Patent Publication Number: US-11385371-B2

Title: Systems and methods of determining parameters of a marine seismic survey

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims the benefit of priority under 35 U.S.C. § 120 as a continuation of U.S. patent application Ser. No. 16/790,272, filed Feb. 13, 2020, which is a continuation of U.S. patent application Ser. No. 16/375,714, filed Apr. 4, 2019, which is a continuation of U.S. patent application Ser. No. 14/864,345, filed Sep. 24, 2015, each of which is hereby incorporated by reference herein in its entirety. 
    
    
     BACKGROUND 
     Seismic data may be evaluated to obtain information about subsurface features. The information can indicate geological profiles of a subsurface portion of earth, such as salt domes, bedrock, or stratigraphic traps, and can be interpreted to indicate a possible presence or absence of minerals, hydrocarbons, metals, or other elements or deposits. 
     SUMMARY 
     At least one aspect is directed to a method of detecting seismic data acquisition unit depth and acoustic signal water column transit velocity for a seismic survey. The method can include obtaining, by a data processing system, seismic data acquired by a plurality of seismic data acquisition units disposed on a seabed responsive to an acoustic signal propagated from an acoustic source through a water column. The method can include determining, by the data processing system, from the seismic data, a direct arrival time for the acoustic signal at each of the plurality of seismic data acquisition units. The method can include obtaining an estimated depth value of each of the plurality of seismic data acquisition units and an estimated water column transit velocity of the acoustic signal. The method can include identifying an average travel time error value based on the direct arrival time for the acoustic signal at each of the plurality of seismic data acquisition units, the estimated depth value, and the estimated water column transit velocity. The method can include determining an initial mean absolute deviation of travel time error from the average travel time error value. The method can include applying a depth model and a water column transit velocity model to the estimated depth value and to the estimated water column transit velocity to determine, using the initial mean absolute deviation of travel time error, an updated depth value and an updated water column transit velocity for each of the plurality of seismic data acquisition units. The method can include creating, by the data processing system, a data structure indicating the updated depth value for each of the plurality of seismic data acquisition units. 
     At least one aspect is directed to a system of detecting parameters related to a marine seismic survey. The system can include a data processing system having a depth value generation module and a water column transit velocity generation module. The data processing system can obtain seismic data acquired by a plurality of seismic data acquisition units disposed on a seabed responsive to an acoustic signal propagated from an acoustic source through a water column. The data processing system can determine, from the seismic data, a direct arrival time for the acoustic signal at each of the plurality of seismic data acquisition units. The data processing system can obtain an estimated depth value of each of the plurality of seismic data acquisition units and an estimated water column transit velocity of the acoustic signal. The data processing system can identify an average travel time error value based on the direct arrival time for the acoustic signal at each of the plurality of seismic data acquisition units, the estimated depth value, and the estimated water column transit velocity. The data processing system can determine an initial mean absolute deviation of travel time error from the average travel time error value. The data processing system can apply a depth model and a water column transit velocity model to the estimated depth value and to the estimated water column transit velocity determine an updated depth value and an updated water column transit velocity for each of the plurality of seismic data acquisition units. The data processing system can create a data structure indicating the updated depth value for each of the plurality of seismic data acquisition units. 
     At least one aspect is directed to a computer readable storage medium storing instructions that when executed by one or more data processors, cause the one or more data processors to perform operations. The operations can include obtaining seismic data acquired by a plurality of seismic data acquisition units disposed on a seabed responsive to an acoustic signal propagated from an acoustic source through a water column as part of a seismic survey. The operations can include determining, from the seismic data, a direct arrival time for the acoustic signal at each of the plurality of seismic data acquisition units, and obtaining an estimated depth value of each of the plurality of seismic data acquisition units and an estimated water column transit velocity of the acoustic signal. The operations can include identifying an average travel time error value based on the direct arrival time for the acoustic signal at each of the plurality of seismic data acquisition units, the estimated depth value, and the estimated water column transit velocity. The operations can include determining an initial mean absolute deviation of travel time error from the average travel time error value. The operations can include determining an updated depth value and an updated water column transit velocity for each of the plurality of seismic data acquisition units. The operations can include creating a data structure indicating the updated depth value for each of the plurality of seismic data acquisition units. 
     These and other aspects and implementations are discussed in detail below. The foregoing information and the following detailed description include illustrative examples of various aspects and implementations, and provide an overview or framework for understanding the nature and character of the claimed aspects and implementations. The drawings provide illustration and a further understanding of the various aspects and implementations, and are incorporated in and constitute a part of this specification. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings are not intended to be drawn to scale. Like reference numbers and designations in the various drawings indicate like elements. For purposes of clarity, not every component may be labeled in every drawing. In the drawings: 
         FIG. 1  is a schematic diagram depicting an example system for detecting parameters related to marine seismic survey, according to an illustrative implementation; 
         FIG. 2  is a block diagram depicting an example environment for detecting parameters related to marine seismic survey, according to an illustrative implementation; 
         FIG. 3  is a flow diagram depicting a method of detecting seismic data acquisition unit depth and acoustic signal water column transit velocity, according to an illustrative implementation; and 
         FIG. 4  is a block diagram illustrating an architecture for a computer system that can be employed to implement the systems and methods described and illustrated herein. 
     
