Positioning method and device for marine seismic exploration towrope

Abstract

The invention discloses a positioning method and device for an offshore seismic exploration towing cable. The method comprises the steps that multiple sets of initial observation values of an offshore seismic exploration towing cable are acquired, and the initial observation values comprise a compass bird observation value and an acoustic distance observation value; respectively 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 a normal equation through 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; and adjusting the initial observation value weight matrix based on the residual vector to obtain target observation value weight matrixes, and determining the position of the marine seismic exploration towing cable based on at least one target observation value weight matrix. And the positioning accuracy of the marine seismic exploration towing cable is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of offshore seismic exploration streamer positioning, and in particular to a method and device for positioning an offshore seismic exploration streamer. Background Art

[0002] Offshore seismic exploration streamers, also known as marine seismic cables or streamers, are important equipment in marine seismic exploration. The positioning of offshore seismic exploration streamers provides an important basis for oil and gas reservoir drilling.

[0003] The main method currently used for positioning offshore seismic exploration streamers is to empirically weight the observations based on the nominal accuracy of the positioning sensor to determine the random model of the observations. However, due to the complex offshore observation environment and frequent changes in sea conditions, the nominal accuracy of the current offshore seismic exploration streamer positioning cannot accurately describe the actual accuracy of the observations, resulting in low positioning accuracy. Summary of the invention

[0004] The invention provides a method and a device for positioning an offshore seismic exploration streamer, so as to solve the problem of low positioning accuracy of the offshore seismic exploration streamer.

[0005] According to one aspect of the present invention, a method for positioning an offshore seismic exploration streamer is provided, the method comprising:

[0006] Acquiring multiple groups of initial observation values ​​of the offshore seismic exploration streamer, wherein the initial observation values ​​include compass bird observation values ​​and acoustic distance observation values;

[0007] Respectively 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;

[0008] Constructing a normal equation by using 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;

[0009] The initial observation value weight matrix is ​​adjusted based on the residual vector to obtain a target observation value weight matrix, and the position of the offshore seismic exploration streamer is determined based on at least one of the target observation value weight matrices.

[0010] According to another aspect of the present invention, there is provided a positioning device for an offshore seismic exploration streamer, the device comprising:

[0011] An observation value acquisition module is used to acquire multiple groups of initial observation values ​​of the offshore seismic exploration streamer, wherein the initial observation values ​​include compass bird observation values ​​and acoustic distance observation values;

[0012] An error function determination module, used 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 value, and a second error function corresponding to the acoustic distance observation value;

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

[0014] A positioning module is used to adjust the initial observation value weight matrix based on the residual vector to obtain a target observation value weight matrix, and determine the position of the offshore seismic exploration streamer based on at least one of the target observation value weight matrices.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; 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 so that the at least one processor can execute the method for positioning an offshore seismic exploration streamer according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions for enabling a processor to implement the method for positioning an offshore seismic exploration streamer according to any embodiment of the present invention when the computer instructions are executed.

[0020] The technical solution of the embodiment of the present invention is to obtain multiple groups of initial observation values ​​of an offshore seismic exploration streamer, wherein the initial observation values ​​include compass bird observation values ​​and acoustic distance observation values; obtain azimuth observation values ​​and distance observation values ​​of the offshore seismic exploration streamer; then, respectively determine 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; construct an initial observation value matrix corresponding to the initial observation values ​​and accurately determine the error function corresponding to the initial observation values, and then construct 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 determine the residual vector corresponding to the initial observation value based on the solution corresponding to the normal equation; accurately determine the error corresponding to the initial observation value; finally, adjust the initial observation value weight matrix based on the residual vector to obtain a target observation value weight matrix, and determine the position of the offshore seismic exploration streamer based on at least one of the target observation value weight matrices, thereby solving the problem of low positioning accuracy of offshore seismic exploration streamers and achieving the beneficial effect of improving the accuracy of positioning of offshore seismic exploration streamers.

