Mapping method for monitoring the condition and / or geolocation of a buried, semi-buried or submerged structure comprising a metallic or magnetic material

Abstract

The present invention relates to a mapping method for monitoring the condition and / or geolocation of a buried, semi-buried or submerged structure comprising a metallic or magnetic material, in which the following are carried out: a step of acquiring spatialized magnetic data obtained by magnetic sensors at different measurement points in the area to be monitored, after injecting a current into the structure, a step of generating a temporary segment, comprising a set of temporary points, and a volume around each temporary point, the volume comprising a cloud of points, and a simulation step, for each point of each volume, making it possible to calculate the simulated magnetic values of the points in the cloud at all or some of the measurement points.

Description

Title of the invention: Mapping method for monitoring the condition and / or geolocation of a buried, semi-buried or submerged structure comprising a metallic or magnetic material Technical field

[0001] The present invention relates to a mapping method for monitoring the condition and / or geolocation of a buried, semi-buried or submerged structure comprising a metallic or magnetic material. The invention will find its application in the location of pipelines, in particular for the transfer of liquid or gas. The invention may also be used for the detection and geolocation of other types of structures or in geophysical research. Also, the invention may be used in the external monitoring of structures both for monitoring the integrity of the structure and for evaluating the magnetic connection between two neighboring structures. Technological background

[0002] Various detection methods using magnetometers for the detection of non-visible structures are known, as well as various associated methods.

[0003] We also know methods using various technologies such as radiodetection, radar, lidar. Each time in these different known techniques, measurements are taken, in particular by scanning the sector to be controlled, then we generate, from the collected data combining the measurements and the positioning of the measurements, a 2D or 3D geolocation map. For the generation of these maps, we do not always check for anomalies in the measurements which can find their sources in various causes and in particular the failure of a sensor or even interference due to nearby structures. As a result, these generated maps generally lack precision and moreover can contain aberrations.

[0004] The applicant has filed an application WO2023148057 to overcome some of the aforementioned drawbacks. In this application, a method is provided for generating an interactive magnetic map from the collected magnetic data. From this interactive magnetic map, an operator can add or delete magnetic data to correct detection anomalies or to interpolate data based on neighboring magnetic data. In the method described in this application, the data and the successive processing or filtering make it possible to give good results in most cases, however this method requires human intervention to correct a certain number of anomalies. This intervention by an operator requires good experience and is time-consuming. In addition, this This type of process does not allow for the automatic invalidation of an erroneous or inconsistent structure layout or positioning, whether the source of these layout errors comes from the magnetic data collected or from a poor choice of model. This type of process also does not allow for the comparison of real data with data from simulation models.

[0005] Technical problem to be solved

[0006] A technical problem that the present invention proposes to solve is to provide a new mapping method in which the magnetic data are compared with simulated data making it possible to improve the accuracy of the location of the structure.

[0007] Another problem that the present invention aims to solve is to propose a method for verifying and / or correcting the results obtained from the simulation and the data collected without human intervention.

[0008] Another problem that the present invention proposes to solve is to prevent the generation of the geolocation map in the event of inconsistency or aberration.

[0009] Another problem that the present invention aims to solve is to propose a method that is simple to implement and makes it possible to test several hypotheses until a coherent geolocation map is obtained. Summary of the invention

[0010] The present invention relates to a mapping method for monitoring the condition and / or geolocation of a buried, semi-buried or submerged structure comprising a metallic or magnetic material, this method comprises the steps described below.

[0011] The mapping method comprises a step of acquiring spatialized magnetic data obtained by magnetic sensors at different measurement points in the area to be controlled, after injecting a current into the structure.

[0012] The method further comprises a step of generating a provisional segment, comprising a set of provisional points (Pi), and a volume (Vi) around each provisional point (Pi), the volume (Vi) comprising a cloud of points.

[0013] The method further comprises a simulation step, for each point of each volume (Vi), making it possible to calculate the simulated magnetic values ​​(VMS) of the points of the cloud at all or part of the measurement points (Pm).

[0014] The method further comprises a step of comparison between the simulated magnetic values ​​(VMS) of the cloud points of each volume (Vi) and the spatialized magnetic values ​​(VM) to assign a score to each cloud point of each volume (Vi),

[0015] The method further comprises a step of selecting, for each volume (Vi), a point of the cloud presenting the best score, the set of selected points (Si) replacing the set of provisional points (Pi) of the provisional segment.

