Patent Description:
In oil and gas exploration and exploitation, marine seismic surveys are an important tool for making drilling-related decisions. Seismic data acquired during such a survey is processed to generate a profile, which is a three-dimensional approximation of the geophysical structure under the seafloor. This profile enables those trained in the field to evaluate the presence or absence of oil and/or gas reservoirs, which leads to better management of reservoir exploitation. Enhancing seismic data acquisition and processing is an ongoing process.

<FIG> is a vertical-plane view of a generic marine survey setup <NUM>. A vessel <NUM> tows a seismic source <NUM> (note that, for simplicity, the source's full configuration is not shown) and streamers (only one streamer <NUM> is visible in this view) in a towing direction T. When the seismic source is activated, seismic energy is emitted into the water and propagates into the rock formation under the seafloor <NUM>. The seismic energy is partially reflected and partially transmitted at interfaces where the acoustic impedance changes, such as at the seafloor <NUM> and at an interface <NUM> inside the rock formation. Reflected energy may be detected by sensors or receivers (where a sensor is understood to mean a physical device that records seismic data and a receiver is understood to mean a unit that includes a plurality of sensors for which the signals measured by the plurality of sensors are combined and represent the signal of the receiver) <NUM> (e.g., hydrophones, geophones and/or accelerometers) carried by the streamers. The seismic data represents the detected energy.

As illustrated in <FIG>, conventional marine seismic surveys typically mobilize a single vessel <NUM> towing typically two airgun source arrays <NUM> in front of a spread of ten or more streamers <NUM>. The data acquired in this way are narrow-azimuth and lack near offsets owing to the distance between the sources and the streamers, which can be in the range of <NUM> to <NUM> for the inner cables and up to <NUM> for the outer cables of the streamer spread.

By moving some of the sources so that they are directly over the deep-towed streamers, a much better and denser sampling of the reflected narrow cone of energy from the target is achieved. Such a configuration was introduced by <CIT> (herein "the '<NUM> publication"), assigned to the assignee of this application. This configuration is illustrated in <FIG> (it corresponds to the configuration shown in <FIG> of the patent application publication noted above) and is capable of recording near- and zero-offset data, which is important to achieve for high-resolution subsurface imaging and to improve multiple prediction and subtraction.

<FIG> illustrates a data acquisition system including two different source sets, a front set including sources <NUM> and a top set including sources <NUM>. Top sources <NUM> are towed directly over the streamer spread <NUM>. Source line <NUM> corresponding to the front source <NUM> coincides with sail line <NUM>, and is offset along a cross-line Y direction from source line <NUM>, which corresponds to top source <NUM>. <FIG> also indicates (using dashed lines) the sail lines <NUM> and <NUM> and corresponding source lines adjacent to sail line <NUM>, along which the illustrated system sails at various times.

A TopSeis configuration <NUM> is considered herein to include, as illustrated in <FIG>, a streamer vessel <NUM> that tows a streamer spread <NUM>, the streamer spread <NUM> including a given number of streamers <NUM>, and a source vessel <NUM> that tows one or more sources <NUM> directly over the streamer spread. These sources are called herein top sources because they are located directly above (along a vertical direction Z) the streamer spread. The streamer vessel <NUM> also tows plural sources <NUM>, which are called herein front sources because these sources are located in front (along the inline direction X) of the streamer spread <NUM>. Note that <FIG> shows the streamer spread <NUM> being connected at point <NUM> to the streamer vessel <NUM> by tow lines <NUM>, which are not part of the streamer spread. Thus, the front sources <NUM> are not directly above (along the vertical Z direction) the streamer spread <NUM>. In one embodiment, the streamer vessel <NUM> may be configured to tow both the front sources <NUM> and the top sources <NUM>. As discussed above, streamers <NUM> may be horizontal, slanted or curved.

In this document, a source is defined as including an array of source elements, where a source element is a single airgun or a single vibrator. It is customary in the marine acquisition field to have the source elements arranged as two or three subarrays, each subarray having a plurality of source elements. The two or three subarrays together form the source or source array. Thus, the source <NUM> or <NUM> in <FIG> includes plural source elements, that may be arranged in one, two, three or more subarrays.