[0021] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 This is a flow chart of a method for positioning a marine seismic exploration streamer according to Embodiment 1 of the present invention;

[0024] Figure 2a This is a flow chart of a method for positioning a marine seismic exploration streamer according to Embodiment 2 of the present invention;

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

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

[0027] Figure 3This is a schematic structural diagram of a positioning device for an offshore seismic exploration streamer provided in accordance with a third embodiment of the present invention;

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

[0029] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment 1

[0032] Figure 1 A flowchart of a method for positioning a marine seismic exploration streamer is provided for the first embodiment of the present invention. This embodiment is applicable to the positioning of marine seismic exploration streamers. The method can be performed by a positioning device for a marine seismic exploration streamer. The positioning device for a marine seismic exploration streamer can be implemented in the form of hardware and / or software. The positioning device for a marine seismic exploration streamer can be configured in an electronic device. Figure 1 As shown, the method includes:

[0033] S110, obtaining multiple groups of initial observation values ​​of the offshore seismic exploration streamer, wherein the initial observation values ​​include compass bird observation values ​​and acoustic distance observation values.

[0034] Among them, the compass bird observation value can be understood as the azimuth observation value, and the acoustic distance observation value can be understood as the distance observation value.

[0035] Specifically, multiple groups of compass bird observations and acoustic distance observations of offshore seismic exploration tow cables are obtained. The compass bird observations are corrected and azimuthally converted to unify the data of the positioning system. The acoustic distance observations are calculated using a network adjustment algorithm to obtain high-precision acoustic node coordinates.

[0036] In the embodiment of the present invention, in the offshore seismic exploration towline operation, the compass bird observation value and the acoustic distance observation value complement each other. The compass bird provides the tangent azimuth information of the cable, and the acoustic positioning device provides the distance information between nodes. By comprehensively utilizing these two initial observation values, it is convenient to subsequently construct a high-precision cable shape model and calculate the precise position of each detection point on the cable.

[0037] S120, respectively 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.

[0038] Among them, the initial observation value weight matrix can be understood as the weight matrix of the initial observation values.

[0039] Specifically, a polynomial curve fitting model is constructed based on the compass bird observation values ​​and the acoustic distance observation values, and the constructed polynomial curve fitting model is used as the towline positioning model.

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

[0041] Determining 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 streamer positioning model;

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

[0043]

[0044] A=[a0,a1,…a n ] T ;

[0045] B=[b0,b1,…b n ] T ;

[0046] S=[s 0 ,s 1 ,…s N ] T ;

[0047] Where x, y are the coordinates of the streamer at an offset of s, N is the polynomial order, A, B are the polynomial coefficients, and S is the offset vector.

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

[0049]

[0050] Λ=diag(0,1,2,…N);

[0051]

[0052] Among them, α i is the observation value of the compass bird at point i on the tow cable, is the residual vector of the compass bird observation value, A 0 , B 0 is the predicted value of the polynomial coefficient, is the correction parameter of the compass bird observation value, It is the predicted value of the compass bird.

[0053] Optionally, the acoustic distance observation value includes a same-cable observation value and a different-cable observation value;

[0054] In the case where the acoustic distance observation value includes a different cable observation value, the second error function between the different cable observation values ​​at point Gcable i and point Hcable j is expressed by the following formula:

[0055]

[0056] Among them, R i,j is the acoustic distance observation value between point i and point j, is the residual vector of the acoustic distance observation, are the predicted values ​​of the polynomial coefficients of G cable and H cable, are the correction parameters of the acoustic distance observations, is the predicted value of acoustic distance;

[0057] In the case where the acoustic distance observation value includes the co-cable observation value, the second error function is expressed by the formula:

[0058]

[0059] S i,j =S j -S i ;

[0060] Among them, A 0 , B 0 is the predicted value of the polynomial coefficient of the towline, is the correction parameter of the acoustic distance observation.

[0061] Optionally, determining an initial observation value weight matrix corresponding to each group of initial observation values ​​includes:

[0062] For each group of initial observation values, an initial weight ratio corresponding to each initial observation value is determined, and an initial observation value weight matrix corresponding to the initial observation value is constructed based on a plurality of the initial weight ratios.

[0063] Specifically, each initial observation value is weighted in advance based on an empirical weighting method to determine an initial weight ratio corresponding to each initial observation value, and an initial observation value weight matrix is ​​constructed based on multiple initial weight ratios.

[0064] Exemplarily, the initial observation weights determined by the empirical weighting method are:

[0065]

[0066] Among them, p i is the weight corresponding to the initial observation value, q i is the quality factor of the initial observation, and c is a constant.

