Joint first arrival travel time chromatography method and system based on streamer and OBN data

Abstract

The invention relates to a combined first arrival travel time chromatography method and system based on streamer and OBN data, belongs to the technical field of seismic exploration modeling, and solves the problems that in the prior art, an existing model is low in precision, insufficient in data utilization rate and not suitable for complex geological structures. The method comprises the following steps: acquiring original towing cable seismic data and original OBN seismic data of a target work area, and after preprocessing, calculating towing cable travel time and OBN travel time of each detection point; an initial seismic velocity model of the target work area is constructed, iterative updating is carried out, during each iteration, a streamer deviation is obtained based on the initial seismic velocity model and the streamer travel time, and an OBN deviation is obtained based on the initial seismic velocity model and the OBN travel time; and calculating a slowness correction based on the streamer deviation and the OBN deviation, and updating the slowness of the initial seismic velocity model based on the slowness correction to obtain an updated initial seismic velocity model as the initial seismic velocity model of the next iteration.

Description

Technical Field

[0001] The present invention relates to the technical field of seismic exploration modeling, and in particular to a combined first arrival travel time tomography method and system based on towed cable and OBN data. Background Art

[0002] With the growing demand for marine resource exploration and the development of exploration technology, accurate acquisition of marine underground geological structure information is crucial for the exploration and development of resources such as oil and natural gas. In the field of marine seismic exploration, streamer and ocean bottom node (OBN) technology are two important data collection methods. However, the data collected by both have certain limitations when used alone, and the existing methods have many problems when processing the combination of streamer and OBN data.

[0003] On the one hand, when constructing seismic velocity models, the adaptability to complex geological structures is poor and the accuracy is often not high because the advantages of towline and OBN data are not fully integrated during the model construction process. Under complex geological conditions, the velocity model cannot accurately describe the changes in the velocity of the underground medium, resulting in large deviations in the subsequent analysis results based on the model, affecting the accurate understanding of the geological structure. On the other hand, in the process of iteratively updating the velocity model, complex geological structures will seriously affect the imaging effect. Due to the accuracy of the velocity model, it is difficult to ensure accuracy and efficiency when updating the velocity model to adapt to complex geological conditions. For example, in areas with complex geological structures, the velocity model may not accurately reflect the heterogeneity and anisotropy of the strata, so that the calculated deviation cannot truly reflect the actual situation, ultimately resulting in poor imaging effects. At the same time, the towline and OBN data have the problem of insufficient data utilization, and fail to fully explore the geological information hidden in the data, so that the constructed velocity model and imaging results cannot meet the needs of high-precision exploration. Summary of the invention

[0004] In view of the above analysis, the embodiments of the present invention aim to provide a joint first arrival travel time tomography method and system based on streamer and OBN data to solve the problems of low accuracy, insufficient data utilization and inapplicability to complex geological structures of existing models.

[0005] In a first aspect, an embodiment of the present invention provides a joint first arrival travel time tomography method based on streamer and OBN data, the method comprising the following steps:

[0006] The original streamer seismic data of the target work area is obtained, and after preprocessing, the first arrival time of the streamer seismic data of each detection point is picked up from the original streamer seismic data;

[0007] Obtain the original OBN seismic data of the target work area, and after preprocessing, pick up the first arrival time of the OBN seismic data of each detection point from the original OBN seismic data;

[0008] The streamer travel time of each detection point is calculated based on the first arrival time of the streamer seismic data of each detection point and the recorded shot point firing time, and the OBN travel time of each detection point is calculated based on the first arrival time of the OBN seismic data of each detection point and the recorded shot point firing time;

[0009] An initial seismic velocity model of the target work area is constructed, and the initial seismic velocity model is iteratively updated until the iterative convergence condition is met to obtain the final seismic velocity model, and the first arrival travel time tomography of the target work area is performed based on the final seismic velocity model; in each iteration, the towline deviation is obtained based on the initial seismic velocity model and the towline travel time, and the OBN deviation is obtained based on the initial seismic velocity model and the OBN travel time; the slowness correction is calculated based on the towline deviation and the OBN deviation, and the slowness of the initial seismic velocity model is updated based on the slowness correction to obtain the updated initial seismic velocity model as the initial seismic velocity model for the next iteration.

[0010] As a further improvement of the present application, obtaining the streamer deviation based on the initial seismic velocity model and the streamer travel time, and obtaining the OBN deviation based on the initial seismic velocity model and the OBN travel time include:

[0011] Perform path ray tracing on the target work area to obtain the shortest streamer seismic wave propagation path and the shortest OBN seismic wave propagation path corresponding to each detection point;

[0012] Based on the initial seismic velocity model and the shortest streamer seismic wave propagation path and the shortest OBN seismic wave propagation path corresponding to each detection point, the predicted streamer travel time and the predicted OBN travel time corresponding to each detection point are output;

[0013] The difference between the predicted streamer travel time and the streamer travel time of each detection point is calculated to obtain the streamer deviation, and the difference between the predicted OBN travel time and the OBN travel time of each detection point is calculated to obtain the OBN deviation.

