Patent Description:
A seismic survey includes generating an image or map of a subsurface region of the Earth by sending sound energy down into the ground and recording the reflected sound energy that returns from the geological layers within the subsurface region.

During a seismic survey, an energy source is placed at various locations on or above the surface region of the Earth, which may include hydrocarbon deposits. Each time the source is activated, the source generates seismic (e.g., sound wave) energy that travels downward through the Earth, is reflected, and, upon its return, is recorded using one or more seismic sensors disposed on or above the subsurface region of the Earth. The seismic data is recorded by the seismic sensors, where the seismic sensors each include a clock that is configured to provide clock data. The seismic data may then be used to create an image or profile of the corresponding subsurface region.

The clock data that is provided by the clock of the seismic sensors should be accurate, so that the seismic data (which is synchronized to the clock data) may be interpreted accurately. However, the seismic sensors may be exposed to an ambient temperature that varies over time, which may cause a drift in the clock data.

According to the invention, the disclosure enables determining a drift in the clock data (that is provided by the clock of a seismic sensor), where the seismic sensor is exposed to an ambient temperature that varies over time.

In some embodiments, the determined drift in the clock data may be corrected, such that the clock data of the seismic sensors is accurate, and such that the seismic data may be interpreted accurately even when the seismic sensors are exposed to an ambient temperature that varies over time.

Aspects and embodiments of the invention are set out in the appended claims. These and other aspects and embodiments of the invention are also described herein.

Embodiments of the present disclosure will now be described, by way of example, with reference to the accompanying drawings, in which:.

In the figures, similar elements bear identical numerical references.

<FIG> schematically illustrates a plurality of example seismic sensors <NUM> disposed in or above a survey area <NUM> of the Earth during a seismic survey. The sensors <NUM> are configured to record the reflected seismic energy that returns from the geological layers within the survey area <NUM>.

A Global Navigation Satellite System (GNSS) <NUM> provides timestamp data to the sensors <NUM> during the seismic survey to help create an image or profile of the corresponding survey area <NUM>.

Before the seismic survey starts, the sensors <NUM> may be initialized, e.g. calibrated. After the seismic survey is finished, the seismic data recorded by the sensors <NUM> may be collected and used to create an image or profile of the corresponding subsurface region. In some embodiments, sensors <NUM> can operate in conjunction with control system <NUM> to perform initialization of the sensors <NUM> and/or to perform collecting of the seismic data that is recorded by the sensors <NUM>.

<FIG> schematically illustrates an example control system <NUM> and a plurality of example seismic sensors <NUM>.

The control system <NUM> comprises a docking station <NUM>, where the plurality of sensors <NUM> may be removably docked, as illustrated by the arrows of <FIG>.

The control system <NUM> can also include a processor <NUM>, a memory <NUM> and/or a communication module <NUM> that are configured to communicate with a communication module of a sensor <NUM>, e.g. when the sensor <NUM> is docked in the docking station <NUM> of the control system <NUM>. The processor <NUM>, the memory <NUM> and the communication module <NUM> can enable the initialization of the sensors <NUM> (e.g. during calibration). The processor <NUM>, the memory <NUM> and/or the communication module <NUM> can also enable the collection/retrieval of the seismic data that has been recorded by the sensors <NUM>, e.g. when the sensors are docked in the docking station <NUM> of the control system <NUM>. In other words, with one example embodiment, prior to being deployed in survey area <NUM>, sensors <NUM> can be initialized by being docked in docking station <NUM>. Next, sensors <NUM> can record seismic data while sensors <NUM> are deployed in the survey area <NUM>. Finally, sensors <NUM> can be gathered from the survey area <NUM> and redocked within docking station <NUM> in order to gather the data that was recorded by sensors <NUM>, while sensors <NUM> were deployed in the survey area <NUM>. With one or more embodiments, clock drift that results from the changing ambient temperature can be corrected at the time that the sensors <NUM> are redocked within docking station <NUM>.

As illustrated in <FIG>, each sensor <NUM> may have at least two configurations. In a first configuration, the sensor <NUM> may be docked in a docking station <NUM> of the control system <NUM>, e.g. for performing initialization and/or for transporting to a survey area. In a second configuration, the sensor <NUM> may be deployed within a survey area for measuring seismic data.

As illustrated in <FIG>, the sensor <NUM> comprises a communication module <NUM> that is configured to communicate with the communication module <NUM> of the control system <NUM>.