While the TopSeis configuration provides an improved azimuth, this configuration is affected by the positioning errors of the receivers and/or sources at the middle part of the streamers. In this regard, <FIG> shows a traditional seismic survey system <NUM> that includes at a head 306A of each streamer <NUM>, a GPS system 320A and at a tail 306B of each streamer, a GPS system 320B. The GPS systems are placed on corresponding buoys that float at the water surface and each buoy is attached with a cable to the streamer. The GPS systems provide information to the vessel <NUM> about the location of the heads and tails of the streamers. This information has an accuracy of about <NUM> along the inline direction X and <NUM> along the cross-line direction Y. The offset axis <NUM> indicates a distance, in meters, from the vessel <NUM>, along the inline direction, to the various elements of the streamer spread.

For the middle portions of the streamers, no GPS systems are available. For these portions, an acoustic network of sensors <NUM> and various compasses <NUM> are attached to the streamers for estimating the receivers' positions. The acoustic network of sensors <NUM> emit and record sound waves for establishing the relative positions of the streamers and the compasses <NUM> determine a direction of the corresponding portions of the streamers. Based on this information, a global processor <NUM> located on the vessel <NUM> estimates the position of each receiver on the streamer. The accuracy of this estimation is about <NUM> along the inline direction and about <NUM> along the cross-line direction for the middle of the streamers.

These accuracies are well suited for conventional acquisition systems, i.e., for systems in which the sources are placed ahead of the streamers along the inline direction, because an error of <NUM> in the middle of the streamer corresponds to an offset of a few kilometers. This means that the position accuracy of the receivers is smaller than <NUM>/<NUM> of the offset.

However, for a TopSeis configuration, where the top source is located on top of the seismic receiver and the offset distance can be as small as <NUM>, the <NUM> accuracy represents about ½ of the offset, which will negatively affect the recorded data as the error positioning of the receivers is comparable to the offset distance.

A technique that uses the direct arrival (i.e., the wave that propagates directly from the source to a receiver) for assessing positions of the receivers has been tried.

Document <CIT> discloses the use of this technique for determining a position on the streamer relative to a reference position not disposed on the streamer, without needing to have GPS positions on the streamer, thus reducing the complexity of the towing arrangement. However, only a time shift measurement is generally used by this technique whereas, at a short range from the source, this approach is not correct. The direct arrival is not a simple event, as it is the product of many source elements recorded by a sensor array. To make the matter even more complex, a source ghost is affecting the phase of the direct arrival in a spatially variant way. Finally, for very near offsets, as in the case of the TopSeis configuration, the direct arrival is so energetic that its amplitude is clipped by the acquisition system. For all those reasons, the peak of the direct arrival wavelet does not correspond to the arrival time of the direct arrival. An inversion based on the arrival time of direct arrivals is therefore inherently unreliable and this is one main reason why the existing methods that use the direct arrival fail to accurately estimate the positions of the receivers and/or sources.

Document <CIT> discloses a method for correcting ocean bottom node position in presence of time distorsions within recorded seismic data, involving selecting unique proposed position minimizing statistical measure of differences as corrected ocean bottom node position.

Thus, there is a need to provide a more accurate positioning method of the receivers and/or sources for a TopSeis configuration.

A first object of the invention is a method for correcting observed positions of seismic sensors and/or seismic sources for a seismic data acquisition system according to claim <NUM>.

Another object of the invention is a computing device for correcting observed positions of seismic sensors and/or seismic sources for a seismic data acquisition system according to claim <NUM>.

Another object of the invention is a method for correcting observed positions of seismic sensors and/or seismic sources for a seismic data acquisition system according to claim <NUM>.

The following description of the embodiments refers to the accompanying drawings. The same reference numbers in different drawings identify the same or similar elements. The following detailed description does not limit the invention. Instead, the scope of the invention is defined by the appended claims. The following embodiments are discussed, for simplicity, with regard to a marine seismic data acquisition having a front set of sources and a top set of sources. However, the current inventive concepts may be used for other types of surveys, such as surveys having only top sources or for surveys that use drones, autonomous underwater vehicles, unmanned survey vessel, or a combination of them to tow one or more of the sources.

Reference throughout the specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with an embodiment is included in at least one embodiment of the subject matter disclosed. Thus, the appearance of the phrases "in one embodiment" or "in an embodiment" in various places throughout the specification is not necessarily referring to the same embodiment. Further, the particular features, structures or characteristics may be combined in any suitable manner in one or more embodiments.

