straight line and a circular area. The first position of the dynamic interference target (such as the current position, or the updated position) is known, the distance to the two intersection points is known, and the moving pace is known. Then, the time from the first position of the dynamic interference target to the nearest edge interference point and the farthest edge interference point can be calculated, and then the current time at the time of calculation is superimposed to determine the first time period, and the first time period is updated.

[0051] The above can more accurately determine the interference of the dynamic interference target on the micro-logging based on its movement and interference information, thereby facilitating the update of the target item of the subsequent stimulation preparation data.

[0052] As a preferred embodiment of the present invention, determining, based on the interference data and the excitation position, a first time period during which the dynamic interference target passes through an interference range, and determining, within a second time period, based on the interference data, a future interference period of the predictive interference target on the micro-logging includes:

[0053] Step: Within a second time period, determine the future interference period based on the interference data, and differentiate the future interference period according to a second interference degree, wherein the interference data of the predictive interference target includes external prediction data. Since the second time period is restricted, the second interference degree at this time is the predictive interference target.

[0054] It should be understood that the interference data of the predictive interference target comes from external prediction data, such as the environmental interference data provided by the meteorological department system. This interference data generally carries the interference degree level, such as the level of wind and rain and the amount of rainfall.

[0055] As a preferred embodiment of the present invention, the target item of the excitation preparation data is updated based on the first time period, the future interference period, and the historical seismic exploration data to obtain first excitation data, and first seismic exploration data collected based on the first excitation data is acquired, wherein the target item includes the excitation period and the excitation charge, and includes:

[0056] Step: determining whether the future interference period overlaps with the excitation period;

[0057] Step: if it is determined that the future interference period overlaps with the excitation period, the non-future interference period is used as an alternative period for the new excitation period, a new excitation period is determined based on the alternative period, and it is determined whether the new excitation period overlaps with the first time period. If so, the process jumps to the pause indication step;

[0058] Specifically, the first time period is the activity period of dynamic interference targets (such as vehicles and machinery); the future interference period is the high noise period caused by environmental vibration (such as wind and rain); the excitation period is the time window for planned seismic exploration, for example, the excitation period is: 09:00-9:50; half an hour before the excitation, it is known that the predictive interference target has changed (inaccurate prediction), and the future interference period of the environment (heavy rain) is: 09:35-10:00 (overlap); therefore, the new excitation period is determined to be 15:00-16:00, which is clear Dynamic future interference period (excavator operation or vehicle entry): 11:30–12:00 (not overlapping with the new excitation period); Processing process: Execute the excitation process according to the new excitation period. If the new excitation period is determined to be 11:50-12:30 or 14:20-15:20 (overlapping with the new excitation period), a shutdown command can be sent to the excavator, requiring it to evacuate (out of the interference range) or shut down at least a certain time in advance based on 15:00. This can avoid data contamination caused by environmental vibration and ensure collection quality. Alternatively, when there are fewer alternative time periods and the future interference period exceeds the preset duration, the future interference period is divided according to the second interference degree. The time when the second interference degree meets the preset mild level and avoids the dynamic future interference period is selected as the new excitation time to avoid delays that affect the new excitation time period. The rainfall at the preset mild level is small, and a higher natural frequency detector can be used to reduce low-frequency interference, and / or, in the subsequent update of the excitation capability, the excitation energy can be appropriately increased (compensating for rainwater absorption loss).

[0059] Step: if it is determined that the future interference period does not overlap with the excitation period, the original excitation period is maintained, and it is determined whether the first time period overlaps with the excitation period. If so, the process jumps to the pause indication step;

[0060] Specifically, when the environmental vibration does not affect the excitation time, the original excitation period is directly maintained, and if the future interference period of the dynamic interference target overlaps with the excitation time, a pause instruction step should be executed, such as sending a stop instruction to the excavator, requiring it to evacuate in advance (out of the interference range) or shut down.

[0061] The pause instruction step includes: giving a pause instruction to the dynamic interference target, that is, requiring it to evacuate (out of the interference range) or shut down in advance, and giving a time-limited movement instruction based on the new excitation period or the excitation period.

[0062] Specifically, pause requires full takeover of the dynamic interference target, while time-limited movement requires completion before the preparation time of the activation period.

[0063] It should be understood that the above can accurately avoid environmental interference (such as weather), actively control dynamic interference (such as vehicles), minimize data contamination risks, and improve construction efficiency. It is suitable for complex environments such as mining areas and cities. Therefore, before the formal interpretation, through the preset avoidance strategy, the quality of coal seam seismic data can be significantly improved, ensuring the reliability of subsequent structural interpretation.