[0014] As a further improvement of the present application, path ray tracing is performed on the target work area to obtain the shortest streamer seismic wave propagation path and the shortest OBN seismic wave propagation path corresponding to each detection point, including:

[0015] Based on the geological structure information of the target work area, the strata of the target work area are gridded to obtain a plurality of grid units;

[0016] Based on the initial seismic velocity model, a corresponding velocity value is assigned to each grid cell;

[0017] Calculate the travel time from each grid cell to the adjacent grid cells based on the velocity value assigned to each grid cell;

[0018] Each grid unit is regarded as a node, the connection between adjacent grid units is regarded as an edge, and the travel time between adjacent grid units is regarded as the weight of the edge to generate a strip diagram of the target work area;

[0019] Based on the Dijkstra algorithm, the strip diagram of the target work area is processed to obtain the shortest streamer seismic wave propagation path from the shot point to the streamer detection point and the shortest OBN seismic wave propagation path from the shot point to each OBN detection point.

[0020] As a further improvement of this application, the final seismic velocity model is:

[0021]

[0022] Among them, s min To detect the minimum value of slowness data, s max To detect the maximum value of slowness data, z i is the depth of the geological layer, z min To detect the minimum value of depth data, Δs n is the slowness correction for the nth iteration.

[0023] As a further improvement of the present application, the calculation of the slowness correction based on the streamer deviation and the OBN deviation includes:

[0024] Perform path ray tracing on the initial seismic initial velocity model to generate the shortest streamer seismic wave propagation path and the shortest OBN seismic wave propagation path;

[0025] Construct the seismic tomography equation, as shown in formula (2);

[0026]

[0027] Among them, ΔS is the slowness correction, ΔT TS is the tow cable deviation; ΔT OBN is the OBN deviation, L TS is the seismic wave propagation path of the end streamer, L OBN is the shortest OBN seismic wave propagation path, is the towline bias weight, is the OBN bias weight, n is the number of iterations;

[0028] The slowness correction is solved based on the seismic tomography equation.

[0029] As a further improvement of the present application, the tow cable deviation weight is as shown in formula (3);

[0030]

[0031] The OBN deviation weight is calculated as shown in formula (4);

[0032]

[0033] in, is the chi-square value of the streamer, is the OBN chi-square value.

[0034] As a further improvement of the present application, the streamer chi-square value is calculated as shown in formula (5);

[0035]

[0036] Among them, N TS is the number of streamer detection points, σ TS is the streamer standard deviation, i is the streamer detection point number;

[0037] The OBN chi-square value is shown in formula (6);

[0038]

[0039] Among them, N OBN is the number of OBN detection points, σ OBN is the OBN standard deviation, and i is the OBN detection point number.

[0040] As a further improvement of this application, the iterative convergence condition is:

[0041] The streamer chi-square value and the OBN chi-square value are less than or equal to 1 or reach the preset upper limit of the number of iterations.

[0042] As a further improvement of the present application, the target work area strip map is processed based on the Dijkstra algorithm to obtain the shortest streamer seismic wave propagation path from the shot point to the streamer detection point and the shortest OBN seismic wave propagation path from the shot point to each OBN detection point, including:

[0043] For any streamer or OBN detection point, the shortest propagation path from the shot point to the detection point is obtained by the following steps:

[0044] Create a visited node set and an unvisited node set. The initial visited node set includes the cannon points, and the initial unvisited node set includes all nodes except the cannon points.

[0045] Search the node closest to the shot point in the unvisited node set, remove it from the unvisited node set, and add it to the visited node set; for each node added to the visited node set, continue to search for the node closest to the node; repeat this operation until the detection point is added to the visited node set;

[0046] Generate the shortest propagation path from the shot point to the receiver point based on the set of visited nodes.

