Quantitative Evaluation Method for the Quality of Continuous Data Acquisition by Node Instruments

Abstract

The present invention relates to the technical field of oil and gas geophysical data acquisition and processing, and particularly relates to a method for quantitatively evaluating the quality of continuously acquired data of a nodal instrument. The method of the present invention is mainly used for quantitatively evaluating and analyzing the noise in seismic data. Through four-dimensional volume dynamic distribution quality quantitative evaluation and analysis along the ground space direction and along the acquisition time direction, finally, the spatial quality analysis results of all position points within the same time period, the data quality analysis results of all times at the same position point, the moving direction and propagation speed analysis results of the noise source are obtained, so as to quantitatively master the noise distribution characteristics and noise generation rules of the monitoring area and ensure the quality of the continuously acquired data of the nodal instrument.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas geophysical data acquisition and processing, and particularly relates to a method for quantitatively evaluating the quality of continuously acquired data by a nodal seismograph. Background Art

[0002] In the processes of seismic exploration acquisition, passive seismic acquisition, microseismic monitoring construction, etc., the quality of field-acquired data determines the subsequent data processing and comprehensive interpretation work. Therefore, the quantitative evaluation of the quality of acquired data is crucial. The nodal seismograph includes functions such as a collector, a receiving station, a power station, a GPS, etc., and can continuously acquire data without interruption, and can record a large amount of seismic data. Especially with the large-scale popularization and application of nodal seismographs, the conventional data quality evaluation and monitoring methods can no longer meet the needs. In addition, the manual operation mode for evaluating the quality of acquired data can no longer fully meet the actual production needs. Currently, the conventional acquisition quality evaluation methods mainly target single-shot records in seismic exploration. In field construction, after the source is excited, the geophones start to record. Usually, the length of a single-shot record is 6s or 8s, and no recording is done during the intervals between source excitations.

[0003] Currently, the relevant technical research includes: the literature "Quality Control and Evaluation of Seismic Data Acquisition in Dongying Urban Area" (Geophysical Prospecting for Petroleum, 2006), which proposed a quality control and evaluation system for seismic data acquisition, carried out controls on the coordinate accuracy of physical points, the accuracy of physical points, the coincidence of physical points in bins, the accuracy of the source-receiver point correspondence relationship, etc. in seismic data acquisition, used a digital data stream system for management, and utilized real-time coverage analysis to ensure the data quality. This method mainly solved the problem of the position offset of geophone points and source points caused by the influence of surface obstacles in urban seismic exploration acquisition.

[0004] The literature "Seismic Acquisition Quality Evaluation Technology in Complex Areas and Its Application" (Geophysical Prospecting for Petroleum, 2019) automatically divides the complex surface into different evaluation areas according to satellite remote sensing data, automatically separates land-geophone-recorded seismic data and water-geophone-recorded seismic data using header information, and according to the construction characteristics of the work area, optimizes the monitoring parameters, analyzes the energy, frequency, abnormal channels, dropped spreads, etc. of single-shot data, sets the threshold range, and conducts a refined evaluation according to different evaluation criteria, thereby solving the problem of seismic acquisition quality evaluation caused by complex surface and large differences in seismic data.

[0005] With the development of geophysical exploration towards single-point and high-density directions, and the extension of production operations to complex areas, how to timely and effectively monitor the quality of seismic data collected in the field and analyze and evaluate it has become an outstanding issue in the quality control and management of field seismic data acquisition. The literature "New Method for On-site Monitoring of G3i Instrument Data Quality" (Geophysical Exploration Equipment, 2017) introduced a method for on-site monitoring and evaluation of G3i seismic data using a real-time monitoring and display software for quality indicators. The functions of the conventional software include: single-shot screen monitoring, list display of amplitude and noise information, histogram statistics of single-shot data, check of array status, first arrival picking, single-shot energy judgment, frequency monitoring, auxiliary trace monitoring, etc. This software stores the array detection content in the trace header of single-shot data and displays the data in the form of histograms and distribution graphs to master the latest array status. It also has a function of statistical analysis results, which can perform statistics on all data after analysis. The obtained results are displayed in the form of histograms to analyze the index situation and unqualified ratio of each survey line.

[0006] The literature "Quantitative Evaluation of Seismic Data Quality during Acquisition" (Coal Geology & Exploration, 2019) proposed a method for automatically quantitatively evaluating the quality of seismic data during acquisition. According to the characteristics of strong signal correlation received by each receiving trace, the relevant energy peaks of a single trace were effectively identified. After stacking the selected data, the signal-to-noise ratio of the data was significantly improved, and the relevant energy axis was significantly enhanced. This method can quickly screen out high-quality data from a large amount of seismic data during acquisition, greatly reducing the workload of further processing and improving the processing effect.