[0016] The method further comprises a step of creating a magnetic map containing all of the selected points (Si).

[0017] Definitions

[0018] According to the present invention, the expression magnetic or metallic material, in this application, refers to any type of conductive material generating a magnetic field after injection of a current, and in particular includes ferromagnetic type materials.

[0019] According to the present invention, the expression point cloud, in this application, refers to an unlimited set of points distributed in an orderly or random manner in a volume. Brief description of the figures

[0020] Other characteristics and advantages of the present invention will emerge from the description of the particular and non-limiting exemplary embodiments of the present invention below, with reference to the appended figures 1 to 4, in which:

[0021] [Fig.l] schematically illustrates part of the steps of the method according to the invention,

[0022] [Fig.2] schematically illustrates an example of a plot generated by the implementation of the method according to the invention,

[0023] [Fig.3] represents an example of a map obtained by implementing the method according to the invention,

[0024] [Fig.4] represents an example of implementation of the method in the form of a diagram showing the different stages of the method according to the invention. Detailed description

[0025] [Fig.l] generally illustrates different steps of the method. More precisely, the method comprises a step of acquiring spatialized magnetic data obtained by magnetic sensors at different measurement points in the area to be controlled, after injecting a current into the structure. These measurement points are represented schematically by the set of points Pm in the upper part of [Fig.l].

[0026] The example of figures 1 and 2 is a simplified example, it therefore comprises a limited number of measurement points Pm at average altitudes, this being the principle of the measurement and the process steps are identical for the processing of a real case even if the number of measurements is greater.

[0027] The magnetic measurement of the measurement points is advantageously carried out by magnetometers, in particular placed on a mobile device such as a vehicle or an aircraft and in particular by a drone equipped with magnetometer ramps. The device mobile moves in line with the area to be controlled advantageously along bands substantially parallel to the assumed positioning of the buried structure or even according to a grid.

[0028] When the measuring points Pm have been obtained, the magnetic data can be processed so that they can be compared in the subsequent steps of the method.

[0029] According to a first example, in order to be able to collect the magnetic data, a step of injecting a current into the structure and a step of processing the signal are carried out, of the electrical component of the signal emitted by the structure in response to the injection of the signal allowing comparison with the simulated magnetic values.

[0030] According to a second advantageous example, this step of acquiring spatialized magnetic data comprises a step of injecting an alternating current into the structure and a step of processing the magnetic measurements via bandpass filtering and a Hilbert filter.

[0031] The method then comprises a step of generating a provisional segment, comprising a set of provisional points Pi. In the simplified example, the provisional segment 1 comprises ten provisional points PI to P10.

[0032] The positioning of its points PI to P10 can be carried out according to several options depending on the actual case to be treated. According to a first embodiment, it is possible to base oneself on terrain data, in particular if one or more positioning points of the structure are known. It is also possible to position this provisional segment 1 from existing cartographic data even if the latter can be improved or is even imprecise. In the absence of data, it is also possible to place the points according to hypotheses on the location of the buried structure or even hypotheses on its general shape.

[0033] The distance between the provisional points Pi can also vary, in particular depending on the precision required for geolocation. Advantageously, the length of a sub-segment between two successive provisional points is between 5 and 15% of the expected length of the smallest dimension of the structure.

[0034] In this step of generating the provisional segment 1, we also plan to generate a volume Vi around each provisional point Pi.

[0035] In the example of Figures 1 and 2, a single volume Vi is represented comprising a cloud of points. This volume Vi is arranged around the provisional point P4. That being said, the method generates a volume Vi around each provisional point Pi to allow the comparison steps described below.

[0036] In the example of figures 1 and 2 this volume Vi around a point Pi is a cube, centered on Pi, whose edge length corresponds to the length of the sub-segment between two successive points Pi. The set of volumes Vi thus forms a volume integrating the whole of the provisional segment 1. However in other embodiments we can provide volumes with different geometries and for example spheres around the points Pi. Also in other embodiments it can be provided that the successive volumes overlap or on the contrary are not in contact.

[0037] Referring to [Fig.l], a simplified example of distribution of the point cloud in a volume Vi is shown. According to an advantageous mode, the cloud points are distributed homogeneously in the volume Vi. However, other distribution modes are also conceivable, such as a random distribution of points in the volume or even increasing or decreasing concentrations or densities of points around the provisional point Pi.