According to various embodiments described in this section, a direct arrival model is generated for the direct arrival seismic waves and an inversion process is used to estimate the acquisition geometry (i.e., positions of sources and receivers) that best predicts the observed data. A direct arrival wave is a wave that propagates in a straight line from the source to the receiver, as illustrated in <FIG> shows a system <NUM> that includes a source element S and a receiver R. The source element S generates plural seismic waves in all directions (<FIG> shows only waves <NUM>, <NUM>, <NUM>, and <NUM>). The seismic wave <NUM> is the direct arrival, the wave <NUM> (the primary) is only reflected from the ocean bottom <NUM> or another subsurface interface, the wave <NUM> is a multiple, i.e., a wave that enters through a layer <NUM> and reflects on another interface <NUM>, and a wave <NUM> (the ghost) that is reflected from the water surface <NUM>.

The observed data is used herein to define data obtained from various devices as illustrated in <FIG> (compass, GPS system) while estimated/calculated data is used herein to refer to positions of the sources and/or receivers calculated according to methods that use a direct arrival model and an inversion process.

The method may be used onboard the towing vessel (either the streamer vessel or the source vessel or both) as an independent quality control (QC) check of the navigation system, but also in the first step of the processing of the seismic data to improve the geometry of the recorded seismic data. In addition of improving the 3D imaging of the surveyed surface, this method could also have a significant impact on 4D seismic acquisition campaigns.

The method takes advantage of the good azimuthal coverage to detect the source position with respect to the receivers as the direct arrival <NUM> is almost perfectly isotropic. The primaries <NUM> and the multiples <NUM> have a potential anisotropy due to dips, rock properties, fractures, and thus, they cannot be used to determine the positions of the receivers and/or sources.

Existing methods that use the direct arrivals extract only the arrival times of these waves and using the symmetry (and/or triangulation), they detect the source position. Note that the direct arrival <NUM> arrives first at the receiver, followed by the ghost <NUM>, primaries <NUM>, and the multiples <NUM>. Thus, the direct arrival wave can easily be identified in the recorded traces for short offset ranges, e.g., less than <NUM>, as this is the first wave that arrives at the receiver (or the first disturbance in a trace).

However, because of the specific configuration of the TopSeis acquisition system, and due to the short range between the top source and the receivers below, the direct arrival waves <NUM> cannot be assumed to be a single event as in the traditional methods. Picking the event time is biased under this scenario. <FIG> shows a traditional system in which a distance L between the receiver R and the source elements S1 to S6 (which form the source S) is in the order of kilometers, and thus, it is assumed that the direct arrival <NUM> is a single wave that propagates from S to R and the individual distances between the source elements Si and Sj is too small to matter. This regime is called far-field in the art. For the TopSeis configuration, which is illustrated schematically in <FIG>, the distance L between the source elements and the receiver is so small, such that the distances dij between the source elements Si and Sj cannot be ignored and the wave from each source element to the receiver should be considered. This regime is called near-field in the art. Thus, the present method considers the waves from each of the individual source elements when propagating to the individual seismic receivers.

The traditional methods also do not take into consideration the ghost <NUM> effect variation with the depth of the source, which induces an offset dependent effect. When the top source is so close to the receiver, the ghost may arrive at the receiver very close in time relative to the direct arrival. Thus, the ghost interference is included by the present method.

Further, the traditional methods do not take into account the phase effect of the acquisition system's filter. In this regard, <FIG> is a synthetic modeling of a direct arrival for a source S at <NUM> depth, whose signature is a simple Ricker wave zero phase centered at T = <NUM>. The responses plotted in <FIG> vary from the response <NUM>, which corresponds to the zero-offset trace (that is, <NUM> meters below the source) to the response <NUM>, which represents the direct arrival response for largest offset. Due to the interference with the ghost, even at the nearest offsets, the maximum of the signature is not centered at zero (as should be the case for a zero-phase wavelet). <FIG> shows that the maximum of the direct arrival is offset from -<NUM> milliseconds for the zero offset, up to -<NUM> milliseconds for the <NUM> meters offset. Thus, this shows that simply extracting the arrival times from the direct arrivals will be tainted with errors and bias.