[0007] Chinese Patent Application CN109212600A proposed a seismic data evaluation method and system based on resolution ability. Lithology logging data and corresponding velocity data were collected, and a lithologic thin interbed model was established based on the lithology logging data and velocity data; the lithologic thin interbed model was transformed into a reflection coefficient sequence; a time window was opened in the target layer area to analyze the frequency and extract the seismic wavelet; the extracted seismic wavelet was convolved with the reflection coefficient sequence to obtain the seismic wave reflection record of the seismic wavelet; the obtained seismic wave reflection record was compared with the lithologic thin interbed model; through the comparative analysis of the two, the evaluation result of the resolution ability of the seismic data was obtained. This patent is a method for evaluating the resolution ability of seismic data, that is, to judge the ability of seismic data to identify lithologic thin interbeds.

[0008] Chinese invention patent CN107576983B proposes a method for improving the accuracy of first arrival picking of single-shot seismic records and a data evaluation method. Exclude energy abnormal channels and transmission error channels in the single-shot record; starting from the first boundary, use continuous M channels as a sliding unit and slide channel by channel towards the second boundary, recording the coordinates of the middle channel when the energy in the sliding unit is the largest; according to the coordinates, re-calculate the offset and the theoretical first arrival time; extend the theoretical first arrival time by 300 - 500 ms along the time direction to obtain the first time window, take N consecutive sampling points starting from the top of the first time window as the first unit, slide along the time direction until the bottom of the first time window, and obtain the actual first arrival time. The evaluation method includes, during the process of evaluating seismic data, using the above picking method to pick the actual first arrival time, which can solve the problem of incorrect first arrival picking for shots with incorrect source-receiver relationships, can meet the needs of field single-shot record monitoring and automatic evaluation, and solve the problem of incorrect first arrival picking for single shots with incorrect source-receiver relationships.

[0009] However, the existing technologies mainly analyze single-shot records or seismic data collected in the field, lacking the evaluation and analysis of the collected data. In particular, there is no relevant report on the quantitative evaluation of the quality of continuously collected data by nodal instruments. Summary of the Invention

[0010] The main objective of the present invention is to provide a method for quantitatively evaluating the quality of continuously collected data by nodal instruments. The method of the present invention is mainly used for quantitatively evaluating and analyzing the noise in seismic data. Through the quality quantitative evaluation and analysis of four-dimensional volume dynamic distribution along the ground spatial direction and along the acquisition time direction, the spatial quality analysis results of all position points within the same time period, the data quality analysis results of all times at the same position point, and the analysis results of the moving direction and propagation speed of the noise source are finally obtained, so as to quantitatively master the noise distribution characteristics and noise generation rules of the monitoring area and ensure the quality of continuously collected data by nodal instruments.

[0011] To achieve the above objective, the present invention adopts the following technical solutions:

[0012] The present invention provides a method for quantitatively evaluating the quality of continuously collected data by nodal instruments, which includes the following steps: collecting data, including continuously collected data by nodal instruments, nodal instrument coordinate position information, and nodal instrument record acquisition time; performing analysis along the ground spatial direction and along the acquisition time direction on the collected data; extracting attribute information in four aspects of energy, frequency, signal, and noise from the continuously collected data by nodal instruments, and establishing a four-factor joint attribute analysis model; performing quality evaluation and analysis of four-dimensional volume dynamic distribution from the ground spatial direction and the acquisition time direction; according to the quality evaluation and analysis results of four-dimensional volume dynamic distribution, obtaining the spatial quality analysis results of all position points within the same time period, the data quality analysis results of all times at the same position point, and the analysis results of the moving direction and propagation speed of the noise source in the monitoring area.

[0013] Furthermore, the node instrument continuously collects data in SEGY format, and the sampling interval can be 0.5 ms, 1 ms, 2 ms or 4 ms; the coordinate position information of the node instrument includes the east-west coordinate, north-south coordinate and elevation information; when collecting the acquisition time recorded by the node instrument, the time synchronization of the node instruments at different positions should be ensured.

[0014] Furthermore, perform analysis on the collected data in the ground space direction, that is, quantitatively evaluate the data quality according to the east-west coordinate, north-south coordinate and elevation of the node instrument: first determine the analysis time window size according to the data characteristics, then analyze the attribute information within a single time window at different times, or use the step-by-step accumulation algorithm to calculate the attribute information within multiple consecutive time windows or multiple spaced time windows. The quantitative evaluation result is a three-dimensional spatial attribute volume.