[0067] S130. Construct a normal equation using the initial observation value weight matrix corresponding to the initial observation value, the first error function, and the second error function, and determine a residual vector corresponding to the initial observation value based on a solution corresponding to the normal equation.

[0068] Specifically, according to the least squares criterion, the first error function and the second error function are used with the initial observation value weight matrix to form a normal equation and solve it to obtain a residual vector corresponding to the initial observation value.

[0069] Exemplarily, the first error function and the second error function are used together with the initial observation value weight matrix to form a normal equation and solve it to obtain a least squares solution;

[0070] The least squares solution is expressed as follows:

[0071]

[0072] in, is the approximate value of the initial observation, l k is a closed vector, A (k) is the design matrix, P (k) is the initial observation weight matrix.

[0073] The residual vector corresponding to the initial observation value is determined based on the least square method and is expressed as follows:

[0074]

[0075] Among them, V (k) is the residual vector.

[0076] S140. Adjust the initial observation value weight matrix based on the residual vector to obtain a target observation value weight matrix, and determine the position of the offshore seismic exploration streamer based on at least one of the target observation value weight matrices.

[0077] Specifically, the initial observation value weight matrix is ​​iteratively adjusted based on the residual vector until the convergence condition is met or a preset number of iterations is reached, the weight matrix after the adjustment is determined as the target observation value weight matrix, and the position of the offshore seismic exploration streamer is determined based on at least one weight corresponding to each observation value in the target observation value weight matrix and each initial observation value.

[0078] The technical solution of the embodiment of the present invention is to obtain multiple groups of initial observation values ​​of an offshore seismic exploration streamer, wherein the initial observation values ​​include compass bird observation values ​​and acoustic distance observation values; obtain azimuth observation values ​​and distance observation values ​​of the offshore seismic exploration streamer; then, respectively determine 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; construct an initial observation value matrix corresponding to the initial observation values ​​and accurately determine the error function corresponding to the initial observation values, and then construct 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 determine the residual vector corresponding to the initial observation value based on the solution corresponding to the normal equation; accurately determine the error corresponding to the initial observation value; finally, adjust the initial observation value weight matrix based on the residual vector to obtain a target observation value weight matrix, and determine the position of the offshore seismic exploration streamer based on at least one of the target observation value weight matrices, thereby solving the problem of low positioning accuracy of offshore seismic exploration streamers and achieving the beneficial effect of improving the accuracy of positioning of offshore seismic exploration streamers.

[0079] Embodiment 2

[0080] Figure 2a A flowchart of a method for positioning an offshore seismic exploration streamer provided in Embodiment 2 of the present invention, this embodiment is a further optimization of how to adjust each of the initial observation value weight matrices based on the residual vector in the above embodiment to obtain a target observation value weight matrix. Optionally, the adjustment of each of the initial observation value weight matrices based on the residual vector to obtain a target observation value weight matrix includes: determining the variance component corresponding to the initial observation value based on the variance component estimation method and the residual vector, and adjusting each of the initial observation value weight matrices based on the variance component to obtain a target observation value weight matrix.

[0081] like Figure 2a As shown, the method includes:

[0082] S210, obtaining multiple groups of initial observation values ​​of the offshore seismic exploration streamer, wherein the initial observation values ​​include compass bird observation values ​​and acoustic distance observation values.

[0083] S220, respectively 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.

[0084] S230, constructing a normal equation using 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.

[0085] S240. Determine the variance components corresponding to the initial observations based on the variance component estimation method and the residual vector, adjust each initial observation weight matrix based on the variance components to obtain a target observation weight matrix, and determine the position of the offshore seismic exploration streamer based on at least one of the target observation weight matrices.

[0086] Specifically, the initial observations are grouped, and variance components are estimated for each group of initial observations to obtain variance components corresponding to each group of initial observations. Based on the results of the variance component estimation, the weight of each observation is adjusted. It is understandable that the weight is usually inversely proportional to the variance of the observation, that is, the smaller the variance, the greater the weight. By adjusting the weight, a target observation weight matrix can be constructed, which reflects the relative importance of different observations in the final position estimation. Use at least one target observation weight matrix, combined with a preset positioning algorithm (e.g., least squares method, Kalman filtering, etc.) to determine the precise position of the offshore seismic exploration streamer.

