Daily variation correction method of natural electric field frequency selection method based on remote reference technology

Abstract

The invention discloses a daily variation correction method of a natural electric field frequency selection method based on a far reference technology. According to the method, a natural electric field frequency selector is used as a remote reference station, and a measuring instrument and the remote reference station keep synchronous acquisition. Due to the fact that daily variation signals recorded by the target measuring point and the remote reference station have high correlation, daily variation and noise in the signals of the target measuring point can be effectively separated, the response characteristics of the underground structure are accurately extracted, and the exploration effect of the natural electric field frequency selection method is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of geophysical exploration technology, and in particular to a diurnal variation correction method of a natural electric field frequency selection method based on a remote reference technology. Background Art

[0002] The Natural Electric Field Frequency Selection Method (NFS) is a passive source electromagnetic exploration technology that relies on natural alternating electric field signals (such as the global electromagnetic field generated by atmosphere-ionosphere coupling or local thunderstorm activity signals) to image underground electrical structures.

[0003] The natural electric field frequency selection method is a geophysical method that uses natural alternating electric fields to image underground structures. This method requires only two measuring electrodes at two nodes to directly measure the natural electric field signal strength of different frequencies. It does not require measuring magnetic field signals or deploying artificial electric fields. It has the advantages of high efficiency and low exploration costs, and thus has obvious advantages in geological exploration. In actual field work, diurnal variations are often assumed to be nearly stable during working hours, and therefore the impact of diurnal variations on observational data is ignored. However, when conducting medium- to deep-level geological exploration, longer observation times are often required, and diurnal variations can no longer be considered a stable signal. If not addressed, this will have a significant impact on the interpretation results. Due to the presence of diurnal variations, the exploration accuracy of this method is low, and interpretation is difficult.

[0004] Based on the problems existing in the current natural electric field frequency selection method, in order to improve the versatility and exploration effect of this method, it is worthwhile to carry out research on the natural electric field diurnal variation correction method, improve the exploration effect of the natural electric field frequency selection method, and provide reliable geophysical information for the fine characterization of geological structures. Summary of the Invention

[0005] The method proposed in the present invention is to deploy a remote reference station in an area far away from the survey area and with little electric field interference. The spatial correlation of the daily variation signal, the spatial independence of the target anomaly signal and the local noise are used to extract the daily variation signal and subtract it from the target measurement point signal, thereby eliminating the impact of daily variation on the observation data and improving the exploration effect.

[0006] A diurnal variation correction method for a natural electric field frequency selection method based on a remote reference technology comprises the following steps:

[0007] (1) Select an area far from the survey area and with little interference from human electric fields as the location for the remote reference station. The natural electric field frequency selector deployed should ensure 24-hour uninterrupted collection of natural electric field signals. If all-weather measurement is not possible, the instrument collection time in the survey area should be within the collection time of the remote reference station, so that the instrument in the survey area and the remote reference station can maintain synchronization during the measurement period.

[0008] (2) According to the surface and human environment of the exploration area, the measuring points are evenly distributed; according to the burial depth of the exploration target, the working frequency range is set, and the natural electric field frequency selector collects the electric field time series data of different measuring points respectively; the greater the exploration depth, the lower the working frequency and the longer the collection time, and vice versa;

[0009] (3) Assume that the target measurement point signal is S T (t), the far reference station signal is S R (t), both can be expressed as:

[0010] S T (t) = S diurnal (t)+S noise (t)+S ano (t)

[0011]

[0012] Among them, S diurnal (t) is the daily varying signal, S noise (t) and are the signals caused by noise interference at the measuring point and the remote reference station, S ano (t) and are the signals caused by the anomalies at the measuring point and the remote reference station respectively; since the noise at the remote reference station and the measuring point and the signal of the anomaly have spatial independence, the diurnal variation signals recorded by the remote reference station and the measuring point are highly correlated; the electric field time series data collected by the measuring point instrument in step (2) and the remote reference station in step (1) are converted into the frequency domain by Fourier transform, and then the frequency spectra of the two signals are analyzed to find the frequency components related to diurnal variation; the diurnal variation signal is obtained based on the frequency spectrum of the remote reference station signal, and the diurnal variation component in the target measuring point signal is deducted to obtain the natural electric field signal with the diurnal variation effect eliminated:

[0013] S′ T (t) = S T (t)-S diurnal (t)

[0014] The natural electric field data of all frequencies at all measuring points are mapped and interpreted to determine the underground geological conditions in the exploration area.

