CN116736383A - Updating method and device of seismic wave velocity model, electronic equipment and storage medium - Google Patents
Updating method and device of seismic wave velocity model, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN116736383A CN116736383A CN202310730120.6A CN202310730120A CN116736383A CN 116736383 A CN116736383 A CN 116736383A CN 202310730120 A CN202310730120 A CN 202310730120A CN 116736383 A CN116736383 A CN 116736383A
- Authority
- CN
- China
- Prior art keywords
- seismic
- velocity model
- time
- updating
- arrival time
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 82
- 238000003860 storage Methods 0.000 title claims abstract description 15
- 238000005520 cutting process Methods 0.000 claims abstract description 44
- 238000012937 correction Methods 0.000 claims abstract description 16
- 238000003384 imaging method Methods 0.000 claims description 15
- 238000013508 migration Methods 0.000 claims description 14
- 230000005012 migration Effects 0.000 claims description 14
- 238000004590 computer program Methods 0.000 claims description 13
- 238000001914 filtration Methods 0.000 claims description 12
- 238000012545 processing Methods 0.000 claims description 12
- 238000012897 Levenberg–Marquardt algorithm Methods 0.000 claims description 9
- 238000010586 diagram Methods 0.000 claims description 7
- 238000007781 pre-processing Methods 0.000 claims description 7
- 239000002360 explosive Substances 0.000 abstract description 11
- 238000009412 basement excavation Methods 0.000 abstract description 3
- 238000012544 monitoring process Methods 0.000 description 9
- 238000004422 calculation algorithm Methods 0.000 description 7
- 239000003245 coal Substances 0.000 description 6
- 238000004891 communication Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000011160 research Methods 0.000 description 4
- 238000004088 simulation Methods 0.000 description 4
- 238000001514 detection method Methods 0.000 description 3
- 238000005065 mining Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 230000005284 excitation Effects 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 230000004807 localization Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000012804 iterative process Methods 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000005019 pattern of movement Effects 0.000 description 1
- 230000000644 propagated effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 239000011435 rock Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/30—Analysis
- G01V1/303—Analysis for determining velocity profiles or travel times
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/36—Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/30—Assessment of water resources
Abstract
According to the updating method, the updating device, the electronic equipment and the storage medium of the seismic wave velocity model, the microseism event acquired by the detector module is acquired, and the microseism event comprises the occurrence coordinates of the microseism event and the cutting time of the microseism event; acquiring P wave arrival time and S wave arrival time of the microseismic event according to the microseismic event; updating a pre-constructed seismic wave velocity model according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time; and predicting the travel time of the seismic waves through the updated seismic wave velocity model. The method does not need to use explosive to excite and generate earthquake waves to correct the velocity model underground, can correct the pre-constructed earthquake wave velocity model through the inherent microseismic event generated in the excavation work, and is a velocity model correction method which can replace an explosive source, is safe and environment-friendly and is simple to operate.
Description
Technical Field
The present invention relates to the technical field of microseism, and in particular, to a method and apparatus for updating a seismic wave velocity model, an electronic device, and a storage medium.
Background
At present, downhole directional hole fracturing of a mine stratum is performed in a bare hole in a backward way, and perforation is not performed, so that a perforation signal cannot be used for correcting a speed model; although velocity model corrections can be made based on calibrated cannons by explosive excitation. However, as the coal mine is more strict in controlling the fire attacks such as explosives, the fire attacks are blown out for many times in the fracturing area, so that the underground environment is polluted, the cost is high, potential safety hazards exist, and the requirements of green mine construction are not met.
In view of the above, there is a need to solve the problems in the prior art.
Disclosure of Invention
The invention provides a method, a device, electronic equipment and a storage medium for updating a seismic wave velocity model, which are used for solving the defect that the velocity model correction is carried out based on a calibration gun in the prior art, and realizing the velocity model correction with simplicity, greenness and low cost.
The invention provides a method for updating a seismic wave velocity model, which comprises the following steps:
acquiring a microseism event acquired by a detector module, wherein the microseism event comprises an occurrence coordinate of the microseism event and cutting time of the microseism event;
acquiring P wave arrival time and S wave arrival time of the microseismic event according to the microseismic event;
updating a pre-constructed seismic wave velocity model according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time;
and predicting the travel time of the seismic waves through the updated seismic wave velocity model.
