SYSTEM FOR THE TEMPORAL STATISTICAL ANALYSIS OF SPATIAL ANOMALIES FOR THE DETECTION AND VISUALIZATION OF AREAS OF FLUID MOVEMENT AND ASSOCIATED METHOD

Abstract

The invention relates to a system for the temporal statistical analysis of spatial anomalies intended for the detection and visualization of fluid movement zones in a geological subsoil, said system comprising an integer number M of sensors (2), said integer number M being greater than or equal to 3, said sensors (2) being configured to measure a wave (3) propagating in said geological subsoil over an observation period to obtain at least one measurement signal and a controller configured to implement several steps of processing said measurement signal. The invention also relates to a method for detecting and visualizing fluid movement zones. The invention further relates to a computer program comprising program code instructions for executing the steps of said method, said program running on a controller. Abstract figure: Fig. 1

Description

Title of the invention: SYSTEM FOR THE TEMPORAL STATISTICAL ANALYSIS OF SPATIAL ANOMALIES INTENDED FOR THE DETECTION AND VISUALIZATION OF AREAS OF FLUID MOVEMENT AND ASSOCIATED METHOD

[0001] The invention relates to a system and a method implemented in the field of geology and, more particularly, of seismic prospecting.

[0002] Known from the prior art is a patent application WO2020038985 disclosing a method for detecting a fluid in the subsoil and an associated system describing means implementing said method. A simplified detection method is proposed compared to the prior art while preserving identical precision. The method comprises a measurement step during which wave sensors detect a mechanical wave, each sensor being able to recognize the amplitude and frequency of the wave. The detection of the wave by the sensor generates a signal which subsequently undergoes a cutting step over several time intervals of predefined duration, between 5 minutes and 2 hours. Thus, samples of the measured signal are obtained. Each signal corresponds to a cutting time interval. An additional step of filtering and / or spectral equalization of the signal can be carried out between the measurement step and the cutting step.The two steps of filtering and spectral equalization allow to reduce the defects or anomalies of the seismic noise in order to improve the accuracy of the signal. An optional step of energy normalization can be performed during which each sample of the signal is standardized in order for each sample to have a similar energy compared to each other. An optional step of autocorrelation of a seismic noise window takes place. The autocorrelation aims to reconstruct a coherent wave field measured by the sensor. A diagram showing all the autocorrelations measured over time is established thanks to these measurements. Thus, it is possible to distinguish a significant change in the autocorrelation values, indicating the presence of a fluid. Optionally, a reference is defined.The reference corresponds to the average of all the autocorrelation values ​​of the samples of the signal considered over a given time period. A step of calculating the temporal coherence of the samples of the measured signal is then implemented. The temporal coherence corresponds to the value of the same sample at two different times. There is also a step of determining the presence of a fluid using the calculation of the temporal coherence. The variations of the temporal coherence values ​​effectively indicate the presence of a fluid but they indicate . also changes in the properties of the fluid. By change in properties, this can include a change in its composition or its migration. However, there is one drawback. While it is possible to determine the presence or absence of fluids on graphs, none of the methods mentioned above allow for geographical identification of the areas where the fluids are located. This makes it difficult to determine precisely where the geological subsoil should be inspected to extract the said fluids.

[0003] The objective of the present invention is to remedy these drawbacks by proposing a system allowing the establishment of a geographical map indicating the areas most likely to contain fluids.