[0047] In a second aspect, an embodiment of the present invention provides a joint first arrival travel time tomography system based on streamer and OBN data, the system comprising:

[0048] The streamer seismic data acquisition module is used to acquire the original streamer seismic data of the target work area, and after preprocessing, pick up the first arrival time of the streamer seismic data of each detection point from the original streamer seismic data;

[0049] The OBN seismic data acquisition module is used to acquire the original OBN seismic data of the target work area, and after preprocessing, pick up the first arrival time of the OBN seismic data of each detection point from the original OBN seismic data;

[0050] A travel time calculation module, used to calculate the towline travel time of each detection point based on the first arrival time of the towline seismic data of each detection point and the recorded shot point firing time, and to calculate the OBN travel time of each detection point based on the first arrival time of the OBN seismic data of each detection point and the recorded shot point firing time;

[0051] The model training module is used to construct an initial seismic velocity model of the target work area, iteratively update the initial seismic velocity model until the iterative convergence condition is met, obtain the final seismic velocity model, and perform first arrival travel time tomography on the target work area based on the final seismic velocity model; in each iteration, the towline deviation is obtained based on the initial seismic velocity model and the towline travel time, and the OBN deviation is obtained based on the initial seismic velocity model and the OBN travel time; the slowness correction is calculated based on the towline deviation and the OBN deviation, and the slowness of the initial seismic velocity model is updated based on the slowness correction to obtain the updated initial seismic velocity model as the initial seismic velocity model for the next iteration.

[0052] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0053] 1. The present invention obtains the original towed cable seismic data and the original OBN seismic data of the target work area, and picks up the first arrival time of the towed cable and OBN seismic data respectively after preprocessing, and then calculates the travel time in combination with the shot point firing time, and constructs the seismic initial velocity model using the characteristics of the towed cable and OBN data. In the iterative update process, the velocity model is further optimized by calculating the deviation and slowness correction of the towed cable and OBN, thereby improving the model accuracy.

[0054] 2. In the process of constructing and iterating the velocity model, the present invention integrates the streamer and OBN data, jointly processes the two types of data, and uses geological structure information when calculating the streamer and OBN deviations and slowness corrections, thereby improving data utilization.

[0055] 3. The present invention constructs a model based on the slowness and depth data of the target work area, and uses the towline and OBN data for iterative updates. It can effectively adapt to complex geological structures, including complex stratigraphic stratification, faults, and areas with drastic velocity changes, overcoming the problem that existing technologies cannot be applied to complex geological structures.

[0056] In the present invention, the above-mentioned technical solutions can also be combined with each other to achieve more preferred combination solutions. Other features and advantages of the present invention will be described in the subsequent description, and some advantages can become obvious from the description, or can be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained through the contents particularly pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings are only used for the purpose of illustrating specific embodiments and are not to be considered as limiting the present invention. In the entire drawings, the same reference symbols represent the same components;

[0058] Figure 1 A schematic flow chart of a combined first arrival travel time tomography method based on streamer and OBN data provided by one embodiment of the present invention;

[0059] Figure 2 A target work area model diagram provided by an embodiment of the present invention;

[0060] Figure 3 A schematic diagram of tow cable-only chromatography results provided by one embodiment of the present invention;

[0061] Figure 4 A schematic diagram of the results of a joint first arrival travel time tomography method based on streamer and OBN data provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0062] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0063] A specific embodiment of the present invention discloses a combined first arrival travel time tomography method based on streamer and OBN data, such as Figure 1 As shown, including:

[0064] S1. Obtain the original streamer seismic data of the target work area, and after preprocessing, pick up the first arrival time of the streamer seismic data of each detection point from the original streamer seismic data;

[0065] Streamer seismic data is seismic wave information collected by streamer equipment in marine seismic exploration. The streamer is a long cable with multiple detectors arranged at equal intervals. During marine exploration, the exploration ship moves on the sea surface dragging the streamer. When seismic waves propagate toward the seabed and underground, they will be reflected and refracted when encountering different geological layers. The reflected and refracted waves return to the sea surface and are received by the detectors on the streamer. The received signals are the original streamer seismic data. The first arrival time of the streamer seismic data is the time when the detectors on the streamer first detect the seismic wave.

[0066] Preprocessing includes denoising the acquired raw streamer seismic data. For example, high-frequency and low-frequency noise in the raw streamer seismic data are removed by bandpass filters. High-frequency noise is caused by factors such as electronic interference of the instrument itself, and low-frequency noise comes from environmental factors such as ocean currents and waves.

[0067] S2, obtaining the original OBN seismic data of the target work area, and after preprocessing, picking up the first arrival time of the OBN seismic data of each detection point from the original OBN seismic data;

[0068] OBN seismic data is seismic wave information collected by OBN seismic data acquisition devices deployed at the Ocean Bottom Node (OBN). When the source excites seismic waves, the seismic waves propagate to the seabed, and the OBN seismic data acquisition device can receive reflected and refracted wave signals from different directions underground. Since the OBN seismic data acquisition device is located on the seabed, it is closer to the shallow underground layer and has a stronger ability to capture detailed information of shallow geological structures. The first arrival time of OBN seismic data is the time when the OBN seismic data acquisition device first collects seismic waves.