    
    
     DETAILED DESCRIPTION 
     Following below are more detailed descriptions of various concepts related to, and implementations of, methods, apparatuses, and systems of determining or estimating the depth of one or more receivers such as seismic data acquisition units associated with a seismic survey, as well as determining or estimating water column transit velocity of an acoustic or other signal that propagates to or from a seismic source through a water column. The various concepts introduced above and discussed in greater detail below may be implemented in any of numerous ways. 
     Systems and method of the present disclosure relate generally to determining or detecting parameters such as seismic data acquisition unit depth or acoustic signal water column transit velocity related to a marine seismic survey. The data processing system described herein can determine seismic data acquisition unit depth for a plurality of seismic data acquisition units, and can determine the water column transit velocity of one or more acoustic signals from (or sometimes exclusively from) seismic data that can include timing information. By applying depth and water column transit velocity models to the seismic data, the data processing system can determine seismic data acquisition unit depth and acoustic signal water column transit velocity from or simultaneously from the seismic data, in the presence of timing errors for any given seismic data acquisition unit, and without zero mean error assumptions on a starting model for receiver depth or water velocity that could for example be present with traveltime inversion techniques. For example, unit depth errors using traveltime inversion techniques may not be zero mean error based due to depth variances associated with an uneven seabed  135  in an area of a seismic survey. 
       FIG. 1  depicts a system  100  for detecting parameters related to a marine seismic survey. The system  100  can include at least one vessel  105 , such as a ship that implements a marine seismic survey. The vessel  105  can travel through a body of water  110 , in direction of motion  115 , for example. The body of water  110  can include fresh water, salt water, mixed water, volumes of oceans, seas, or lakes, or mixed or transition zones such as inlets, deltas, or bays. The vessel  105  can include, be equipped with, or tow at least one seismic source  120  through the body of water  110 . 
     The seismic sources  120  can include at least one air gun or other device that generates seismic energy. The seismic source(s)  120  can be towed behind or positioned underneath the vessel  105 , and disposed under the surface of the body of water  110 . For example, at least one cable  125  can tow the seismic source  120  behind the vessel at a depth of between 2 and 80 meters below the surface of the body of water  110 . In one implementation the seismic source depth is 10 meters below the surface of the both of water  110 . The seismic source  120  can actuate to produce at least one pulse of acoustic energy (e.g. at least one acoustic signal) that propagates from the seismic source  120  through the water column  130 , where it passes through the seabed  135  and penetrates beneath the surface of the earth. The acoustic energy can reflect or refract off of subsurface features, such as geologic boundaries or layers. The reflected or refracted signals can be detected or recorded as seismic data by at least one seismic data acquisition unit  140  disposed on the seabed  135 . In some implementations, a plurality of seismic sources  120  are disposed in an array of individual air guns of varying sizes, disposed at the same or varying depths, that can be simultaneously actuated to generate the acoustic signal or sequentially actuated to generate multiple acoustic signals. Further, multiple cables  125  can attach multiple seismic sources  120  to the vessel  105 . For example, the vessel  105  can tow multiple cables  125  in parallel with seismic sources  120  arranged in a parallel line or grid configuration and attached to the cables  125 . 
     The system  100  can include a plurality of seismic data acquisition units  140 . The seismic data acquisition units  140  can each include at least one geophone or hydrophone to detect the seismic data. The seismic data acquisition units  140  can each include at least one power source, memory, hydrophone, geophone, and communication interface to transmit the seismic data out from the seismic data acquisition unit  140 . The seismic data acquisition units  140  can be deployed from the vessel  105  that is associated with the seismic source, or from a different vessel to the seabed  135 . One or more remote operating vehicle (ROV) can assist with deployment and collection of the seismic data acquisition units  140 . For example, the ROV can be a submersible autonomous vehicle that can place or collect the seismic data acquisition units  140  on or from the seabed  135 . The seismic data acquisition units  140  can be disposed in an array such as a grid pattern (e.g., a symmetric formation) on the seabed  135 . Each seismic data acquisition unit  140  can collect and store seismic data. Upon retrieval, for example by an ROV or via a cable, the seismic data can be extracted or obtained from the seismic data acquisition units  140 . For example the seismic data can be transmitted or manually extracted from the seismic data acquisition units  140 . The seismic data can be interpreted to identify geologic boundaries or formations that may indicate the presence of minerals, hydrocarbons, or various earth elements. In addition to ROV or manual seismic data extraction, the seismic data acquisition units  140  can also transmit the acquired seismic data to a database or data processing system via wired communication using at least one data communications cable connected to the seismic data acquisition unit, or via wireless communication such as laser or optic based subsurface communications through the water column  130  between seismic data acquisition units  140  and additional relay, computing, or data storage devices. 
     Referring to  FIG. 2 , among others, the system  100  can include at least one data processing system  205 , such as at least one logic device such as a computing device, server, personal computer, laptop, desktop, tablet, mobile, personal digital assistant, or smartphone computing device having at least one processor. The data processing system  205  can be located on the vessel  105 , or separate from the vessel  105  in a land based facility. The data processing system  205  can include at least one server. For example, the data processing system  205  can include a plurality of servers located in at least one data center or server farm. The data processing system  205  can estimate or otherwise determine seismic data acquisition unit depth and acoustic signal water column transit velocity from the seismic data. In some implementations, the data processing system  205  estimates or determines the seismic data acquisition unit depth and acoustic signal water column transit velocity exclusively from the seismic data, which includes timing information related to the acoustic signal. 
     The data processing system  205  can include at least one water column transit velocity generation module  210 , at least one depth value generation module  215 , and at least one database  220 . The water column transit velocity generation module  210  and the depth value generation module  215  can each include at least one processing unit, server, virtual server, circuit, engine, agent, appliance, or other logic device such as programmable logic arrays configured to communicate with the database  220  and with other computing devices  225  (e.g., other laptop, personal, desktop, tablet, or smartphone computing devices via a computer network). The database  220  can store the seismic data obtained from the seismic data acquisition units  140  as well as data generated by the water column transit velocity generation module  210  and the depth value generation module  215 , for example. 
     The water column transit velocity generation module  210  and the depth value generation module  215  can include or execute at least one computer program or at least one script. The water column transit velocity generation module  210  and the depth value generation module  215  can be separate components, a single component, or part of the data processing system  205 . The water column transit velocity generation module  210  and the depth value generation module  215  can include combinations of software and hardware, such as one or more processors configured to obtain and evaluate seismic data from the seismic data acquisition units  140 , determine direct arrival times for the acoustic signal at one or more of the seismic data acquisition units  140 , obtain estimated depth values of one or more of the seismic data acquisition units  140 , obtain estimated water column transit velocities of one or more of the seismic data acquisition units  140 , identify average travel time error values of the seismic data and initial mean absolute deviation values of the average travel time error values, apply depth models and water column transit velocity models to the estimated depth value and the estimated water column transit velocity to determine updated depth values and updated water column velocities, and to create one or more data structures indicating the updated depth values or updated water column velocities, for example. 
