Positioning method and device for marine seismic exploration streamer

Abstract

The application discloses a positioning method and device for offshore seismic exploration streamer. The method comprises: obtaining a plurality of groups of initial observation values of the offshore seismic exploration streamer, wherein the initial observation values comprise compass bird observation values and acoustic distance observation values; determining an initial observation value weight matrix corresponding to each group of initial observation values, a first error function corresponding to the compass bird observation values and a second error function corresponding to the acoustic distance observation values; constructing a normal equation through the initial observation value weight matrix corresponding to the initial observation values, the first error function and the second error function; determining a residual error vector corresponding to the initial observation values based on a solution corresponding to the normal equation; adjusting the initial observation value weight matrix based on the residual error vector to obtain a target observation value weight matrix; and determining the position of the offshore seismic exploration streamer based on at least one target observation value weight matrix. The accuracy of offshore seismic exploration streamer positioning is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of positioning of marine seismic exploration streamer, and particularly relates to a positioning method and device of marine seismic exploration streamer. BACKGROUND

[0002] The marine seismic exploration streamer, also known as marine seismic cable or streamer, is an important equipment in marine seismic exploration, and the positioning of the marine seismic exploration streamer provides an important basis for oil and gas drilling.

[0003] The positioning of the marine seismic exploration streamer currently mainly applies a method of determining a random model of an observation value according to a nominal accuracy of a positioning sensor to empirically weight the observation value. However, the current positioning of the marine seismic exploration streamer cannot accurately describe the actual accuracy of the observation value due to the complex marine observation environment and frequent sea conditions, and the positioning accuracy is low. SUMMARY

[0004] The present application provides a positioning method and device of marine seismic exploration streamer to solve the problem of low positioning accuracy of marine seismic exploration streamer.

[0005] According to an aspect of the present application, a positioning method of marine seismic exploration streamer is provided, which comprises:

[0006] obtaining a plurality of groups of initial observation values of the marine seismic exploration streamer, wherein the initial observation values comprise compass bird observation values and acoustic distance observation values;

[0007] determining an initial observation value weight matrix corresponding to each group of initial observation values, a first error function corresponding to the compass bird observation values, and a second error function corresponding to the acoustic distance observation values, respectively;

[0008] constructing a normal equation through the initial observation value weight matrix corresponding to the initial observation values, the first error function, and the second error function, and determining a residual vector corresponding to the initial observation values based on a solution corresponding to the normal equation;

[0009] adjusting the initial observation value weight matrix based on the residual vector to obtain a target observation value weight matrix, and determining the position of the marine seismic exploration streamer based on at least one target observation value weight matrix.

[0010] According to another aspect of the present application, a positioning device of marine seismic exploration streamer is provided, which comprises:

[0011] an observation value obtaining module configured to obtain a plurality of groups of initial observation values of the marine seismic exploration streamer, wherein the initial observation values comprise compass bird observation values and acoustic distance observation values;

[0012] an error function determining module configured to determine an initial observation weight matrix corresponding to each group of initial observation values, a first error function corresponding to the compass bird observation values and a second error function corresponding to the acoustic distance observation values respectively;

[0013] a residual vector determining module configured to construct normal equations by the initial observation weight matrix corresponding to the initial observation values, the first error function and the second error function, and determine a residual vector corresponding to the initial observation values based on a solution corresponding to the normal equations;

[0014] a positioning module configured to adjust the initial observation weight matrix based on the residual vector to obtain a target observation weight matrix, and determine the position of the marine seismic exploration streamer based on at least one of the target observation weight matrix.

[0015] According to another aspect of the present application, an electronic device is provided, which comprises:

[0016] at least one processor; and

[0017] a memory connected to the at least one processor in communication; wherein,

[0018] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the positioning method of the marine seismic exploration streamer according to any one of the embodiments of the present application.

[0019] According to another aspect of the present application, a computer readable storage medium is provided, which stores computer instructions for enabling a processor to perform the positioning method of the marine seismic exploration streamer according to any one of the embodiments of the present application when executed by the processor.

[0020] The technical scheme of the embodiment of the present application comprises the following steps: obtaining a plurality of groups of initial observation values of a marine seismic exploration streamer, wherein the initial observation values comprise a compass bird observation value and an acoustic distance observation value; obtaining a direction observation value and a distance observation value of the marine seismic exploration streamer; then, determining an initial observation value weight matrix corresponding to each group of initial observation values, a first error function corresponding to the compass bird observation value and a second error function corresponding to the acoustic distance observation value; constructing an initial observation value matrix corresponding to the initial observation values and accurately determining an error function corresponding to the initial observation values, and then constructing a normal equation by using the initial observation value weight matrix corresponding to the initial observation values, the first error function and the second error function, and determining a residual vector corresponding to the initial observation values based on a solution corresponding to the normal equation; accurately determining an error corresponding to the initial observation values; finally, adjusting the initial observation value weight matrix based on the residual vector to obtain a target observation value weight matrix, and determining the position of the marine seismic exploration streamer based on at least one target observation value weight matrix, thereby solving the problem of low positioning accuracy of the marine seismic exploration streamer and achieving the beneficial effect of improving the positioning accuracy of the marine seismic exploration streamer.