[0069] The preprocessing of the original OBN seismic data is the same as the preprocessing of the acquired original streamer seismic data, and will not be described in detail here.

[0070] When collecting streamer seismic data and OBN seismic data, the shot points are usually located underwater. The specific depth depends on the exploration target and equipment capabilities. In marine seismic exploration, the shot points are located from a few meters to tens of meters below the water surface to ensure that the seismic waves can effectively propagate to the target strata. When the shot points are excited, strong seismic waves are generated, which propagate in the seawater and reach the seabed. On the seabed, seismic waves will encounter strata with different densities and elastic properties, penetrate different strata and refract into the underground.

[0071] When arranging the shot points, the direction of the shot point excitation should be perpendicular or oblique to the formation direction to generate effective refraction waves. In areas with simpler geological structures, the shot point spacing can be appropriately increased; while in areas with complex geological structures, the shot point spacing should be reduced to ensure that the refraction wave information can be accurately obtained. The arrangement of the detector points should be arranged in a linear or grid shape to cover the target work area. The distance between the detector points is determined based on the expected formation thickness and velocity changes. In shallow layers and areas with drastic velocity changes, the distance between the detector points is smaller to accurately capture the refraction wave signal.

[0072] For example, Figure 2 As shown. The target work area is 10 km long horizontally, 5 km deep vertically, and the seawater layer is 0.5 km deep. When acquiring the original streamer seismic data of the target work area, the distance between the shot points is 25 m, the distance between the detection points is 12.5 m, and the length of the streamer is 5000 m; when acquiring the original OBN seismic data of the target work area, the detection points are located at the bottom of the seawater, the distance between the detection points is 200 m, and 51 OBN seismic data acquisition devices are deployed.

[0073] S3, calculating the towline travel time of each detection point based on the first arrival time of the towline seismic data of each detection point and the recorded shot point firing time, and calculating the OBN travel time of each detection point based on the first arrival time of the OBN seismic data of each detection point;

[0074] The travel time is the time it takes for a seismic wave to propagate from a shot point through various geological media to a detection point. Specifically, the towline travel time is the time from when the shot point excites the seismic wave to when a certain detection point on the towline receives the first valid seismic wave signal, which is the towline travel time of the detection point. The OBN travel time is the time from when the shot point excites the seismic wave to when the OBN detection point receives the first valid seismic wave signal, which is the OBN travel time of the detection point.

[0075] S4. Construct an initial seismic velocity model of the target work area based on the geological structure information of the target work area obtained from the exploration, iteratively update the initial seismic velocity model until the iterative convergence condition is met to obtain the final seismic velocity model, and perform first-arrival travel time tomography on the target work area based on the final seismic velocity model; in each iteration, obtain the towline deviation based on the initial seismic velocity model and the towline travel time, and obtain the OBN deviation based on the initial seismic velocity model and the OBN travel time; calculate the slowness correction based on the towline deviation and the OBN deviation, and update the slowness of the initial seismic velocity model based on the slowness correction to obtain the updated initial seismic velocity model as the initial seismic velocity model for the next iteration.

[0076] The initial seismic velocity model of the target area is constructed based on the geological structure information of the target area obtained through exploration. The geological structure information of the target area can be obtained by obtaining the geological exploration report or drilling data of the target area. The geological exploration report includes information such as the stratigraphic distribution, lithological characteristics, and geological structure (such as faults, folds, etc.) of the target area. The drilling data can reflect the lithology and stratigraphic conditions at different depths underground.

[0077] Different types of geological layers can be identified based on the distribution of strata, lithological characteristics and geological structures. Each geological layer has its own specific seismic wave propagation velocity. Slowness data can be obtained based on different seismic wave propagation velocities. The seismic wave propagation velocities of different rock layer types can be obtained from geological literature or measured in advance from laboratory tests. Borehole data provides depth information of underground rock layers. The depth distribution of different geological layers can be determined by analyzing borehole core samples.

[0078] The initial seismic velocity model is:

[0079]

[0080] Among them, s min To detect the minimum value of slowness data, s max To detect the maximum value of slowness data, Z i is the depth of the geological layer, z min It is the minimum value of the detected depth data.

[0081] Further, obtaining the streamer deviation based on the initial seismic velocity model and the streamer travel time, and obtaining the OBN deviation based on the initial seismic velocity model and the OBN travel time includes:

[0082] S401: Perform path ray tracing on the target work area to obtain the shortest streamer seismic wave propagation path and the shortest OBN seismic wave propagation path corresponding to each detection point.

[0083] Ray tracing is a method used in seismic exploration to determine the propagation path of seismic waves and calculate travel time. First, an initial seismic velocity model is constructed based on the geological structure information of the target area obtained from the exploration.