[0087] Optionally, the variance component corresponding to the initial observation is determined by the following formula:

[0088]

[0089] r i =n i -tr(N -1 N i );

[0090] N=A T PA;

[0091]

[0092] in, is the variance component, Vi is the residual vector corresponding to the initial observation value, P i is the initial observation weight matrix, r i is the error observation component of the initial observation value, n i is the number of initial observations, N, N i is the design matrix corresponding to the initial observations.

[0093] Optionally, the compass bird observation values ​​include acoustic network coverage observation values ​​and no-acoustic network coverage observation values; the variance components include a first variance component corresponding to the same-cable observation values, a second variance component corresponding to the different-cable observation values, a third variance component corresponding to the acoustic network coverage observation values, and a fourth variance component corresponding to the no-acoustic network coverage observation values; the variance component corresponding to the initial observation value is determined based on the variance component estimation method and the residual vector, including: determining 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 no-acoustic network coverage observation value, respectively, based on the variance component estimation method and the residual vector.

[0094] Exemplarily, the acoustic distance observations are divided into the same-cable observations and the different-cable observations, and the compass bird observations are divided into the acoustic network coverage observations and the non-acoustic network coverage observations. The residual vectors of the four groups of observations are calculated respectively. The variance component estimation method is used to minimize the objective function, such as the weighted residual sum of squares, to obtain the variance components of the four groups of observations. Specifically, for each group of observations, the variance components are iteratively adjusted based on the least squares principle until the objective function is minimized. Initialize the variance components, use the current variance components to calculate the weighted residual sum of squares, adjust the variance components through a preset optimization algorithm (such as the gradient descent method), and repeat the above steps until the variance components converge or reach a predetermined number of iterations to obtain the variance components corresponding to each group of predicted values. The variance components can be used to adjust the weight ratio in the initial observation weight matrix.

[0095] Optionally, adjusting each of the initial observation weight matrices based on the variance component to obtain a target observation weight matrix includes:

[0096] The initial observation value weight matrix is ​​adjusted 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.

[0097] Specifically, the initial observation value 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 a target observation value weight matrix is ​​determined based on the observation value weight matrix after the iterative adjustment. The weight ratio corresponding to the target observation value weight matrix is ​​the target weight ratio corresponding to the initial observation value.

[0098] Optionally, the initial observation weight matrix is ​​adjusted based on the variance components using the formula:

[0099]

[0100] Where C is a constant, usually The values ​​in the adjusted weight matrix

[0101] Specifically, according to the adjusted weight matrix P (k+1) Restructure the normal equation and solve it to get a new approximation to the initial observed value and the new residual vector V (k+1) ,make According to the new residual vector V (k+1) Calculate the variance components of each group of observations If the first preset condition, the second preset condition and the third preset condition are met at the same time, the iteration is exited; otherwise, the process returns to recalculate the first error function and the second error function.

[0102] Exemplarily, the first preset condition is expressed by the following formula:

[0103]

[0104] Wherein, ε1 is the first preset convergence threshold.

[0105] The second precondition is expressed by the following formula:

[0106]

[0107] Wherein, ε2 is the second preset convergence threshold.

[0108] The third precondition includes the variance components of each set of observations is not greater than a third preset convergence threshold.

[0109] The technical solution of the embodiment of the present invention uses a variance component estimation method to estimate the variance component of each observation type. Based on the result of the variance component estimation, the weight of each observation is adjusted to obtain a target observation value weight matrix, and the position of the offshore seismic exploration streamer is determined based on the target observation value matrix and a preset positioning algorithm, thereby improving the accuracy of the offshore seismic exploration streamer positioning.

[0110] As an optional example of the first embodiment of the present invention, the positioning method of the offshore seismic exploration streamer of this embodiment specifically includes the following steps:

[0111] Step 1: Determine the initial weight ratio of the compass bird observation value and the acoustic distance observation value based on the empirical weighting method.

[0112] Exemplarily, the initial observation weights determined by the empirical weighting method are:

[0113]

[0114] Among them, p i is the weight corresponding to the initial observation value, q i is the quality factor of the initial observation, and c is a constant.