[0015] Furthermore, perform analysis on the collected data in the acquisition time direction, that is, quantitatively evaluate the data quality of the node instrument at different times according to the acquisition time of the node instrument: first determine the analysis time window size according to the data characteristics, then analyze the attribute information of the single-channel node instrument data, or use the step-by-step accumulation algorithm to calculate the attribute information of the single-channel node instrument and the data of the surrounding node instruments.

[0016] Furthermore, the four-factor combined attribute analysis model is:

[0017] attr(n,t) = α × en(n,t) * β × f(n,t) * ε × sig(n,t) * φ × no(n,t)

[0018] Where: attr(n,t) is the result of the four-factor combined attribute analysis, n is the node instrument trace number, and t is the time; α is the energy control factor, and en(n,t) is the energy control factor; β is the frequency control factor, and f(n,t) is the frequency control factor; ε is the signal control factor, and sig(n,t) is the signal control factor; φ is the noise control factor, and no(n,t) is the noise control factor.

[0019] The control factor and the control factor are in a multiplication operation, and the weight of the control factor is adjusted through the control factor; the different control factors are in a convolution operation, and multiple attribute information is synthesized into one attribute information. The four-factor combined attribute analysis mechanism not only considers the influence of different attribute information, but also improves the evaluation and analysis efficiency, and at the same time avoids the influence of the subjective factors of selecting attribute information.

[0020] Furthermore, perform quality evaluation and analysis on the four-dimensional body dynamic distribution from the ground space direction and the acquisition time direction. The four-dimensional body includes: east-west coordinate, north-south coordinate, elevation and acquisition time.

[0021] The analysis results in the ground space direction can provide a three-dimensional attribute volume at a certain moment. Using this three-dimensional attribute volume, the distribution laws and variation characteristics of effective signals and noises in the ground space direction can be analyzed. The analysis results in the acquisition time direction can clarify the variation of the three-dimensional attribute volume with time, and as the acquisition time progresses, the distribution laws and variation characteristics of effective signals and noises in the acquisition time direction can be clarified.

[0022] Further, the above-mentioned attribute information includes: energy value, abnormal amplitude, signal-to-noise ratio, single-frequency noise, instrument noise, main frequency value, peak frequency. According to the characteristics of the attribute information, it is divided into four aspects: energy, frequency, signal, and noise.

[0023] Further, in the four-dimensional volume, after the acquisition time is fixed, the distribution laws and variation characteristics of effective signals and noises in the ground space direction can be analyzed; when the acquisition time changes gradually, the distribution laws and variation characteristics of effective signals and noises in the acquisition time direction can be clarified. By analyzing the position change and time interval of moving noises in the four-dimensional volume, the analysis results of the moving direction and propagation speed of noise sources in the monitoring area can be obtained.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] The method of the present invention conducts a quality evaluation of the dynamic distribution of the four-dimensional volume from the ground space direction + acquisition time direction through the analysis of data quality in the ground space direction and the analysis of data quality in the acquisition time direction. According to the combined attribute analysis results of the four factors of the acquired data, the spatial quality analysis results of all position points within the same time period, the quantitative evaluation analysis results of data quality at all times at the same position point, and the analysis results of the moving direction and propagation speed of noise sources can be obtained, realizing the quantitative grasp of the noise distribution characteristics and noise generation rules in the monitoring area and ensuring the quality of continuously acquired data by the node instrument.

[0026] The method of the present invention can quantitatively evaluate and analyze the noise in seismic data, filling the gap in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings forming a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention.

[0028] Figure 1 It is a flowchart of the method for quantitatively evaluating the quality of continuously acquired data by the node instrument according to Embodiment 1 of the present invention;

[0029] Figure 2 It is a diagram of continuously acquired data by the node instrument in Embodiment 1 of the present invention;

[0030] Figure 3It is the energy histogram of continuously collected data in Embodiment 1 of the present invention;

[0031] Figure 4 It is the single-frequency noise diagram of continuously collected data in Embodiment 1 of the present invention;

[0032] Figure 5 It is the time-frequency spectrum diagram of continuously collected data in Embodiment 1 of the present invention;

[0033] Figure 6 It is the spatial quality attribute diagram of all position points within the same time period in Embodiment 1 of the present invention;

[0034] Figure 7 It is the data quality attribute diagram of all times at the same position point in Embodiment 1 of the present invention;

[0035] Figure 8 It is the noise source moving direction and propagation speed attribute diagram in Embodiment 1 of the present invention. Detailed implementation manners

[0036] It should be noted that the following detailed description is exemplary and is intended to provide further illustration of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0037] It should be noted that the terms used herein are only for describing specific implementation manners and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular forms are also intended to include the plural forms. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, and / or combinations thereof.