[0021] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0023] Figure 1 is a flow chart of a positioning method of a marine seismic exploration streamer according to the first embodiment of the present application;

[0024] Figure 2a is a flow chart of a positioning method of a marine seismic exploration streamer according to the second embodiment of the present application;

[0025] Figure 2b A streamer positioning schematic diagram of an optional example of a positioning method of a marine seismic exploration streamer is provided;

[0026] Figure 2c A positioning effect schematic diagram of a variance component estimation method of an optional example of a positioning method of a marine seismic exploration streamer is provided;

[0027] Figure 3It is a structural schematic diagram of a positioning device of a marine seismic exploration streamer according to an embodiment of the present application.

[0028] Figure 4 It is a structural schematic diagram of an electronic device for implementing a positioning method of a marine seismic exploration streamer according to an embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to make the personnel in the technical field better understand the present application scheme, the technical scheme in the embodiment of the present application will be described clearly and completely below in combination with the drawings in the embodiment of the present application. Obviously, the described embodiment is only a part of the embodiment of the present application, but not all. Based on the embodiment in the present application, all other embodiments obtained by the person skilled in the art without creative labor should belong to the protection scope of the present application.

[0030] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment one

[0032] Figure 1 A flowchart of a positioning method of a marine seismic exploration streamer is provided for the first embodiment of the present application. The present embodiment can be applied to the positioning of a marine seismic exploration streamer. The method can be performed by a positioning device of a marine seismic exploration streamer, which can be realized in the form of hardware and / or software, and can be configured in an electronic device. As shown in the figure, the method comprises: Figure 1

[0033] S110, obtaining a plurality of groups of initial observation values of the marine seismic exploration streamer, wherein the initial observation values include compass bird observation values and acoustic distance observation values.

[0034] The compass bird observation value can be understood as a bearing observation value. The acoustic distance observation value can be understood as a distance observation value.

[0035] ​Specifically, multiple sets of compass bird observations and acoustic distance observations are acquired from the towed cable of marine seismic exploration. The compass bird observations are corrected and their azimuths are converted to facilitate data unification within the positioning system. High-precision acoustic node coordinates are calculated from the acoustic distance observations using a network adjustment algorithm.

[0036] In this embodiment of the invention, during offshore seismic exploration towed cable operations, compass bird observations and acoustic distance observations are complementary. The compass bird provides tangential azimuth information of the cable, while the acoustic positioning device provides distance information between nodes. By comprehensively utilizing these two initial observations, it is easier to subsequently construct a high-precision cable shape model and calculate the precise location of each receiver point on the cable.

[0037] S120. Determine the initial observation weight matrix corresponding to each group of initial observations, the first error function corresponding to the compass bird observations, and the second error function corresponding to the acoustic distance observations.

[0038] The initial observation weight matrix can be understood as the weight matrix of the initial observations.

[0039] Specifically, a polynomial curve fitting model is constructed based on the observations of the compass bird and the acoustic distance, and the constructed polynomial curve fitting model is used as the towed cable positioning model.

[0040] Optionally, determining the first error function corresponding to the compass bird observation value and the second error function corresponding to the acoustic distance observation value includes:

[0041] Based on the pre-constructed towed cable positioning model, a first error function corresponding to the compass bird observation value and a second error function corresponding to the acoustic distance observation value are determined respectively.

[0042] The tow cable positioning model is expressed by the following formula:

[0043] ;

[0044] ;

[0045] ;

[0046] ;

[0047] in, , The offset on the tow cable is The coordinates of the location Let be the order of the polynomial. , For polynomial coefficients, This is the offset vector.

[0048] Optionally, the first error function is expressed by the following formula:

[0049] ;

[0050] ;

[0051] ;

[0052] ;

[0053] wherein, is the compass bird observation value at the point of the tow cable, is the residual error vector of the compass bird observation value, , , is the predicted value of the polynomial coefficient, , is the correction parameter of the compass bird observation value, is the compass prediction value.

[0054] Optionally, the acoustic distance observation value includes same-cable observation value and different-cable observation value;

[0055] In the case where the acoustic distance observation value includes different-cable observation value, the second error function between the different-cable observation value of the point of the G cable and the point of the H cable is expressed by the following formula:

[0056] ;

[0057] ;

[0058] wherein, is the acoustic distance observation value between the point and the point, is the residual error vector of the acoustic distance observation value, , , , , , are respectively the predicted values of the polynomial coefficients of the G cable and the H cable, , , , , , are respectively the correction parameters of the acoustic distance observation value, is the acoustic distance prediction value;

[0059] In the case where the acoustic distance observation value includes same-cable observation value, the second error function is expressed by the following formula:

[0060] ;

[0061] ;

[0062] wherein, , is a polynomial coefficient prediction value of the tow cable, , is a correction parameter of the acoustic range observation value.