[0064] As a preferred embodiment of the present invention, the target item of the excitation preparation data is updated based on the first time period, the future interference period, and the historical seismic exploration data to obtain first excitation data, and first seismic exploration data collected based on the first excitation data is acquired, wherein the target item includes the excitation period and the excitation charge, and includes:

[0065] Under the new excitation period, or under the condition of maintaining the original excitation period, determining first historical seismic exploration sub-data that meets the preset similarity condition of the excitation position in the historical seismic exploration data of the micro-logging;

[0066] Specifically, under the new excitation period, or maintaining the original excitation period, it is indicated that a new preliminary parameter condition is formed. One of the two situations is selected. The preset similar conditions include historical seismic exploration data (sub-dataset) in the same coal seam dip area, and ensure that the observation system (detector arrangement, sampling rate) and other parameters of the historical data are consistent with the current micro-log (generally from other micro-logs).

[0067] The excitation charge is modified according to the signal-to-noise ratio of the first historical seismic exploration sub-data.

[0068] Optionally, the modifying the excitation dose according to the signal-to-noise ratio of the first historical seismic exploration sub-data includes:

[0069] Compare the changes in the signal-to-noise ratio of the first historical seismic exploration sub-data and determine whether the surface roll has changed, and determine the corresponding change in the excitation charge amount.

[0070] Specifically, the historical seismic exploration data (sub-dataset) in the same coal seam dip area as the target micro-logging well is extracted, and the observation system (detector arrangement, sampling rate) and other parameters of the historical data are ensured to be consistent with those of the current micro-logging well. The signal-to-noise ratio (SNR) is calculated based on the common shot point gather (CSP) or common receiver point gather (CRP) of the historical seismic exploration data, where SNR = 10l g{effective signal energy (coal seam reflection time window) / noise energy (first arrival or after reflection time window)}; mark the excitation charge and well depth of each shot data, draw a three-dimensional scatter plot (well depth, charge, SNR), fit the trend surface (such as polynomial regression), and then determine the micro-logging charge based on the fitted trend surface; or input the historical seismic exploration data into the trained neural network model, and finally the micro-logging charge can be obtained. The calculation results are given below: When the SNR increases with the increase of charge, the charge should be appropriately increased (for example, according to the first preset increment, such as +10%-20%), based on: the increase in charge can enhance the energy of seismic waves, effectively suppress random noise, and thus improve the signal-to-noise ratio SNR ; When the SNR increases with the dose but the surface wave is enhanced, the dose is slightly increased (for example, according to the second preset increment, the second preset increment is lower than the first preset increment, for example +5%-10%) and combined with FK filtering; basis: large doses will excite stronger low-frequency surface waves, and it is necessary to suppress the surface wave interference through FK filtering while improving the signal energy to achieve a balance between energy and noise. When the SNR is saturated or decreases after a certain dose, the historical optimal dose is not adjusted; when the SNR is always low (lower than the preset signal-to-noise ratio), the well depth is insufficient, resulting in energy loss. At this time, the well depth should be increased instead of the dose; the above can be achieved through dose optimization driven by historical data, such as improving the quality of micro-logging seismic data.

[0071] like Figure 4 As shown, the types and development of interference waves are given so that effective measures can be taken to suppress various interference waves to the maximum extent. The main interference waves in the study area include surface waves, refraction waves, microseismic waves and acoustic waves. To address this problem, the present invention provides a detailed embodiment. Based on avoiding the interference of the first target, the corresponding high-frequency random noise and low-frequency waves, as well as directional low-frequency vibration characteristics are avoided. Furthermore, the first seismic exploration data is parsed by a preset denoising scheme, wherein the preset denoising scheme is used to remove interference caused by non-first targets and includes:

[0072] Based on a preset order in the preset denoising scheme, domain transformation and physical resection are performed on the first seismic survey data.

[0073] Specifically, the first seismic exploration data is analyzed and processed in the order of acoustic wave → refracted wave → surface wave. For the acoustic wave, the near-path resection (Mute) is first used to directly remove the data of the near offset (such as <300 meters), and then the FK filter is used to remove the low-speed energy in the FK domain (speed <500m / s); for the refracted wave, the first-arrival resection is first used to remove the refracted wave within the first-arrival time window (such as 0-300ms), and then the Radon transform is used to separate the linear phase axis (refracted wave) and the hyperbolic reflection wave; and for the surface wave, the FK filter is first used to remove the low-frequency fan-shaped energy (speed <1000m / s, frequency <15Hz), and then the wavelet transform is used to threshold the low-frequency wavelet coefficients. The above can suppress limited noise interference while retaining the effective signal of the coal seam to the maximum extent, thereby ensuring the reliability of the structural interpretation.