[0004] To achieve this objective, the invention proposes a system for temporal statistical analysis of spatial anomalies intended for the detection and visualization of zones of fluid movement in a geological subsoil comprising: - an integer number M of sensors, said integer number M being greater than or equal to 3, said sensors being configured to measure at least one wave propagating in said geological subsoil over an observation period to obtain at least one measurement signal, said sensors forming pairs of sensors, a first 2 sensor and a second sensor forming a sensor pair; - a controller configured to: - reconstructing a series of waveforms by interferometry of said measurement signal from said pair of sensors at a regular time interval over said observation period; - extracting a coherence time series associated with said pair of sensors, all of said pairs of sensors forming a plurality of coherence time series; - spatially interpolating said plurality of coherence time series; - represent a plurality of results from the spatial interpolation of said plurality of coherence time series in the form of a coherence map having a plurality of cells, each cell representing an elementary part of the geological subsoil; - set a statistical analysis duration; - calculate a plurality of anomaly occurrence values ​​Oc;k corresponding to the number of times the value of a mesh is lower than a predefined threshold value; - calculate the probability density function of the appearance of an anomaly for said mesh using the following formula: pj fk _ with pd fk being the probability of coherence anomaly for the i - i ' i th mesh at the &-th analysis period of N days; and Oc^ being the occurrence of coherence anomaly for the i-th mesh at the ^-th analysis period of N days; - establish a probability map of anomaly occurrence by listing each probability value of an anomaly appearing for the mesh; - obtain a frequency at which the anomaly occurs and a location of changes in said geological subsoil based on the probability of coherence anomaly.

[0005] Thanks to the invention, it is possible to precisely locate the areas of the geological subsoil presenting a high probability of harboring a fluid.

[0006] Advantageously, said controller is configured to spatially interpolate said plurality of coherence time series by a tomographic inversion process.

[0007] Spatial interpolation by tomographic inversion allows for an irregular weighting of the information on the anomaly occurrence probability map. Thus, this process also allows for the correction of geometric effects resulting from all the sensors present in the studied territory.

[0008] Advantageously, said controller is configured to spatially interpolate said plurality of coherence time series by calculating average values ​​distributed over beam trajectories.

[0009] Preferably, said integer M is equal to 3, said sensors being aligned.

[0010] Thus, the system is functional from only 3 sensors.

[0011] Advantageously, said sensors are geophones or hydrophones.

[0012] Thus, the detection of waves is permitted on an emerged land or on a seabed.

[0013] Preferably, said wave is a wave emanating from a natural source.

[0014] The study of ambient seismic noise, or continuous seismic noise, is thus permitted.

[0015] Preferably, said wave is a wave emanating from an artificial source.

[0016] Advantageously, said card comprises between 10 and 20,000 meshes, preferably between 100 and 10,000 meshes, more preferably between 1,000 and 5,000 meshes.

[0017] Furthermore, the invention also relates to a method for temporal statistical analysis of spatial anomalies intended for the detection and visualization of zones of fluid movement in said geological subsoil implementing said system according to the present invention comprising the following steps: - a step of acquiring at least one measurement signal during an observation period; - a step of reconstructing a series of waveforms by interferometry of said measurement signal from said pair of sensors at regular time intervals over said observation period; - a step of extracting a coherence time series associated with said pair of sensors by measuring the evolution of a waveform by autocorrelation over a given period, all of said pairs of sensors forming a plurality of coherence time series; - a step of spatial interpolation of said plurality of coherence time series; - a step of representing the results from the spatial interpolation of the plurality of coherence time series in the form of a coherence map presenting a plurality of cells, each cell representing an elementary part of the geological subsoil; - a step of setting a statistical analysis duration;- a step of calculating the anomaly occurrence values ​​Oc;k corresponds to the number of times the value of a mesh is lower than a threshold value; - a step of calculating the probability density function of the appearance of a anomaly for each mesh by the following formula: p(l fk — with prf fk being the probability of coherence anomaly for the i-th mesh at the ^-th period of N days; and Oc1- being the occurrence of coherence anomaly for the i-th mesh at the £-th period of N days; - a step of modeling a probability map of anomaly occurrence by listing each probability value of an anomaly appearing for each mesh; - a step of obtaining the frequency at which the anomaly occurs and the location of changes in said geological subsoil on the basis of the probability of coherence anomaly.