[0063] Optionally, the determining of the initial observation value weight matrix corresponding to each group of initial observation values comprises:

[0064] For each group of initial observation values, determining an initial weight ratio corresponding to each initial observation value, and constructing an initial observation value weight matrix corresponding to the initial observation values based on a plurality of initial weight ratios.

[0065] Specifically, each initial observation value is assigned a weight in advance based on an empirical weight determination method to determine an initial weight ratio corresponding to each initial observation value. An initial observation value weight matrix is constructed based on a plurality of initial weight ratios.

[0066] Exemplarily, the initial observation value weight determined by the empirical weight determination method is:

[0067] ;

[0068] wherein, is a weight corresponding to the initial observation value, is a quality factor of the initial observation value, is a constant.

[0069] S130, constructing a normal equation based on the initial observation value weight matrix corresponding to the initial observation value, the first error function and the second error function, and determining a residual vector corresponding to the initial observation value based on a solution corresponding to the normal equation.

[0070] Specifically, according to the least square criterion, the first error function and the second error function are used to construct a normal equation with the initial observation value weight matrix and to solve the normal equation to obtain a least square solution, wherein the residual vector corresponding to the initial observation value is obtained.

[0071] Exemplarily, the first error function and the second error function are used to construct a normal equation with the initial observation value weight matrix and to solve the normal equation to obtain a least square solution.

[0072] wherein, the least square solution is expressed as follows:

[0073] ;

[0074] wherein, is an approximate value of the initial observation value, is a closed vector, is a design matrix, is an initial observation weight matrix.

[0075] The residual vector corresponding to the initial observation is determined based on least squares and is expressed by the following formula:

[0076] ;

[0077] wherein, is a residual vector.

[0078] S140, adjust the initial observation weight matrix based on the residual vector to obtain a target observation weight matrix, and determine the position of the marine seismic exploration streamer based on at least one target observation weight matrix.

[0079] Specifically, the initial observation weight matrix is iteratively adjusted based on the residual vector until a convergence condition is met or a preset number of iterations is reached, the weight matrix after adjustment is determined as the target observation weight matrix, and the position of the marine seismic exploration streamer is determined based on the weight corresponding to each observation in at least one target observation weight matrix and each initial observation.

[0080] The technical scheme of the embodiment of the application obtains a plurality of groups of initial observation values of a marine seismic exploration streamer, wherein the initial observation values include compass bird observation values and acoustic distance observation values; obtains azimuth observation values and distance observation values of the marine seismic exploration streamer; then, determines an initial observation weight matrix corresponding to each group of initial observation values, a first error function corresponding to the compass bird observation values, and a second error function corresponding to the acoustic distance observation values; constructs an initial observation matrix corresponding to the initial observation values and accurately determines an error function corresponding to the initial observation values, and then constructs a normal equation by using the initial observation weight matrix corresponding to the initial observation values, the first error function, and the second error function, determines a residual vector corresponding to the initial observation values based on a solution corresponding to the normal equation, and accurately determines an error corresponding to the initial observation values; finally, the initial observation weight matrix is adjusted based on the residual vector to obtain a target observation weight matrix, and the position of the marine seismic exploration streamer is determined based on at least one target observation weight matrix, thereby solving the problem of low positioning accuracy of the marine seismic exploration streamer and achieving the beneficial effect of improving the positioning accuracy of the marine seismic exploration streamer.

[0081] Embodiment two

[0082] Figure 2aA flowchart of a positioning method of a marine seismic exploration streamer is provided in Embodiment Two of the present application. The present embodiment is a further optimization of how to adjust each initial observation weight matrix based on the residual vector to obtain a target observation weight matrix in the above-mentioned embodiments. Optionally, the adjustment of each initial observation weight matrix based on the residual vector to obtain a target observation weight matrix comprises: determining a variance component corresponding to the initial observation based on a variance component estimation method and the residual vector, and adjusting each initial observation weight matrix based on the variance component to obtain a target observation weight matrix.

[0083] As shown in Figure 2a , the method comprises:

[0084] S210, a plurality of groups of initial observations of a marine seismic exploration streamer are obtained, wherein the initial observations comprise compass bird observations and acoustic distance observations.

[0085] S220, an initial observation weight matrix corresponding to each group of initial observations, a first error function corresponding to the compass bird observations, and a second error function corresponding to the acoustic distance observations are respectively determined.