[0074] like Figure 5 As shown, as another preferred embodiment of the present invention, on the other hand, a coal seam seismic exploration data analysis system 200 includes:

[0075] A first parsing module 210 is configured to parse historical seismic exploration data and historical record data of the micro-logging to obtain interference data related to the micro-logging and acquire excitation preparation data of the micro-logging, wherein the excitation preparation data includes an excitation position, an excitation period, and an excitation charge. The interference data is used to characterize the interference of a first target on the seismic exploration, wherein the first target includes a predictive interference target and / or a dynamic interference target.

[0076] a time period determination module 220 configured to determine, based on the interference data and the excitation position, a first time period during which the dynamic interference target passes through an interference range, and, within a second time period, determine, based on the interference data, a future interference period of the predictive interference target on the micro-log, wherein the interference range is determined based on the micro-log, and the second time period covers the excitation period and is at least a preset time period in advance;

[0077] an excitation data updating module 230 for updating target items of the excitation preparation data based on the first time period, the future interference period, and the historical seismic exploration data to obtain first excitation data, and acquiring first seismic exploration data collected based on the first excitation data, wherein the target items include the excitation period and the excitation charge;

[0078] The second parsing module 240 is configured to parse the first seismic exploration data using a preset denoising scheme, wherein the preset denoising scheme is configured to remove interference caused by objects other than the first target.

[0079] As a preferred embodiment of the present invention, the first parsing module 210 is specifically configured to:

[0080] Performing spectrum feature recognition and detector array analysis on historical seismic exploration data to identify periods of suspected interference caused by suspicious factors, including environmental vibrations and weather changes;

[0081] Identify based on historical record data, determine the first target within the suspected interference period and obtain a characteristic identifier of the first target;

[0082] The interference data of the first target is acquired according to the feature identifier.

[0083] It should be noted that, referring to the specific implementation description of a coal seam seismic exploration data analysis method in the aforementioned embodiment, the implementation methods of the above two embodiments completely correspond to the corresponding method steps and will not be described again here.

[0084] In order to enable the above-mentioned method and system to be loaded and run smoothly, in addition to the various modules mentioned above, the system may also include more or fewer components than described above, or a combination of certain components, or different components, for example, it may include input and output devices, network access devices, buses, processors and memories, etc.

[0085] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor. The processor is the control center of the system, connecting various components using various interfaces and lines.

[0086] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A coal seam seismic exploration data analysis method, characterized in that: include: parsing historical seismic exploration data and historical record data of the micro-logging to obtain interference data related to the micro-logging and acquiring excitation preparation data of the micro-logging, wherein the excitation preparation data includes an excitation position, an excitation period, and an excitation charge amount, and the interference data is used to characterize the interference of a first target on the seismic exploration, wherein the first target includes a predictive interference target and / or a dynamic interference target; Determining, based on the interference data and the excitation position, a first time period during which the dynamic interference target passes through an interference range, and determining, within a second time period, based on the interference data, a future interference period of the predictive interference target on the micro-well logging, wherein the interference range is determined based on the micro-well logging, and the second time period covers the excitation period and is at least a preset time period in advance; updating target items of the excitation preparation data according to the first time period, the future interference period, and the historical seismic exploration data to obtain first excitation data, and acquiring first seismic exploration data collected according to the first excitation data, wherein the target items include the excitation period and the excitation charge; The first seismic exploration data is parsed using a preset denoising scheme, wherein the preset denoising scheme is used to remove interference caused by objects other than the first target.

2. The coal seam seismic exploration data analysis method according to claim 1, characterized in that: The analyzing of historical seismic exploration data and historical record data of micro-logging to obtain interference data related to micro-logging includes: Performing spectrum feature recognition and detector array analysis on the historical seismic exploration data to determine a period of suspicious interference caused by suspicious factors, wherein the suspicious factors include environmental vibrations and weather changes; Identify based on the historical record data, determine a first target within the suspected interference period and obtain a feature identifier of the first target; The interference data of the first target is acquired according to the feature identifier.

3. The coal seam seismic exploration data analysis method according to claim 2, characterized in that: The step of determining, based on the interference data and the excitation position, a first time period during which the dynamic interference target passes through an interference range, and determining, within a second time period, a future interference period of the predictive interference target on the micro-logging based on the interference data comprises: Determining a position and a first interference degree of the dynamic interference target according to the characteristic identifier of the dynamic interference target; Reversely determining the interference range centered on the micro-logging according to the first interference degree and the excitation position; Determining the moving direction and moving speed of the dynamic interference target according to the position and movement information of the dynamic interference target; According to the moving direction, the first position of the dynamic interference target, and the interference range, determine the distance information of the dynamic interference target from the first position to the nearest edge interference point and the farthest edge interference point in the interference range; based on the distance information and the moving pace, determine the first time period in which the dynamic interference target passes through the interference range.