[0018] The invention also relates to a method for the temporal statistical analysis of spatial anomalies intended for the detection and visualization of zones of fluid movement in a geological subsoil, said method implementing an integer number M of sensors, said integer number M being greater than or equal to 3, said sensors being configured to measure at least one wave propagating in said geological subsoil over an observation period to obtain at least one measurement signal, said sensors forming pairs of sensors, including a first sensor 2 and a second sensor forming a pair of sensors, characterized in that said method comprises the following steps: - a step of acquiring at least one measurement signal during an observation period; - a step of reconstructing a series of waveforms by interferometry of the measurement signal from said pair of sensors at a regular time interval over an observation period; - a step of extracting a coherence time series associated with said pair of sensors by measuring the evolution of a waveform by autocorrelation over a given period, all of said pairs of sensors forming a plurality of coherence time series; - a step of spatial interpolation of said plurality of coherence time series; - a step of representing the results from the spatial interpolation of the plurality of coherence time series in the form of a coherence map presenting a plurality of cells, each cell representing an elementary part of the geological subsoil; - a step of setting a statistical analysis duration; - a step of calculating the anomaly occurrence values ​​Oc;k corresponds to the number of times where the value of a mesh is lower than a threshold value; - a step of calculating the probability density function of the appearance of an anomaly for each mesh by the following formula: pj fk „ e^Oc: with prf being the probability of coherence anomaly for the z-th mesh at the ^-th period of N days; and Oc1} being the occurrence of coherence anomaly for the z-th mesh at the £-th period of N days; - a step of modeling a probability map of anomaly occurrence by listing each probability value of an anomaly appearing for each mesh; - a step of obtaining a frequency at which the anomaly occurs and a location of the changes in said geological subsoil on the basis of the probability of coherence anomaly.

[0019] Preferably, the extraction step implements a method for monitoring the speed variations of said waveforms.

[0020] Advantageously, the spatial interpolation step is carried out by a tomographic inversion process.

[0021] Advantageously, the spatial interpolation step is carried out by calculating average values ​​distributed over beam trajectories.

[0022] Furthermore, the invention also relates to a computer program comprising program code instructions for executing the steps of the method of temporal statistical analysis of spatial anomalies intended for the detection and visualization of areas of fluid movement in the geological subsoil, when the said program runs on a controller.

[0023] Automating the implementation of the process makes it possible to reduce the human resources required for its execution. Limiting human resources results in a reduction in the number of errors that can occur and a reduction in the execution time of the process.

[0024] The invention will be further detailed by the description of a non-limiting embodiment, and on the basis of the appended figures illustrating variants of the invention, in which: - [Fig.l] schematically illustrates a seismic data acquisition system for the temporal statistical analysis of spatial anomalies in the context of the detection and visualization of fluid movement zones; - [Fig.2] schematically illustrates a method of temporal statistical analysis of spatial anomalies intended for the detection and visualization of fluid movement zones.

[0025] [Fig.l] schematically illustrates a seismic data acquisition system for the temporal statistical analysis of spatial anomalies in the context of the detection and visualization of fluid movement zones in a geological subsoil. [Fig.l] represents a surface 1 delimiting said geological subsoil that it is desired to study. Four sensors are arranged on said surface 1. The sensors are otherwise called geophones when they are located on an emerged land or hydrophones when they are located on a seabed. The geological subsoil is defined as designating the entire Earth's crust. The invention can therefore be implemented on an emerged land or on a seabed. Commonly, work taking place on the emerged land is called "onshore", while work taking place on a seabed is called "offshore".In an alternative, the sensors 2 are distributed under the surface 1 in boreholes, otherwise called wells. The geological subsoil comprises a plurality of waves 3 originating from a continuous seismic noise. The continuous seismic noise corresponds to all the waves 3 naturally present in the subsoil, without any human intervention necessary. The sensors 2 measure the frequency and amplitude of the mechanical wave 3 generated by the fluid present in the geological subsoil. The sensors 2 commonly comprise a heavy mass connected by at least one spring to a frame. When the earth starts moving, the frame moves. However, the mass, due to its inertia, moves very little relative to a geographical reference point. The sensors 2 are therefore able to measure the relative movement between the mass and the frame. This information is then transmitted to a controller (not shown in [Fig.l]) for processing.