[0084] After the initial model is established, the locations of the source and receiver points for ray tracing can be determined through the seismic monitoring network or a specific survey layout.

[0085] Furthermore, path ray tracing is performed on the target work area to obtain the shortest streamer seismic wave propagation path and the shortest OBN seismic wave propagation path corresponding to each detection point, including:

[0086] Based on the geological structure information of the target work area, the strata of the target work area are gridded to obtain a plurality of grid units;

[0087] Based on the initial seismic velocity model, a corresponding velocity value is assigned to each grid cell;

[0088] The shortest streamer seismic wave propagation path and the shortest OBN seismic wave propagation path corresponding to each detection point are generated based on the Dijkstra algorithm.

[0089] Specifically, the shortest streamer seismic wave propagation path and the shortest OBN seismic wave propagation path corresponding to each detection point are generated based on the Dijkstra algorithm, including:

[0090] The path ray tracing is performed on the target work area to obtain the shortest streamer seismic wave propagation path and the shortest OBN seismic wave propagation path corresponding to each detection point, including:

[0091] Based on the geological structure information of the target work area, the strata of the target work area are gridded to obtain a plurality of grid units;

[0092] Based on the initial seismic velocity model, a corresponding velocity value is assigned to each grid cell;

[0093] Calculate the travel time from each grid cell to the adjacent grid cells based on the velocity value assigned to each grid cell;

[0094] Each grid unit is regarded as a node, the connection between adjacent grid units is regarded as an edge, and the travel time between adjacent grid units is regarded as the weight of the edge to generate a strip diagram of the target work area;

[0095] Based on the Dijkstra algorithm, the strip diagram of the target work area is processed to obtain the shortest streamer seismic wave propagation path from the shot point to the streamer detection point and the shortest OBN seismic wave propagation path from the shot point to each OBN detection point.

[0096] When the target work area is gridded, the size and shape of the grid unit are determined according to the scope of the target work area and the required accuracy. According to the initial seismic velocity model, each grid unit is assigned a corresponding seismic wave propagation velocity value. A grid unit can have 4 or 8 adjacent grid units, and there are multiple paths from the shot point to the detection point.

[0097] Furthermore, for any streamer detection point or OBN detection point, the shortest propagation path from the shot point to the detection point is obtained by the following steps:

[0098] Create a visited node set and an unvisited node set. The initial visited node set includes the cannon points, and the initial unvisited node set includes all nodes except the cannon points.

[0099] Search the node closest to the shot point in the unvisited node set, remove it from the unvisited node set, and add it to the visited node set; for each node added to the visited node set, continue to search for the node closest to the node; repeat this operation until the detection point is added to the visited node set;

[0100] Generate the shortest propagation path from the shot point to the receiver point based on the set of visited nodes.

[0101] The Dijkstra algorithm is a method for finding the shortest path between nodes in a weighted graph. When generating the shortest path from the shot point to each detection point based on the Dijkstra algorithm, each grid unit is regarded as a node in the graph, and the connection between adjacent grid units is regarded as an edge. The weight of the edge is the travel time between adjacent grid units. The grid model of the entire work area is converted into a weighted graph. Two types of attribute information are assigned to each node, one is the distance information from the node to the shot point, and the other is the predecessor node information, which indicates the node before the current node on the path from the shot point to the current node.

[0102] Based on the Dijkstra algorithm, the strip diagram of the target work area is processed to obtain the shortest streamer seismic wave propagation path from the shot point to the streamer detection point and the shortest OBN seismic wave propagation path from the shot point to each OBN detection point. First, two sets are created, the visited node set and the unvisited node set. Initially, the visited node set only includes the shot point, and the unvisited node set includes the nodes corresponding to all grid units except the shot point. Search the node closest to the shot point in the unvisited node set, remove it from the unvisited node set, and add it to the visited node set. At the same time, for each adjacent node of the node, calculate the distance from the shot point through this node to the adjacent node, and add the distance from the node to the shot point to the weight of the edge between this node and the adjacent node. If the calculated distance is less than the distance to the shot point previously recorded by the adjacent node, update the distance from the adjacent node to the shot point to the newly calculated value, and mark the predecessor node of the adjacent node as the current node. Repeat the operation of searching, moving nodes and updating adjacent node information in the unvisited node set until all detection points are added to the visited node set. Starting from the detection point, trace back to the shot point based on the predecessor node information, and the node sequence passed through is the shortest path from the shot point to the detection point.

[0103] S402, outputting the predicted streamer travel time and the predicted OBN travel time corresponding to each detection point based on the initial seismic velocity model and the shortest streamer seismic wave propagation path and the shortest OBN seismic wave propagation path corresponding to each detection point;

[0104] For the shortest streamer seismic wave propagation path and the shortest OBN seismic wave propagation path corresponding to each detection point, the propagation time of the seismic wave on the path is calculated by dividing the length of each grid cell on the path by the velocity of the cell, and the velocity of each grid cell is output through the initial seismic velocity model.