[0015] Preferably, in step (3), the target measuring point signal ST (t) and the reference station signal S R (t) has a linear relationship:

[0016] S T (t) = αS R (t)+β

[0017] The coefficients α and β are obtained by fitting using the least squares method, thereby reconstructing the diurnal variation component represented by the distant reference station at the target measurement point:

[0018] S diurnal (t) = αS R (t)+β.

[0019] Beneficial effects

[0020] Compared to existing technologies, the present invention offers the following advantages: It uses a natural electric field frequency selector as a remote reference station, with the measuring instrument and the remote reference station maintaining synchronous data acquisition. Because the diurnal variation signals recorded at the target measuring point and the remote reference station have a high correlation, the diurnal variation and noise in the target measuring point signal can be effectively separated, allowing for accurate extraction of underground structural response characteristics. This ensures the effectiveness of the natural electric field frequency selection method, improves its accuracy, and ultimately yields more accurate geological exploration results. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a flow chart of a diurnal variation correction method of a natural electric field frequency selection method based on remote reference technology of the present invention;

[0022] Figure 2 This is a flow chart of the conventional exploration method of the existing natural electric field frequency selection method;

[0023] Figure 3 Schematic diagram of the field arrangement of instruments for a diurnal variation correction method using a natural electric field frequency selection method according to the present invention;

[0024] Figure 3 The hollow circle indicates the location of the far reference point, the solid circle indicates the location of the measuring point, the square indicates the size of the measuring area, and 1-25 are the numbers of the 25 measuring points. DETAILED DESCRIPTION

[0025] The following references Figure 1 、 Figure 2 and Figure 3 The present invention will be further described in conjunction with specific implementation methods.

[0026] A diurnal variation correction method for natural electric field frequency selection based on remote reference technology, the specific steps are as follows:

[0027] (1) Select an area that is far away from the survey area and has little human interference as the location for the remote reference station. The natural electric field frequency selector should ensure 24-hour uninterrupted collection of natural electric field signals. When all-weather measurement is not possible, it is necessary to ensure that the instrument collection time in the survey area is within the collection time of the remote reference station, so that the measuring instrument and the remote reference station are synchronized during the measurement period. The selection of the remote reference station can be made in combination with the previous geophysical data. In order to reduce human interference and electromagnetic interference, the remote reference station should be as far away as possible from towns, high-voltage lines, cement roads and other areas. The distance between the remote reference station and the survey area can be roughly determined based on the working frequency. When the acquisition frequency is high frequency, the remote reference station can be closer to the survey area. However, when the acquisition frequency is low frequency, in order to ensure the processing effect of the low frequency, it needs to be farther away. It is recommended that the remote reference station collect the natural alternating electric field in the north-south direction (corresponding to the x direction) and the east-west direction (corresponding to the y direction) at the same time to ensure the richness of the collected data.

[0028] (2) According to the surface and human environment of the survey area, the measurement points should be arranged to ensure that the measurement points are evenly distributed as much as possible. According to the burial depth of the exploration target, the working frequency range should be set, and one or more natural electric field frequency selectors should be used to collect electric field time series data at different measurement points. Generally speaking, the greater the exploration depth, the lower the working frequency and the longer the collection time; vice versa. To ensure the consistency of the observation results, consistency tests should be conducted on all natural electric field frequency selectors, and inconsistent instruments should be calibrated. In order to ensure the accuracy of the measurement results, non-polarized electrodes should be used. The collection time of the instrument in the survey area should be within the collection period of the remote reference station, otherwise it will not be possible to perform diurnal variation correction. In addition to the pole distance, the settings of other parameters of the natural electric field frequency selectors used in the survey area and the remote reference station should be consistent. The electrode distance in the survey area can be adjusted according to the actual situation, and can be consistent with the pole distance of the remote reference point or inconsistent.