[0026] It is illustrated schematically in [Fig.2], in the form of a flowchart, a temporal statistical analysis process of spatial anomalies intended for the detection and visualization of fluid movement zones. During an acquisition step EI, a seismic noise measurement signal is recorded over a given period of time, called the "observation period". Seismic noise is defined as all the waves present in the ground. The waves come from a natural phenomenon such as a meteorological event for example. They can also come from human activity: for example, a study of seismic noise near a railway track will necessarily be impacted by the passage of a train creating vibrations in the ground. Seismic noise can therefore be continuous seismic noise, that is to say seismic noise naturally present in the geological subsoil.Seismic noise can also be seismic noise of artificial origin, that is, seismic noise emanating from an artificial source developed by humans. For example, it could be a vehicle traveling over the terrain under study, thus creating artificial waves. Seismic noise data is obtained through sensors, where M is an integer greater than or equal to 3, and said sensors are implemented in pairs. Among the M sensors, there are pairs . 2 of sensors, including at least a first sensor and a second sensor forming a pair of sensors. When said number M is equal to 3, said sensors are aligned so that the various trajectories connecting each sensor to each other overlap. The sensors are connected to a controller. The data concerning the frequency and amplitude of the waves detected by said pair of sensors are electrically transmitted to the controller for processing. Preferably, the controller is a computer. During a reconstruction step E2, a series of waveforms are reconstructed by interferometry from said measurement signal of said pair of sensors at a regular time interval over said observation period. Seismic interferometry is a technique for investigating the subsoil by studying overlapping waves, thus creating an interference phenomenon. The interference phenomenon is characterized by the ability of two waves of the same frequency to combine. There are two types of interference. Constructive interference occurs when two waves of the same frequency combine in phase. In the case of constructive interference, a wave of greater amplitude is created by the combination of the two initial waves of lower amplitude. Destructive interference occurs when two waves of the same frequency combine out of phase. In this way, the amplitude of the two waves will be combined and give rise to a wave of lower amplitude, the amplitudes of each of the two initial waves canceling each other out. The waves initially collected during step E1 are therefore combined in order to be reconstructed depending on whether we are in the case of an in constructive interference or destructive interference. The reconstruction of these waves is carried out at a regular time interval during the previously defined observation period. For example, the regular time interval is between 10 minutes and 50 minutes, preferably 30 minutes. Thus, every 30 minutes, said waves are reconstructed. During an extraction step E3, a coherence time series associated with said pair of sensors is extracted from the series of waveforms established following the reconstruction step E2. Since a plurality of pairs of sensors is present, each pair of sensors generates a coherence time series. There is therefore a plurality of coherence time series. Coherence is the set of temporal or spatial correlation properties of waves. When the properties of the same wave are measured at two different times, temporal coherence is studied.When measuring the properties of the same wave at two different locations, spatial coherence is studied. To perform this extraction, a measurement of the evolution of a waveform is implemented. The measurement of the evolution of a waveform is based on the coherence of correlated waveforms of seismic noise. The measurement of the evolution of a waveform is carried out by autocorrelation over a given period. Thus, the series of waveforms is analyzed in order to follow its evolution over a defined period of time. From this data, coherence time series are extracted. Alternatively, a method for monitoring the speed variations of said waveforms is applied. In this way, a probability map of occurrence of a speed variation anomaly is obtained from the speed variation values ​​of said waveforms.During a spatial interpolation step E4, said coherence time series associated with all of said pairs of sensors are processed in order to be presented in the form of time series of a coherence map. Spatial interpolation is defined as a set of mathematical functions making it possible to illustrate values ​​in the form of points whose values ​​are known to estimate unknown values. Preferably, spatial interpolation is carried out by a tomographic inversion process. In the seismic field, tomography is defined as an imaging technique widely used in geology. It allows in particular the analysis of geological structures. The technique consists of recording the arrival time of waves, natural or artificially created, emanating from the ground over time via a seismological sensor, otherwise called a geophone or a seismic station.This data is transmitted electrically to a seismograph, which then generates a seismogram. All the seismograms generated make it possible to determine the speed of wave propagation. The properties of the subsoil, such as the presence of a fluid, are deduced from this information on the speed of wave propagation. This data is then processed by a process. optimization, also called inverse problem, we then speak of tomographic inversion process. The tomographic inversion process allows the development of a three-dimensional image of the subsoil thus revealing precisely the probable presence of a zone of fluid movements for example. However, any other spatial interpolation method can be used to implement the spatial interpolation step E4. In another example, the spatial interpolation is carried out by calculating average values ​​distributed over ray trajectories. The ray trajectory is here defined as being the path traveled in space between each pair of sensors, that is to say between at least said first sensor and said second sensor. At a first point in space on said trajectory, the average of all the coherence values ​​passing through said point is calculated.Between said first point and a second point in space, random values ​​are distributed between said first point and said second point. During a representation step E5, the results of the spatial interpolation of the coherence time series from the plurality of pairs of sensors are represented in the form of a coherence map. The coherence map has cells, each of the cells representing an elementary part of the geological subsoil studied by said sensors. Indeed, said coherence map representing the studied territory covered by sensors is gridded in such a way that said map is divided into X integer number of cells, each cell representing a part of said territory. Each cell representing the same surface area. The larger the number X, the more the resolution of said map is improved.In the context of the invention, said map may comprise between 10 and 20,000 cells so that the resolution allows the results of the analysis to be used. The map may comprise between 100 and 10,000 cells, or even between 1,000 and 5,000 cells. During a parameterization step E6, a statistical analysis duration is determined: this is the period of time during which the statistical analysis will take place. During a step of calculating the anomaly occurrence values ​​Oc;k E7, the number of times during which a cell presented an anomaly during the statistical analysis period is counted. This value corresponds to the anomaly occurrence value Oc;k. A step of calculating the probability density function for the appearance of an anomaly E8 is carried out for each cell. The calculation is carried out by the following formula: with . Pd being the probability of coherence anomaly for the i-cmc cell at the Cèinc period of N days; and Oc^ being the occurrence of coherence anomaly for the i-th cell at the / <-th period of N days. This calculation makes it possible to determine the probability of occurrence of an anomaly and therefore the probability of presence of a fluid in the subsoil. During a modeling step E9, the probability of occurrence map is established by listing each probability value of occurrence of an anomaly for each mesh. Thus, it is easy to visualize which areas of the subsoil probably contain a fluid. Advantageously, a computer program allows the implementation of the previously described process. In this way, the process is implemented automatically without the need for any human intervention.