The sensor <NUM> also comprises a processor <NUM> and a memory <NUM>. In some examples, the sensor <NUM> may comprise a thermometer <NUM>.

The sensor <NUM> can also include a clock <NUM> that is configured to provide clock data.

The sensor <NUM> can include an antenna <NUM> that is configured to receive timestamp data that is provided by the GNNS <NUM>. In some examples, the timestamp data that is provided by the GNNS <NUM> may be used by the sensor <NUM> to correct temporal irregularities in the periods of the clock data that are provided by the clock <NUM> (of sensor <NUM>). Temporal irregularities can be considered to be divergences between the clock data of clock <NUM> and the received timestamp data. As described above, with one or more embodiments, the temporal irregularities can be corrected at the time that the sensors <NUM> are redocked within docking station <NUM>.

The present invention considers the timestamp data (received from GNNS <NUM>) as being a reliable/authoritative source of time data. As such, in order to correct the above-described temporal irregularities, the clock data (that is provided by clock <NUM>) is compared against the received timestamp (that is provided by the GNNS <NUM>). In the event that deviations/discrepancies exist between the clock data and the timestamp data, such deviations/discrepancies are considered to be the temporal irregularities. The above-described clock drift is evidenced by such temporal irregularities. After comparing the received timestamp (that is provided by the GNNS <NUM>) against the clock data (that is provided by the clock <NUM>), sensor <NUM> can correct the temporal irregularities, as described in more detail below.

<FIG> schematically illustrates an example amount of clock drift that occurs to a clock over time. As illustrated in <FIG>, the clock data that is provided by a clock during a seismic survey may be affected by a drift which creates temporal irregularities over time. In <FIG>, the curve with the circles corresponds to measurements of drift (as determined by comparing the received clock data against the received timestamp data) over a time period of around <NUM> days. As reflected by the curve with circles (of <FIG>), the drift can dynamically change across the time period of <NUM> days. For example, between days <NUM>-<NUM>, the drift amount tends to get further into the negative, until reaching an amount of about -<NUM>. After the <NUM>th day, the drift amount tends to increase into the positive, until reaching an amount of about <NUM> on the <NUM>th day. As shown above, the trend of the drift amount is dynamically changing, and the dynamically changing trend cannot be accurately represented by a simplistic two-point trendline. For example,
suppose that a two-point trendline is drawn between a first measurement at the beginning (of day <NUM>) and a second measurement at the end of the <NUM>th day. This two-point trendline would merely reflect an upward, increasing, drift, which does not accurately reflect the actual, dynamically changing drift amounts. One or more embodiments can accurately account for dynamically changing drift amounts, and one or more embodiments can correct for such dynamically changing drift amounts.

<FIG> schematically illustrates an example plot of a drift rate that is exhibited by clock data (as expressed as a function of the ambient temperature). As illustrated in <FIG>, the rate of the drift in the clock data during a seismic survey can be a function of the ambient temperature that surrounds the seismic sensor during collection of the seismic data. <FIG> schematically illustrates an example plot of a drift rate in the clock data as a function of the ambient temperature. In the example of <FIG>, the drift rate varies linearly with the temperature within a temperature range of about 20C (e.g. between -40C and -20C in <FIG>), but the variation of the drift rate is non-linear above a certain temperature (e.g. for temperatures above -20C in <FIG>).

In some examples, the temperature range of the ambient temperature surrounding the sensor during seismic surveys can be so large such that the sensor may be unable to adjust its clock with sufficient regularity by using the timestamp data that is provided by the GNSS.

Accordingly, one or more embodiments of the present invention determines a drift in the clock data, where the clock data is provided by the clock of a seismic sensor, and where the seismic sensor is exposed to an ambient temperature that varies over time.

In some embodiments, the determined drift in the clock data may be adjusted/corrected, such that the clock data of the seismic sensors is made accurate, and such that the seismic data may be interpreted accurately even when the seismic sensors are exposed to an ambient temperature that varies over time.

One or more embodiments of the present invention determines an amount of drift by using received temperature data, and one or more embodiments can use the received temperature data to correct/adjust the drift.

<FIG> shows an example plot of temperature data obtained e.g. by a thermometer of a seismic sensor, which reflects the ambient temperature, as a function of time. <FIG> shows an example of obtained temperature data T(t) which reflects the ambient temperature surrounding the sensor, during a seismic survey, as a function of time. The obtained temperature data T(t) may be provided e.g. by a thermometer of the sensor. As illustrated in <FIG>, in some examples, the temperature data can be represented by a representative curve, where the representative curve is determined by performing a smoothing function upon the temperature data.