Another effect that is ignored by the traditional methods is the response of the electronics of the acquisition chain. In this regard, the receivers measure pressure changes by producing an electrical signal in volts. This signal is clipped by the electronics at a certain value before being filtered and sampled. Signal clipping applies only to very large amplitudes and does not normally concern conventional seismic data. However, in the case of the direct arrival at very low offset, as in the TopSeis configuration, the recorded amplitude is typically clipped by more than <NUM>%. Thus, this clipping effect should be implemented into the model to make it possible to better take into account the position of the maximum of the signal. In this respect, it is known that the signal propagating to the seismic sensor has a maximum at a position t = <NUM>. After the signal is clipped by the electronics, for example at <NUM>, the filtered version of the clipped signal exhibits two maxima instead of one and these maxima are not placed at t = <NUM>. This effect is implemented into the model used in this method.

Still another factor that is not taken into consideration by the traditional estimation methods is the full signal shape of the direct arrival and its variations due to position changes. In this regard, <FIG> illustrate the effect that all the above factors have on the direct arrival model. <FIG> shows one direct arrival wave <NUM> (forward linear moveout (LMO) has been applied to flatten the wave) and one ghost wave <NUM> having constant amplitude. Both the source and the receiver are considered to be punctual elements. <FIG> shows the same when the source is still considered to be a single point and the receiver includes an array of receivers (e.g., <NUM> receives in this case), i.e., a composite receiver. The interference generated by the signals is responsible for the amplitude variation noted in this figure.

<FIG> show the waves recorded by the receiver when the source is replaced with a source array (e.g., the source array includes <NUM> source elements) and the receiver is a point receiver. Strong interference is still present, which is responsible for the amplitude variation. <FIG> combines the source array with the sensor array (i.e., composite receiver), which is responsible for <NUM> individual contributions (<NUM> for the source times <NUM> for the sensors), with very strong amplitude variation.

<FIG> illustrates a configuration that produces plural seismic waves which are recorded with plural seismic sensors. In the following, the term "receiver" is used interchangeably with the term "compounded receiver. " The system in <FIG> includes plural source elements Si, which form source array S, and plural individual receivers Rj, that form the composite receiver R, where i and j can vary from one to any integer. Note that if j is <NUM> or larger, the signals from each individual receiver Rj is added to the other individual receivers that form composite receiver R, and thus, the combined recorded seismic data for the j individual receivers is sent to the vessel as a single trace that corresponds to the composite receiver R. The star in the streamer <NUM> indicates the physical position attributed to the composite receiver R that is used for processing the traces. In the embodiment shown in <FIG>, the individual receivers Rj that form the composite receiver R are selected over a distance of about <NUM> along the streamer <NUM>. Other distances may be used or each individual receiver may be considered in its own as being the receiver R.

In the method of the present invention, each source element Rj and each individual receiver Ri are considered when calculating the direct arrival and the contribution of each source element is considered as following a different ray path to a corresponding individual receiver. The signature of each source element is also considered in these calculations. The signatures (i.e., the pressure wave generated by the source over time) of eight source elements is shown in <FIG> and it can be seen that each signature is different from the others. In this regard, note that the traditional methods that use the direct arrival waves for determining the position of the source consider that all the source elements have the same signature.

When the features identified above (i.e., geometry of the source array, individual source element signature, ghost interference, phase effect, clipping, and full signal shape) are taken into consideration by the model used by the present method to describe the direct arrival, a much accurate relative position estimate between the receivers and the sources is found. In this regard, <FIG> shows the recorded data for the direct arrivals for a given source-receiver configuration for a marine seismic survey while <FIG> shows the direct arrival model for the same configuration, where the above noted factors are taken into consideration. The distortion between the model data and the recorded data is interpreted by the method as potential relative position errors between the sources and the receivers and a correction of these errors by an inversion method would produce the estimated positions of the receivers and/or sources.

The method is based on a precise modeling of the direct arrival, which includes (<NUM>) source modeling, i.e., taking into account the contribution from each individual source element (e.g., gun) with its own characteristic (position, relative position to the other source elements, volume of air of each source element if the source element is a gun, signature of each source element), (<NUM>) the propagation of a theoretical shot through the water, which includes surface reflection (ghost), attenuation effects, ghost interference, and (<NUM>) modeling of the acquisition system, which includes receiver array geometry (see <FIG>), clipping of the voltage recorded by each receiver, filtering, sampling, and calibration.

