A seismic data processing quality monitoring method

Abstract

The application discloses a kind of seismic data processing quality monitoring method, it is related to seismic data monitoring technical field, comprising the following steps: S1: collection historical seismic data, and according to historical seismic data is constructed seismic data processing quality sample set;S2: construction seismic data processing quality evaluation model;The seismic data processing quality monitoring technique, by inputting seismic data into quality evaluation model, the evaluation of seismic data is carried out, according to the evaluation result, the shot number of secondary product and tertiary product is obtained, according to the evaluation result, feedback rectification suggestion is automatically generated by rectification suggestion generation model, the generated evaluation result and corresponding feedback rectification suggestion are sent to relevant staff, can automatically monitor seismic data processing quality, obtain seismic data processing quality evaluation, according to the evaluation result, feedback rectification suggestion is automatically generated, so as to rectify in time, so that seismic data acquisition data has higher quality.

Description

Technical Field

[0001] This invention relates to the field of seismic data monitoring technology, specifically a method for monitoring the quality of seismic data processing. Background Technology

[0002] An earthquake, also known as a seismic event or ground vibration, is a natural phenomenon caused by the rapid release of energy in the Earth's crust, generating seismic waves. The collision and compression between tectonic plates, causing faulting and fracturing along plate boundaries and within plates, is the primary cause of earthquakes. Seismic data acquisition involves artificially generating seismic waves. On land, explosive sources are typically used. A shallow well, usually 6-30 meters deep, is drilled at a selected blasting point. The explosive charge, typically 1-25 kilograms, is placed in an electric detonator at the bottom of the well and detonated to generate seismic waves. Ground-based seismic receivers then record the ground vibration signals caused by the reflected seismic waves onto magnetic tape. This data is then sent to an indoor computing center for further processing. Seismic data processing primarily utilizes computer equipment and appropriate seismic data processing software, based on seismic wave propagation theory, to process the raw seismic data acquired in the field. This processing yields "seismic profiles" reflecting underground geological structures and information such as seismic wave amplitude, frequency, and propagation velocity reflecting changes in underground rocks. Used to study underground geological structures, find favorable oil and gas traps, and determine drilling locations.

[0003] The purpose of seismic data processing is to refine and verify seismic data, ultimately obtaining effective information that accurately reflects the underground geological conditions. Therefore, high-quality seismic data is crucial for successful oil and gas exploration. Firstly, high-quality field acquisition is the foundation of successful seismic exploration; if the raw data has serious defects, there is no way to compensate for them. Secondly, seismic data processing involves various methods and steps; deviations in each step, as well as unreasonable processing parameters, will affect the final processing results. Therefore, rigorous and scientific quality control of each step in the data processing process is a vital aspect of successful exploration. Qualitative analysis and evaluation methods are generally used to evaluate acquired seismic data during acquisition. However, qualitative analysis and evaluation methods are heavily influenced by human factors, lacking objectivity, accuracy, and impartiality. They are not only time-consuming and labor-intensive, but also difficult to identify and correct problems in a timely manner, and even more difficult to detect hidden problems in the acquisition process, resulting in poor quality control of seismic data processing. Therefore, a seismic data processing quality control method is proposed. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method for monitoring the quality of seismic data processing, which solves the problems mentioned in the background section.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for monitoring the quality of seismic data processing, comprising the following steps:

[0006] S1: Collect historical earthquake data and construct a sample set of earthquake data processing quality based on the historical earthquake data;

[0007] S2: Construct a seismic data processing quality evaluation model;

[0008] S3: Input the seismic data into the quality assessment model to evaluate the seismic data;

[0009] S4: Based on the evaluation results, obtain the number of shots for Grade II and Grade III products;

[0010] S5: Based on the evaluation results, feedback rectification opinions are automatically generated through the rectification opinion generation model;

[0011] S6: Send the generated evaluation results and corresponding feedback and rectification suggestions to the relevant staff.

[0012] Optionally, step S4, which involves obtaining the number of shots for grade II and grade III products based on the evaluation results, includes: S41: setting evaluation standards for grade II and grade III products based on the data; S42: evaluating the number of shots for grade II and grade III products based on the evaluation results and the set evaluation standards for grade II and grade III products.

[0013] Optionally, step S5, which involves automatically generating feedback rectification opinions based on the evaluation results using the rectification opinion generation model, includes: S51: Constructing a seismic data acquisition model to simulate different seismic data quality conditions; S52: Training the rectification opinion generation model based on the acquired simulated seismic data; S53: Adjusting the seismic data acquisition model based on the feedback rectification opinions generated by the rectification opinion generation model; S54: Simulating the adjusted seismic data acquisition model and verifying the acquired data using the seismic data processing quality evaluation model.