[0029] (3) Assume that the target measurement point signal is S T (t), the far reference station signal is S R (t), both can be expressed as:

[0030] S T (t) = S diurnal (t)+S noise (t)+S ano (t)

[0031]

[0032] Among them, S diurnal (t) is the daily varying signal, S noise (t) and are the noise interference of the measuring point and the remote reference station, S ano (t) and are the signals caused by the anomalies below the measuring point and the remote reference station, respectively. Since the noise of the remote reference station and the measuring point and the signal of the anomaly are spatially independent, the diurnal variation signals recorded by them have a high correlation. The electric field time series data collected by the measuring point instrument in step (2) and the remote reference station in step (1) are converted to the frequency domain through Fourier transform, and then the frequency spectrum of the two signals is analyzed to find the frequency components related to diurnal variation. According to the frequency spectrum of the remote reference station signal, the diurnal variation component in the target measuring point signal is deducted to obtain the natural electric field signal that eliminates the influence of diurnal variation:

[0033] S′ T (t) = S T (t)-S diurnal (t)

[0034] Although the natural alternating electric field data measured at the measuring point and remote reference station have different signal strengths at different times and there is always some random interference, the diurnal variation signals at the measuring point and remote reference station have spatial correlation, and the noise data have spatial independence. Remote reference technology can not only eliminate the influence of diurnal variation, but also suppress the impact of noise on the data, thereby improving the exploration effect.

[0035] (4) Carry out mapping analysis and interpretation of the natural electric field data of all frequencies at all measuring points to determine the underground geological conditions in the exploration area. Based on the natural electric field data of different frequencies at all measuring points, the geological stratification and geological anomalies at all measuring points can be qualitatively divided, thus providing reliable physical data for geological interpretation.

[0036] The present invention utilizes the principle of spatial separation and the independence of noise / anomaly signals between remote reference stations and measuring points, but the highly correlated characteristics of diurnal variation signals. By jointly processing the remote reference station and measuring point signals, the diurnal variation interference and local anomaly signals are effectively separated to achieve the elimination of diurnal variation signals.

[0037] The present invention introduces a remote reference station and a linear regression model to establish a linear regression model between the measuring point and the reference station signal, thereby innovatively solving the problem of diurnal interference in the natural electric field method.

[0038] like Figure 3 As shown, it is necessary to Figure 3 The new diurnal variation correction method proposed in this invention was used to carry out natural electric field frequency selection exploration at 25 measuring points in the middle survey area. The specific steps are as follows:

[0039] (1) Select two natural electric field frequency selectors and conduct consistency tests on them. If the systematic errors of the two instruments are not within the allowable range, use one frequency selector as a basis to perform system calibration on the other frequency selector to ensure the consistency of data acquisition between the two frequency selectors.

[0040] (2) A natural electric field frequency selector is deployed as a remote reference station in an area far away from the measurement area and with little interference from human electric fields. The natural alternating electric field signals in the north-south direction (corresponding to the x-direction) and the east-west direction (corresponding to the y-direction) are measured simultaneously. To improve the stability of the natural electric field signal at the remote reference point, non-polarized electrodes are used as measuring electrodes, and the distance between the two measuring electrodes in these two directions is 20 meters. In order to facilitate the construction of the measurement area and to ensure that the time period of the observation data is covered by the time period data of the remote reference point, a 24-hour uninterrupted power supply is provided.