[0038] According to another embodiment, it is also provided that additional cloud points of a volume Vi are created successively during the simulation step and positioned in the volume Vi according to the scores of the cloud points simulated in the simulation step.

[0039] According to the invention, the method further consists of carrying out a simulation step, for each point of each volume Vi, making it possible to calculate the simulated magnetic values ​​(VMS) of the points of the cloud at all or part of the measurement points.

[0040] In the example of Figures 1 and 2, the magnetic value of each cloud point of each volume Vi is advantageously simulated at the level of all the measurement points Pm. However, this simulation requires a very large calculation volume when the cloud points on the one hand and the measurement points on the other hand are numerous. To limit the calculation requirement, the magnetic value of each cloud point can also be simulated on only a part of the measurement points Pm.

[0041] For example, it will be possible to simulate the magnetic value (VMS) of a cloud point only on the measurement points located at a distance less than a value D from said point. This limitation makes it possible to reduce the calculation requirements while keeping the simulated magnetic values ​​on the measurement points Pm that are most significant for the cloud point considered.

[0042] By way of example, it is also provided that the simulation step, for each point of each volume (Vi), makes it possible to calculate the simulated magnetic values ​​(VMS) of the points of the cloud at a number N of measurement points among the set of measurement points and corresponding to the N measurement points closest to the point Pi of the volume (Vi) considered.

[0043] The simulation of the magnetic value of a point of the volume on all or part of the measurement points Pm is obtained by applying the Biot and Savart formula defining the magnetic field vector as a function of the set of infinitesimal functions of the pipeline sections.

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[0052] The following formula is applied for the simulation of the simulated magnetic values ​​with the variables listed in the table below: [Formula 1] b( T ) = V > 471C [Tables 1] Variable Meaning B(r) The magnetic field at the point considered with coordinates x, y, z. Ho 4tt A constant specific to the medium considered homogeneous. (Magnetic permeability of vacuum). ï The direction of the direct current in the infinitesimal section of the pipeline. dT Generator of the section considered with a section length is a unit vector in three dimensions. r Vector defining the oriented distance between the origin of the considered frame and the measurement point. f Vector defining the oriented distance between the origin of the considered frame and the center of the infinitesimal section of the section. Line integral. This formula is then adapted to a computer simulation in which infinitesimal sections of pipelines are considered as portions of short distances. For each section, the following formula is obtained: [Formula 2] dB(r) = IM with g(r) = ^cdB(r) This second formula allows the creation of a function to simulate the magnetic values ​​at the measurement points (VMS) based on a configuration of sections for cloud points.

[0053] When the simulation step is completed with the calculation of the simulated magnetic values ​​(VMS), the method further comprises performing a comparison step between the simulated magnetic values ​​(VMS) of the cloud points of each volume Vi and the spatialized magnetic data to assign a score to each cloud point of each volume Vi.

[0054] Advantageously, the score assigned to a point of a point cloud is a function of the comparison between the simulated magnetic values ​​(VMS) of this point at the measurement points Pm and the measured values ​​(VM) at these measurement points Pm, i.e. the measured values ​​(VM) obtained by the magnetometers, possibly corrected or processed to be able to be compared with the simulated magnetic values ​​(VMS).

[0055] Generally speaking, the best score will be assigned to the point in the cloud whose VMS are closest to the VM of the measurement points.

[0056] At this level, different types of scoring algorithms can be considered, including algorithms using different convergence methods such as the methods shown in the table below:

[0057] [Tables2] Method Explanation Nelder-Mead The Nelder-Mead method is a numerical method optimized for minimizing nonlinear problems where the derivative is unknown. It is a heuristic search method that can converge to non-stationary points. Powell The Powell method is an iterative minimization method for least-squares problems. This method uses gradient descent to search for parameter sets. CG The conjugate gradient method finds the local minimum closest to minimization by performing multidimensional gradient descent. BFGS The Broyden-Fletcher-Goldfarb-Shanno method is an unconstrained nonlinear minimization method. This method is based on the analysis of successive gradients without constructing Hessian matrices. This method assumes a solution to the optimum being quadratic around the optimum.L-BFGS-B This BFGS-based method adds memory size limitation and constraints on the minimization parameters to guide gradient descent and avoid solution divergence. SLSQP The SQP-based sequential least squares programmed optimization method is a method for quasi-Newtonian problems to model the local parameter problem as a quadratic hyperplane to find the global minimum.