[0038] In order to enable those skilled in the art to more clearly understand the technical solution of the present invention, the technical solution of the present invention will be described in detail below in conjunction with specific embodiments.

[0039] Embodiment 1

[0040] As Figure 1 shown, the method for quantitatively evaluating the quality of continuously collected data by the node instrument includes the following steps:

[0041] The first step: Collect the continuously collected data of the node instrument, the coordinate position information of the node instrument, and the acquisition time recorded by the node instrument:

[0042] The node instrument continuously collects data in SEGY format. The sampling interval can be 0.5 ms, 1 ms, 2 ms, 4 ms, etc., and can be adjusted as needed. The coordinate position information of the node instrument includes the east-west coordinate, north-south coordinate, and elevation information, with the unit being m. The recording acquisition time of the node instrument is synchronized by GPS, with an error less than 1 ns, ensuring the time synchronization of node instruments at different positions. The continuously collected data of the node instrument is as Figure 2 shown. The abscissa is the trace number, and the ordinate is the time, with the unit being ms.

[0043] Step 2: According to the collected data, perform data quality analysis along the ground space direction and along the acquisition time direction:

[0044] The analysis along the ground space direction is to quantitatively evaluate the data quality based on the east-west coordinate, north-south coordinate, and elevation of the node instrument. First, determine the size of the analysis time window, and then analyze the attribute information within a single time window at different times, or use the step-by-step cumulative algorithm to calculate the attribute information within multiple consecutive time windows or multiple spaced time windows. The quantitative evaluation result is a three-dimensional spatial attribute volume.

[0045] The analysis along the acquisition time direction is to quantitatively evaluate the data quality of the node instrument at different times based on the acquisition time of the node instrument. First, determine the size of the analysis time window, and then analyze the attribute information of the data of a single node instrument, or use the step-by-step cumulative algorithm to calculate the attribute information of the data of this single node instrument and the surrounding node instruments.

[0046] The calculated attribute information includes: energy value, abnormal amplitude, signal-to-noise ratio, single-frequency noise, instrument noise, main frequency value, and peak frequency. The energy value reflects the background noise and effective signal conditions at the coordinate position of the node instrument. The abnormal amplitude reflects random noise interference. The signal-to-noise ratio reflects the magnitudes of the signal and noise. The single-frequency noise reflects industrial electricity interference, pumping unit interference, large drill interference, etc. The instrument noise reflects the working state of the node instrument. The main frequency value and peak frequency reflect the frequency characteristics of the effective signal and noise.

[0047] Step 3: Extract attribute information such as energy value, abnormal amplitude, signal-to-noise ratio, single-frequency noise, instrument noise, main frequency value, and peak frequency from the continuously collected data of the node instrument. Figure 3 is the energy histogram of the continuously collected data. The abscissa is the trace number, and the ordinate is the energy value; Figure 4 is the single-frequency noise of the continuously collected data. The abscissa is the frequency, with the unit being Hz, and the ordinate is the amplitude value; Figure 5 is the time-frequency spectrum of the continuously collected data. The abscissa is the frequency, with the unit being Hz, and the ordinate is the time, with the unit being ms.

[0048] Starting from the four aspects of energy, frequency, signal, and noise, a four-factor combined attribute analysis model is established, and its mathematical expression is: attr(n,t) = α × en(n,t) * β × f(n,t) * ε × sig(n,t) * φ × no(n,t)

[0049] Where: attr(n,t) is the result of the four-factor combined attribute analysis, n is the channel number of the node instrument, and t is the time; α is the energy control factor, and en(n,t) is the energy control factor; β is the frequency control factor, and f(n,t) is the frequency control factor; ε is the signal control factor, and sig(n,t) is the signal control factor; φ is the noise control factor, and no(n,t) is the noise control factor.

[0050] Step 4: Conduct a quality evaluation analysis of the four-dimensional volume dynamic distribution from the ground space direction + acquisition time direction. The four-dimensional volume includes: east-west coordinates, north-south coordinates, elevation, and acquisition time.

[0051] The analysis result along the ground space direction can provide the three-dimensional attribute volume at a certain moment. Using this three-dimensional attribute volume, the distribution law and change characteristics of the effective signal and noise along the ground space direction can be analyzed. The analysis result along the acquisition time direction can clarify the change of the three-dimensional attribute volume with time. As the acquisition time progresses, the distribution law and change characteristics of the effective signal and noise along the acquisition time direction can be clarified.