     The data processing system  205  can include servers or end user computing devices configured to display data (directly at a monitor or indirectly by communicating via a computer network to another computing device such as the computing device  225 ) such as the updated depth value of one or more seismic data acquisition units  140  or the updated water column transit velocity of the acoustic signal, as well as other data such as interpretations of the seismic data indicating the presence or absence of geologic boundaries, layers, formations, mineral or hydrocarbon deposits, or other conditions such as salt domes. The data processing system  205  can include desktop computers, laptop computers, tablet computers, smartphones, personal digital assistants, mobile devices, end user computing devices, consumer computing devices, servers, clients, and other computing devices. The data processing system  205  can include user interfaces such as microphones, speakers, touchscreens, keyboards, pointing devices, a computer mouse, touchpad, or other input or output interfaces. 
     The data processing system  205  can include the water column transit velocity generation module  210  or the depth value generation module  215  as part of one or more servers of a seismic data interpretation system to receive seismic data from the seismic data acquisition units  140  directly, manually (via a memory stick, disk, or removable media transferred from the seismic data acquisition units  140  to the data processing system  205 ) or via a wired or wireless network such as the internet or local, wide, or metro area network, and to provide output data such as updated depth values that indicate the subsurface depth of the seismic data acquisition units  140  when disposed on the seabed  135 , as well as updated water column transit velocity values that indicate a velocity of one or more acoustic signals through the water column  130  from the seismic source  120  to the seismic data acquisition units  140  or vice-versa. 
     The water column transit velocity generation module  210  or the depth value generation module  215  can be part of, or can include scripts executed by, one or more servers in the data processing system  205  (e.g., a search engine system) to determine depth values and water column transit velocity values. The water column transit velocity generation module  210  can be part of the same computing device or a different computing device as the depth value generation module  215  in the data processing system  205 . From the seismic data, the water column transit velocity generation module  210  can determine water column transit velocity values, and can refine or update those values. Also from the seismic data, the depth value generation module  215  can determine depth values of the seismic data acquisition units  140 , and can update those values. 
     The data processing system  205  can include multiple servers or other computing devices (laptop, desktop, mobile, tablet, or smartphone computing device) in communication with each other via a network. The network can include computer networks such as the internet, local, wide, metro or other area networks, intranets, satellite networks, other computer networks such as voice or data mobile phone communication networks, and combinations thereof. 
     In some implementations, the data processing system  205  can obtain the seismic data. For example, the vessel  105  can tow at least one seismic source  120 . The seismic source  120  can be actuated to generate at least one acoustic signal that propagates through the water column  130 . At least some of the acoustic signal can pass through the seabed  135 , down into the earth, and reflect or refract off of subsurface geologic formations, back (e.g., up) toward the surface of seabed  135  (e.g., the ocean floor). The seismic data acquisition units  140  can detect, collect, acquire, or record this reflected or refracted seismic data. The seismic data can then be transferred (e.g., via wired, wireless, manual, optical, or direct transmissions) from the seismic data acquisition units  140  to the data processing system  205 . The data processing system  205  can obtain the seismic data while present on the vessel  105  (e.g., as a computing device disposed in a control station of the vessel  105 ) or at a land based location. Thus, the data processing system  205  can obtain the seismic data that was first acquired by the seismic data acquisition units  140  responsive to propagation of the acoustic signal from the acoustic source through the water column. The seismic data can include timing data related to actuation of the seismic source  120  or related to time of acquisition of the seismic data by the seismic data acquisition units  140 . 
     From the seismic data, the data processing system  205  can determine a direct arrival time for the acoustic signal at each or at least one of the seismic data acquisition units  140 . The direct arrival time indicates a time period from generation of the acoustic signal to detection of the seismic data by a seismic data acquisition unit  140 . The data processing system  205  can determine the direct arrival time using a first break picking detection technique. For example, the data processing system  205  can determine the direct arrival time by determining the time of maximum amplitude of the seismic wavelet after applying a source designature. The seismic data analyzed by the data processing system  205  to determine the direct arrival time can be a raw wavelet that is unprocessed or unchanged from the seismic data as acquired by the seismic data acquisition unit  140 , or can be filtered to remove minimum phase or zero phase occurrences. 
     The data processing system  205  (or component thereof such as the depth value generation module  215 ) can determine an estimated depth value of each of the plurality of seismic data acquisition units  140 . For example, the estimated depth value can be an initial estimated depth of a seismic data acquisition unit  140  disposed on the seabed  135  at the bottom of the water column  130 . The data processing system  205  can update this initial estimated depth value to determine a more precise updated depth value as described herein. In some implementations, a remote operated vehicle (ROV) or autonomous underwater vehicle (AUV), (e.g., an unmanned submarine) equipped with a pressure sensor or other depth sensor can pass generally near (e.g., within 50 meters) seismic data acquisition units  140  and based on water pressure or other measurement can determine a depth. The data processing system  205  can obtain this information (or determine the estimated depth from pressure or other information received from the ROV or AUV or from the seismic data acquisition units  140  themselves) and can assign depth values to each seismic data acquisition unit  140 . The data processing system  205  can also determine the estimated depth values for each of the seismic data acquisition units  140  from data obtained via echo sounding, sonar, or fathometer techniques that are implemented from the vessel  105 , or from preexisting data, e.g., obtained from the database  220 . The estimated depth value of the seismic data acquisition units  140  can be within 100 meters of the actual depth of the seismic data acquisition units  140 . In some implementations, the estimated depth value is within 50 meters of the actual depth value of the seismic data acquisition units. 
     The water column transit velocity generation module  210  or other component of the data processing system  205  can obtain at least one estimated water column transit velocity of the acoustic signal. The estimated water column transit velocity can be an initial estimated transit velocity of the acoustic signal through the water column  130 . The estimated water column transit velocity can be a predetermined (e.g., rather than measured) velocity. For example, the estimated water column transit velocity can be a predetermined time constant and depth invariant water velocity of 1500 meters/second, although other values above and below this value can be used. The data processing system  205  can update this initial estimated water column transit velocity to determine a more precise updated water column transit velocity as described herein. 
     The data processing system  205  can identify or determine an average travel time error value for the acoustic signal(s) at each of the plurality of seismic data acquisition units  140 , based on the direct arrival time of the acoustic signal at each of the plurality of seismic data acquisition units  140  and based on the estimated depth values and estimated water column transit velocity of the acoustic signal(s). 
     Travel time error can be the difference between a modeled travel time and the actual picked travel time, or direct arrival time, represented for example by the following equation: 
     