Claims

1. Claims System for temporal statistical analysis of spatial anomalies intended for the detection and visualization of zones of fluid movement in a geological subsoil comprising: - an integer number M of sensors, said integer number M being greater than or equal to 3, said sensors being configured to measure at least one wave propagating in said geological subsoil over an observation period to obtain at least one measurement signal, said sensors forming pairs of sensors, including a first sensor and 2 a second sensor forming a pair of sensors; - a controller configured to: - reconstructing a series of waveforms by interferometry of said measurement signal from said pair of sensors at a regular time interval over said observation period; - extracting a coherence time series associated with said pair of sensors, all of said pairs of sensors forming a plurality of coherence time series; - spatially interpolating said plurality of coherence time series; - represent a plurality of results from the spatial interpolation of said plurality of coherence time series in the form of a coherence map having a plurality of cells, each cell representing an elementary part of the geological subsoil; - set a statistical analysis duration; - calculate a plurality of anomaly occurrence values ​​Oc;k corresponding to the number of times the value of a mesh is lower than a predefined threshold value; - calculate the probability density function of the appearance of an anomaly for said mesh using the following formula: PDF k = -^~~ 1Y. : with pdfk being the probability of coherence anomaly for the i-th mesh at the k-th analysis period of N days; and Oc^ being the occurrence of coherence anomaly for the i-th mesh at the k-th analysis period of N days; - establish a probability map of anomaly occurrence by re- listing each probability value of occurrence of an anomaly for the mesh; - obtaining a frequency at which the anomaly occurs and a location of the changes in said geological subsoil on the basis of the probability of coherence anomaly.