4. The coal seam seismic exploration data analysis method according to any one of claims 1 to 3, characterized in that: The step of determining, based on the interference data and the excitation position, a first time period during which the dynamic interference target passes through an interference range, and determining, within a second time period, a future interference period of the predictive interference target on the micro-logging based on the interference data comprises: In the second time period, the future interference period is determined according to the interference data, and the future interference period is differentiated according to a second interference degree, wherein the interference data of the predictive interference target includes external prediction data.

5. The coal seam seismic exploration data analysis method according to claim 2 or 3, characterized in that: The target item of the excitation preparation data is updated according to the first time period, the future interference period, and the historical seismic exploration data to obtain first excitation data, and first seismic exploration data collected according to the first excitation data is acquired, wherein the target item includes the excitation period and the excitation charge, and includes: Determining whether the future interference period overlaps with the excitation period; If it is determined that the future interference period overlaps with the excitation period, the non-future interference period is used as an alternative period for the new excitation period, the new excitation period is determined based on the alternative period, and it is determined whether the new excitation period overlaps with the first time period. If so, the process jumps to the pause indication step; If it is determined that the future interference period does not overlap with the excitation period, the original excitation period is maintained, and it is determined whether the first time period overlaps with the excitation period. If so, the process jumps to the pause indication step. The pause instruction step includes: making a pause instruction to the dynamic interference target, and making a time-limited movement instruction based on the new excitation period or the excitation period.

6. The coal seam seismic exploration data analysis method according to claim 5, characterized in that: The target item of the excitation preparation data is updated according to the first time period, the future interference period, and the historical seismic exploration data to obtain first excitation data, and first seismic exploration data collected according to the first excitation data is acquired, wherein the target item includes the excitation period and the excitation charge, and includes: Under the new excitation period, or under the condition of maintaining the original excitation period, determining first historical seismic exploration sub-data that meets the preset similarity condition of the excitation position in the historical seismic exploration data of the micro-logging; The excitation charge is modified according to the signal-to-noise ratio of the first historical seismic exploration sub-data.

7. The coal seam seismic exploration data analysis method according to claim 6, characterized in that: The modifying the excitation charge according to the signal-to-noise ratio of the first historical seismic exploration sub-data includes: Compare the changes in the signal-to-noise ratio of the first historical seismic exploration sub-data and determine whether the surface roll has changed, and determine the corresponding change in the excitation charge amount.

8. The coal seam seismic exploration data analysis method according to any one of claims 1 to 3, characterized in that: The first seismic exploration data is parsed using a preset denoising scheme, wherein the preset denoising scheme is used to remove interference caused by non-first targets and includes: Based on a preset order in the preset denoising scheme, domain transformation and physical resection are performed on the first seismic survey data.

9. A coal seam seismic exploration data analysis system, characterized in that: The method for analyzing coal seam seismic exploration data according to any one of claims 1 to 8 is applied, comprising: a first parsing module, configured to parse historical seismic exploration data and historical record data of the micro-logging, obtain interference data related to the micro-logging, and acquire excitation preparation data of the micro-logging, wherein the excitation preparation data includes an excitation position, an excitation period, and an excitation charge amount, and the interference data is used to characterize the interference of a first target on the seismic exploration, wherein the first target includes a predictive interference target and / or a dynamic interference target; a time period determination module, configured to determine, based on the interference data and the excitation position, a first time period during which the dynamic interference target passes through an interference range, and, within a second time period, determine, based on the interference data, a future interference period of the predictive interference target on the micro-logging, wherein the interference range is determined based on the micro-logging, and the second time period covers the excitation period and is at least a preset time period in advance; an excitation data updating module, configured to update target items of the excitation preparation data according to the first time period, the future interference period, and the historical seismic exploration data, to obtain first excitation data, and acquire first seismic exploration data collected according to the first excitation data, wherein the target items include the excitation period and the excitation charge; The second parsing module is configured to parse the first seismic exploration data using a preset denoising scheme, wherein the preset denoising scheme is configured to remove interference caused by targets other than the first target.

10. The coal seam seismic exploration data analysis system according to claim 9, characterized in that: The first parsing module is specifically used for: Performing spectrum feature recognition and detector array analysis on historical seismic exploration data to identify periods of suspected interference caused by suspicious factors, including environmental vibrations and weather changes; Identify based on historical record data, determine the first target within the suspected interference period and obtain a characteristic identifier of the first target; The interference data of the first target is acquired according to the feature identifier.

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