[0105] S403, calculating the difference between the predicted towline travel time of each detection point and the towline travel time to obtain the towline deviation, and calculating the difference between the predicted OBN travel time of each detection point and the OBN travel time to obtain the OBN deviation.

[0106] The streamer deviation is the difference between the predicted streamer travel time and the streamer travel time at each detection point, and the OBN deviation is the difference between the predicted OBN travel time and the OBN travel time at each detection point.

[0107] Furthermore, the initial seismic velocity model is iteratively updated. In each iteration, the slowness correction is calculated based on the streamer deviation and the OBN deviation, and the slowness of the initial seismic velocity model is updated based on the slowness correction to obtain an updated initial seismic velocity model as the initial seismic velocity model for the next iteration.

[0108] In seismology, slowness is used to describe the characteristics of seismic wave propagation in a medium. It is the inverse of velocity and its unit is seconds per meter (s / m). The slowness correction is a parameter for iteratively adjusting the initial seismic velocity model. In each iteration, the slowness correction is calculated based on the streamer deviation and OBN deviation. The slowness of the initial seismic velocity model is updated based on the slowness correction to obtain the updated initial seismic velocity model as the initial seismic velocity model for the next iteration.

[0109] The slowness correction calculated based on the streamer deviation and OBN deviation includes:

[0110] Construct the seismic tomography equation, as shown in formula (2);

[0111]

[0112] Among them, ΔS is the slowness correction, ΔT TS is the tow cable deviation; ΔT OBN is the OBN deviation, L TS is the shortest streamer seismic wave propagation path, L OBN is the shortest OBN seismic wave propagation path, is the towline bias weight, is the OBN bias weight, n is the number of iterations;

[0113] The slowness correction can be obtained by transforming and solving the seismic tomography equation.

[0114] Furthermore, the tow cable deviation weight is calculated as shown in formula (3);

[0115]

[0116] The OBN deviation weight is calculated as shown in formula (4);

[0117]

[0118] in, is the chi-square value of the streamer, is the OBN chi-square value.

[0119] The chi-square value of the streamer is shown in formula (5);

[0120]

[0121] Among them, N TS is the number of streamer detection points, σ TS is the streamer standard deviation, i is the streamer detection point number;

[0122] The OBN chi-square value is shown in formula (6);

[0123]

[0124] Among them, N OBN is the number of OBN detection points, σ OBN is the OBN standard deviation, and i is the OBN detection point number.

[0125] The iterative convergence condition of the initial seismic velocity model is that the streamer chi-square value and the OBN chi-square value are less than or equal to 1 or the preset upper limit of the number of iterations is reached.

[0126] The streamer chi-square value is used to measure the difference between the observed value of the streamer travel time and the theoretical value predicted based on the current initial seismic velocity model, and the OBN chi-square value is used to measure the difference between the observed value of the OBN travel time and the theoretical value predicted based on the current initial seismic velocity model.

[0127] When the tow cable chi-square value and the OBN chi-square value are less than or equal to 1, it means that the tow cable travel time and the OBN travel time predicted by the current initial seismic velocity model are very close to the actually observed travel time, and the model has achieved a high accuracy. The purpose of setting a preset upper limit on the number of iterations is to prevent the iteration process from falling into an infinite loop or excessive iterations. During implementation, due to data noise, complex geological structures and other reasons, the tow cable chi-square value and the OBN chi-square value may not converge to the ideal state of less than or equal to 1. When the number of iterations reaches the preset upper limit, the iteration is stopped even if the tow cable chi-square value and the OBN chi-square value do not meet the condition of less than or equal to 1. The preset upper limit on the number of iterations can be set to 20-50 times.

[0128] When the iterative convergence conditions are met, the final seismic velocity model is obtained:

[0129]

[0130] Among them, s min To detect the minimum value of slowness data, s max To detect the maximum value of slowness data, Z i is the depth of the geological layer, z min To detect the minimum value of depth data, Δs n is the slowness correction for the nth iteration.

[0131] In order to verify the effectiveness of this embodiment, Figure 3 This is a schematic diagram of the first arrival wave tomography results obtained when only the streamer data is used. Figure 4 A schematic diagram of the first arrival wave tomography results of the combined first arrival travel time tomography method based on towed cable and OBN data provided in an embodiment of the present invention. Comparing the two figures, it can be seen that when the depth is greater than 2.5 km, the reflection of the stratum structure is not accurate enough when only the towed cable data is used, and the deep effect is not good. There are many gray gradient areas, which indicates that the resolution ability of the deep underground structure is weak. The tomographic imaging results of the combined first arrival travel time tomography method based on towed cable and OBN data provided in an embodiment of the present invention can show a clearer velocity structure and stratum structure.