According to the method for updating the seismic wave velocity model provided by the invention, the P wave arrival time and the S wave arrival time of the microseismic event are obtained according to the occurrence coordinates and the cutting time, and the method specifically comprises the following steps:
carrying out data preprocessing on the microseismic event, wherein the preprocessing comprises denoising processing, filtering processing and gain correction processing;
and carrying out first arrival pickup on the preprocessed microseismic event to acquire the P wave arrival time and the S wave arrival time of the microseismic event.
According to the method for updating the seismic wave velocity model provided by the invention, the pre-constructed seismic wave velocity model is updated according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time, and the method specifically comprises the following steps:
inputting the occurrence coordinates into the speed model to obtain a prediction travel time of the seismic waves;
obtaining real travel time of the seismic waves according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time;
and updating the speed model according to the predicted travel time and the real travel time.
According to the method for updating the seismic wave velocity model provided by the invention, the velocity model is updated according to the prediction travel time and the real travel time, and the method specifically comprises the following steps:
and updating the speed model according to the predicted travel time and the real travel time through a Levenberg-Marquardt algorithm.
According to the updating method of the seismic wave velocity model provided by the invention, the microseismic event acquired by the detector module is acquired, and the method specifically comprises the following steps:
and acquiring the microseismic events acquired by the detector module according to a preset time interval.
According to the method for updating the seismic wave velocity model provided by the invention, after the travel of the seismic source to the detector module is predicted through the updated seismic wave velocity model, the method further comprises the following steps:
and performing prestack migration imaging according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time to obtain a migration imaging result diagram of the microseismic event.
The invention also provides a device for updating the seismic wave velocity model, which comprises the following steps:
the acquisition unit is used for acquiring the microseism event acquired by the detector module, wherein the microseism event comprises the occurrence coordinate of the microseism event and the cutting time of the microseism event;
the computing unit is used for acquiring the P wave arrival time and the S wave arrival time of the microseismic event according to the microseismic event;
the updating unit is used for updating a pre-constructed seismic wave velocity model according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time;
and the prediction unit is used for predicting the travel time of the seismic waves through the updated seismic wave velocity model.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method for updating the seismic wave velocity model according to any one of the above when executing the program.
The invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method of updating a seismic velocity model as described in any of the above.
The invention also provides a computer program product comprising a computer program which when executed by a processor implements a method of updating a seismic velocity model as described in any of the above.
According to the updating method, the updating device, the electronic equipment and the storage medium of the seismic wave velocity model, the microseism event acquired by the detector module is acquired, and the microseism event comprises the occurrence coordinates of the microseism event and the cutting time of the microseism event; acquiring P wave arrival time and S wave arrival time of the microseismic event according to the microseismic event; updating a pre-constructed seismic wave velocity model according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time; and predicting the travel time of the seismic waves through the updated seismic wave velocity model. The method does not need to use explosive to excite and generate earthquake waves to correct the velocity model underground, can correct the pre-constructed earthquake wave velocity model through the inherent microseismic event generated in the excavation work, and is a velocity model correction method which can replace an explosive source, is safe and environment-friendly and is simple to operate.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for updating a seismic velocity model provided by the invention;
FIG. 2 is a schematic diagram of a detector module arrangement provided by the present invention;
FIG. 3 is a schematic diagram of the structure of the seismic velocity model updating apparatus provided by the present invention;
fig. 4 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
At present, downhole directional hole fracturing of a mine stratum is performed in a bare hole in a backward way, and perforation is not performed, so that a perforation signal cannot be used for correcting a speed model; although velocity model corrections can be made based on calibrated cannons by explosive excitation. However, as the coal mine is more strict in controlling the fire attacks such as explosives, the fire attacks are blown out for many times in the fracturing area, so that the underground environment is polluted, the cost is high, potential safety hazards exist, and the requirements of green mine construction are not met.
In order to solve the above problems, the present invention proposes a method for updating a seismic velocity model, which includes, but is not limited to, steps 110-140:
step 110, acquiring a microseism event acquired by a detector module, wherein the microseism event comprises an occurrence coordinate of the microseism event and a cutting time of the microseism event.