[0086] S230, a normal equation is constructed by the initial observation weight matrix corresponding to the initial observation, the first error function, and the second error function, and a residual vector corresponding to the initial observation is determined based on a solution corresponding to the normal equation.

[0087] S240, a variance component corresponding to the initial observation is determined based on a variance component estimation method and the residual vector, each initial observation weight matrix is adjusted based on the variance component to obtain a target observation weight matrix, and the position of the marine seismic exploration streamer is determined based on at least one target observation weight matrix.

[0088] Specifically, the initial observations are grouped, a variance component estimation is performed on each group of initial observations to obtain a variance component corresponding to each group of initial observations, and the weight of each observation is adjusted based on the result of the variance component estimation. It can be understood that the weight is usually inversely proportional to the variance of the observation, i.e., the smaller the variance, the greater the weight. By adjusting the weight, a target observation weight matrix reflecting the relative importance of different observations in the final position estimation can be constructed. At least one target observation weight matrix is used in combination with a preset positioning algorithm (e.g., least square method, Kalman filter, etc.) to determine the accurate position of the marine seismic exploration streamer.

[0089] Optionally, the variance component corresponding to the initial observation is determined by the following formula:

[0090] ;

[0091] ;

[0092] ;

[0093] ;

[0094] wherein, is a variance component, is a residual vector corresponding to the initial observation value, is an initial observation value weight matrix, is an error observation component of the initial observation value, is a number of initial observation values, , is a design matrix corresponding to the initial observation value.

[0095] Optionally, the compass bird observation value includes an acoustic network coverage observation value and a non-acoustic network coverage observation value; the variance component includes a first variance component corresponding to a same-cable observation value, a second variance component corresponding to a different-cable observation value, a third variance component corresponding to the acoustic network coverage observation value, and a fourth variance component corresponding to the non-acoustic network coverage observation value; and the estimating the variance component corresponding to the initial observation value based on the variance component estimation method and the residual vector includes: respectively estimating the first variance component corresponding to the same-cable observation value, the second variance component corresponding to the different-cable observation value, the third variance component corresponding to the acoustic network coverage observation value, and the fourth variance component corresponding to the non-acoustic network coverage observation value based on the variance component estimation method and the residual vector.

[0096] Illustratively, the acoustic distance observation value is divided into a same-cable observation value and a different-cable observation value, and the compass bird observation value is divided into an acoustic network coverage observation value and a non-acoustic network coverage observation value. Residual vectors of the four groups of observation values are respectively calculated. A variance component estimation method is used to minimize an objective function, such as a weighted residual sum of squares, to obtain variance components of the four groups of observation values. Specifically, for each group of observation values, the variance component is iteratively adjusted based on the least square principle until the objective function reaches a minimum. The variance component is initialized, the weighted residual sum of squares is calculated using the current variance component, the variance component is adjusted by a preset optimization algorithm (such as a gradient descent method), and the above steps are repeated until the variance component converges or a predetermined number of iterations is reached, to obtain a variance component corresponding to each group of predicted values. The variance component can be used to adjust the weight ratio in the initial observation value weight matrix.

[0097] Optionally, the adjusting the initial observation value weight matrix based on the variance component to obtain a target observation value weight matrix includes:

[0098] adjust the initial observation weight matrix based on the first variance component, the second variance component, the third variance component and the fourth variance component to obtain a target observation weight matrix.

[0099] Specifically, the initial observation weight matrix is iteratively adjusted based on the first variance component, the second variance component, the third variance component and the fourth variance component until a preset convergence threshold is met, and the target observation weight matrix is determined based on the observation weight matrix after the iterative adjustment. The weight ratio corresponding to the target observation weight matrix is the target weight ratio corresponding to the initial observation.

[0100] Optionally, the adjustment of the initial observation weight matrix based on the variance components can be represented by the following formula:

[0101] ;

[0102] wherein, a is a constant, and is usually taken as the value of in the formula, and the adjusted weight matrix . .

[0103] Specifically, the method equation is re-established according to the adjusted weight matrix , and a new approximation of the initial observation and a new residual error vector are obtained by solving the method equation, and . The variance components of each group of observations are calculated according to the new residual error vector . If the first preset condition, the second preset condition and the third preset condition are all met, the iteration is exited, otherwise the first error function and the second error function are recalculated.

[0104] Exemplarily, the first preset condition can be represented by the following formula:

[0105] ;

[0106] wherein, a is the first preset convergence threshold. The second preset condition can be represented by the following formula:

[0107] ; wherein, a is the second preset convergence threshold.

[0108] The third preset condition includes that the variance component of each group of observations is not greater than the third preset convergence threshold.

[0109]

[0110] ​​The technical solution of this invention utilizes variance component estimation to estimate the variance components of each observation type. Based on the variance component estimation results, the weights of each observation are adjusted to obtain a target observation weight matrix. The position of the offshore seismic exploration towed cable is then determined based on the target observation matrix and a preset positioning algorithm, thus improving the accuracy of offshore seismic exploration towed cable positioning.