[0014] Optionally, in step S41, setting the evaluation criteria for Grade II and Grade III seismic samples based on the data, the thresholds for Grade II and Grade III seismic samples can be set based on the signal-to-noise ratio statistics of the seismic data in the exploration area, thereby calculating the number of shots for Grade II and Grade III seismic samples; the thresholds for Grade II and Grade III seismic samples can be set based on the background interference statistics of the seismic data in the exploration area, thereby calculating the number of shots for Grade II and Grade III seismic samples; the thresholds for Grade II and Grade III seismic samples can be set based on the low-frequency interference statistics of the seismic data in the exploration area, thereby calculating the number of shots for Grade II and Grade III seismic samples; and the thresholds for Grade II and Grade III seismic samples can be set based on the high-frequency interference statistics of the seismic data in the exploration area, thereby calculating the number of shots for Grade II and Grade III seismic samples.

[0015] Optionally, after step S6 sends the generated evaluation results and corresponding feedback rectification opinions to relevant staff, the relevant staff review the generated feedback rectification opinions and evaluation results, and then output them.

[0016] Optionally, the adjusted seismic data acquisition model in step S54 is simulated and the acquired data is verified through the seismic data processing quality evaluation model. If problems still occur after verification, the staff will optimize and adjust the rectification opinion generation model accordingly.

[0017] Optionally, in step S2, the seismic data processing quality evaluation model is constructed based on artificial intelligence technology.

[0018] Optionally, in step S51, which involves constructing a seismic data acquisition model to simulate different seismic data quality conditions, the seismic data acquisition model is constructed based on three-dimensional simulation technology.

[0019] This invention provides a method for monitoring the quality of seismic data processing, which has the following beneficial effects:

[0020] This seismic data processing quality monitoring method involves inputting seismic data into a quality evaluation model to evaluate the data. Based on the evaluation results, it obtains the shot counts for Class II and Class III quality. Then, based on the evaluation results, a rectification suggestion generation model automatically generates feedback rectification suggestions. The generated evaluation results and corresponding feedback rectification suggestions are sent to relevant personnel. This method can automatically monitor the quality of seismic data processing, obtain seismic data processing quality evaluations, and automatically generate feedback rectification suggestions based on the evaluation results for timely rectification, thus ensuring high-quality seismic data acquisition. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the steps and structure of the present invention;

[0022] Figure 2 This is a flowchart illustrating the steps in S4 of the present invention to obtain the number of shots for grade II and grade III products based on the evaluation results;

[0023] Figure 3 The step diagram of automatically generating feedback rectification opinions based on the evaluation results in S5 of this invention is described. Detailed Implementation

[0024] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0025] Please see Figures 1 to 3 This invention provides a technical solution: a method for monitoring the quality of seismic data processing, comprising the following steps:

[0026] S1: Collect historical earthquake data and construct a sample set of earthquake data processing quality based on the historical earthquake data;

[0027] S2: Construct a seismic data processing quality evaluation model;

[0028] S3: Input the seismic data into the quality assessment model to evaluate the seismic data;

[0029] S4: Based on the evaluation results, obtain the number of shots for Grade II and Grade III products;

[0030] S5: Based on the evaluation results, feedback rectification opinions are automatically generated through the rectification opinion generation model;

[0031] S6: Send the generated evaluation results and corresponding feedback and rectification suggestions to the relevant staff.

[0032] Furthermore, the step S4, which obtains the number of shots for Grade II and Grade III products based on the evaluation results, includes: S41: setting the evaluation criteria for Grade II and Grade III products based on the data; S42: evaluating the number of shots for Grade II and Grade III products based on the evaluation results and the set evaluation criteria for Grade II and Grade III products.

[0033] Furthermore, S5, based on the evaluation results, automatically generates feedback rectification opinions through the rectification opinion generation model, including the following steps: S51: Constructing a seismic data acquisition model to simulate different seismic data quality conditions; S52: Training the rectification opinion generation model based on the acquired simulated seismic data; S53: Adjusting the seismic data acquisition model based on the feedback rectification opinions generated by the rectification opinion generation model; S54: Simulating the adjusted seismic data acquisition model and verifying it through the acquired data using the seismic data processing quality evaluation model.

[0034] Furthermore, in step S41, which sets the evaluation criteria for Grade II and Grade III seismic samples based on the data, the thresholds for Grade II and Grade III seismic samples are set according to the signal-to-noise ratio statistics of the seismic data in the exploration area, thus allowing the number of shots for Grade II and Grade III to be calculated; the thresholds for Grade II and Grade III seismic samples are set according to the background interference statistics of the seismic data in the exploration area, thus allowing the number of shots for Grade II and Grade III to be calculated; the thresholds for Grade II and Grade III seismic samples are set according to the low-frequency interference statistics of the seismic data in the exploration area, thus allowing the number of shots for Grade II and Grade III to be calculated; and the thresholds for Grade II and Grade III seismic samples are set according to the high-frequency interference statistics of the seismic data in the exploration area, thus allowing the number of shots for Grade II and Grade III to be calculated.