       
         
           
             
               
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     In this equation s is a unique source, r is a unique receiver. The coordinates s x , s y , and s z  are the modeled source X Y and Z coordinates. The coordinates r x , r y , and r z  are the modeled receiver X Y and Z coordinates, in the case of this process r z  is variable. The variable v(t, r z ) is the time and depth variable velocity function at the time of the acoustic signal (e.g., shot) and depth of the receiver. DA(s,r) is the picked direct arrival time for the unique source receiver pair. 
     For example, the data processing system  205  can determine the travel time error for individual seismic data acquisition units  140  that indicates a time difference between the determined direct arrival time for a given seismic data acquisition unit  140  (determined from the seismic data) and a model arrival time based on the estimated depth value and the estimated water column transit velocity for that given seismic data acquisition unit  140 . The data processing system  205  can average the travel time error values of each seismic data acquisition unit  140  to identify or determine the average travel time error value for a seismic survey or portion thereof such as one or more acoustic signals propagated from at least one seismic source  120 . 
     From the average travel time error value, the data processing system  205  can determine an initial mean absolute deviation of travel time error. The initial mean absolute deviation can be determined from the travel time error of the initial model of a given vessel pass, using the initially defined velocity and receiver depth. The mean absolute deviation can be the average of the absolute value of the difference between the travel time errors and the average travel time error, represented for example by the following equations, where T error (s,r,t) is the travel time error for a given trace (unique source receiver pair), and n is the number of traces in the grouping of traces analyzed: 
     
       
         
           
             