After computing the direct arrival time and amplitude, for example, from gun volume and spherical divergence, and the ghost arrival time and amplitude, for example, from the gun volume, spherical divergence and surface reflection, the signature of the individual source elements are applied to correct the phase and amplitude. Then, all these contributions are summed together and a Green Function may be applied for taking care of the anti aliasing filter, clipping, sampling and calibration. Note that there are known methods in the art of seismic industries for performing each of these steps, but there is no known method that combines all these steps as discussed in this document.

This modeling can be performed very efficiently, allowing the estimation of different positioning errors and detecting the source-receiver geometry that best explains the observed data. An inversion process based on minimizing the mismatch between the model and the observed data results in an optimal solution.

The process may be performed for every shot-receiver pair below a certain offset range. The restriction of the offset range is imposed to allow for reliable modelling of the direct arrival and comparison with the clean direct arrival in the observed data. This allows the extraction of a global position error with the robustness of statistical methods. The process may be performed on a shot-by-shot basis, and is stable enough to avoid the need for smoothing between shots. This allows correcting for potential instability of the navigation results. In a variant of the process, it is also possible to extract individual cable corrections and even vertical positioning errors for the receivers. The method can be used to determine positioning errors for both sources and receivers.

As previously discussed, the conventional streamer positioning systems suffer from position errors ranking from around a meter at the head or tail of streamer (which are close to GPS measurements) to up to the order of <NUM> in the middle of the streamer. For near-offset acquisition techniques, such as TopSeis, these errors will have a significant impact on data quality and should be reduced. The method discussed next does exactly this. Further, the method has the potential to extract vertical positioning errors, important for a good de-ghosting (because guns are subject to up and down movement due to sea wave, whereas streamers are not affected). The proposed new method is based on an analysis of observed data, and therefore, does not require any expensive hardware to be added to the acquisition system to solve the positioning problem.

A first implementation of this method is now discussed with regard to <FIG>. In step <NUM>, each individual contribution of the source-receiver marine system is input. For example, in sub-step <NUM>, the information about the source is provided. As discussed above, this information may include the geometry of the source array, the number of source elements, the signature of each source element, the volume of each source element. In sub-step <NUM>, the information about the composite receivers is provided. This information may include the number of individual sensors, the distance between the individual sensors, the position of each individual sensor and/or receiver along the streamer, calibration information, etc..

For a typical marine seismic survey system, the source array includes between <NUM> and <NUM> individual guns whereas every composite receiver is the stack of typically <NUM> individual seismic sensors. The source array may include, instead of or in addition to the guns, vibrational elements. The seismic sensors may include hydrophones, geophones, accelerometers, distributed acoustic sensing using an optical fiber, electromagnetic sensors, gravity sensitive sensors, etc. To correctly model the direct arrival from each gun to each individual seismic receiver, it is necessary to characterize all individual guns, by at least their position in the source array and their signatures, and all individual seismic sensors, by at least their position along the streamer and potentially their calibration.

The information obtained in step <NUM> may be received in real time, at the global controller of the vessel that tows the streamers and/or sources, directly from the source array and from the various seismic receivers, or via a communication link (e.g., satellite, radio-frequency, etc.) between the global controller and a land facility of the operator of the seismic survey, and/or from a storage medium that is on board of the vessel. Note that this information is typically available before the seismic survey is started. In one embodiment, it is possible that the global controller, which is in direct communication with the source array and the seismic receivers, pings each element for obtaining the information noted above.

Based on the information obtained in step <NUM>, the global controller on the vessel, which may be part of the navigation system, is programmed to calculate/estimate in step <NUM> the complete geometry of all gun-sensors contributions. The global controller calculates the energy propagating through the water from each gun of the source array to each individual sensor Ri of the composite receiver R. This step calculates not only the direct energy that propagates from the gun to the individual seismic sensor, but also the ghost energy (the energy that is reflected from the water surface before arriving at the individual receiver). These calculations generate not only the amplitude, but also the phase of the waves arriving at the individual sensors. This modeling process takes into account the spherical divergence, surface reflection (ghost) and gun signature for each gun.