<FIG> shows an example of an integral of an ambient temperature T(t) between a time to that is associated with a start of a recording period (e.g. at a beginning of a seismic survey) and a current time t (e.g. during the seismic survey).

<FIG> shows a flow chart illustrating a method <NUM>, according to the invention, by using the received clock data and the received temperature data as explained above. As described in more detail below, the method <NUM> outputs corrective data, which may be used to correct the drift in the clock data.

The method <NUM> illustrated in <FIG> includes, at S1 , obtaining temperature data that reflects the ambient temperature (around a sensor) as a function of time. As described above, the temperature data can be provided by a thermometer, for example. The method <NUM> also includes, at S2, obtaining clock data that is provided by a clock of the sensor.

In some examples, the temperature data that is obtained at S1 may be provided by the thermometer of the sensor. Alternatively or additionally, the temperature data may be provided by other means, such as by other thermometers, e.g. thermometers provided in the control system. As described above, the control system can operate in conjunction with the sensors when initializing the sensors or when retrieving/collecting the seismic data from the sensors.

An example of obtained temperature data is illustrated in <FIG> and has been already discussed. The obtained temperature data can be used to correct for drift, as described in more detail below.

In addition to the clock data obtained (at S2), timestamp data (at S3) is provided by the GNSS. As described above, by comparing the timestamp data against the clock data that is provided by the clock of the sensor, drift data (at S4) that reflects a temporal drift in the clock data, is determined by determining a difference between the clock data (that is provided by the clock) and the timestamp data (that is provided by the GNSS). Differences between the clock data and the timestamp data indicate that drift has occurred.

The method <NUM> may further comprise determining and outputting, at S5, corrective data. One or more embodiments can use the determined corrective data to correct the clock data, as explained below. As described below, the corrective data can be determined based on the received temperature data.

In some examples, determining, at S5, the corrective data comprises parameterizing drift D(t), where: <MAT>.

In the equation (E) above, θ is an integral of the ambient temperature T(t) between time t0, associated with a start of a recording period for the sensor, and a current time t, during the recording period of the sensor, such that: <MAT>.

An example of θ is illustrated in <FIG> and has already been discussed.

In some examples, the recording period may correspond to e.g. a few hours or a few days. In some examples, the recording period may correspond to a duration of a seismic survey during which the seismic sensor is deployed for measuring seismic data.

In the drift D(t) of equation (E) above, the parameters (a, b) are parameters which are determined in order to minimize a difference between D(t) and a measured temporal drift (as determined by comparing the clock data against the timestamp data). As such, with one or more embodiments, determining the corrective data at S5 can include determining parameters (a, b). D(t0) may be such that: <MAT>.

It should thus be understood that, at S5, one or more embodiments determine the corrective data, where the difference between the determined drift data and the measured temporal drift is minimized.

In other words, by determining the parameters (a, b) to minimize the above-described difference, one or more embodiments can determine a best-fit curve to describe the drift D(t).

The method <NUM> of <FIG> further comprises outputting, at S5, corrective data based on the determined drift data. The drift in the clock data may be corrected, based on the outputted corrective data. In some examples, determining the corrective data comprises determining parameters (a, b) for equation (E).

With one or more embodiments, once the corrective data is determined, the corrective data can be used to correct occurrences of drift in the clock data. Such correction can occur when data that is recorded by the sensors is being gathered by the docking station, for example. In other words, with one or more embodiments, the corrective data corrects occurrences of drift after the data has all been received by the sensor.

In some examples, outputting the corrective data (at S5) can include performing at least one of:.

As illustrated in <FIG> and <FIG> (discussed above), the ambient temperature may vary within one or more temperature ranges during one or more recording periods. In the example of <FIG>, the ambient temperature varies between a first range (e.g. a range of temperatures below -40C), a second range (e.g. a range between -40C and -20C), and a third range (e.g. a range above -20C), for example. The method may thus include determining the corrective data that corresponds to each temperature range of the ambient temperature.

In some examples, determining the corrective data comprises determining parameters (a, b) for equation (E), as described above.

Alternatively or additionally, in some examples, the corrective data may comprise temperature data. As described above, the correction data can correspond to different temperature ranges of the ambient temperature. The temperature data associated with the corrective data may comprise data associated with at least one of the following:.