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     This can be applied to a sail line, source pass, or any other collection of source locations that are reasonably close in spatial location and time of acquisition, within the offset range selected for analysis. In some implementations, the initial mean absolute deviation is determined, rather than standard deviation, as the travel time error values may not have a standard distribution. The data processing system  205  can update this initial mean absolute deviation of travel time error to determine a more precise mean absolute deviation of travel time error value. 
     Thus, the data processing system  205  can determine or obtain the (initial) estimated depth value and (initial) estimated water column transit velocity associated with each seismic data acquisition unit  140 , as well as an initial absolute deviation of travel time error. With the estimated depth value, the estimated water column transit velocity, and the initial mean absolute deviation of travel time error, the date processing system  205  can determine an updated depth value and an updated water column transit velocity for each of the acoustic signal/seismic data acquisition unit  140  pairs. The updated receiver depth and water column transit velocity can be selected from a predetermined grid of variances of the initial modelled values. The grid can have regular variations, random variations, or pseudo random variations. For example, the updated depth value and water column transit velocity can selected from the pair that results in the lowest mean absolute deviation of error of all pairs iterated. 
     For example, the data processing system  205  or components such as the depth value generation module  215  and the water column transit velocity module  210  can apply a depth model and a water column transit velocity transit model to the estimated depth value and to the estimated water column transit velocity model, respectively, to determine, using the initial mean absolute deviation of travel time error, an updated depth value for all or at least one of the seismic data acquisition units  140  and an updated water column transit velocity of at least one acoustic signal to or from at least one of the seismic data acquisition units  140 . 
     The process of updating the estimated depth value and the estimated water column transit velocity for associated with the seismic source(s)  120  and seismic data acquisition units  140  can include iterative calculations of depth values and water column velocities for the seismic source  120  (or for the acoustic signals emanating from those sources) and the seismic data acquisition units  140 . For example, the estimated depth value can be adjusted by a predetermined amount such as 1.5 meters, and the estimated water column transit velocity of the acoustic signal can be adjusted by a predetermined velocity such as 0.5 meters/second. These values are examples and other values above and below these values can be used. With these adjusted values, the data processing system  205  can determine new or updated depth values and water column transit velocity. For example, an average travel time error value that indicates an average of the differences between the direct arrival time (from the obtained seismic data) and the modeled arrival time based on the values adjusted by 1.5 m and 0.5 m/s can be determined for a series of acoustic signals (e.g., from a source pass of the seismic source  120 ) and each seismic data acquisition unit  140 . The data processing system  205  can determine a new mean absolute deviation from this (new) average travel time error value for the given depth/velocity pair adjusted by 1.5 m and 0.5 m/s. The data processing system  205  can compare the new mean absolute deviation of travel time error (that is based on the adjusted values) with the initial mean absolute deviation (based on the original values). When the new mean absolute deviation of travel time error is less than (and therefore better than) the initial (or other previous) mean absolute deviation the data processing system  205  can update the water column transit velocity with the new value (e.g., adjusted by 0.5 m/s), or can update the estimated depth value of a seismic data acquisition unit  140  with the new value (e.g., adjusted by 1.5 m). This example results in a refinement of the originally estimated depth and water column transit velocity values. 
     The updated values can be referred to as the best values at this stage in the iterative process. This process can repeat in an iterative manner. For example, the data processing system  205  can adjust the depth value of a seismic data acquisition unit  140  by another 1.5 m, and the water column transit velocity by another 0.5 m/s. From this data another (newer) mean absolute deviation of travel time error can be determined and compared with the previous or best mean absolute deviation of travel time error. If the newer mean absolute deviation of travel time error is less than the previous or best absolute deviation of travel time error, the data processing system  205  can again update the water column transit velocity or can again update the estimated depth value. If the newer mean absolute deviation of travel time error is greater than or equal to the previous or best absolute deviation of travel time error, the data processing system  205  can discard the newer mean absolute deviation of travel time error (or associated depth value or water column transmit velocity) and continue to use the previous best values. The data processing system  205  can execute any number of these iterations. For example, the data processing system  205  can run 41 iterations where the estimated water column transit velocity or estimated depth value are adjusted 41 times at predetermined step values of 1.5 m for the estimated depth values of 0.5 m/s for the estimated water column transit velocity. 
     In some implementations, having determined the initial mean absolute deviation of travel time error, the data processing system  205  applies a depth model (e.g., using the depth value generation module  215 ) and applies a water column transit velocity generation model (e.g., using the water column transit velocity generation module  210 ) to implement one or more of the following operations to update the estimated depth value and the estimated water column transit velocity model: 
     1.) Identify the step size or adjustment value from the (e.g., initial) estimated values of the depth value (e.g., 1.5 m) and of the water column transit velocity (e.g., 0.5 m/s) and a number of iterations (e.g., 41 iterations at these step sizes for both the depth value and the water column transit velocity). These may be referred to as the model values. 
     2.) Determine the travel time error value between the direct arrival time determined from the seismic data and the direct arrival time determined from the adjusted values. 
     3.) Determine the average travel time error with the adjusted (or updated) depth value and water column transit velocity for a source pass or series of acoustic signals for each seismic data acquisition unit  140 . 
     4.) Determine the (updated) mean absolute deviation from the average travel time error value for each adjusted depth value/water column transit velocity pair using the adjusted values. 
     5.) Compare the updated mean absolute deviation from the average travel time error value with the initial mean absolute deviation of travel time error from the average travel time error value. When the updated mean absolute deviation is less than the initial mean absolute deviation (or less than a previous best mean absolute deviation value), the data processing system  205  assigns or classifies the adjusted depth value as the (best available) updated depth value, or the data processing system assigns or classifies the adjusted water column transit velocity as the (best available) updated water column transit velocity for at least one seismic data acquisition unit  140 . When the updated mean absolute deviation is greater than or equal to the initial mean absolute deviation (or to a previous best mean absolute deviation value), the data processing system  205  does not modify the initial, estimated, or previously updated best depth value and water column transit velocity for at least one seismic data acquisition unit  140 . In this latter example, the data processing system  205  can discard the updated (greater) depth or values associated with the updated mean absolute deviation. 