[0111] As an optional example of Embodiment 1 of the present invention, the positioning method of the marine seismic exploration towed cable in this embodiment specifically includes the following steps:

[0112] Step 1: Determine the initial weighting ratio between the compass bird observations and the acoustic distance observations based on empirical weighting methods.

[0113] For example, the initial observation weights determined by the empirical weighting method are:

[0114] ;

[0115] in, The weights corresponding to the initial observations. The quality factor of the initial observations. It is a constant.

[0116] Step 2: Based on the pre-built towed cable positioning model, determine the first error function corresponding to the compass bird observation value and the second error function corresponding to the acoustic distance observation value.

[0117] Optionally, determining the first error function corresponding to the compass bird observation value and the second error function corresponding to the acoustic distance observation value includes:

[0118] Based on the pre-constructed towed cable positioning model, a first error function corresponding to the compass bird observation value and a second error function corresponding to the acoustic distance observation value are determined respectively.

[0119] The tow cable positioning model is expressed by the following formula:

[0120] ;

[0121] ;

[0122] ;

[0123] ;

[0124] in, , The offset on the tow cable is The coordinates of the location Let be the order of the polynomial. , For polynomial coefficients, This is the offset vector.

[0125] Optionally, the first error function is expressed by the following formula:

[0126] ;

[0127] ;

[0128] ;

[0129] ;

[0130] in, For the tow cable Observation values ​​of the compass bird at the point. The residual vector of the compass bird observations. , These are the predicted values ​​of the polynomial coefficients. , Correction parameters for compass bird observations, This is the predicted value for the compass bird.

[0131] Optionally, the acoustic distance observations include observations from the same cable and observations from different cables;

[0132] When the acoustic distance observations include cross-cable observations, the second error function between the cross-cable observations at point i of cable G and point j of cable H is expressed by the following formula:

[0133] ;

[0134] ;

[0135] in, for Point and Acoustic distance observations between points The residual vector of acoustic distance observations. , , , They are respectively Cable and Predicted values ​​of the polynomial coefficients of the cable. , , , These are the correction parameters for the acoustic distance observations. This is the predicted acoustic distance value;

[0136] In the case that the acoustic range observations include same-cable observations, the second error function is expressed by the formula:

[0137] ;

[0138] ;

[0139] wherein, , is a polynomial coefficient prediction of the tow cable, , is a correction parameter of the acoustic range observations.

[0140] Step three: constructing a normal equation based on the initial observation weight matrix corresponding to the initial observation, the first error function and the second error function, and determining a residual vector corresponding to the initial observation based on a solution corresponding to the normal equation.

[0141] Specifically, according to the least square criterion, the first error function and the second error function are used to construct a normal equation with the initial observation weight matrix and to solve the normal equation, so as to obtain a least square solution, wherein a residual vector corresponding to the initial observation is obtained.

[0142] For example, the first error function and the second error function are used to construct a normal equation with the initial observation weight matrix and to solve the normal equation, so as to obtain a least square solution.

[0143] wherein the least square solution is expressed by the formula:

[0144] ;

[0145] wherein, is an approximation of the initial observation, is a closure vector, is a design matrix,

[0146] is the initial observation weight matrix.

[0147] The residual vector corresponding to the initial observation determined based on the least square solution is expressed by the formula:

[0148] ;

[0149] wherein, is the residual vector.

[0150] Step four: determining a variance component corresponding to the initial observation based on the variance component estimation method and the residual vector, and adjusting each initial observation weight matrix based on the variance component, so as to obtain a target observation weight matrix.

[0151] Optionally, the variance components corresponding to the initial observations can be determined using the following formula:

[0152] ;

[0153] ;

[0154] ;

[0155] ;

[0156] in, For variance components, This is the residual vector corresponding to the initial observation. The initial observation weight matrix, The error observation component of the initial observation value. The number of initial observations. , This is the design matrix corresponding to the initial observations.

[0157] Optionally, the initial observation weight matrix can be adjusted based on the variance components, as expressed by the following formula:

[0158] ;

[0159] in, It is a constant, usually taken as The values ​​in the adjusted weight matrix .

[0160] Step 5: Reconstruct the normal equations based on the adjusted observation weight matrix and solve iteratively until the equations are satisfied.

[0161] The preset conditions are met.

[0162] Specifically, according to the adjusted weight matrix Reconstruct the normal equations and solve them to obtain new approximate values ​​corresponding to the initial observations. and the new residual vector ,make Based on the new residual vector Calculate the variance components of each group of observations. If the first, second, and third preset conditions are all met simultaneously, the iteration exits; otherwise, it returns to recalculate the first and second error functions.