In step 110, microseismic events of the region to be detected need to be acquired by a detector module, so as to obtain occurrence coordinates of the microseismic events and cutting time of the microseismic events.
A detector is a device or apparatus for detecting and measuring a signal. In seismic monitoring, detectors, also known as seismometers, are used to measure the vibrations of seismic waves. The detector module is a set of detectors arranged in the area to be detected, as shown in fig. 2. By arranging the detector module, microseismic events of the region to be detected can be acquired.
Microseismic events refer to very small amplitude seismic activity on earth. They are usually caused by rock fracture or movement in the crust of the earth, but the scale of energy release is very small. Microseismic events are typically recorded in a seismic monitoring network. These events are of great significance in seismic studies and can help understand the pattern of movement and seismic activity of the crust. The microseismic event in the invention refers to a microseismic event generated by cutting of a coal mining machine, and the microseismic event generated by cutting of the coal mining machine is an interference signal for hydraulic fracturing microseismic monitoring. However, the invention can utilize the inherent microseismic events generated by the cutting of the coal cutter without using explosive to excite underground to generate seismic waves to correct the velocity model.
And 120, acquiring the P wave arrival time and the S wave arrival time of the microseismic event according to the microseismic event.
In step 120, the arrival time of P wave and the arrival time of S wave are obtained according to the obtained microseismic event. The P-wave arrival time and S-wave arrival time of microseismic events are important parameters for measuring the propagation time of seismic waves. P-waves (longitudinal waves) are a type of compressional wave that propagates along a medium, while S-waves (transverse waves) are a type of shear wave that propagates along a medium. P-wave arrival time refers to the time from when the seismic event occurs until the P-wave first reaches the seismic detection point. It is the initial stage of the propagation of a seismic wave in the earth's crust, typically the wave that is recorded first. The P-wave arrival information may be used to determine the time of occurrence of the earthquake and the approximate location of the seismic source. The S-wave arrival time refers to the time from when the seismic event occurs until the S-wave first arrives at the seismic detection point. The S-wave propagates slower than the P-wave and is therefore later in the sequence in which the seismic wave arrives. The arrival time information of the S-wave may help determine the magnitude of the seismic and a more accurate location of the source. By measuring the arrival of P-waves and S-waves at a plurality of seismic detection points, triangulation or other seismic localization algorithms may be performed to determine the source location and depth of the seismic. This is important for seismic research and seismic monitoring and can be used for the operation of seismic early warning systems.
And step 130, updating a pre-constructed seismic wave velocity model according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time.
In step 130, the actual travel time measured by steps 110 and 120 needs to be compared with the predicted travel time predicted by the pre-constructed seismic velocity model, and the velocity model is iteratively updated continuously using the Levenberg-Marquard (LM) algorithm until the difference between the observed travel time and the forward travel time is minimal.
Specifically, the ray tracing forward modeling method obtains travel time of the seismic source to each detector, namely travel time of an inherent microseism event generated by cutting of the coal mining machine to each detector. The ray-tracing forward method is a commonly used method of modeling the propagation of seismic waves and can be used to calculate the travel time of the seismic waves from the source to each detector. The method comprises the following specific steps:
constructing a speed model: first, a seismic velocity model needs to be built to describe the velocity distribution inside the earth. This model is typically obtained based on seismic or geophysical survey data.
Emitting rays: from the source, a beam of rays (i.e., seismic wave paths) is emitted and propagated in all directions. The path of the ray may be curved, refracted or reflected in response to the velocity changes of the different mediums in the seismic velocity model.
Calculating travel time: travel time for each ray is calculated based on the ray path and the velocity model. The travel time depends on the length of the ray and the speed of the different media that is passed.
Summarizing travel time: for each detector, the travel times of all rays to that detector are summed to obtain the total travel time of the source to each detector.
Travel time information obtained by a ray tracing forward method can be used for applications such as seismic localization, seismic waveform simulation, seismic imaging, seismic velocity model verification and the like. The method has wide application value in seismology research and earthquake monitoring.
And 140, predicting the travel time of the seismic waves through the updated seismic wave velocity model.
In step 140, travel time of the seismic wave can be predicted by the updated seismic wave velocity model. It will be appreciated that the updated seismic velocity model is more accurate than the non-updated seismic velocity model.