[0115] Step 2: Based on the pre-constructed streamer 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 respectively determined.

[0116] Optionally, the determining of a first error function corresponding to the compass bird observation value and a second error function corresponding to the acoustic distance observation value comprises:

[0117] Determining 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 streamer positioning model;

[0118] The towline positioning model is expressed by the following formula:

[0119]

[0120] A=[a0,a1,…a n ] T ;

[0121] B=[b0,b1,…b n ] T ;

[0122] S=[s 0 ,s 1 ,…s N ] T ;

[0123] Where x, y are the coordinates of the streamer at an offset of s, N is the polynomial order, A, B are the polynomial coefficients, and S is the offset vector.

[0124] Optionally, the first error function is expressed by the following formula:

[0125]

[0126] Λ=diag(0,1,2,…N);

[0127]

[0128] Among them, α i is the observation value of the compass bird at point i on the tow cable, is the residual vector of the compass bird observation value, A 0 , B 0 is the predicted value of the polynomial coefficient, is the correction parameter of the compass bird observation value, It is the predicted value of the compass bird.

[0129] Optionally, the acoustic distance observation value includes a same-cable observation value and a different-cable observation value;

[0130] In the case where the acoustic distance observation value includes a different cable observation value, the second error function between the different cable observation values ​​at point Gcable i and point Hcable j is expressed by the following formula:

[0131]

[0132] Among them, R i,j is the acoustic distance observation value between point i and point j, is the residual vector of the acoustic distance observation, are the predicted values ​​of the polynomial coefficients of G cable and H cable, are the correction parameters of the acoustic distance observations, is the predicted value of acoustic distance;

[0133] In the case where the acoustic distance observation value includes the co-cable observation value, the second error function is expressed by the formula:

[0134]

[0135] S i,j =S j -S i ;

[0136] Among them, A 0 , B 0 is the predicted value of the polynomial coefficient of the towline, is the correction parameter of the acoustic distance observation.

[0137] Step three: construct a normal equation using the initial observation value weight matrix corresponding to the initial observation value, the first error function and the second error function, and determine the residual vector corresponding to the initial observation value based on the solution corresponding to the normal equation.

[0138] Specifically, according to the least squares criterion, the first error function and the second error function are used with the initial observation value weight matrix to form a normal equation and solve it to obtain a residual vector corresponding to the initial observation value.

[0139] Exemplarily, the first error function and the second error function are used together with the initial observation value weight matrix to form a normal equation and solve it to obtain a least squares solution;

[0140] The least squares solution is expressed as follows:

[0141]

[0142] in, is the approximate value of the initial observation, l k is a closed vector, A (k) is the design matrix, P (k) is the initial observation weight matrix.

[0143] The residual vector corresponding to the initial observation value is determined based on the least square method and is expressed as follows:

[0144]

[0145] Among them, V (k) is the residual vector.

[0146] Step 4: Determine the variance components corresponding to the initial observations based on the variance component estimation method and the residual vector, and adjust each of the initial observation weight matrices based on the variance components to obtain a target observation weight matrix.

[0147] Optionally, the variance component corresponding to the initial observation is determined by the following formula:

[0148]

[0149] r i =n i -tr(N -1 N i );

[0150] N=A T PA;

[0151]

[0152] in, is the variance component, V i is the residual vector corresponding to the initial observation value, P i is the initial observation weight matrix, r i is the error observation component of the initial observation value, ni is the number of initial observations, N, N i is the design matrix corresponding to the initial observations.

[0153] Optionally, the initial observation weight matrix is ​​adjusted based on the variance components using the formula:

[0154]

[0155] Where C is a constant, usually The values ​​in the adjusted weight matrix

[0156] Step 5: Reconstruct the normal equation according to the adjusted observation value weight matrix and solve it iteratively until the preset conditions are met.

[0157] Specifically, according to the adjusted weight matrix P (k+1) Restructure the normal equation and solve it to get a new approximation to the initial observed value and the new residual vector V (k+1) ,make According to the new residual vector V (k+1) Calculate the variance components of each group of observations If the first preset condition, the second preset condition and the third preset condition are met at the same time, the iteration is exited; otherwise, the process returns to recalculate the first error function and the second error function.