In some examples, outputting the corrective data, at S5, may comprise storing the corrective data corresponding to each temperature range in a library that is associated with a plurality of temperature ranges. The library may be located in the memory of the sensor and/or in the memory of the control system.

As illustrated in <FIG>, one or more embodiments, at S5, can output the corrective data by performing at least one of the following: Method S5, at S51, includes determining one or more corrective data for one or more calibration periods and/or one or more seismic survey periods. Method S5, at S52, can also include updating, at S52, the determined one or more corrective data (which was previously determined). Method S5, at S53, includes outputting the updated corrective data.

As illustrated in <FIG>, in some examples, updating at S52 the determined one or more corrective data (which was previously determined) may include at least one of the following. As described above, the corrective data can include, at least, parameters (a, b), which allow calculation of drift from temperature. Method S52 includes, at S521, comparing the determined one or more corrective data (e.g. comparing previously-determined corrective data against newly-determined corrective data). Method S52 can also include selecting, at S522, the determined one or more corrective data, based on the comparing. In other words, the newly-determined corrective data can be selected as the applicable corrective data. Method S52 can also include averaging, at S523, the determined one or more corrective data. In other words, the previously-determined corrective data can be combined and/or averaged with the newly-determined corrective data.

In some examples, selecting (at S522) the determined one or more corrective data may comprise outputting the corrective data outputted during a previous one or more recording periods for the sensor and/or for at least one other sensor.

In some examples, the method <NUM> may be implemented, at least partly, by system <NUM> of <FIG> and/or the sensor <NUM> of <FIG>.

The method <NUM> may enable reducing the presence of timing errors within seismic data, where the seismic data is provided by sensors, and where the sensors have been unable to adjust their clocks with sufficient regularity by using timestamp data that is provided by the GNSS <NUM>.

<FIG> schematically illustrates a method <NUM> for processing clock data that is provided by the clock of a seismic sensor, where the seismic sensor has been exposed to an ambient temperature that varies over time.

The method <NUM> illustrated in <FIG> includes one or more of, obtaining, at S10, the clock data and timestamp data (where the timestamp data is provided by the global navigation satellite system). Method <NUM> can also include determining, at S20, whether the obtained timestamp data comprises at least one temporal gap greater than a predetermined threshold.

With one or more embodiments, a temporal gap can be defined as a duration of time between successive receptions of timestamp data from the GNSS. With one or more embodiments, the predetermined threshold can be a duration of time between <NUM> hour and <NUM> hours, such as, for example, <NUM> hours. In that example, a temporal gap of more than <NUM> hours means that the sensor did not receive the timestamp data from the GNSS for at least <NUM> hours.

If it is determined at S20 that the obtained timestamp data comprises at least one determined temporal gap greater than a predetermined threshold, the method <NUM> may further comprise estimating, at S30, corrective data associated with a drift in the clock data as a function of the time and the ambient temperature. In some examples, the corrective data may be determined, at least partly, by the method <NUM> according to the disclosure, for the sensor and/or for at least one other sensor.

The method <NUM> may further comprise, for each temporal gap that is greater than the predetermined threshold, correcting, at S40, the corresponding clock data based on the obtained corrective data.

The method <NUM> may enable reducing timing errors in seismic data that are provided by sensors, where the sensors have been unable to adjust their clocks with sufficient regularity by using timestamp data that is provided by the GNSS <NUM>.

In some examples, the method <NUM> may be implemented, at least partly, by system <NUM> of <FIG> and/or sensor <NUM> of <FIG>.

In some examples, alternatively or additionally the communication module <NUM> of <FIG> may be configured to wirelessly communicate with the communication module <NUM>.

In some examples, communication between the communication module <NUM> and the communication module <NUM> of <FIG> may include at least one of the following:.

Claim 1:
A method (<NUM>) for determining a drift in clock data that is provided by a clock (<NUM>) of a seismic sensor (<NUM>), wherein the sensor is exposed to an ambient temperature that varies over time, the method comprising:
obtaining temperature data (S1) from the seismic sensor (<NUM>) exposed to the ambient environment, wherein the temperature data is associated with the ambient temperature as a function of time;
obtaining the clock data (S2);
obtaining timestamp (S3) data provided by a global navigation satellite system (<NUM>);
determining a temporal drift (S3) in the clock data based on a difference between the clock data and the timestamp data; characterized in that the method comprises:
parametrizing drift data based on the temperature data obtained from the seismic sensor; and
determining corrective data for correcting the clock data by minimizing a difference between the parametrized drift data and the temporal drift in the clock data.