[0041] (3) Arrange 25 measuring points numbered 1-25 in the survey area. The data collection work of the natural electric field in the survey area should be carried out after the remote reference station is laid out. In order to enrich the data, the natural electric field signals in the north-south direction and the east-west direction are collected at the same time, that is, each measuring point has two measuring electrodes arranged in the north-south and east-west directions, and a total of 4 measuring electrodes are used. Among them, the distance between the two measuring electrodes in each direction of each measuring point is 20 meters. The settings of other parameters of the natural electric field frequency selector used in the survey area and the remote reference station should be consistent. After the natural electric field data collection of the 25 measuring points in the survey area is completed, the collection of the natural electric field data of the remote reference point is stopped.

[0042] (4) The time domain signals of the natural electric field collected in the measurement area and the remote reference point in step (3) and step (2) are Fourier transformed and converted into the frequency domain. The spectrum characteristics of the signals at the measurement point and the remote reference point are analyzed to find the frequency components related to the diurnal variation signal. Based on the spectrum of the remote reference station signal, the diurnal variation component in the target measurement point signal is deducted to achieve the purpose of eliminating the diurnal variation effect. The application of remote reference technology can effectively separate the diurnal variation and noise in the target measurement point signal and extract the underground structure response information, thereby improving the exploration effect and accuracy.

[0043] (5) Carry out graphic analysis and interpretation of the natural electric field data of all measuring points within the survey area. Using the skin depth principle, based on the natural electric field data of different frequencies at all measuring points, the stratification of the underground medium, geological structural characteristics, and geological anomalies within the study area can be qualitatively divided, providing more accurate physical property information for geological interpretation.

[0044] 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, improvements, etc. made within the spirit and principles of the present invention should be included in the present invention.

Claims

1. A diurnal variation correction method for natural electric field frequency selection based on remote reference technology, characterized in that: The following steps are involved: (1) Select an area far from the exploration area and with little human electric field interference as the location for the remote reference station. The natural electric field frequency selector deployed should ensure 24-hour uninterrupted collection of natural electric field signals; In the case that all-weather measurement is not possible, it is necessary to ensure that the acquisition time of the exploration area instrument is within the acquisition time of the remote reference station, so that the exploration area instrument and the remote reference station are synchronized during the measurement period; (2) According to the surface and human environment of the exploration area, the measuring points are evenly distributed; according to the burial depth of the exploration target, the working frequency range is set, and the natural electric field frequency selector collects the electric field time series data of different measuring points respectively; the greater the exploration depth, the lower the working frequency and the longer the collection time, and vice versa; (3) Assume that the target measurement point signal is S T (t), the far reference station signal is S R (t), both can be expressed as: S T (t)=S diurnal (t)+S noise (t)+S ano (t) Among them, S diurnal (t) is the daily varying signal, S noise (t) and are the signals caused by noise interference at the measuring point and the remote reference station, S ano (t) and are the signals caused by the anomalies at the measuring point and the remote reference station respectively; since the noise at the remote reference station and the measuring point and the signal of the anomaly have spatial independence, the diurnal variation signals recorded by the remote reference station and the measuring point are highly correlated; the electric field time series data collected by the measuring point instrument in step (2) and the remote reference station in step (1) are converted into the frequency domain by Fourier transform, and then the frequency spectra of the two signals are analyzed to find the frequency components related to diurnal variation; the diurnal variation signal is obtained based on the frequency spectrum of the remote reference station signal, and the diurnal variation component in the target measuring point signal is deducted to obtain the natural electric field signal with the diurnal variation effect eliminated: S′ T (t)=S T (t)-S diurnal (t) (4) Carry out graphic analysis and interpretation of the natural electric field data of all frequencies at all measuring points to determine the underground geological conditions in the exploration area.

2. The diurnal variation correction method of the natural electric field frequency selection method based on remote reference technology according to claim 1 is characterized in that: In step (3), the target measurement point signal S T (t) and the reference station signal S R (t) has a linear relationship: S T (t)=αS R (t)+β The coefficients α and β are obtained by fitting using the least squares method, thereby reconstructing the diurnal variation component represented by the distant reference station at the target measurement point: S diurnal (t)=αS R (t)+β.

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