Step <NUM> includes a sub-step <NUM> of receiving, from the other components of the navigation system, navigation information related to the source array and the individual sensors. The navigation information includes the global position of the sources and sensors, obtained from GPS information, compass information, etc., as discussed above with regard to <FIG>. The navigation information is available at each streamer vessel of a marine seismic survey system. This information may be obtained in real-time as the seismic survey progresses. The calculations performed in step <NUM> may be performed during each sail line of a seismic survey. Alternatively, the calculations in step <NUM> may be performed at a given time, for example, every few seconds or minutes or hours during the seismic survey. One skilled in the art would understand that these calculations can be performed as often as necessary is deemed by the operator of the survey. In one application, the calculations may be performed a posteriori, i.e., whenever the operator of the survey decides or just before processing the seismic data in a land facility.

Once all energy contributions of the signals recorded by the individual sensors are known in step <NUM>, the method advances to step <NUM>, where the calculated energy for every individual sensor is summed to obtain the energy that would be recorded by each composite seismic receiver R.

Prior to comparing the estimated energy calculated in step <NUM>, for the composite seismic receivers, with the corresponding recorded energy, the method calculates/models in step <NUM> the acquisition system effect on the recorded direct arrival data. As previously discussed, this step takes into consideration various factors, which are received in step <NUM>. The factors that are received in step <NUM> may include, for example, information related to the anti-alias filtering and re-sampling of the data. In the particular case of the TopSeis configuration, this step also takes into consideration the clipping introduced by the hardware and potentially, a calibration factor. These factors are received in step <NUM> from the acquisition system.

In step <NUM>, the method compares the estimated positions for the source elements and/or individual sensors with the observed positions of these elements (as noted in <FIG>). The estimated positions were calculated in step <NUM> while the observed positions are received in step <NUM>. Still in step <NUM>, the method selects an optimum solution based on quantitative criterion for the mismatch with the observed data.

To compare how correct the estimated positions calculated in step <NUM> are relative to the observed positions obtained in step <NUM>, it is necessary to measure the mismatch between the current direct arrival model and the observed data. To do so, it is possible to use matching attributes like time shift, or nrmse, which is the normalized root mean square envelop, which is given by <MAT>, rms ratio, which is given by <MAT>, and each of them is being stored to be used as an objective function for the final selection step.

The method then advances to step <NUM>, where at least one position of a source element of the source and/or at least one position of an individual seismic sensor of the composite receiver is perturbated. In one application, all the elements of the source array or all the sensors of the composite receiver are perturbed at once, along one given direction, with a given step length. A perturbation should be understood in this embodiment as a change in at least one coordinate (preferred along the inline or cross-line direction, but also possible along the depth direction) by a given amount. This amount varies depending with the scope for which the perturbation is performed. For example, for an initial test or QC phase, large range perturbations around <NUM> to <NUM> meters along the sail line direction and <NUM> meters perpendicular to sail line direction may be used. Then, during the iterative process, random changes may be selected in this range. In some cases, it is possible to use smaller ranges for the perturbation, for example, <NUM> or <NUM> meters if it is desired to perform a residual re-positioning after an initial re-positioning.

By adjusting the source and/or sensor positions to test most or all of the possible errors, the method returns to step <NUM> each time a perturbation is generated and repeats all the steps back to step <NUM>. After performing the desired number of perturbations, which can be defined by the operator of the seismic survey, the method advances to step <NUM> for selecting the optimum solution. This step is performed by finding the source/sensor positions that produce the best objective function, i.e., the objective function has the minimum or the maximum value for the best solution. In one application, an L2 norm may be used for determining the difference between the estimated position data and the observed data. An example of an objective function F is as follows: <MAT> where D(t) is the direct arrival observed/recorded data, and Δ(t) is the direct arrival model. The sensitivity factor is a scaling property depending only on the sensor trace's location with respect to the source location, so it is a weighting on the individual objective function when extracting the global solution for the entire composite receiver. The objective function f performs a sum for all samples t in a window including the direct arrival and its ghost. This allows the method to extract the optimum position correction for each receiver p that minimizes the function f.