     6.) Repeat operations 1-5 for a number of iterations. For example, the data processing system  205  can adjust the depth value and water column transit velocity value at the 1.5 m and 0.5 m/s steps, respectively, 41 times (or any other number) so that, in this example, 41 potential depth values and 41 potential water column transit velocities are evaluated for each acoustic signal and each seismic data acquisition unit  140 , which may be referred to as a 41×41 grid. 
     In the above example, the data processing system  205  has determined an updated depth value and updated water column transit velocity for at least one (or for all) of the seismic data acquisition units  140  using, for example, the coarse adjustment values of 1.5 m for depth values and 0.5 m/s for water column transit velocity. In some implementations, the data processing system  205  refines (or continues updating) these updated values. For example, the data processing system  205  (and components thereof) can repeat operations 1-6 with smaller adjustment values of, for example, 0.15 m depth steps and 0.1 m/s velocity increments again on a 41×41 grid for all or some of the seismic data acquisition units  140 . The depth model and the water column transit velocity transit model can be a single model (or module) or separate models, and can include one or mode scripts, applications or code that can be, for example, accessed from the database  220  (or other memory) and executed by the data processing system  205  to determine the updated depth values and updated water column transit velocity for a given source pass, or series of acoustic signals from one pass of the vessel  105  and seismic source  120  over the seismic data acquisition units  140 . 
     The data processing system  205  can determine updated depth values and updated water column transit velocity for the seismic data acquisition units  140  for multiple source passes, or multiple trips of the vessel  105  and seismic source  120  over at least a portion of the seismic data acquisition units  140 . In some implementations, the depth value generation module  215  (or other component of the data processing system  205 ) can determine the average of the final or updated depth values from a series of source passes for each seismic data acquisition unit  140 . In this example, the average receiver depth is determined from multiple source  120 /vessel  105  passes. For example, there may be depth changes between source passes due to tidal or current changes, or to variations in the depths of the seismic sources  120  beneath the surface of the body of water  110 . The water column transit velocity can then be further refined or updated with the depth value fixed at the average depth value. For example, the data processing system  205  can fix the depth value at the average depth value, and starting with the estimated water column transit velocity of 1500 m/s, can repeat the iterative process (e.g., operations 1.-6.) with the fixed average depth value and with 0.1 m/s adjustments to the estimated water column transit velocity from the 1500 m/s starting point or from the best previously determined water column transit velocity. In one implementation, the data processing system  205  repeats this process for 201 iterations, although other values above and below this number are possible. 
     For example, the data processing system  205  can perform the following operations with the fixed average depth value to further refine the update water column transit velocity (e.g., by applying the depth/water column transit velocity model(s): 
     1.) With the fixed average depth value (of at least one seismic data acquisition unit  140 ) the data processing system  205  can determine the travel time error value between the direct arrival time determined from the seismic data and the direct arrival time determined from the fixed average depth value and the adjusted water column transit velocity (e.g., adjusted by 0.1 m/s increments). 
     2.) Determine the average travel time error for at least one seismic data acquisition unit  140  for a source pass over the seismic data acquisition unit(s)  140  with the adjusted water column transit velocity. 
     3.) Determine the (new) mean absolute deviation from the average travel time error for the given adjusted water column transit velocity. 
     4.) Compare the (new) mean absolute deviation from operation 3 immediately above with the best previously determined mean absolute deviation. When the new mean absolute deviation is less than the best previously determined mean absolute deviation, then replace the best previously determined mean absolute deviation with the new mean absolute deviation. When the new mean absolute deviation is great than or equal to the best previously determined mean absolute deviation, then do not replace the best previously determined mean absolute deviation. 
     5.) Repeat operations 1-4 immediately above for all grid values (e.g., 201 iterations with 0.1 m/s adjustments to the water column transit velocity). 
     In the above example, the data processing system  205  can determine that, so far, the best updated water column transit velocity is the one associated with the best mean absolute deviation value. 
     The data processing system  205  can create one or more data structures indicating the updated depth value or the updated water column transit velocity for all or at least one of the seismic data acquisition units  140 . In some implementations, the data structure includes one or more ASCII files that, for example, identify individual seismic data acquisition units  140  and indicate their associated updated depth values or updated water column transit velocity associated with one or more acoustic signals. The data structure can be written to or read from the database  220 , and can be provided for display or rendering at one or more computing devices  225 , e.g., as a report. The computing devices  225  can be part of the data processing system  205  or separate from the data processing system  205 . For example, the data processing system  205  can transmit the data structure as a report to the computing device  225  via the internet or other computer network for display by the computing device  225 . The data structures described herein can include other text or character coding schemes, such as UTF-8 coding schemes. 
     The water column transit velocity of acoustic signals can change based on factors such as time or the depth of the water column  130 . In some implementations, the water column transit velocity model includes a two layer model, where the water column transit velocity of the acoustic signal through the deep layer of the water column  130  (e.g., greater than 1250 meters) is determined by the data processing system  205  to be a function of the depth of the water with no time dependent variation. In this example, the shallow layer (e.g., less than 1250 m) is determined by the data processing system  205  to have the majority or all of the time dependent velocity variation. In some implementations, the data processing server  205  determines the water column transit velocity for a deep layer of the water column  130 . The deep layer velocity can be determined as a function of water depth, based, for example on the following equation, where V 1250  is the interval velocity, e.g., 1488.6 m/sec, at water depth of 1250 m, and z is the water depth at which to compute the interval velocity:
 
