Patent Publication Number: US-2023161373-A1

Title: Clock drift

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a National Phase Entry into the U.S. under 35 U.S.C. § 371 of and claims priority to PCT Application No. PCT/GB2020/052597 filed Oct. 15, 2020, entitled “Clock Drift,” which claims benefit of Great Britain Patent Application No. 1914919.4 filed Oct. 15, 2019, and entitled “Clock Drift,” the entire contents of each being incorporated herein by reference for all purposes. 
    
    
     STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT 
     Not applicable. 
     TECHNICAL FIELD 
     The disclosure relates to, but is not limited to, methods for determining drifts in clock data and methods for processing clock data. The disclosure also relates to corresponding apparatuses, computer programs or computer program products. 
     BACKGROUND 
     This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present disclosure, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art. 
     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. 
     BRIEF SUMMARY 
     A summary of certain embodiments disclosed herein is set forth below. It should be understood that these aspects are presented merely to provide the reader with a brief summary of these certain embodiments and that these aspects are not intended to limit the scope of this disclosure. Indeed, this disclosure may encompass a variety of aspects that may not be set forth below. 
     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. 
     Accordingly, present embodiments of the disclosure may enable 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 are set out in the appended claims. These and other aspects and embodiments are also described herein. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Embodiments of the present disclosure will now be described, by way of example, with reference to the accompanying drawings, in which: 
         FIG.  1    schematically illustrates a plurality of example seismic sensors disposed in or above a survey area during a seismic survey; 
         FIG.  2    schematically illustrates an example control system and a plurality of example seismic sensors; 
         FIG.  3    schematically illustrates an example seismic sensor; 
         FIG.  4    schematically illustrates an example amount of clock drift that occurs to a clock over time; 
         FIG.  5    schematically illustrates an example plot of a drift rate that is exhibited by clock data (expressed as a function of the ambient temperature); 
         FIG.  6    shows an example plot of temperature data obtained e.g. by a thermometer of a seismic sensor and reflecting the ambient temperature, as a function of time; 
         FIG.  7    shows an example chart of a determined integral of an ambient temperature T(t) between time to (associated with a start of a recording period of a sensor) and time t; 
         FIG.  8    shows a flow chart which schematically illustrates an example method according to the disclosure; 
         FIG.  9    shows a flow chart which schematically illustrates detailed steps of the example method of  FIG.  8   ; 
         FIG.  10    shows a flow chart which schematically illustrates other detailed steps of the example method of  FIG.  8   ; and 
         FIG.  11    shows a flow chart which schematically illustrates another example method according to the disclosure. 
     
    
    
