Seismic data static correction processing method and device, computer equipment and storage medium
A technology of seismic data and processing methods, applied in seismic signal processing, seismology, measuring devices, etc., can solve problems such as complex near-surface velocity modeling process, difficulty in obtaining near-surface velocity models, and influence on static correction, so as to avoid near-surface velocity Surface modeling process, effect of efficient and accurate static correction processing function
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Embodiment 1
[0048] The seismic data static correction processing method provided by this application can be applied to such as figure 1 shown in the application environment. Wherein, the computer 102 communicates with the server 104 through the network. Wherein, the terminal 102 can be, but not limited to, various personal computers, servers, notebook computers, smart phones, tablet computers and portable wearable devices, and the server 104 can be realized by an independent server or a server cluster composed of multiple servers. The user sends the target seismic data to the server 104 through the terminal 102, and the server 104 obtains the target seismic data; the target seismic data is input into the pre-trained initial picking neural network model for training, and the first arrival time data including the first first arrival time data are obtained. Picking up data; inputting the first-arrival picking-up data including the first first-arrival time data into the static correction pro...
Embodiment 2
[0050] In this example, if figure 2 As shown, a static correction processing method for seismic data is provided, which includes:
[0051] Step 210, acquiring target seismic data.
[0052] Step 220, input the target seismic data into the pre-trained initial picking neural network model for training, and obtain the first arrival picking data including the first first arrival time data.
[0053] Specifically, the data volume of the sample seismic data is extracted from the target seismic data, and the file header description information and trace header information of the sample seismic data are removed. The acquisition of the verification data volume is to generate a data volume of the same size as the seismic data volume. The value of each sampling point in the data volume is set to 0, and then the value of the sampling point corresponding to the first arrival time of each trace is set to 1, indicating The first arrival time position of this data.
[0054] Extract one piece ...
Embodiment 3
[0085] The present invention uses a deep neural network to automatically pick up the first arrival of seismic data, and after obtaining the first arrival data, uses the deep neural network to process the first arrival data to obtain the relationship between the first arrival time and the surface elevation. Using the relationship between the first arrival time and the surface elevation, by setting different target surface elevations and calculating the first arrival time of the corresponding elevation, the direct static correction process is realized. The process of direct static correction is: set a uniform surface elevation, use the deep neural network to calculate the first arrival time of the unified elevation, subtract the first arrival time of the unified elevation from the actual first arrival time, obtain the time correction amount of the target elevation, and use The time correction amount is directly subjected to static correction processing.
[0086] In this embodime...
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