[0163] For example, the first preset condition is expressed by the following formula:

[0164] ;

[0165] in, is a first preset convergence threshold. The second preset condition is expressed by a formula as follows:

[0166] ;

[0167] wherein, is a second preset convergence threshold.

[0168] The third preset condition includes a variance component of each group of observation values is not greater than a third preset convergence threshold.

[0169] Figure 2b A towed cable positioning diagram of an optional example of a positioning method of a marine seismic exploration towed cable is provided. Figure 2b As shown in the figure, the towed cable positioning diagram can accurately position the towed cable.

[0170] Figure 2c A positioning effect diagram of a variance component estimation method of an optional example of a positioning method of a marine seismic exploration towed cable is provided. Figure 2c As shown in the figure, the technical scheme of the embodiment of the present application can better eliminate the influence of inaccurate nominal accuracy of observation values on weighting. In marine seismic exploration, the towed cable positioning sensor is located in seawater, the observation environment is complex, and the nominal accuracy of the positioning observation value cannot accurately describe the actual observation accuracy, resulting in unreasonable observation value weight obtained by the traditional experience weighting method. However, the technical scheme of the embodiment of the present application uses variance component estimation to weight the observation value, which can effectively eliminate this influence.

[0171] The technical scheme of the embodiment of the present application uses variance component estimation to determine the weight ratio between different types of observation values in the towed cable positioning network. The variance component estimation can estimate the variance component of the observation value according to the posterior residual information of the observation value, and adjust the weight matrix according to the variance component, so that the weight ratio between different types of towed cable positioning observation values tends to be reasonable, and the precision of the towed cable positioning is improved.

[0172] Embodiment three

[0173] Figure 3 A structure diagram of a positioning device of a marine seismic exploration towed cable provided by the embodiment three of the present application is provided. Figure 3 As shown in the figure, the device includes an observation value acquisition module 310, an error function determination module 320, a residual vector determination module 330, and a positioning module 340.

[0174] The observation value acquisition module 310 is configured to acquire a plurality of groups of initial observation values of the marine seismic exploration streamer, wherein the initial observation values include compass bird observation values and acoustic distance observation values.

[0175] The technical scheme of the embodiment of the present application acquires a plurality of groups of initial observation values of the marine seismic exploration streamer, wherein the initial observation values include compass bird observation values and acoustic distance observation values; acquires the azimuth observation values and the distance observation values of the marine seismic exploration streamer; then, respectively determines the initial observation value weight matrix corresponding to each group of initial observation values, the first error function corresponding to the compass bird observation values and the second error function corresponding to the acoustic distance observation values; constructs the initial observation value matrix corresponding to the initial observation values and accurately determines the error function corresponding to the initial observation values, and then constructs the normal equation through the initial observation value weight matrix corresponding to the initial observation values, the first error function and the second error function, determines the residual vector corresponding to the initial observation values based on the solution corresponding to the normal equation; accurately determines the error corresponding to the initial observation values; finally, adjusts the initial observation value weight matrix based on the residual vector to obtain the target observation value weight matrix, and determines the position of the marine seismic exploration streamer based on at least one target observation value weight matrix, thereby solving the problem of low positioning accuracy of the marine seismic exploration streamer and achieving the beneficial effect of improving the positioning accuracy of the marine seismic exploration streamer.

[0176] Optionally, the first error function is expressed by the following formula:

[0177] ;

[0178] ;

[0179] ;

[0180] ;

[0181] wherein, is the compass bird observation value at the point of the streamer, ​ is a residual vector of the compass bird observation value, , is a predicted value of the polynomial coefficient, , is a correction parameter of the compass bird observation value, is a compass bird predicted value.

[0182] Optionally, the acoustic distance observation value includes homocable observation value and heterocable observation value; accordingly, in the case that the acoustic distance observation value includes heterocable observation value, the second error function is expressed by the following formula:

[0183] ;

[0184] ;

[0185] wherein, is the acoustic distance observation value between the point and the point, is a residual vector of the acoustic distance observation value, , , , , are respectively predicted values of the polynomial coefficient of the cable and the cable, , , , , , are respectively correction parameters of the acoustic distance observation value, is an acoustic distance predicted value;

[0186] in the case that the acoustic distance observation value includes homocable observation value, the second error function is expressed by the following formula:

[0187] ;

[0188] ;

[0189] wherein, , is a predicted value of the polynomial coefficient of the cable, , is a correction parameter of the acoustic distance observation value.

[0190] Optionally, the error function determination module is specifically used for:

[0191] determining respectively a first error function corresponding to the compass bird observation value and a second error function corresponding to the acoustic distance observation value based on a pre-constructed towed cable positioning model;

[0192] wherein the streamer positioning model is expressed by the following formula:

[0193] ;

[0194] ;

[0195] ;

[0196] ;

[0197] wherein, , is a coordinate of the offset of the streamer, is a polynomial order, , , is a polynomial coefficient, is an offset vector.