     In the figures, similar elements bear identical numerical references. 
     DETAILED DESCRIPTION 
       FIG.  1    schematically illustrates a plurality of example seismic sensors  15  disposed in or above a survey area  16  of the Earth during a seismic survey. The sensors  15  are configured to record the reflected seismic energy that returns from the geological layers within the survey area  16 . 
     A Global Navigation Satellite System (GLASS)  20  provides timestamp data to the sensors  15  during the seismic survey to help create an image or profile of the corresponding survey area  16 . 
     Before the seismic survey starts, the sensors  15  may be initialized, e.g. calibrated. After the seismic survey is finished, the seismic data recorded by the sensors  15  may be collected and used to create an image or profile of the corresponding subsurface region. 
     In some embodiments, sensors  15  can operate in conjunction with control system  10  to perform initialization of the sensors  15  and/or to perform collecting of the seismic data that is recorded by the sensors  15 . 
       FIG.  2    schematically illustrates an example control system  10  and a plurality of example seismic sensors  15 . 
     The control system  10  comprises a docking station  14 , where the plurality of sensors  15  may be removably docked, as illustrated by the arrows of  FIG.  2   . 
     The control system  10  can also include a processor  11 , a memory  12  and/or a communication module  13  that are configured to communicate with a communication module of a sensor  15 , e.g. when the sensor  15  is docked in the docking station  14  of the control system  10 . The processor  11 , the memory  12  and the communication module  13  can enable the initialization of the sensors  15  (e.g. during calibration). The processor  11 , the memory  12  and/or the communication module  13  can also enable the collection/retrieval of the seismic data that has been recorded by the sensors  15 , e.g. when the sensors are docked in the docking station  14  of the control system  10 . In other words, with one example embodiment, prior to being deployed in survey area  16 , sensors  15  can be initialized by being docked in docking station  14 . Next, sensors  15  can record seismic data while sensors  15  are deployed in the survey area  16 . Finally, sensors  15  can be gathered from the survey area  16  and redocked within docking station  14  in order to gather the data that was recorded by sensors  15 , while sensors  15  were deployed in the survey area  16 . With one or more embodiments, clock drift that results from the changing ambient temperature can be corrected at the time that the sensors  15  are redocked within docking station  14 . 
     As illustrated in  FIG.  2   , each sensor  15  may have at least two configurations, In a first configuration, the sensor  15  may be docked in a docking station  14  of the control system  10 , e.g. for performing initialization and/or for transporting to a survey area. In a second configuration, the sensor  15  may be deployed within a survey area for measuring seismic data. 
     As illustrated in  FIG.  3   , the sensor  15  comprises a communication module  151  that is configured to communicate with the communication module  13  of the control system  10 . 
     The sensor  15  also comprises a processor  152  and a memory  153 . In some examples, the sensor  15  may comprise a thermometer  154 . 
     The sensor  15  can also include a clock  155  that is configured to provide clock data. 
     The sensor  15  can include an antenna  156  that is configured to receive timestamp data that is provided by the GNNS  20 . In some examples, the timestamp data that is provided by the GNNS  20  may be used by the sensor  15  to correct temporal irregularities in the periods of the clock data that are provided by the clock  155  (of sensor  15 ). Temporal irregularities can be considered to be divergences between the clock data of clock  155  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  15  are redocked within docking station  14 . 
     One or more embodiments can consider the timestamp data (received from GNNS  20 ) as being a reliable/authoritative source of time data. As such, in order to correct the above-described temporal irregularities, one or more embodiments can compare the clock data (that is provided by clock  155 ) against the received timestamp (that is provided by the GNNS  20 ). In the event that deviations/discrepancies exist between the clock data and the timestamp data, one or more embodiments can consider such deviations/discrepancies to be the temporal irregularities. The above-described clock drift can be evidenced by such temporal irregularities. After comparing the received timestamp (that is provided by the GNNS  20 ) against the clock data (that is provided by the clock  155 ), sensor  15  can correct the temporal irregularities, as described in more detail below. 
       FIG.  4    schematically illustrates an example amount of clock drift that occurs to a clock over time. As illustrated in  FIG.  4   , 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.  4   , 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 8 days. As reflected by the curve with circles (of  FIG.  4   ), the drift can dynamically change across the time period of 8 days. For example, between days 1-5, the drift amount tends to get further into the negative, until reaching an amount of about −25 ms. After the 5th day, the drift amount tends to increase into the positive, until reaching an amount of about 90 ms on the 8th 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 1) and a second measurement at the end of the 8th 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.  5    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.  5   , 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.  5    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.  5   , the drift rate varies linearly with the temperature within a temperature range of about 20 C (e.g. between −4 0C and −20 C in  FIG.  5   ), but the variation of the drift rate is non-linear above a certain temperature (e.g. for temperatures above −20 C in  FIG.  5   ). 
     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 can determine 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 can determine 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.  6    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.  6    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.  6   , 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.  7    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.  8    shows a flow chart illustrating an example method  100 , according to the disclosure, by using the received clock data and the received temperature data as explained above. As described in more detail below, the example method  100  can output corrective data, which may be used to correct the drift in the clock data. 
     The method  100  illustrated in  FIG.  8    can include, at S 1 , 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  100  can also include, at S 2 , obtaining clock data that is provided by a clock of the sensor. 
     In some examples, the temperature data that is obtained at S 1  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.  6    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 S 2 ), one or more embodiments can also obtain timestamp data (at S 3 ) that 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, one or more embodiments can determine drift data (at S 4 ) that reflects a temporal drift in the dock data, 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 can indicate that drift has occurred. 
     The method  100  may further comprise determining and outputting, at S 5 , 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 S 5 , the corrective data comprises parameterizing drift D(t), where: 
         D ( t )=[ a ×θ( t )]+( b×t )   (E)
 
     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: 
       θ( t )=∫ t0   t   T.  
 