2. System according to claim 1 characterized in that said controller is configured to spatially interpolate said plurality of coherence time series by a tomographic inversion process.

3. System according to claim 1 characterized in that said controller is configured to spatially interpolate said plurality of coherence time series by calculating average values ​​distributed over beam trajectories.

4. System according to any one of claims 1 to 3 characterized in that said integer M is equal to 3, said sensors being aligned.

5. System according to any one of claims 1 to 4 characterized in that said sensors are geophones or hydrophones.

6. System according to any one of claims 1 to 5 characterized in that said wave is a wave emanating from a natural source.

7. System according to any one of claims 1 to 5 characterized in that said wave is a wave emanating from an artificial source.

8. System according to any one of claims 1 to 7, characterized in that said card comprises between 10 and 20,000 meshes, preferably between 100 and 10,000 meshes, more preferably between 1,000 and 5,000 meshes.

9. Method for temporal statistical analysis of spatial anomalies intended for the detection and visualization of zones of fluid movement in a geological subsoil, said method implementing an integer number M of sensors, said integer number M being greater than or equal to 3, said sensors being configured to measure at least one wave propagating in said geological subsoil over an observation period to obtain at least one measurement signal, said sensors forming pairs of sensors, including a first sensor and a second sensor forming a pair of sensors, characterized in that said method comprising the following steps: - a step of acquiring (El) at least one measurement signal during an observation period; - a step of reconstructing (E2) a series of waveforms by in- terferometry of the measurement signal from said pair of sensors at a regular time interval over an observation period; - a step of extracting (E3) a coherence time series associated with said pair of sensors by measuring the evolution of a waveform by autocorrelation over a given period, all of said pairs of sensors forming a plurality of coherence time series; - a step of spatial interpolation (E4) of said plurality of coherence time series; - a step of representing (E5) the results from the spatial interpolation of the plurality of coherence time series in the form of a coherence map having a plurality of cells, each cell representing an elementary part of the geological subsoil; - a step of parameterizing (E6) a statistical analysis duration; - a step of calculating the anomaly occurrence values ​​Oc;k(E7) corresponds to the number of times the value of a cell is less than a threshold value; - a step of calculating the probability density function of occurrence of an anomaly (E8) for each cell by the following formula: prf fk — ' with pJ being the probability of anomaly of J ' J1 coherence for the i-th cell at the £-th period of N days; and Oc}- being the occurrence of anomaly of coherence for the i-th cell at the ^-th period of N days; - a step of modeling (E9) a probability map of occurrence of anomaly by listing each value of probability of occurrence of an anomaly for each cell; - a step of obtaining (E10) a frequency at which the anomaly occurs and a location of the changes in said geological subsoil on the basis of the probability of anomaly of coherence.;

10. Method according to claim 9 characterized in that the extraction step (E3) implements a method for monitoring the speed variations of said waveforms.

11. Method according to any one of claims 9 to 10 characterized in that the spatial interpolation step (E4) is carried out by a tomographic inversion process.

12. Method according to any one of claims 9 to 10 characterized in that the spatial interpolation step (E4) is carried out by calculating average values ​​distributed over ray trajectories.

13. A computer program comprising program code instructions for performing the steps of the method of temporal statistical analysis of spatial anomalies for detecting and visualizing areas of fluid movement in the geological subsoil according to any one of claims 9 to 12, when said program operates on a controller.

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