As a result of this step, the method ends up with a positioning solution per each receiver involved (typically <NUM> to <NUM>,<NUM> for the TopSeis configuration). Extracting the final solution is performed in step <NUM> by using statistical methods. For example, to extract the global solution for a receiver, the method performs a statistical extraction of the global position correction Pglobal = Σtrα(tr) · p(tr) by applying a weighed sum to take into account the sensitivity α of each receiver, depending on its location with respect to the source.

All solutions are weighted, see weight α in equation (<NUM>) above so that the method can take into account resolution and sensitivity differences. Typically, the weights are different depending on the direction of the residual that the method is trying to extract, the relative position of receivers, the strength and shape of the direct arrival seen by a reflector, and finally by the type of correction, i.e., global, per cable, per source, per gun, or per receiver.

About the sensitivity, note that for the cross-line direction, the best measurements are achieved at minimum offset. The outer streamers are more sensitive than the inner streamers and the streamer just below the top source is almost insensitive. The positive offsets are symmetric relative to the negative offsets. For the inline direction, the best measurements are achieved at larger offset, the inner streamers are more sensitive than the outer streamers and the streamer below the top source is almost insensitive. The positive offsets are antisymmetric relative to the negative offsets. For the depth direction, most of the streamers appear to be insensitive to errors. The streamer just below the source is sensitive only at ultra-small offsets. The sensitivity is symmetric for positive and negative offsets.

The method discussed above may be implemented for each shoot, only for selected shots, or only for given times. The results obtained in step <NUM>, i.e., the estimated positions of the source elements and/or the individual seismic sensors are used in conjunction with the recorded seismic data for a better positioning of each recorded trace. In this regard, a recorded trace (which includes signals from the hydrophones, geophones, accelerometers, etc.) needs to be positioned, prior to being processed with known seismic methods for generating an image of the surveyed subsurface, where the actual seismic receiver is located. However, as discussed earlier, the observed positions of the seismic sensors lack accuracy, especially for the middle of the streamer, where a top source is placed. Thus, the results of step <NUM> are used to correct the observed positions, for associating the recorded traces with the corrected positions.

A second implementation of the direct arrival method is now discussed with regard to <FIG>. The first couple of steps are similar to the corresponding steps of Claim <NUM>. For this reasons, the description of the steps <NUM> to <NUM>, <NUM>, and <NUM> is not repeated herein.

Instead of step <NUM>, the method of Claim <NUM> implements a step <NUM> in which an autocorrelation is performed between (i) the estimated data obtained with the direct arrival model in step <NUM>, and (ii) the observed data received in step <NUM>. Then, this step extracts a matching quantitative attribute per receiver. This attribute may be a time shift error, an amplitude ratio, nrmse, etc. Then, the method uses this attribute, for example, the time shift error for each receiver, to apply in step <NUM> an inversion process to directly find in step <NUM> the desired positioning residuals. In one embodiment, any known inversion engine can be used to extract the positioning residuals. In one embodiment, the inversion uses an objective function that is a least square fit of a shifted hyperbola. Other implementations may be used.

The positioning residual is nothing else than the corrected navigation positions of the source array and/or the composite receivers. That is, a revised position for all sources and/or receivers of the acquisition system is produced in step <NUM> and these corrected positions best honor the observed data.

The method discussed with regard to <FIG> may be implemented for each shot, only for selected shots, or only for given times. The results obtained in step <NUM>, i.e., the estimated positions of the source elements and the individual seismic receivers are used in conjunction with the recorded seismic data for a better positioning of each recorded trace.

<FIG> illustrate how the positions of the sensors and sources are corrected based on the results calculated in step <NUM>. <FIG> shows the trajectories (or successive positions) <NUM> of a sensor for each streamer that is towed by the streamer vessel. <FIG> also shows the trajectory <NUM> of the source. It can be seen in this figure the non-physical position errors, which would imply that in a few seconds, the <NUM> long streamer has jumped laterally several meters. After the application of the residual positioning corrections obtained with one of the methods illustrated in <FIG> and <FIG>, it can be observed in <FIG> smoother and more realistic trajectories for both the sensors and the source. In these figures, the horizontal direction (sailed line) is compressed by a factor of <NUM> relative to the transverse dimension for reasons of readability.