     An example of θ is illustrated in  FIG.  7    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 S 5  can include determining parameters (a, b). D(t0) may be such that: 
         D ( t 0)=0. 
     It should thus be understood that, at S 5 , 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  100  of  FIG.  8    further comprises outputting, at S 5 , 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 S 5 ) can include performing at least one of:
         (1) storing the corrective data in the memory of the seismic sensor and/or in the memory of the control system (e.g. for further reference); and/or (2) providing the corrective data to the processor of the seismic sensor and/or to the processor of the control system (e.g. for immediate use, e.g. for correction of the drift).       

     As illustrated in  FIGS.  5  and  6    (discussed above), the ambient temperature may vary within one or more temperature ranges during one or more recording periods. In the example of  FIG.  5   , the ambient temperature varies between a first range (e.g. a range of temperatures below −40 C), a second range (e.g. a range between −40 C and −20 C), and a third range (e.g. a range above −20 C), 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:
         a maximum temperature of each temperature range; and/or   a minimum temperature of each temperature range; and/or   an average temperature of each temperature range.       

     In some examples, outputting the corrective data, at S 5 , 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.  9   , one or more embodiments, at S 5 , can output the corrective data by performing at least one of the following: Method S 5 , at S 51 , includes determining one or more corrective data for one or more calibration periods and/or one or more seismic survey periods. Method S 5 , at S 52 , can also include updating, at S 52 , the determined one or more corrective data (which was previously determined). Method S 5 , at S 53 , includes outputting the updated corrective data. 
     As illustrated in  FIG.  10   , in some examples, updating at S 52  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 S 52  includes, at S 521 , comparing the determined one or more corrective data (e.g. comparing previously-determined corrective data against newly-determined corrective data). Method S 52  can also include selecting, at S 522 , 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 S 52  can also include averaging, at S 523 , 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 S 522 ) 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  100  may be implemented, at least partly, by system  10  of  FIG.  2    and/or the sensor  15  of  FIG.  3   . 
     The method  100  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  20 . 
       FIG.  11    schematically illustrates a method  200  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  200  illustrated in  FIG.  11    can include one or more of, obtaining, at S 10 , the clock data and timestamp data (where the timestamp data is provided by the global navigation satellite system). Method  200  can also include determining, at S 20 , 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 1 hour and 10 hours, such as, for example, 6 hours. In that example, a temporal gap of more than 6 hours means that the sensor did not receive the timestamp data from the GNSS for at least 6 hours. 
     If it is determined at S 20  that the obtained timestamp data comprises at least one determined temporal gap greater than a predetermined threshold, the method  200  may further comprise estimating, at S 30 , 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  100  according to the disclosure, for the sensor and/or for at least one other sensor. 
     The method  200  may further comprise, for each temporal gap that is greater than the predetermined threshold, correcting, at S 40 , the corresponding clock data based on the obtained corrective data. 
     The method  200  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  20 . 
     In some examples, the method  200  may be implemented, at least partly, by system  10  of  FIG.  2    and/or sensor  15  of  FIG.  3   . 
     Modifications and Variations 
     In some examples, alternatively or additionally the communication module  151  of  FIG.  3    may be configured to wirelessly communicate with the communication module  13 . 
     In some examples, communication between the communication module  13  and the communication module  151  of  FIG.  3    may include at least one of the following:
         (1) configuration data from the control system  10  to the sensor  15 , e.g. for setting a recording gain of the sensor  15 ; and/or   (2) seismic data from the sensor  15  to the system  10 , e.g. during and/or after a seismic survey; and/or   (3) the temperature data from/to the sensor  15  to/from the system  10 , e.g.   during and/or after a seismic survey; and/or   (4) the drift data from/to the sensor  15  to/from the system  10 , e.g. during and/or after a seismic survey; and/or   (5) the corrective data from/to the sensor  15  to/from the system  10 , e.g. during and/or after a seismic survey.       

     Other data may also be envisaged. 
     In some examples, the effects of the clock ageing and/or the effects of hysteresis can either be negligible or there can be sufficient timestamp data to characterize them. 
     With one or more embodiments, for a given clock, the main determinant of clock drift variations is the changes in the ambient temperature. In some examples, the temperature of the sensor can be recorded continuously throughout its deployment.