[0052] Step 5: According to the quality evaluation analysis result of the four-dimensional volume dynamic distribution, the spatial quality analysis result of all position points within the same time period and the data quality analysis result of all times at the same position point can be obtained.

[0053] Figure 6 is the spatial quality attribute map of all position points within the same time period. The abscissa is the east-west direction, the ordinate is the north-south direction, and the unit is m; Figure 7 is the data quality attribute map of all times at the same position point. The abscissa is the time, the unit is ms, and the ordinate is the energy value.

[0054] Step 6: According to the quality evaluation analysis result of the four-dimensional volume dynamic distribution, the analysis result of the moving direction and propagation speed of the noise source in the monitoring area can be obtained.

[0055] Figure 8 is the attribute map of the moving direction and propagation speed of the noise source, which includes the attribute maps of three moments. As the acquisition time progresses, the positions of most noise sources remain fixed, indicating that they are fixed interference sources. Among them, one noise source moves gradually from left to right, indicating that it is a moving interference source. Using the moving distance of this noise source and the acquisition record time, the propagation speed of this moving noise source can be calculated. The abscissa is the east-west direction, the ordinate is the north-south direction, and the unit is m.

[0056] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be equivalent replacement methods and are all included in the protection scope of the present invention.

Claims

1. A quantitative evaluation method for the quality of continuously collected data by a node instrument, characterized in that, It includes the following steps: Collect data, including continuously collecting data by the node instrument, the coordinate position information of the node instrument, and the acquisition time recorded by the node instrument; analyze the collected data in the ground space direction and in the acquisition time direction; extract the attribute information of four aspects of energy, frequency, signal, and noise from the continuously collected data by the node instrument, and establish a four-factor combined attribute analysis model; conduct a quality evaluation analysis of the four-dimensional body dynamic distribution from the ground space direction and the acquisition time direction; according to the results of the four-dimensional body dynamic distribution quality evaluation analysis, obtain the spatial quality analysis results of all position points within the same time period, the data quality analysis results of all times at the same position point, and the analysis results of the moving direction and propagation speed of the noise source in the monitoring area; The four-factor combined attribute analysis model is: attr(n,t)=α×en(n,t)*β×f(n,t)*ε×sig(n,t)*φ×no(n,t) Where: attr(n,t) is the four-factor combined attribute analysis result, n is the node instrument channel number, and t is the time; α is the energy control factor, and en(n,t) is the energy control factor; β is the frequency control factor, f(n,t) is the frequency control factor; ε is the signal control factor, sig(n,t) is the signal control factor; φ is the noise control factor, and no(n,t) is the noise control factor.

2. The evaluation method according to claim 1, wherein Analyze the collected data in the ground space direction, that is, quantitatively evaluate the data quality according to the east-west coordinate, north-south coordinate, and elevation of the node instrument: first determine the analysis time window size according to the data characteristics, and then analyze the attribute information within a single time window at different times, or use the step-by-step cumulative algorithm to calculate the attribute information within multiple consecutive time windows or multiple spaced time windows. The quantitative evaluation result is a three-dimensional spatial attribute body.

3. The evaluation method according to claim 1, wherein Analyze the collected data in the acquisition time direction, that is, quantitatively evaluate the data quality of the node instrument at different times according to the acquisition time of the node instrument: first determine the analysis time window size according to the data characteristics, and then analyze the attribute information of the data of a single node instrument, or use the step-by-step cumulative algorithm to calculate the attribute information of the data of this single node instrument and the surrounding node instruments.

4. The evaluation method according to claim 1, characterized in that, Conduct a quality evaluation analysis of the four-dimensional body dynamic distribution from the ground space direction and the acquisition time direction, and the four-dimensional body includes: east-west coordinate, north-south coordinate, elevation, and acquisition time.

5. The evaluation method according to any one of claims 1 to 3, characterized in that, The attribute information includes: energy value, abnormal amplitude, signal-to-noise ratio, single-frequency noise, instrument noise, main frequency value, peak frequency; according to the characteristics of the attribute information, it is divided into four aspects of energy, frequency, signal, and noise.

6. The evaluation method according to claim 1 or 4, characterized in that In the four-dimensional body, after the acquisition time is fixed, the distribution law and change characteristics of the effective signal and noise in the ground space direction can be analyzed; when the acquisition time changes step by step, the distribution law and change characteristics of the effective signal and noise in the acquisition time direction can be clarified.

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