[0158] Exemplarily, the first preset condition is expressed by the following formula:

[0159]

[0160] Wherein, ε1 is the first preset convergence threshold.

[0161] The second precondition is expressed by the following formula:

[0162]

[0163] Wherein, ε2 is the second preset convergence threshold.

[0164] The third precondition includes the variance components of each set of observations is not greater than a third preset convergence threshold.

[0165] Figure 2b A schematic diagram of streamer positioning is provided for an optional example of a method for positioning a streamer for offshore seismic exploration. Figure 2b As shown, the streamer positioning schematic diagram can accurately position the streamer.

[0166] Figure 2cA schematic diagram of the positioning effect of a variance component estimation method of an optional example of a positioning method for an offshore seismic exploration streamer is provided. Figure 2c As shown, the technical solution of the embodiment of the present invention can effectively eliminate the influence of inaccurate nominal accuracy of observation values ​​on weight determination. In offshore seismic exploration, the towed cable positioning sensor is located in the seawater, the observation environment is complex, and affected by the sea conditions. The nominal accuracy of the positioning observation value cannot accurately describe its actual observation accuracy, resulting in unreasonable weight ratio of the observation value obtained by the traditional empirical weight determination method. The technical solution of the embodiment of the present invention uses variance component estimation to weight the observation value, which can effectively eliminate this influence.

[0167] The technical solution of an embodiment of the present invention uses variance component estimation to determine the weight ratio between different types of observations in the towed cable positioning network. The variance component estimation can estimate the variance components of the observations based on the posterior residual information of the observations, and adjust the weight matrix based on the variance components. This can make the weight ratio between different types of towed cable positioning observations tend to be reasonable and improve the accuracy of towed cable positioning.

[0168] Embodiment 3

[0169] Figure 3 This is a schematic diagram of the structure of a positioning device for an offshore seismic exploration streamer provided in Embodiment 3 of the present invention. Figure 3 As shown, 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.

[0170] Among them, the observation value acquisition module 310 is used to obtain multiple groups of initial observation values ​​of the offshore seismic exploration streamer, wherein the initial observation values ​​include compass bird observation values ​​and acoustic distance observation values; the error function determination module 320 is used to respectively determine 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; the residual vector determination module 330 is used to construct 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 determine the residual vector corresponding to the initial observation value based on the solution corresponding to the normal equation; the positioning module 340 is used to adjust the initial observation value weight matrix based on the residual vector to obtain a target observation value weight matrix, and determine the position of the offshore seismic exploration streamer based on at least one of the target observation value weight matrices.

[0171] The technical solution of the embodiment of the present invention is to obtain multiple groups of initial observation values ​​of an offshore seismic exploration streamer, wherein the initial observation values ​​include compass bird observation values ​​and acoustic distance observation values; obtain azimuth observation values ​​and distance observation values ​​of the offshore seismic exploration streamer; then, respectively determine 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; construct an initial observation value matrix corresponding to the initial observation values ​​and accurately determine the error function corresponding to the initial observation values, and then construct 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 determine the residual vector corresponding to the initial observation value based on the solution corresponding to the normal equation; accurately determine the error corresponding to the initial observation value; finally, adjust the initial observation value weight matrix based on the residual vector to obtain a target observation value weight matrix, and determine the position of the offshore seismic exploration streamer based on at least one of the target observation value weight matrices, thereby solving the problem of low positioning accuracy of offshore seismic exploration streamers and achieving the beneficial effect of improving the accuracy of positioning of offshore seismic exploration streamers.

[0172] Optionally, the first error function is expressed by the following formula:

[0173]

[0174] Λ=diag(0,1,2,…N);

[0175]

[0176] Among them, α i is the observation value of the compass bird at point i on the tow cable, is the residual vector of the compass bird observation value, A 0 , B 0 is the predicted value of the polynomial coefficient, is the correction parameter of the compass bird observation value, It is the predicted value of the compass bird.