[0058] Of course, other convergence methods can also be considered for calculating the score; depending on the application, one of the minimization methods will be selected and associated with a score calculation function.

[0059] The score calculation may be, according to a first embodiment, based on the errors at the measurement points between the actual measurement VM and the simulated value VMS. Among the different functions allowing this score calculation, a function may be used from the non-limiting list of the following functions: f (sum of the squared errors between the VMS and the VM), f (average of the squared errors between the VMS and the VM), f (median of the squared errors between the VMS and the VM), f (90th percentile of the squared errors between the VMS and the VM), f (maximum squared errors between the VMS and the VM).

[0060] The score calculation may also be, according to a second exemplary embodiment, based on the variation at the measurement points between the actual measurement and the simulated value. Among the different functions allowing this score calculation, a function may be used from the non-limiting list of the following functions shown in the table below with their description.

[0061] [Tables3] Function Description Log_pearson _ / W 103 2 - pearsonmag . mag A 1 y °measure' '-synthetic / / equation allows to have a minimum when the correlation is maximum Sum_square_diff_normali ze V / , - / This L mag - normalize mag fl r "y cmeasure y °syntnetic / / equation looks at the normalized squared error, in order to remove the initialization problem in C. Log_spearman Ios2-spearman(mag , mag nThis 1 y ^measure' “synthetic / / equation allows to have a minimum when the correlation is maximum Variance Minimization of the vailmag -mag z \ °measure ^synthetic / variance STD Minimization of the deviation sta mag -mag . z] y '-measure Dsyntnet)c / type

[0062] The choice of the minimization method and the calculation of the score allows the operator to highlight different parameters such as the speed of convergence towards the point of the cloud to be selected, the convergence towards a global optimum, or even the precision of the convergence when the convergence stops.

[0063] When the comparison step is completed with the calculation of the scores of the points of the cloud, the method further consists of carrying out a step of selecting, for each volume Vi, a point of the cloud having the best score, the set of selected points Si replacing the set of provisional points Pi of the provisional segment 1.

[0064] Referring to [Fig.2], we see the definitive segment referenced 2. Compared to the provisional segment, only point PI is retained, the definitive segment 2 being arranged slightly below the provisional segment.

[0065] According to an advantageous embodiment of the invention, the selection step consists of retaining the point of the cloud having the best score and preventing the generation of the magnetic card if a selected point If at least one of the sub-segments has an insufficient score compared to a predetermined score value.

[0066] This feature is particularly important since it prevents the generation of geolocation maps presenting aberrations or anomalies.

[0067] According to this characteristic, if the score is insufficient, which corresponds to too great a divergence between the simulated magnetic values ​​(VMS) and the measured values ​​(VM), different possibilities are possible. According to a first option, the method generates an error message for the operator. The operator can then analyze the reasons for the failure of the map generation and restart the process.

[0068] According to a second option, if a selected point Si has an insufficient score, the method resumes at the first step of generating a segment with other hypotheses and in particular a new magnetic data set, or another numerical simulation model or another buried structure scenario, or another initial positioning of provisional segment. This procedure can advantageously be restarted until a hypothesis makes it possible to obtain points Si having sufficient scores.

[0069] Of course, in the method according to the invention, it is not necessary to go through steps of displaying the positions of the measurement points Pm, of the provisional segment 1 or even of the definitive segment 2. These display steps can however be provided in an alternative embodiment to improve the understanding of the results for the operator.

[0070] The method according to the invention makes it possible to determine by calculation and simulation the selected points Si. This determination of the points Si will make it possible to carry out the step of creating a magnetic map containing all the selected points Si.

[0071] Referring to [Fig.3] we see an example of a magnetic card 4 according to the invention.

[0072] In the example of [Fig.3], we see that the segment corresponding to the structure has softened angles. According to an advantageous characteristic of the invention, during the step of creating the magnetic map 4, a smoothing step is provided to limit the angles between two successive sub-segments. This step makes it possible to refine the general shape of the final segment to make it compatible with the expected general shape of the structure to be geolocated.

[0073] According to an advantageous embodiment, the magnetic creation step allows a display of zones of variable precision depending on the scores of each sub-segment and / or the final segment score 2. These different zones will allow an operator to quickly view the zones depending on the estimated precision of the location. In the example of [Fig.3] the gray levels make it possible to identify the precision of one zone in relation to another. However, in other embodiments the precision of the zones could be indicated differently, for example by a color code or even numerical values.