[0035] Furthermore, after S6 sends the generated evaluation results and corresponding feedback rectification opinions to relevant staff, the relevant staff will review the generated feedback rectification opinions and evaluation results, and then output them to ensure that the feedback rectification opinion plan can be used.

[0036] Furthermore, the S54-adjusted seismic data acquisition model is simulated and run. The acquired data is then verified using the seismic data processing quality evaluation model. If problems still arise after verification, the staff will optimize and adjust the rectification suggestion generation model accordingly to ensure the accuracy of the feedback rectification suggestion plan generated by the rectification suggestion generation model.

[0037] Furthermore, in the step of S2, the seismic data processing quality evaluation model is constructed based on artificial intelligence technology.

[0038] Furthermore, in the step S51 of constructing a seismic data acquisition model to simulate different seismic data quality conditions, the seismic data acquisition model is constructed based on three-dimensional simulation technology and is capable of simulating different seismic data quality conditions.

[0039] In summary, this seismic data processing quality monitoring method involves several steps. First, historical seismic data is collected, and a seismic data processing quality sample set is constructed based on this data. Then, a seismic data processing quality evaluation model is built. This model is trained using the quality sample set to obtain the final seismic data processing quality evaluation model. Next, a seismic data acquisition model is constructed to simulate different seismic data quality conditions. Based on the simulated seismic data, a rectification suggestion generation model is trained. The model generates feedback rectification suggestions, which are then used to adjust the seismic data acquisition model. The adjusted model is then simulated, and the acquired data is validated using the seismic data processing quality evaluation model. In practical use, seismic data is input into the quality evaluation model for evaluation. Based on the evaluation results, the shot counts for Class II and Class III quality are obtained. The rectification suggestion generation model automatically generates feedback rectification suggestions based on the evaluation results, and the generated evaluation results and corresponding feedback rectification suggestions are sent to relevant personnel.

[0040] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method of seismic data processing quality monitoring, characterized by: The method comprises the following steps: S1: collecting historical seismic data, and constructing a seismic data processing quality sample set according to the historical seismic data; S2: constructing a seismic data processing quality evaluation model; S3: inputting the seismic data into the quality evaluation model to evaluate the seismic data; S4: obtaining the number of shots of the second and third grade products according to the evaluation results; S5: automatically generating feedback rectification suggestions through a rectification suggestion generation model according to the evaluation results; the specific steps include: S51: constructing a seismic data acquisition model to simulate different seismic data quality conditions; S52: training the rectification suggestion generation model according to the simulated seismic data acquisition conditions; S53: adjusting the seismic data acquisition model according to the feedback rectification suggestions generated by the rectification suggestion generation model; S54: simulating the adjusted seismic data acquisition model, and verifying the collected data through the seismic data processing quality evaluation model; S6: sending the generated evaluation results and corresponding feedback rectification suggestions to relevant staff. The step S4 of obtaining the number of shots of the second and third grade products according to the evaluation results comprises: S41: setting the second and third grade product evaluation standards according to the data; and S42: evaluating the number of shots of the second and third grade products according to the evaluation results and the set second and third grade product evaluation standards.

2. The method of claim 1, wherein: In the step S41 of setting the second and third grade product evaluation standards according to the data, the number of shots of the second and third grade products can be counted by setting the thresholds of the second and third grade products according to the signal-to-noise ratio of the seismic data in the exploration area, the background interference of the seismic data in the exploration area, the low-frequency interference of the seismic data in the exploration area, and the high-frequency interference of the seismic data in the exploration area.

3. The method of claim 2, wherein: After the step S6 of sending the generated evaluation results and corresponding feedback rectification suggestions to relevant staff, the relevant staff audits the generated feedback rectification suggestions and evaluation results, and then outputs.

4. The method of claim 1, wherein: In the step S54 of simulating the adjusted seismic data acquisition model, if problems still exist after verification, the staff optimizes and adjusts the rectification suggestion generation model accordingly.

5. The method of claim 1, wherein: In the step S2 of constructing the seismic data processing quality evaluation model, the seismic data processing quality evaluation model is constructed based on artificial intelligence technology.

6. The method of claim 1, wherein: In the step S51 of constructing the seismic data acquisition model to simulate different seismic data quality conditions, the seismic data acquisition model is constructed based on three-dimensional simulation technology.

7. The method of claim 1, wherein: ​

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