 V   deep ( Z )= V   1250 +( z− 1250)*0.0166
 
     In this example, the data processing system  205  can determine the average velocity of the deep layer as the average of V deep  (z) and V 1250 . This value can be referred to as the deep layer water column transit velocity. 
     Using the deep layer water column transit velocity and the best updated water column transit velocity, the data processing system  205  or component thereof such as the water column transit velocity generation module  210  can determine the shallow layer water column transit velocity. For example, for a given source pass of the seismic source  120  over at least some of the seismic data acquisition units  140 , the data processing system  205  can determine the average shallow layer velocity and the average time of the sail line. 
     The average time of the sail line can be the average of the time of the sources  120 , each time of shot (e.g., actuation of seismic source(s)  120 ) can be given a numerical time value (e.g., seconds from the beginning of a year, or floating point day of year units that could be used). The data processing system  205  can determine the average shallow layer velocity by first computing the shallow layer velocity for each seismic data acquisition unit  140 /sail line pair, and then averaging the velocity for all receivers that recorded the sail line. For example, the shallow layer velocity can be determined by using the following equation: 
     
       
         
           
             
               
                 
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     In the above equation, V T (z,t) is the total layer velocity determined by the processing system in step 5 above; z is the depth of the receiver determined in the previous section; V deep (z) is the depth dependent interval velocity defined by the equation above; 1250 is the chosen thickness of the time variant water column transit velocity layer (other values can be used); t is the average time of the sail line; V avg (t) is the average shallow layer velocity at time t; and m is the number of seismic data acquisition units  140  (e.g., receivers) that recorded the sail line (e.g., seismic data during a source pass or vessel  105  pass), within the offset range selected for analysis. 
     The above equation is an example to compute the shallow layer velocity from a known total layer velocity and a known deep layer, and the data processing system  205  can use other methods to determine the shallow layer velocity. Further, this process need not be applied only to deep (e.g., greater than 1250 m depth) seismic data acquisition units  140 , as the main assumption is that the deep layer velocity either does not change as a function of time or varies slowly. For example, the second possibility is a reasonable assumption in most water exceeding about 400 m of depth. In areas where the water depth to the receivers is less than 1250 m the equations to compute the deep layer can change, or be replaced with water velocity measurements made by instruments placed on the ROVs or other devices. 
     The data processing system  205  can create at least one data structure (e.g., an ASCII file) indicating each average sail line time and shallow layer water column transit velocity. Data structures generated by the data processing system  205  (or obtained from the database  220 ) can be provided for display as a report by the data processing system  205  or be the computing device  225 . 
     In some implementations, the data processing system  205  can identify or determine a first layer (e.g., deep) water column transit velocity for the acoustic signal and each of the plurality of seismic data acquisition units  140 . The data processing system  205  can also identify or determine a second layer water (e.g., shallow) column transit velocity for the acoustic signal and each of the seismic data acquisition units  140  based on the first layer water column transit velocity and based on the updated water column transit velocity. 
     The data processing system  205  can also determine an average second layer (e.g., deep) water column transit velocity for at least one acoustic signal, for example by averaging the second layer water column transit velocities of an acoustic signal for a plurality of seismic data acquisition units  140 . The data processing system  205  can also identify a time invariant second layer water column velocity for the second (e.g., deep) layer of the water column. The data processing system  205  can create a data structure (that can be displayed as a report) that indicates or includes the average second layer water column transit velocity for at least one acoustic signal. 
       FIG. 3  illustrates a method  300  of detecting seismic data acquisition unit depth and acoustic signal water column transit velocity, according to an illustrative implementation. The method  300  can include an act of obtaining seismic data (ACT  305 ). For example, the data processing system  205  can obtain seismic data that was acquired by the seismic data acquisition units  140  responsive to at least one acoustic signal generated by the seismic source  120 . The method  300  can include an act of determining the direct arrival time (ACT  310 ) that indicates a time period from generation of the acoustic signal to detection of the seismic data by a seismic data acquisition unit  140 . The method  300  can include an act of obtaining, e.g., by the data processing system  205 , at least one estimated depth value of at least one seismic data acquisition unit  140 , and at least one estimated water column transit velocity of at least acoustic signal through the water column  130  (ACT  315 ). The method  300  can include an acts of identifying, by the data processing system  205 , the average travel time error value (ACT  320 ), and determining the initial mean absolute deviation of the travel time error (ACT  325 ). The method  300  can include the data processing system  205  applying at least one of a depth model and a water column transit velocity model to the estimated depth value or to the estimated water column transit velocity to determine at least one updated depth value or at least one updated water column transit velocity (ACT  330 ). The method  300  can include creating, by the data processing system  205 , at least one data structure indicating the updated depth value for at least one (or for each) of the seismic data acquisition units  140 , or indicating the updated water column transit velocity of the acoustic signal (ACT  335 ). 
     Thus, the operations described herein can derive data acquisition unit  140  depth and water column transit velocity of acoustic signals as a function of time and depth, from the seismic data. Timing related to the receipt of the seismic data or acoustic signal by the seismic data acquisition units may not be absolutely known, so the systems and methods described herein can account for or ignore timing errors when determining the depth values and water column transit velocities. The data processing system  205  can employ a constant velocity positioning sequence to determine the position of the seismic data acquisition units  140  on the seabed  135 . 
       FIG. 4  is a block diagram of a computer system  400  in accordance with an implementation of the systems and methods described herein. The computer system or computing device  400  can include or be used to implement the system  100 , data processing system  205 , water column transit velocity generation module  210 , depth value generation module  215 , or database  220 . 
     The computing system  400  can include at least one bus  405  or other communication component for communicating information and at least one processor  410 ( a - n ) or processing circuit coupled to the bus  405  for processing information. The computing system  400  can also include one or more processors  410  or processing circuits coupled to the bus  405  for processing information such as the seismic data, depth values, or water column transit velocity values. The computing system  400  can include main memory  415 , such as a random access memory (RAM) or other dynamic storage device, coupled to the bus  405  for storing information, and instructions to be executed by the processor  410 . The Main memory  415  can include or be part of the database  220  and can be used for storing seismic data, depth model data, water column transit velocity model data, depth and updated depth values, water column transmit velocity and update water column transit velocity values, images, reports, executable code, temporary variables, or other intermediate information during execution of instructions by the processor  410 . The computing system  400  may further include a read only memory (ROM)  420  or other static storage device coupled to the bus  405  for storing static information and instructions for the processor  1210 . A storage device  425 , such as a solid state device, magnetic disk or optical disk, is coupled to the bus  405  for persistently storing information and instructions. The storage device  425  can include or be part of the database  220 . 
     The computing system  400  can be coupled via the bus  405  to a display  435  (e.g., of the data processing system  205 ), such as a liquid crystal display or an active matrix display, for displaying information to a user. An input device  430 , such as a keyboard including alphanumeric and other keys, may be coupled to the bus  405  for communicating information and command selections to the processor  410 . The input device  430  can include a touch screen display  435 . The input device  430  can also include a cursor control, such as a mouse, a trackball, or cursor direction keys, for communicating direction information and command selections to the processor  410  and for controlling cursor movement on the display  435 . 
     The processes, systems and methods described herein can be implemented by the computing system  400  in response to the processor  410  executing an arrangement of instructions contained in main memory  415 . Such instructions can be read into main memory  415  from another computer-readable medium, such as the storage device  425 . Execution of the arrangement of instructions contained in main memory  415  causes the computing system  400  to perform the illustrative processes described herein. One or more processors in a multi-processing arrangement may also be employed to execute the instructions contained in main memory  415 . In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to effect illustrative implementations. Thus, embodiments are not limited to any specific combination of hardware circuitry and software. 