[0074] Referring this time to [Fig. 4], an example of the implementation of the method is shown in the form of a diagram. The different stages of the mapping method are summarized in the form of a diagram allowing the operation and advantages of the invention to be understood, particularly in relation to the state of the art.

[0075] Of course, other characteristics within the reach of those skilled in the art could also have been envisaged without departing from the scope of the invention as defined in the following claims.

Claims

Claims

1. Mapping method for monitoring the condition and / or geolocation of a buried, semi-buried or submerged structure comprising a metallic or magnetic material, characterized in that it comprises: - a step of acquiring spatialized magnetic data obtained by magnetic sensors at different measurement points of the area to be monitored, after injecting a current into the structure, - a step of generating a temporary segment, comprising a set of temporary points (Pi), and a volume (Vi) around each temporary point (Pi), the volume (Vi) comprising a cloud of points, - a simulation step, for each point of each volume (Vi), making it possible to calculate the simulated magnetic values ​​(VMS) of the points of the cloud at all or part of the measurement points (Pm),- a step of comparison between the simulated magnetic values ​​(VMS) of the cloud points of each volume (Vi) and the magnetic values ​​(VM) of the spatialized magnetic data to assign a score to each cloud point of each volume (Vi), - a step of selection, for each volume (Vi), of a point of the cloud presenting the best score, the set of selected points (Si) replacing the set of provisional points (Pi) of the provisional segment, - a step of creation of a magnetic map including the set of selected points (Si).,

2. Mapping method according to claim 1 in which the volume (Vi) around a provisional point (Pi) is a cube, centered on (Pi), whose edge length corresponds to the length of the sub-segment between two successive provisional points (Pi).

3. Mapping method according to any one of the preceding claims in which the cloud points are distributed homogeneously in the volume (Vi)

4. A mapping method according to any preceding claim wherein the simulated magnetic value (SMV) of a cloud point at a measurement point is obtained by applying the following formula: dB(?) = 3(7) =fcdB(T)

5. Mapping method according to any one of the preceding claims in which the score attributed to a point of a point cloud is a function of the comparison between the simulated magnetic values ​​(VMS) of this point at the measurement points and the measured values ​​(VM) at these measurement points (PM).

6. A mapping method according to claim 5 wherein the calculation of the score of a cloud point is based on the errors at the measurement points between the measured magnetic value (VM) and the simulated magnetic value (VMS).

7. A mapping method according to claim 5 wherein the calculation of the score of a cloud point is based on the variation at the measurement points between the measured magnetic value (VM) and the simulated magnetic value (VMS).

8. Mapping method according to any one of the preceding claims in which the simulation step, for each point of each volume (Vi), makes it possible to calculate the simulated magnetic values ​​(VMS) of the points of the cloud at a number N of measurement points among the set of measurement points and corresponding to the N measurement points closest to the point Pi of the volume (Vi) considered.

9. A mapping method according to any preceding claim wherein additional cloud points of a volume (Vi) are successively created during the simulation step and positioned in the volume (Vi) based on the scores of the cloud points simulated in the simulation step.

10. Mapping method according to any one of the preceding claims in which the selection step consists of retaining the point of the cloud having the best score and preventing the generation of the magnetic map if a selected point (Si) of at least one of the sub-segments has an insufficient score compared to a predetermined score value.

11. A mapping method according to any preceding claim wherein if a selected point (Si) has an insufficient score, the method resumes at the first step of generating a segment with a new magnetic data set, or another digital simulation model, another buried structure scenario, or another initial provisional segment positioning.

12. A mapping method according to any preceding claim wherein the magnetic creation step enables a display of areas of variable precision depending on the scores of each final sub-segment (2) and / or the score of the final segment (2).

13. Mapping method according to any one of the preceding claims in which it is provided that said creation step comprises a smoothing step making it possible to limit the angles between two successive definitive sub-segments (2).

14. Mapping method according to any one of the preceding claims in which the step of acquiring the spatialized magnetic data comprises: - a step of injecting a current into the structure, - a step of processing the signal, of the electrical component of the signal emitted by the structure in response to the injection of the signal allowing comparison with the simulated magnetic values.

15. Mapping method according to any one of the preceding claims in which the step of acquiring the spatialized magnetic data comprises: - a step of injecting an alternating current into the structure, - a step of processing the magnetic measurements via bandpass filtering and a Hilbert filter.

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