Applying the analysis described above, it is possible to extract, for each sensor of a streamer, a calibration curve of the applied errors. The fact that this curve is identical in a first order for the <NUM> cables of the acquisition device is an additional argument about the robustness for the applied solution.

The above-discussed procedures and methods may be implemented in a computing device as illustrated in <FIG>. Hardware, firmware, software or a combination thereof may be used to perform the various steps and operations described herein.

Computing device <NUM> (which may represent global controller <NUM>) suitable for performing the activities described in the embodiments may include a server <NUM>. Such a server <NUM> may include a central processor (CPU) <NUM> coupled to a random access memory (RAM) <NUM> and to a read-only memory (ROM) <NUM>. ROM <NUM> may also be other types of storage media to store programs, such as programmable ROM (PROM), erasable PROM (EPROM), etc. Processor <NUM> may communicate with other internal and external components through input/output (I/O) circuitry <NUM> and bussing <NUM> to provide control signals and the like. Processor <NUM> carries out a variety of functions as are known in the art, as dictated by software and/or firmware instructions.

Server <NUM> may also include one or more data storage devices, including disk drives <NUM>, CD-ROM drives <NUM> and other hardware capable of reading and/or storing information, such as DVD, etc. In one embodiment, software for carrying out the above-discussed steps may be stored and distributed on a CD-ROM or DVD <NUM>, a removable media <NUM> or other form of media capable of portably storing information. These storage media may be inserted into, and read by, devices such as CD-ROM drive <NUM>, disk drive <NUM>, etc. Server <NUM> may be coupled to a display <NUM>, which may be any type of known display or presentation screen, such as LCD, plasma display, cathode ray tube (CRT), etc. A user input interface <NUM> is provided, including one or more user interface mechanisms such as a mouse, keyboard, microphone, touchpad, touch screen, voice-recognition system, etc..

Server <NUM> may be coupled to other devices, such as sources, detectors, etc. The server may be part of a larger network configuration as in a global area network (GAN) such as the Internet <NUM>, which allows ultimate connection to various landline and/or mobile computing devices.

The disclosed embodiments provide a method that estimates with higher accuracy than the existing methods the positions of the receivers and/or sources for a seismic acquisition system while acquiring seismic data. It should be understood that this description is not intended to limit the invention, the scope thereof being solely defined by the appended claims. Further, in the detailed description of the exemplary embodiments, numerous specific details are set forth in order to provide a comprehensive understanding of the claimed invention. However, one skilled in the art would understand that various embodiments may be practiced without such specific details.

The methods or flowcharts provided in the present application may be implemented in a computer program, software or firmware tangibly embodied in a computer-readable storage medium for execution by a general-purpose computer or a processor.

Claim 1:
A method for correcting observed positions of seismic sensors and/or seismic sources for a seismic data acquisition system, the method comprising the following steps implemented by a computer:
estimating (<NUM>) a source element energy generated by each source element (Si) of a plurality of source elements which belong to a source array (S);
calculating (<NUM>) a respective energy propagating from each source element (Si) to each individual seismic sensor (Rj) of a plurality of individual seismic sensor which belong to a composite receiver (R), taking into account a position of each source element (Si) within the source array (S) based on an observed position of the source array (S) and a position of each individual seismic sensor (Rj) within the composite receiver based on an observed position of the composite receiver (R);
summing (<NUM>), for each individual seismic sensor (Rj), all the estimated energies from the all the source elements to obtain an estimation of the energy that would be recorded by said composite receiver (R);
estimating (<NUM>) a model of direct arrival waves that propagate from the source elements to the individual seismic sensors, based on characteristics of the acquisition system; the clipping effect being implemented into the model or the full signal shape of the direct arrival and its variations due to position changes is taken into consideration by the model;
calculating (<NUM>) positions of the individual seismic sensors and/or of the source elements based on the model of direct arrival waves;
comparing (<NUM>) how correct the calculated positions of the individual seismic sensors and/or of the source elements are relative to observed positions of the individual seismic sensors and/or of the source elements based on an objective function measuring a mismatch between the model of direct arrival waves and observed data;
determining (<NUM>) a best calculated position for each of the individual seismic sensors and/or of the source elements based on said objective function; and
correcting (<NUM>) the observed positions of the individual seismic sensors and/or of the source elements with corresponding best calculated positions.