[0132] Compared with the prior art, the present embodiment provides a joint first arrival travel time tomography method based on streamer and OBN data, which improves data utilization by fusing streamer and OBN data and jointly processing the two types of data. It also uses geological structure information when calculating streamer and OBN deviations and slowness corrections, and can effectively adapt to complex geological structures, including complex stratigraphic stratification, faults, and areas with drastic velocity changes, thereby overcoming the problem that the prior art cannot be applied to complex geological structures. It also uses streamer and OBN data for iterative updates, thereby improving the accuracy of the model.

[0133] Another specific embodiment of the present invention discloses a combined first arrival travel time tomography system based on streamer and OBN data, comprising:

[0134] The streamer seismic data acquisition module is used to acquire the original streamer seismic data of the target work area, and after preprocessing, pick up the first arrival time of the streamer seismic data of each detection point from the original streamer seismic data;

[0135] The OBN seismic data acquisition module is used to acquire the original OBN seismic data of the target work area, and after preprocessing, pick up the first arrival time of the OBN seismic data of each detection point from the original OBN seismic data;

[0136] A travel time calculation module, used to calculate the towline travel time of each detection point based on the first arrival time of the towline seismic data of each detection point and the recorded shot point firing time, and to calculate the OBN travel time of each detection point based on the first arrival time of the OBN seismic data of each detection point and the recorded shot point firing time;

[0137] The model training module is used to construct an initial seismic velocity model of the target work area based on the geological structure information of the target work area obtained from the exploration, iteratively update the initial seismic velocity model until the iterative convergence condition is met to obtain the final seismic velocity model, and perform first-arrival travel time tomography on the target work area based on the final seismic velocity model; in each iteration, the towline deviation is obtained based on the initial seismic velocity model and the towline travel time, and the OBN deviation is obtained based on the initial seismic velocity model and the OBN travel time; the slowness correction is calculated based on the towline deviation and the OBN deviation, and the slowness of the initial seismic velocity model is updated based on the slowness correction to obtain the updated initial seismic velocity model as the initial seismic velocity model for the next iteration.

[0138] It can be understood that the combined first-arrival travel time tomography system based on streamer and OBN data corresponds to each step in a combined first-arrival travel time tomography method based on streamer and OBN data, which will not be described in detail here.

[0139] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0140] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A combined first arrival travel time tomography method based on streamer and OBN data, characterized in that: The method comprises the following steps: The original streamer seismic data of the target work area is obtained, and after preprocessing, the first arrival time of the streamer seismic data of each detection point is picked up from the original streamer seismic data; Obtain the original OBN seismic data of the target work area, and after preprocessing, pick up the first arrival time of the OBN seismic data of each detection point from the original OBN seismic data; The streamer travel time of each detection point is calculated based on the first arrival time of the streamer seismic data of each detection point and the recorded shot point firing time, and the OBN travel time of each detection point is calculated based on the first arrival time of the OBN seismic data of each detection point and the recorded shot point firing time; An initial seismic velocity model of the target work area is constructed based on the geological structure information of the target work area obtained from exploration. The initial seismic velocity model is iteratively updated until the iterative convergence condition is met to obtain the final seismic velocity model. The first arrival travel time tomography of the target work area is performed based on the final seismic velocity model. In each iteration, the towline deviation is obtained based on the initial seismic velocity model and the towline travel time, and the OBN deviation is obtained based on the initial seismic velocity model and the OBN travel time. The slowness correction is calculated based on the towline deviation and the OBN deviation, and the slowness of the initial seismic velocity model is updated based on the slowness correction to obtain the updated initial seismic velocity model as the initial seismic velocity model for the next iteration.

2. The method according to claim 1, characterized in that The streamer deviation is obtained based on the initial seismic velocity model and the streamer travel time. The OBN deviation is obtained based on the initial seismic velocity model and the OBN travel time, including: Perform path ray tracing on the target work area to obtain the shortest streamer seismic wave propagation path and the shortest OBN seismic wave propagation path corresponding to each detection point; Based on the initial seismic velocity model and the shortest streamer seismic wave propagation path and the shortest OBN seismic wave propagation path corresponding to each detection point, the predicted streamer travel time and the predicted OBN travel time corresponding to each detection point are output; The difference between the predicted streamer travel time and the streamer travel time of each detection point is calculated to obtain the streamer deviation, and the difference between the predicted OBN travel time and the OBN travel time of each detection point is calculated to obtain the OBN deviation.