[0177] Optionally, the acoustic distance observation value includes a same-cable observation value and a different-cable observation value; accordingly, in the case where the acoustic distance observation value includes a different-cable observation value, the second error function is expressed by the following formula:

[0178]

[0179] Among them, R i,j is the acoustic distance observation value between point i and point j, is the residual vector of the acoustic distance observation, are the predicted values ​​of the polynomial coefficients of G cable and H cable, are the correction parameters of the acoustic distance observations, is the predicted value of acoustic distance;

[0180] In the case where the acoustic distance observation value includes the co-cable observation value, the second error function is expressed by the formula:

[0181]

[0182] S i,j =S j -S i ;

[0183] Among them, A 0 , B 0 is the predicted value of the polynomial coefficient of the towline, is the correction parameter of the acoustic distance observation.

[0184] Optionally, the error function determination module is specifically used for:

[0185] Determining 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 streamer positioning model;

[0186] The towline positioning model is expressed by the following formula:

[0187]

[0188] A=[a0,a1,…a n ] T ;

[0189] B=[b0,b1,…b n ] T ;

[0190] S=[s 0 ,s 1 ,…s N ] T ;

[0191] Where x, y are the coordinates of the streamer at an offset of s, N is the polynomial order, A, B are the polynomial coefficients, and S is the offset vector.

[0192] Optionally, the positioning module is specifically used for:

[0193] The variance components corresponding to the initial observation values ​​are determined based on the variance component estimation method and the residual vector, and each initial observation value weight matrix is ​​adjusted based on the variance component to obtain a target observation value weight matrix.

[0194] Optionally, the compass bird observation values ​​include acoustic network coverage observation values ​​and no acoustic network coverage observation values; the variance components include a first variance component corresponding to the same-cable observation value, a second variance component corresponding to the different-cable observation value, a third variance component corresponding to the acoustic network coverage observation value, and a fourth variance component corresponding to the no acoustic network coverage observation value;

[0195] Accordingly, the positioning module is specifically used for:

[0196] Based on the variance component estimation method and the residual vector, a first variance component corresponding to the same-cable observation value, a second variance component corresponding to the different-cable observation value, a third variance component corresponding to the acoustic network coverage observation value, and a fourth variance component corresponding to the no-acoustic network coverage observation value are respectively determined.

[0197] Optionally, the positioning module is specifically used for:

[0198] The initial observation value weight matrix is ​​adjusted 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.

[0199] Optionally, the variance component corresponding to the initial observation is determined by the following formula:

[0200]

[0201] r i =n i -tr(N -1 N i );

[0202] N=A T PA;

[0203]

[0204] in, is the variance component, V i is the residual vector corresponding to the initial observation value, P i is the initial observation weight matrix, r i is the error observation component of the initial observation value, n i is the number of initial observations, N, N i is the design matrix corresponding to the initial observations.

[0205] Optionally, the error function determination module is specifically used for:

[0206] For each group of initial observation values, an initial weight ratio corresponding to each initial observation value is determined, and an initial observation value weight matrix corresponding to the initial observation value is constructed based on a plurality of the initial weight ratios.

[0207] The positioning device for offshore seismic exploration streamers provided in the embodiments of the present invention can execute the positioning method for offshore seismic exploration streamers provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0208] Embodiment 4

[0209] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0210] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to 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.

[0211] A number of 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, speakers, etc.; a storage unit 18, such as a 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.

[0212] The processor 11 may be a variety of general and / or special 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 dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, such as the method for positioning the offshore seismic exploration streamer.

[0213] In some embodiments, the method for positioning the offshore seismic exploration streamer can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on 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 for positioning the offshore seismic exploration streamer described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the method for positioning the offshore seismic exploration streamer in any other suitable manner (for example, by means of firmware).

[0214] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0215] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0216] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0217] To provide interaction with a user, the systems and techniques described herein may 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 trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0218] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may 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.

[0219] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may 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 difficult management and weak business scalability in traditional physical hosts and VPS services.

[0220] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0221] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for positioning a streamer for offshore seismic exploration, characterized in that: include: Acquiring multiple groups of initial observation values ​​of the offshore seismic exploration streamer, wherein the initial observation values ​​include compass bird observation values ​​and acoustic distance observation values; Respectively 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 a normal equation by using 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; The initial observation value weight matrix is ​​adjusted based on the residual vector to obtain a target observation value weight matrix, and the position of the offshore seismic exploration streamer is determined based on at least one of the target observation value weight matrices.