According to the updating method, the updating device, the electronic equipment and the storage medium of the seismic wave velocity model, the microseism event acquired by the detector module is acquired, and the microseism event comprises the occurrence coordinates of the microseism event and the cutting time of the microseism event; acquiring P wave arrival time and S wave arrival time of the microseismic event according to the microseismic event; updating a pre-constructed seismic wave velocity model according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time; and predicting the travel time of the seismic waves through the updated seismic wave velocity model. The method does not need to use explosive to excite and generate earthquake waves to correct the velocity model underground, can correct the pre-constructed earthquake wave velocity model through the inherent microseismic event generated in the excavation work, and is a velocity model correction method which can replace an explosive source, is safe and environment-friendly and is simple to operate.
According to the method for updating the seismic wave velocity model provided by the invention, the P wave arrival time and the S wave arrival time of the microseismic event are obtained according to the occurrence coordinates and the cutting time, and the method specifically comprises the following steps:
carrying out data preprocessing on the microseismic event, wherein the preprocessing comprises denoising processing, filtering processing and gain correction processing;
and carrying out first arrival pickup on the preprocessed microseismic event to acquire the P wave arrival time and the S wave arrival time of the microseismic event.
In this embodiment, in order to obtain more accurate P-wave arrival time and S-wave arrival time of a microseismic event, the microseismic event data needs to be preprocessed to reduce the influence of noise, and then first arrival pickup is performed to determine the arrival times of the P-wave and S-wave of the seismic waves.
The pre-processing of the data for the microseismic events typically includes denoising, filtering, and gain correction. These steps help to extract the microseismic signals and reduce the effects of noise.
Denoising: the objective of the denoising process is to reduce the interference of background noise on the microseismic signal. Common denoising methods include median filtering, wavelet denoising, frequency domain filtering, and the like. These methods may select the most appropriate method to reduce the noise level according to the circumstances.
And (3) filtering: the filtering process is used to selectively enhance the frequency content of the microseismic signals and reduce the effects of other frequency content. Bandpass filters are typically used to filter out low and high frequency noise to highlight the frequency characteristics of microseismic events. Common filtering methods include low-pass filtering, high-pass filtering, and band-pass filtering.
Gain correction processing: the gain correction process aims to adjust the amplitude of the microseismic signal to achieve better visualization and more accurate first arrival pickup. Common gain correction methods include linear gain correction and logarithmic gain correction. These methods can be adjusted according to the dynamic range of the signal to emphasize the microseismic signal and maintain proper contrast.
The first arrival pickup of the preprocessed microseismic event may be performed manually or automatically.
And (5) manual first arrival pickup: in manual first-arrival picking, seismology specialists carefully observe the preprocessed microseismic signals and mark the arrival times of the P-wave and the S-wave. This typically involves visualizing the arrival times of the signals to determine the arrival times of the P-wave and S-wave of the seismic waves.
Automatic first arrival pickup: automatic first arrival picking is the automatic identification and extraction of arrival times of microseismic events using computer algorithms. This may be achieved by applying signal processing and machine learning techniques. The automatic first arrival picking method can improve efficiency and perform quick first arrival extraction in a large amount of data.
The goal of the first-arrival pickup is to determine the arrival times of the P-waves and S-waves of the microseismic event, thereby providing time and location information about the earthquake. This is of great importance for seismic monitoring and seismology research.
According to the method for updating the seismic wave velocity model provided by the invention, the pre-constructed seismic wave velocity model is updated according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time, and the method specifically comprises the following steps:
inputting the occurrence coordinates into the speed model to obtain a prediction travel time of the seismic waves;
obtaining real travel time of the seismic waves according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time;
and updating the speed model according to the predicted travel time and the real travel time.
In this embodiment, the method for updating the seismic velocity model may be performed according to the following steps:
inputting the occurrence coordinates into the velocity model: based on the occurrence coordinates, it is input as an input parameter into a pre-constructed seismic velocity model. This can be used to calculate the predicted travel time of the seismic wave at that location.
Acquiring real travel time according to the occurrence coordinates, cutting time, P wave arrival time and S wave arrival time: by using the data of the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time, the real travel time of the seismic wave can be calculated. The data may be based on seismic observation data, a seismic grid, or other related measurement methods.