[0198] Optionally, the positioning module is specifically configured to:

[0199] determine variance components corresponding to the initial observation values based on the variance component estimation method and the residual vector, and adjust the initial observation value weight matrix based on the variance components to obtain a target observation value weight matrix.

[0200] Optionally, the compass bird observation values include acoustic network coverage observation values and non-acoustic network coverage observation values; the variance components include first variance components corresponding to same-cable observation values, second variance components corresponding to different-cable observation values, third variance components corresponding to the acoustic network coverage observation values, and fourth variance components corresponding to the non-acoustic network coverage observation values.

[0201] Correspondingly, the positioning module is specifically configured to:

[0202] determine first variance components corresponding to same-cable observation values, second variance components corresponding to different-cable observation values, third variance components corresponding to the acoustic network coverage observation values, and fourth variance components corresponding to the non-acoustic network coverage observation values based on the variance component estimation method and the residual vector, respectively.

[0203] Optionally, the positioning module is specifically configured to:

[0204] adjust the initial observation value weight matrix based on the first variance components, the second variance components, the third variance components, and the fourth variance components to obtain a target observation value weight matrix.

[0205] Optionally, the variance components corresponding to the initial observation values are determined by the following formula:

[0206] ;

[0207] ;

[0208] ;

[0209] ;

[0210] wherein, is a variance component, is a residual vector corresponding to the initial observation value, is an initial observation value weight matrix, is an error observation component of the initial observation value, is a number of initial observation values, , is a design matrix corresponding to the initial observation value.

[0211] Optionally, the error function determination module is specifically configured to:

[0212] determine an initial weight ratio corresponding to each initial observation value for each group of initial observation values, and construct an initial observation value weight matrix corresponding to the initial observation value based on the plurality of initial weight ratios.

[0213] The positioning device for the marine seismic exploration streamer provided in the embodiments of the present application can execute the positioning method for the marine seismic exploration streamer provided in any of the embodiments of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0214] Embodiment four

[0215] Figure 4 A structural schematic diagram of an electronic device 10 that can be used to implement embodiments of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices (e.g., headsets, glasses, watches, etc.), and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present application described and / or claimed in this document.

[0216] As Figure 4As shown, the electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., communicatively connected to the at least one processor 11, where the memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0217] Various components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc., an output unit 17, such as various types of displays, a speaker, etc., a storage unit 18, such as a magnetic disk, an optical disk, etc., and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0218] The processor 11 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the method of positioning marine seismic exploration streamers.

[0219] In some embodiments, the method of positioning marine seismic exploration streamers can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method of positioning marine seismic exploration streamers described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the method of positioning marine seismic exploration streamers by any other appropriate means, such as by means of firmware.

[0220] The various embodiments of the systems and techniques described above can be implemented in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a load programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0221] Computer programs used to implement the processes of the application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer program

[0222] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store computer programs for use by or in connection with an instruction execution system, apparatus, or device. Computer-readable storage media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0223] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0224] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0225] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0226] It should be understood that the various forms of flow shown above can be re-ordered, added to, or deleted from without departing from the scope of the present disclosure. For example, the steps recited in the present disclosure can be executed in parallel, executed in sequence, or executed in a different order, as long as the desired results of the present disclosure are achieved, and the present disclosure is not limited herein.

[0227] The specific embodiments described above are not intended to be limiting, and persons skilled in the art will appreciate that various modifications, combinations, sub-combinations and alternatives can be made to the specific embodiments without departing from the spirit and principles of the disclosure. Accordingly, the disclosure is not limited to the specific embodiments described above, but only by the scope of the appended claims.

Claims

1. A method of positioning a marine seismic streamer, characterized in that, The method comprises: obtaining a plurality of groups of initial observation values of a marine seismic exploration streamer, wherein the initial observation values comprise compass bird observation values and acoustic distance observation values; determining an initial observation value weight matrix corresponding to each group of initial observation values, a first error function corresponding to the compass bird observation values, and a second error function corresponding to the acoustic distance observation values; constructing a normal equation based on the initial observation value weight matrix corresponding to the initial observation values, the first error function, and the second error function, and determining a residual vector corresponding to the initial observation values based on a solution corresponding to the normal equation; adjusting the initial observation value weight matrix based on the residual vector to obtain a target observation value weight matrix, and determining the position of the marine seismic exploration streamer based on at least one target observation value weight matrix; the adjustment of each initial observation value weight matrix based on the residual vector to obtain a target observation value weight matrix comprises: determining a variance component corresponding to the initial observation values based on a variance component estimation method and the residual vector, and adjusting each initial observation value weight matrix based on the variance component to obtain a target observation value weight matrix; the compass bird observation values comprise acoustic network coverage observation values and non-acoustic network coverage observation values; and the variance components comprise a first variance component corresponding to same-cable observation values, a second variance component corresponding to different-cable observation values, a third variance component corresponding to the acoustic network coverage observation values, and a fourth variance component corresponding to the non-acoustic network coverage observation values; the determination of the variance component corresponding to the initial observation values based on the variance component estimation method and the residual vector comprises: determining a first variance component corresponding to same-cable observation values, a second variance component corresponding to different-cable observation values, a third variance component corresponding to the acoustic network coverage observation values, and a fourth variance component corresponding to the non-acoustic network coverage observation values based on the variance component estimation method and the residual vector.