3. The method according to claim 2, characterized in that The path ray tracing is performed on the target work area to obtain the shortest streamer seismic wave propagation path and the shortest OBN seismic wave propagation path corresponding to each detection point, including: Based on the geological structure information of the target work area, the strata of the target work area are gridded to obtain a plurality of grid units; Based on the initial seismic velocity model, a corresponding velocity value is assigned to each grid cell; Calculate the travel time from each grid cell to the adjacent grid cells based on the velocity value assigned to each grid cell; Each grid unit is regarded as a node, the connection between adjacent grid units is regarded as an edge, and the travel time between adjacent grid units is regarded as the weight of the edge to generate a strip diagram of the target work area; Based on the Dijkstra algorithm, the strip diagram of the target work area is processed to obtain the shortest streamer seismic wave propagation path from the shot point to the streamer detection point and the shortest OBN seismic wave propagation path from the shot point to each OBN detection point.

4. The method according to claim 3, characterized in that The final seismic velocity model is: Among them, s min To detect the minimum value of slowness data, s max To detect the maximum value of slowness data, z i is the depth of the geological layer, z min To detect the minimum value of depth data, Δs n is the slowness correction for the nth iteration.

5. The method according to claim 4, characterized in that The calculation of the slowness correction based on the streamer deviation and the OBN deviation includes: Construct the seismic tomography equation, as shown in formula (2); Among them, ΔS is the slowness correction, ΔT TS is the tow cable deviation; ΔT OBN is the OBN deviation, L TS is the shortest streamer seismic wave propagation path, L OBN is the shortest OBN seismic wave propagation path, is the towline bias weight, is the OBN bias weight, n is the number of iterations; The slowness correction is solved based on the seismic tomography equation.

6. The method according to claim 5, characterized in that The tow cable deviation weight is shown in formula (3); The OBN deviation weight is calculated as shown in formula (4); in, is the chi-square value of the streamer, is the OBN chi-square value.

7. The method according to claim 6, characterized in that The chi-square value of the streamer is shown in formula (5); Among them, N TS is the number of streamer detection points, σ TS is the streamer standard deviation, i is the streamer detection point number; The OBN chi-square value is shown in formula (6); Among them, N OBN is the number of OBN detection points, σ OBN is the OBN standard deviation, and i is the OBN detection point number.

8. The method according to claim 7, characterized in that The iterative convergence condition is: The streamer chi-square value and the OBN chi-square value are less than or equal to 1 or reach the preset upper limit of the number of iterations.

9. The method according to claim 3, characterized in that: Based on the Dijkstra algorithm, the strip diagram of the target work area is processed to obtain the shortest streamer seismic wave propagation path from the shot point to the streamer detection point and the shortest OBN seismic wave propagation path from the shot point to each OBN detection point, including: For any streamer or OBN detection point, the shortest propagation path from the shot point to the detection point is obtained by the following steps: Create a visited node set and an unvisited node set. The initial visited node set includes the cannon points, and the initial unvisited node set includes all nodes except the cannon points. Search the node closest to the shot point in the unvisited node set, remove it from the unvisited node set, and add it to the visited node set; for each node added to the visited node set, continue to search for the node closest to the node; repeat this operation until the detection point is added to the visited node set; Generate the shortest propagation path from the shot point to the receiver point based on the set of visited nodes.

10. A combined first arrival travel time tomography system based on streamer and OBN data, characterized in that: The system comprises: The streamer seismic data acquisition module is used to acquire the original streamer seismic data of the target work area, and after preprocessing, pick up the first arrival time of the streamer seismic data of each detection point from the original streamer seismic data; The OBN seismic data acquisition module is used to acquire the original OBN seismic data of the target work area, and after preprocessing, pick up the first arrival time of the OBN seismic data of each detection point from the original OBN seismic data; A travel time calculation module, used to calculate the towline travel time of each detection point based on the first arrival time of the towline seismic data of each detection point and the recorded shot point firing time, and to calculate the OBN travel time of each detection point based on the first arrival time of the OBN seismic data of each detection point and the recorded shot point firing time; The model training module is used to construct an initial seismic velocity model of the target work area based on the geological structure information of the target work area obtained from the exploration, iteratively update the initial seismic velocity model until the iterative convergence condition is met to obtain the final seismic velocity model, and perform first-arrival travel time tomography on the target work area based on the final seismic velocity model; in each iteration, the towline deviation is obtained based on the initial seismic velocity model and the towline travel time, and the OBN deviation is obtained based on the initial seismic velocity model and the OBN travel time; the slowness correction is calculated based on the towline deviation and the OBN deviation, and the slowness of the initial seismic velocity model is updated based on the slowness correction to obtain the updated initial seismic velocity model as the initial seismic velocity model for the next iteration.

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