Updating the speed model: by comparing the predicted travel time with the actual travel time, the accuracy and error of the velocity model can be evaluated. Based on the comparison result, an update of the velocity model may be performed. One common approach is to use an inversion algorithm to adjust parameters in the velocity model by minimizing the difference between the predicted travel time and the real travel time.
This updating method allows to refine the seismic velocity model from the actual observation data, thus describing the velocity structure inside the earth more accurately. The method has important significance for seismology research, earthquake monitoring and earthquake prediction, and is beneficial to improving the accuracy of earthquake positioning and earthquake waveform simulation.
According to the method for updating the seismic wave velocity model provided by the invention, the velocity model is updated according to the prediction travel time and the real travel time, and the method specifically comprises the following steps:
and updating the speed model according to the predicted travel time and the real travel time through a Levenberg-Marquardt algorithm.
In this embodiment, the update method of the seismic velocity model may use a Levenberg-Marquardt algorithm to update the velocity model. The Levenberg-Marquardt algorithm is a nonlinear least squares optimization algorithm commonly used for parameter estimation and model fitting. The specific updating steps are as follows:
first, an objective function is constructed based on the difference between the predicted travel time and the actual travel time, and the objective function is used to measure the fitting degree of the velocity model. The Levenberg-Marquardt algorithm is then used to minimize the objective function. The algorithm will search the parameter space of the velocity model for an optimal solution to minimize the objective function.
In the iterative process of the Levenberg-Marquardt algorithm, the parameters of the velocity model are updated according to the difference between the predicted travel time and the real travel time. Through iterative optimization, the speed model can be gradually adjusted so as to be better matched with actual observation data.
The Levenberg-Marquardt algorithm has the advantage of handling non-linearity problems and has the property of fast convergence. It is widely used in updating and inverting seismic velocity models to improve the description of velocity structures within the earth. Updating the velocity model by using the Levenberg-Marquardt algorithm can improve the accuracy of seismic wave propagation simulation, and is beneficial to improving the results of applications such as seismic positioning, seismic waveform simulation, seismic prediction and the like.
According to the updating method of the seismic wave velocity model provided by the invention, the microseismic event acquired by the detector module is acquired, and the method specifically comprises the following steps:
and acquiring the microseismic events acquired by the detector module according to a preset time interval.
In this embodiment, the microseismic events acquired by the detector module are acquired according to a preset time interval.
Specifically, the time interval is determined: an appropriate time interval is set according to the needs and the actual situation, and the frequency of the microseismic events is indicated. The time interval may be determined based on the needs of the study, the purpose of the monitoring, or the requirements of the data acquisition system.
Setting a data acquisition system: the detector module is configured to collect at preset time intervals. This may be done by corresponding software or hardware settings. Ensuring that the detector module performs data acquisition during each time interval.
Acquiring microseismic event data: and after the preset time interval is finished, acquiring the acquired microseismic event data from the detector module. Such data is typically stored in digital form and may include the amplitude of the microseismic signals, time stamps and other relevant parameters.
According to the method for updating the seismic wave velocity model provided by the invention, after the travel of the seismic source to the detector module is predicted through the updated seismic wave velocity model, the method further comprises the following steps:
and performing prestack migration imaging according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time to obtain a migration imaging result diagram of the microseismic event.
In this embodiment, pre-stack migration imaging may be performed after predicting the travel of the source to the detector module to obtain a migration imaging result map of the microseismic event. The method comprises the following specific steps:
pre-stack migration data is prepared: the predicted travel time data from the seismic source to the detector module is used as input, and the data for pre-stack migration is prepared by combining information such as generation coordinates, cutting time, P wave arrival time and S wave arrival time.
Pre-stack offset imaging is performed: and processing the prepared data according to a prestack migration algorithm to generate a migration imaging result graph of the microseismic event. Prestack migration is a common seismic imaging technique that restores subsurface seismic reflection interfaces and bulk wave scattering by back-propagating and overlaying data in a seismic velocity model.
Analyzing the offset imaging results: by analyzing the offset imaging result map, information about the subsurface structure, such as the position, morphology, reflection intensity, etc., of the subsurface reflection interface can be obtained. This facilitates applications such as geologic interpretation, subsurface formation analysis, and survey target identification.