2. The method according to claim 1, characterized in that The first error function is expressed by the following formula: Λ=diag(0,1,2,…N); Among them, α i is the observation value of the compass bird at point i on the tow cable, is the residual vector of the compass bird observation value, A 0 , B 0 is the predicted value of the polynomial coefficient, is the correction parameter of the compass bird observation value, It is the predicted value of the compass bird.

3. The method according to claim 2, characterized in that The acoustic distance observation values ​​include same-cable observation values ​​and different-cable observation values; In the case where the acoustic distance observation value includes a different cable observation value, the second error function is expressed by the following formula: Among them, R i,j is the acoustic distance observation value between point i and point j, is the residual vector of the acoustic distance observation, are the predicted values ​​of the polynomial coefficients of G cable and H cable, are the correction parameters of the acoustic distance observations, is the predicted value of acoustic distance; In the case where the acoustic distance observation value includes the co-cable observation value, the second error function is expressed by the formula: S i,j =S j -S i ; Among them, A 0 , B 0 is the predicted value of the polynomial coefficient of the towline, is the correction parameter of the acoustic distance observation.

4. The method according to claim 2 or 3, characterized in that: The determining of a first error function corresponding to the compass bird observation value and a second error function corresponding to the acoustic distance observation value comprises: Determining 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 streamer positioning model; The towline positioning model is expressed by the following formula: A=[a0,a1,…a n ] T ; B=[b0,b1,…b n ] T ; S=[s 0 ,s 1 ,…s N ] T ; Where x, y are the coordinates of the position on the streamer at an offset of s, N is the polynomial order, A, B are the polynomial coefficients, and S is the offset vector.

5. The method according to claim 1, characterized in that: The adjusting each of the initial observation value weight matrices based on the residual vector to obtain a target observation value weight matrix includes: The variance components corresponding to the initial observation values ​​are determined based on the variance component estimation method and the residual vector, and each initial observation value weight matrix is ​​adjusted based on the variance component to obtain a target observation value weight matrix.

6. The method according to claim 5, characterized in that The compass bird observation values ​​include acoustic network coverage observation values ​​and no acoustic network coverage observation values; the variance components include a first variance component corresponding to the same-cable observation value, a second variance component corresponding to the different-cable observation value, a third variance component corresponding to the acoustic network coverage observation value, and a fourth variance component corresponding to the no acoustic network coverage observation value; The determining of the variance component corresponding to the initial observation value based on the variance component estimation method and the residual vector comprises: Based on the variance component estimation method and the residual vector, a first variance component corresponding to the same-cable observation value, a second variance component corresponding to the different-cable observation value, a third variance component corresponding to the acoustic network coverage observation value, and a fourth variance component corresponding to the no-acoustic network coverage observation value are respectively determined.

7. The method according to claim 6, characterized in that The adjusting each of the initial observation weight matrices based on the variance component to obtain a target observation weight matrix includes: The initial observation value weight matrix is ​​adjusted 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.

8. The method according to claim 5, characterized in that The variance component corresponding to the initial observation is determined by the following formula: r i =n i -tr(N -1 N i ); N=A T PA; in, is the variance component, V i is the residual vector corresponding to the initial observation value, P i is the initial observation weight matrix, r i is the error observation component of the initial observation value, n i is the number of initial observations, N, N i is the design matrix corresponding to the initial observations.

9. The method according to claim 1, characterized in that: 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 an initial observation value weight matrix corresponding to the initial observation value is constructed based on a plurality of the initial weight ratios.

10. A positioning device for an offshore seismic exploration streamer, characterized in that: include: An observation value acquisition module, used to acquire multiple groups of initial observation values ​​of the offshore seismic exploration streamer, wherein the initial observation values ​​include compass bird observation values ​​and acoustic distance observation values; An error function determination module, used 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 value, and a second error function corresponding to the acoustic distance observation value; a residual vector determination module, configured to construct a normal equation by using the initial observation value weight matrix corresponding to the initial observation value, the first error function, and the second error function, and determine a residual vector corresponding to the initial observation value based on a solution corresponding to the normal equation; A positioning module is used to adjust the initial observation value weight matrix based on the residual vector to obtain a target observation value weight matrix, and determine the position of the offshore seismic exploration streamer based on at least one of the target observation value weight matrices.

Images