2. The method of claim 1, wherein, The first error function is expressed by the following formula: ； ； ； ； wherein is the compass bird observation at the point of the streamer is the compass bird observation, is the residual vector of the compass bird observation, , is the predicted value of the polynomial coefficients, , is the correction parameter of the compass bird observation, is the compass bird prediction.

3. The method of claim 2, wherein, the acoustic distance observation values comprise same-cable observation values and different-cable observation values; in the case where the acoustic distance observation values comprise different-cable observation values, the second error function is expressed by the following formula: ； ； wherein is point and acoustic distance observations between the points, is a residual vector of the acoustic distance observations, , , , are respectively polynomial coefficients of the cable and polynomial coefficients of the cable, , , , are respectively correction parameters of the acoustic distance observations, is an acoustic distance prediction; in the case where the acoustic distance observation values comprise same-cable observation values, the second error function is expressed by the following formula: ； ； wherein , is a polynomial coefficient prediction of the streamer, , is a correction parameter for the acoustic range observation.

4. The method according to claim 2 or 3, characterized in that, the determination of the first error function corresponding to the compass bird observation values and the second error function corresponding to the acoustic distance observation values comprises: determining the first error function corresponding to the compass bird observation values and the second error function corresponding to the acoustic distance observation values based on a pre-constructed streamer positioning model; wherein the streamer positioning model is expressed by the following formula: ； ； ； ； wherein , is the coordinate of the offset at , is the polynomial order, , is the polynomial coefficient, is the offset vector.

5. The method of claim 1, wherein, the adjustment of each initial observation value weight matrix based on the variance component to obtain a target observation value weight matrix comprises: adjusting the initial observation value weight matrix based on the first variance component, the second variance component, the third variance component, and the fourth variance component to obtain a target observation value weight matrix.

6. The method of claim 1, wherein, the variance component corresponding to the initial observation values is determined by the following formula: ； ； ； ； wherein is a variance component, is a residual vector corresponding to the initial observations, is an initial observation weight matrix, is an error observation component of the initial observations, is a number of initial observations, , is a design matrix corresponding to the initial observations.

7. The method of claim 1, wherein, The determining of the initial observation value weight matrix corresponding to each group of initial observation values comprises: For each group of initial observation values, an initial weight ratio corresponding to each initial observation value is determined, and a plurality of initial weight ratios are used to construct an initial observation value weight matrix corresponding to the initial observation values.

8. A positioning device for a marine seismic streamer, characterized in that Comprise: An observation value acquisition module is configured to acquire a plurality of groups of initial observation values of a marine seismic exploration streamer, wherein the initial observation values comprise compass bird observation values and acoustic distance observation values; An error function determination module is configured to respectively determine an initial observation value weight matrix corresponding to each group of initial observation values, a first error function corresponding to the compass bird observation values, and a second error function corresponding to the acoustic distance observation values; A residual vector determination module is configured to construct normal equations by using the initial observation value weight matrix corresponding to the initial observation values, the first error function, and the second error function, and determine a residual vector corresponding to the initial observation values based on a solution corresponding to the normal equations; A positioning module is configured to adjust the initial observation value weight matrix based on the residual vector to obtain a target observation value weight matrix, and determine a position of the marine seismic exploration streamer based on at least one target observation value weight matrix; The positioning module is specifically configured to: Determine a variance component corresponding to the initial observation values based on a variance component estimation method and the residual vector, and adjust each initial observation value weight matrix based on the variance component to obtain a target observation value weight matrix; The compass bird observation values comprise acoustic network coverage observation values and non-acoustic network coverage observation values; and the variance components comprise a first variance component corresponding to homocable observation values, a second variance component corresponding to heterocable observation values, a third variance component corresponding to the acoustic network coverage observation values, and a fourth variance component corresponding to the non-acoustic network coverage observation values; The positioning module is specifically configured to: Determine a first variance component corresponding to homocable observation values, a second variance component corresponding to heterocable observation values, a third variance component corresponding to the acoustic network coverage observation values, and a fourth variance component corresponding to the non-acoustic network coverage observation values based on a variance component estimation method and the residual vector, respectively.

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