By performing prestack migration imaging, the data of microseismic events can be converted into images of subsurface structures, providing more visual and detailed geological information. This can help seismology researchers and exploration geophysicists to understand the subsurface structure in depth, further refine the seismic velocity model, and promote the development of seismic monitoring and subsurface resource exploration.
With reference to fig. 3, the following description will describe a device for updating a seismic velocity model according to the present invention, and the device for updating a seismic velocity model described below and the method for updating a seismic velocity model described above may be referred to correspondingly with each other.
The invention also provides a device for updating the seismic wave velocity model, which comprises the following steps:
an obtaining unit 310, configured to obtain a microseismic event collected by the detector module, where the microseismic event includes an occurrence coordinate of the microseismic event and a cutting time of the microseismic event;
the calculating unit 320 is configured to obtain a P-wave arrival time and an S-wave arrival time of the microseismic event according to the microseismic event;
an updating unit 330, configured to update a pre-constructed seismic wave velocity model according to the occurrence coordinates, the cutting time, the P-wave arrival time and the S-wave arrival time;
and a prediction unit 340 for predicting travel time of the seismic wave by the updated seismic wave velocity model.
Fig. 4 illustrates a physical schematic diagram of an electronic device, as shown in fig. 4, which may include: processor 410, communication interface (Communications Interface) 420, memory 430 and communication bus 440, wherein processor 410, communication interface 420 and memory 430 communicate with each other via communication bus 440. Processor 410 may invoke logic instructions in memory 430 to perform a method of updating a seismic velocity model, the method comprising:
acquiring a microseism event acquired by a detector module, wherein the microseism event comprises an occurrence coordinate of the microseism event and cutting time of the microseism event;
acquiring P wave arrival time and S wave arrival time of the microseismic event according to the microseismic event;
updating a pre-constructed seismic wave velocity model according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time;
and predicting the travel time of the seismic waves through the updated seismic wave velocity model.
Further, the logic instructions in the memory 430 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product comprising a computer program, the computer program being storable on a non-transitory computer readable storage medium, the computer program, when executed by a processor, being capable of performing a method of updating a seismic velocity model provided by the methods described above, the method comprising:
acquiring a microseism event acquired by a detector module, wherein the microseism event comprises an occurrence coordinate of the microseism event and cutting time of the microseism event;
acquiring P wave arrival time and S wave arrival time of the microseismic event according to the microseismic event;
updating a pre-constructed seismic wave velocity model according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time;
and predicting the travel time of the seismic waves through the updated seismic wave velocity model.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform a method of updating a seismic velocity model provided by the above methods, the method comprising:
acquiring a microseism event acquired by a detector module, wherein the microseism event comprises an occurrence coordinate of the microseism event and cutting time of the microseism event;
acquiring P wave arrival time and S wave arrival time of the microseismic event according to the microseismic event;
updating a pre-constructed seismic wave velocity model according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time;
and predicting the travel time of the seismic waves through the updated seismic wave velocity model.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for updating a seismic velocity model, comprising:
acquiring a microseism event acquired by a detector module, wherein the microseism event comprises an occurrence coordinate of the microseism event and cutting time of the microseism event;
acquiring P wave arrival time and S wave arrival time of the microseismic event according to the microseismic event;
updating a pre-constructed seismic wave velocity model according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time;
and predicting the travel time of the seismic waves through the updated seismic wave velocity model.
2. The method for updating a seismic velocity model according to claim 1, wherein acquiring the P-arrival time and the S-arrival time of the microseismic event according to the occurrence coordinates and the cutting time comprises:
carrying out data preprocessing on the microseismic event, wherein the preprocessing comprises denoising processing, filtering processing and gain correction processing;
and carrying out first arrival pickup on the preprocessed microseismic event to acquire the P wave arrival time and the S wave arrival time of the microseismic event.
3. The method for updating a seismic velocity model according to claim 1, wherein updating the pre-constructed seismic velocity model according to the occurrence coordinates, the cutting time, the P-wave arrival time and the S-wave arrival time specifically comprises:
inputting the occurrence coordinates into the speed model to obtain a prediction travel time of the seismic waves;
obtaining real travel time of the seismic waves according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time;
and updating the speed model according to the predicted travel time and the real travel time.