     The systems and methods described herein can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed herein and their structural equivalents, or in combinations of one or more of them. The subject matter described herein can be implemented as one or more computer programs, e.g., one or more circuits of computer program instructions, encoded on one or more computer storage media for execution by, or to control the operation of, data processing apparatus. The program instructions can be encoded on an artificially generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information for transmission to suitable receiver apparatus for execution by a data processing apparatus. A computer storage medium can be, or be included in, a computer-readable storage device, a computer-readable storage substrate, a random or serial access memory array or device, or a combination of one or more of them. Moreover, while a computer storage medium is not a propagated signal, a computer storage medium can be a source or destination of computer program instructions encoded in an artificially generated propagated signal. The computer storage medium can also be, or be included in, one or more separate components or media (e.g., multiple CDs, disks, or other storage devices). 
     The operations described herein can be performed by a data processing apparatus on data stored on one or more computer-readable storage devices or received from other sources. The term “data processing system” or “computing device” encompasses various apparatuses, devices, and machines for processing data, including by way of example a programmable processor, a computer, a system on a chip, or multiple ones, or combinations of the foregoing. The apparatus can include special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit). The apparatus can also include, in addition to hardware, code that creates an execution environment for the computer program in question, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, a cross-platform runtime environment, a virtual machine, or a combination of one or more of them. The apparatus and execution environment can realize various different computing model infrastructures, such as web services, distributed computing and grid computing infrastructures. 
     A computer program (also known as a program, software, software application, app, script, or code) can be written in any form of programming language, including compiled or interpreted languages, declarative or procedural languages, and it can be deployed in any form, including as a stand-alone program or as a circuit, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program can be stored (e.g., in the database  220 ) in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more circuits, subprograms, or portions of code). A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network. 
     While various implementations have been described and illustrated herein, those of ordinary skill in the art will readily envision a variety of other means or structures for performing the function or obtaining the results or one or more of the advantages described herein, and each of such variations or modifications is deemed to be within the scope of the inventive embodiments described herein. Parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, or configurations may depend upon the specific application or applications. 
     The above-described embodiments can be implemented in any of numerous ways. For example, the embodiments may be implemented using hardware, software or a combination thereof. When implemented in software, the software code can be executed on any suitable processor or collection of processors, whether provided in a single computer or distributed among multiple computers. 
     The implementations described herein can be embodied as a computer readable storage medium (or multiple computer readable storage media) (e.g., a computer memory, one or more floppy discs, compact discs, optical discs, magnetic tapes, flash memories, circuit configurations in Field Programmable Gate Arrays or other semiconductor devices, or other non-transitory medium or tangible computer storage medium) encoded with one or more programs that, when executed on one or more computers or other processors, perform methods that implement the various embodiments of the solution discussed above. The computer readable medium or media can be transportable, such that the program or programs stored thereon can be loaded onto one or more different computers or other processors to implement various aspects of the present solution as discussed above. 
     The terms “program” or “software” refer to any type of computer code or set of computer-executable instructions that can be employed to program a computer or other processor to implement various aspects of embodiments as discussed herein. Additionally, one or more computer programs that when executed perform operations described herein need not reside on a single computer or processor, but may be distributed in a modular fashion amongst a number of different computers or processors. 
     Data structures may be stored in computer-readable media in any suitable form. Data structures may be shown to have fields that are related through location in the data structure. Such relationships may likewise be achieved by assigning storage for the fields with locations in a computer-readable medium that convey relationship between the fields. However, pointers, tags or other mechanisms can be used to establish a relationship between information in fields of a data structure, or between data elements. 
     While operations are depicted in the drawings in a particular order, such operations are not required to be performed in the particular order shown or in sequential order, and all illustrated operations are not required to be performed. Actions described herein can be performed in a different order. 
     The separation of various system components does not require separation in all implementations, and the described program components can be included in a single hardware or software product. For example, the water column transit velocity generation module  210  or the depth value generation module  215  can be a single module, a logic device having one or more processing circuits, or part of one or more servers of the data processing system  205 . 
     Having now described some illustrative implementations, it is apparent that the foregoing is illustrative and not limiting, having been presented by way of example. In particular, although many of the examples presented herein involve specific combinations of method acts or system elements, those acts and those elements may be combined in other ways to accomplish the same objectives. Acts, elements and features discussed in connection with one implementation are not intended to be excluded from a similar role in other implementations or implementations. 
     The phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. The use of “including” “comprising” “having” “containing” “involving” “characterized by” “characterized in that” and variations thereof herein, is meant to encompass the items listed thereafter, equivalents thereof, and additional items, as well as alternate implementations consisting of the items listed thereafter exclusively. In one implementation, the systems and methods described herein consist of one, each combination of more than one, or all of the described elements, acts, or components. 
     Any references to implementations or elements or acts of the systems and methods herein referred to in the singular may also embrace implementations including a plurality of these elements, and any references in plural to any implementation or element or act herein may also embrace implementations including only a single element. References in the singular or plural form are not intended to limit the presently disclosed systems or methods, their components, acts, or elements to single or plural configurations. References to any act or element being based on any information, act or element may include implementations where the act or element is based at least in part on any information, act, or element. 
     Any implementation disclosed herein may be combined with any other implementation or embodiment, and references to “an implementation,” “some implementations,” “an alternate implementation,” “various implementations,” “one implementation” or the like are not necessarily mutually exclusive and are intended to indicate that a particular feature, structure, or characteristic described in connection with the implementation may be included in at least one implementation or embodiment. Such terms as used herein are not necessarily all referring to the same implementation. Any implementation may be combined with any other implementation, inclusively or exclusively, in any manner consistent with the aspects and implementations disclosed herein. 
     References to “or” may be construed as inclusive so that any terms described using “or” may indicate any of a single, more than one, and all of the described terms. References to “at least one” of a list of elements indicates an inclusive OR combination of the listed elements. 
     Where technical features in the drawings, detailed description or any claim are followed by reference signs, the reference signs have been included to increase the intelligibility of the drawings, detailed description, and claims. Accordingly, neither the reference signs nor their absence have any limiting effect on the scope of any claim elements. 
     The systems and methods described herein may be embodied in other specific forms without departing from the characteristics thereof. The foregoing implementations are illustrative rather than limiting of the described systems and methods. For example, the marine seismic surveys can include ocean, sea, lake, transit-zone, salt water, fresh water, or mixed water surveys. Scope of the systems and methods described herein is thus indicated by the appended claims, rather than the foregoing description, and changes that come within the meaning and range of equivalency of the claims are embraced therein.