4. A method for updating a seismic velocity model according to claim 3, characterized in that said velocity model is updated according to said predicted travel time and said real travel time, in particular comprising:
and updating the speed model according to the predicted travel time and the real travel time through a Levenberg-Marquardt algorithm.
5. The method for updating a seismic velocity model according to claim 1, wherein acquiring microseismic events acquired by the geophone module comprises:
and acquiring the microseismic events acquired by the detector module according to a preset time interval.
6. The method of updating a seismic velocity model of claim 1, wherein after predicting travel of a source to the geophone module from the updated seismic velocity model, the method further comprises:
and performing prestack migration imaging according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time to obtain a migration imaging result diagram of the microseismic event.
7. An apparatus for updating a seismic velocity model, comprising:
the acquisition unit is used for acquiring the microseism event acquired by the detector module, wherein the microseism event comprises the occurrence coordinate of the microseism event and the cutting time of the microseism event;
the computing unit is used for acquiring the P wave arrival time and the S wave arrival time of the microseismic event according to the microseismic event;
the updating unit is used for updating a pre-constructed seismic wave velocity model according to the occurrence coordinates, the cutting time, the P wave arrival time and the S wave arrival time;
and the prediction unit is used for predicting the travel time of the seismic waves through the updated seismic wave velocity model.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements a method for updating a seismic velocity model according to any of claims 1 to 6 when executing the program.
9. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor implements a method of updating a seismic velocity model according to any of claims 1 to 6.
10. A computer program product comprising a computer program which, when executed by a processor, implements a method of updating a seismic velocity model according to any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310730120.6A CN116736383A (en) | 2023-06-19 | 2023-06-19 | Updating method and device of seismic wave velocity model, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310730120.6A CN116736383A (en) | 2023-06-19 | 2023-06-19 | Updating method and device of seismic wave velocity model, electronic equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116736383A true CN116736383A (en) | 2023-09-12 |
Family
ID=87907801
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310730120.6A Pending CN116736383A (en) | 2023-06-19 | 2023-06-19 | Updating method and device of seismic wave velocity model, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116736383A (en) |
-
2023
- 2023-06-19 CN CN202310730120.6A patent/CN116736383A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR101548976B1 (en) | Estimation of soil properties using waveforms of seismic surface waves | |
| RU2457513C2 (en) | Methods and systems for processing microseismic data | |
| US10073184B2 (en) | Sensor system of buried seismic array | |
| RU2518577C2 (en) | Continuous adaptive surface wave analysis for three-dimensional seismic data | |
| US20130215716A1 (en) | Integrated Passive and Active Seismic Surveying Using Multiple Arrays | |
| KR20200014387A (en) | Detection of underground structures | |
| EP2972502B1 (en) | System for seismic surveying of a subsurface volume | |
| US10345463B2 (en) | Methods and systems for using known source events in seismic data processing | |
| CN101086535A (en) | A process and program for characterising evolution of an oil reservoir over time | |
| WO2017035104A1 (en) | Velocity model seismic static correction | |
| EA032186B1 (en) | Seismic adaptive focusing | |
| Bellino et al. | An automatic method for data processing of seismic data in tunneling | |
| US20160161619A1 (en) | Systems and methods for aligning a monitor seismic survey with a baseline seismic survey | |
| CN111123359B (en) | Logging while drilling and stratum grid constrained well periphery seismic imaging detection method and device | |
| US20150268365A1 (en) | Method to characterize geological formations using secondary source seismic data | |
| US20180164454A1 (en) | Determining residual statics of survey receivers | |
| Liu et al. | Detection of karst voids at pile foundation by full-waveform inversion of single borehole sonic data | |
| US20180335531A1 (en) | Salt proximity imaging using reverse time migration of transmitted vertical seismic profile data | |
| EP3359983B1 (en) | Seismic polynomial filter | |
| CN116736383A (en) | Updating method and device of seismic wave velocity model, electronic equipment and storage medium | |
| CN110579799B (en) | Seismic acquisition observation method and system with equal travel time intervals | |
| CN110579798B (en) | Seismic acquisition observation method and system with equal reflection angle intervals | |
| Liu et al. | An inverted heterogeneous velocity model for microseismic source location in deep buried tunnels | |
| US20120143511A1 (en) | Removing ground roll from geophysical data | |
| CN113267810B (en) | Seismic exploration full-depth velocity modeling method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |