Patent Publication Number: US-2023151732-A1

Title: Flowback monitoring system and methods

Description:
RELATED APPLICATIONS 
     This application claims priority to U.S. Application No. 63/264,017, filed Nov. 12, 2021, which is incorporated by reference in its entirety herein. 
    
    
     FIELD OF THE DISCLOSURE 
     The disclosure relates generally to the field of oil well flowback monitoring. More specifically, the disclosure relates to using computerized processes to increase efficiencies of the flowback monitoring process. 
     BRIEF SUMMARY OF INVENTION 
     The following presents a simplified summary of the invention in order to provide a basic understanding of some aspects of the invention. This summary is not an extensive overview of the invention. It is not intended to identify critical elements of the invention or to delineate the scope of the invention. Its sole purpose is to present some concepts of the invention in a simplified form as a prelude to the more detailed description that is presented elsewhere. 
     In some aspects, the embodiments described herein relate to a method of well flowback monitoring, the method including connecting a number of wells to a test separator and a commingle separator such that the number of wells are in selective fluid connection with the test separator and the commingle separator, wherein the number of wells is greater than one; monitoring the number of wells via the test separator and the commingle separator and a computing system, the monitoring the number of wells including: coupling a first well of the number of wells to the test separator, wherein the first well is solitarily coupled to the test separator; measuring a plurality of output values of the first well via the test separator for a first predetermined measurement period; recording and analyzing the plurality of output values of the first well via the computing system; coupling the first well to the commingle separator, wherein the first well is no longer in fluid connection with the test separator; coupling a second well of the number of wells to the test separator, wherein the second well is solitarily coupled to the test separator; measuring a plurality of output values of the second well with the test separator for a second predetermined measurement period; recording and analyzing the plurality of output values of the second well via the computing system; taking measurements via the commingle separator of a subset of the number of wells, the subset including the first well and not including the second well, the measurements relating to data associated with the subset of the number of wells; determining an interpolated value of the first well based on the plurality of output values of the first well; and using the interpolated value of the first well against the measurements relating to data associated with the subset of the number of wells to determine a percentage of a total of the measurements relating to the first well; wherein each well of the number of wells is rotated through the test separator for precise measuring of associated output values, the associated output values used to determine associated interpolated values for use with measurements taken via the commingle separator. 
     In some aspects, the embodiments described herein relate to a method, wherein the interpolated value is an average of the plurality of output values of the first well. 
     In some aspects, the embodiments described herein relate to a method, further including coupling the first well to the test separator for a second time, wherein the first well is solitarily coupled to the test separator; measuring a second plurality of output values of the first well via the test separator for a third predetermined measurement period; recording the second plurality of output values of the first well via the computing system; and updating the interpolated value of the first well based on the second plurality of output values. 
     In some aspects, the embodiments described herein relate to a method, further including modifying the interpolated value based on one or more predefined settings. 
     In some aspects, the embodiments described herein relate to a method, further including modifying the interpolated value in response to one or more operating conditions. 
     In some aspects, the embodiments described herein relate to a method, further including determining the one or more operating conditions through machine learning analysis of the computing system. 
     In some aspects, the embodiments described herein relate to a method, wherein the one or more operating conditions are user input. 
     In some aspects, the embodiments described herein relate to a method, wherein the plurality of output values of the first well and the plurality of output values of the second well are measurements selected from a group including a number of barrels of material flowing through the test separator; a pressure reading of material flowing through the test separator; a temperature reading of material flowing through the test separator; and a flow rate reading of material flowing through the test separator. 
     In some aspects, the embodiments described herein relate to a method, wherein the computing system is at least partially housed within one of the test separator and the commingle separator. 
     In some aspects, the embodiments described herein relate to a method, wherein the computing system is separate from the test separator and the commingle separator and is in remote data communication with the test separator and the commingle separator. 
     In some aspects, the embodiments described herein relate to a method, further including using a plurality of valves to selectively couple the number of wells with the test separator and the commingle separator. 
     In some aspects, the embodiments described herein relate to a method, further including connecting the number of wells with one or more storage tanks, the one or more storage tanks to receive material from the number of wells through the test separator and the commingle separator. 
     In some aspects, the embodiments described herein relate to a system for well flowback monitoring, the system including: a test separator; a commingle separator; a number of wells in selective fluid connection with both the test separator and the commingle separator, the number of wells is greater than one; a computing system in data communication with the test separator and the commingle separator, the computing system, test separator, and commingle separator monitor the number of wells; a plurality of output values of a first well of the number of wells as tested from the test separator for a predetermined measurement period, the plurality of output values tested while the first well is solitarily coupled to the test separator, and the plurality of output values of the first well recorded and analyzed via the computing system; a plurality of output values of a second well of the number of wells as tested from the test separator for a second predetermined measurement period, the plurality of output values tested while the second well is solitarily coupled to the test separator, and the plurality of output values of the second well recorded and analyzed via the computing system; a plurality of measurements taken from the commingle separator of a subset of the number of wells, the subset including the first well and not including the second well, the measurements relating to data associated with the subset of the number of wells; and an interpolated value of the first well based on the plurality of output values of the first well; wherein the interpolated value of the first well is used against the measurements relating to data associated with the subset of the number of wells to determine a percentage of a total of the measurements relating to the first well; and wherein each well of the number of wells is rotated through the test separator for precise measuring of associated output values, the associated output values used to determine associated interpolated values for use with measurements taken via the commingle separator. 
     In some aspects, the embodiments described herein relate to a system, wherein the interpolated value is an average of the plurality of output values of the first well. 
     In some aspects, the embodiments described herein relate to a system, further including a second plurality of output values of the first well as measured via the test separator for a third predetermined measurement period, as the first well is solitarily coupled to the test separator for a second time, the second plurality of output values recorded and analyzed via the computing system; wherein the second plurality of output values is used to update the interpolated value of the first well. 
     In some aspects, the embodiments described herein relate to a system, further including one or more predefined settings used to modify the interpolated value either through user input or through operation of the computing system. 
     In some aspects, the embodiments described herein relate to a system, wherein the interpolated value is modified in response to one or more operating conditions. 
     In some aspects, the embodiments described herein relate to a system, wherein the one or more operating conditions are determined through machine learning analysis of the computing system. 
     In some aspects, the embodiments described herein relate to a system, wherein the one or more operating conditions are user input. 
     In some aspects, the embodiments described herein relate to a system, wherein the plurality of output values of the first well and the plurality of output values of the second well are measurements selected from a group including a number of barrels of material flowing through the test separator; a pressure reading of material flowing through the test separator; a temperature reading of material flowing through the test separator; and a flow rate reading of material flowing through the test separator. 
     In some aspects, the embodiments described herein relate to a system, wherein the computing system is at least partially housed within one of the test separator and the commingle separator. 
     In some aspects, the embodiments described herein relate to a system, wherein the computing system is separate from the test separator and the commingle separator and in remote data communication with the test separator and the commingle separator. 
     In some aspects, the embodiments described herein relate to a system, further including a plurality of valves to selectively couple the number of wells with the test separator and the commingle separator. 
     In some aspects, the embodiments described herein relate to a system, further including a storage tank fluidly connected to the test separator and the commingle separator, the storage tank receives material from the number of wells through the test separator and the commingle separator. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
       Illustrative embodiments of the present disclosure are described in detail below with reference to the attached drawing figures. 
         FIG.  1    schematically shows an example flowback monitoring system, according to an embodiment. 
         FIGS.  2 A- 2 B  schematically shows a first and second operational step of the flowback monitoring system of  FIG.  1   . 
         FIG.  3    shows an example spreadsheet of data of the flowback monitoring system of  FIG.  1   . 
         FIG.  4    schematically shows a computing system for use with the flowback monitoring system of  FIG.  1   . 
         FIG.  5    shows a flowchart illustrating a method of using the flowback monitoring system of  FIG.  1   , according to an embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     Flowback systems and methods are known in the art. Typically, these flowback systems are used after a well bore (e.g., for drilling oil, natural gas, etc.) has been established. Establishing a well bore involves injecting proppants (e.g., sand) and other fluids such as water into the well to ready it for extraction of the hydrocarbons. Before the well site can be used for regular oil/natural gas production, these excess contaminants must first be extracted. Flowback devices such as separators (each of which may include a high-pressure separator and a low-pressure separator, as is known in the art) are used to extract this combination of oil, natural gas, water, and/or proppants until satisfactory amounts of water and proppants are removed from the well site. Regular oil/natural gas production may commence thereafter. The artisan understands that it is desirable to remove sand prior to entering a processing facility because sand is erosive, can damage equipment, and may create production losses. 
     A well site may comprise a plurality of wells. Conventionally, during flowback, each of these wells is associated with a separator device, where proppants, water, oil, and/or natural gas are separated and measured. Each well may produce different volumes and concentrations of each of these materials, and these amounts may vary over time. It is desirable to know these quantities since they may indicate the viability of each well (e.g., indicate when each well is ready for regular production by ensuring the initial flowrate is not unsuitably high and/or there is not an undue amount of sand that is being extracted). Thus, it is beneficial to monitor and measure the materials being extracted during flowback. 
     Monitoring the operations of each of these wells during flowback is no easy task. Typically, each of the separators associated with each of the wells is configured to measure the characteristics of the material (e.g., volume of each material, type of each material, flowrate of each material, temperature, pressure, etc.) collected from the well. Each well in the prior art is associated with a solitary separator during the flowback process as this one-to-one correspondence allows for data of each well to be easily captured using measurements taken at the separator associated with each individual well. This prior art practice of using one separator for each well may be costlier and less efficient than using one separator for multiple wells. If multiple wells are fluidly coupled to the same separator, it may become difficult to identify flowback data of each well. For this reason, the prior art maintains a different separator for each well. The present disclosure may allow for multiple wells to be selectively fluidly coupled to the same separator while allowing for data associated with each well to be determined or estimated with suitably high precision. Using fewer separators than there are wells may reduce the costs associated with the flowback process and improve the efficiency of the flowback process. 
       FIGS.  1  through  5    depict and illustrate the workings of a flowback monitoring system  100 , according to an example embodiment. As shown in  FIG.  1   , the flowback monitoring system  100 , in this example, includes a test separator  122 , a commingle separator  124 , one or more storage tanks  130 , and one or more computing systems  160  ( FIG.  4   ). As also shown in  FIG.  1   , the flowback monitoring system  100  having its two separators  122  and  124  is being used to monitor flowback of more than two wells  110  (i.e., well  110   a ,  110   b ,  110   c ,  110   d , and  110   n ). Well  110   n  indicates that the flowback of any number of wells may be monitored using the system  100 . Further, while  FIG.  1    shows two separators, teachings of the present disclosure are applicable to any system having X wells and Y separators where Y is less than X. The test separator  122  and the commingle separator  124  may collectively be referred to herein as separators  120 . 
     The system  100  may be used to implement embodiments of a method  200  ( FIG.  5   ), as detailed below. Each of the plurality of wells  110  is fluidly connected to the one or more storage tanks  130  via the plurality separators  120 . In operation, the wells  110  may be used to extract material (e.g., natural gas, oil, water, proppants, such as sand and inorganic materials, etc.) from underground, and deliver said material to the separators  120 . The separators  120  may process the received material by separating it into its individual components. The separators  120  may also monitor the processed material, such as measure an amount or volume of the material, identify the type of material, identify other characteristics of the material such as temperature and pressure, et cetera. Well Flowback rate may be controlled based on these characteristics in order to maximize production of hydrocarbons from the well. Once processed, the material may be routed to the one or more storage tanks  130 . Monitoring of these wells  110  using a number of separators that is less than the number of wells being monitored may be achieved in an embodiment by implementing the method  200 , as described in greater detail below. In embodiments, the number of separators  120  employed in the process may be related to the number of active wells  110  (e.g., two separators may be used for four wells, three separators may be used for 10 wells, et cetera). 
     Each of the plurality of wells  110  may comprise any suitable equipment now known or subsequently developed for extracting material, such as sand, other proppants, water, oil, natural gas, et cetera. The number of wells  110  used may be influenced by factors such as the amount of material to be extracted, size of the land that needs to be covered, size and characteristics of the reservoir, et cetera. Each of the wells  110  may be in selective communication with more than one of the plurality of separators  120 . For example, as depicted in  FIG.  1   , each of the wells  110  are selectively coupled to both the test separator  122  and the commingle separator  124  via valves  112  (i.e.,  112   a - 112   n ). As will become clear, each well  110   a - 110   n  will be fluidly coupled to only one of the test separator  122  and the commingle separator  124  at one time. The valves  112   a - 112   n  may allow for such selective fluid coupling to be effectuated (e.g., valve  112   a  may be placed in one position to fluidly couple the well  110   a  to the test separator  122  and may be placed in another position to fluidly couple the well  110   a  to the commingle separator  124 ). In some embodiments, the valves  112   a - 112   n  may be omitted and other means may be employed to switch each well  110   a - 110   n  from one separator to another as desired. 
     The separators  120  may comprise any suitable equipment now know or subsequently developed for receiving material, separating material, and measuring characteristics of the material extracted from the wells  110 . The separators  120  may be coupled to one or more storage tanks  130  such that the material processed by the separators  120  may be stored therein. In embodiments, the separators  120  may be configured to route different constituents of the extracted material to different storage tanks  130  (e.g., the separators  120  may route oil to one storage tank  130 , natural gas to another storage tank  130 , water and/or proppants to yet another storage tank  130 , et cetera). Alternately or additionally, the separators  120  may be configured to route one or more constituents directly to a sales line to a production facility. One or more of the separators  120  may have associated therewith a Human Machine Interface (HMI) (e.g., the test separator  122  may have an HMI  126   a  and the commingle separator  124  may have an HMI  126   b ). In operation, the HMIs  126   a ,  126   b  may house at least in part the computing system  160  and/or be communicatively coupled to the computing system  160 , and may allow a user to manipulate the operation and/or the settings of the system  100 , as will be described in greater detail below. The separators  120  may make use of one or more sensors  128  ( FIG.  4   ) to measure the characteristics of the extracted material, e.g., the pressure, temperature, flow rate, density, etc., thereof. 
     Each of the separators  120  may be fluidly coupled to one or more of the wells  110  as chosen by the operator and/or the computing system  160 . In embodiments, the test separator  122  may receive extracted material from only one well  110  at any given time, whereas the commingle separator  124  may receive the extracted material from multiple wells  110  (e.g., the remaining wells  110 ). 
     In operation, the wells  110  may be divided between the plurality of separators  120  for the processing of the material they extract. In embodiments, a single well  110  may correspond to the test separator  122 , while the remaining wells  110  may correspond to the commingle separator  124 . The wells  110  may be divided amongst the separators  120  via the valves  112 , which the artisan will understand to be any suitable device or combination of devices for selectively directing material from one location to one or more other locations (e.g., automated valves, semi-automatic valves, et cetera). For instance, the valve  112   a  may direct the well  110   a  to the test separator  122 , and the valves  112   b ,  112   c ,  112   d , and  112   n  may direct wells  110   b ,  110   c ,  110   d , and  110   n  to the commingle separator  124 , respectively. Because only a single well  110  routes material to the test separator  122  at any given time, measurements at the test separator  112  may provide actual, precise, data for that solitary well  110  in granular detail. For example, the test separator  122  may measure characteristics such as volume, flowrate, temperature, pressure, and type of material extracted from the well  110  fluidly coupled thereto. This data may be routed to the computing system  160 , where it may be stored and/or otherwise used, such as in the method  200 . The commingle separator  124  may gather the same kind of material data, but measurements taken at the commingle separator  124  may be associated with the collective output of all the wells  110  fluidly coupled to the commingle separator  124  at that time. The commingle separator  124  may not be able to determine what portion and/or characteristics of the extracted material originated from which of the wells  110 . For example, the commingle separator  124  may be accepting the output of four different wells  110 , and the commingle separator  124  may measure an extracted material volume of forty barrels of oil. In this situation, the commingle separator  124  may not be able to distinguish if all four wells  110  are producing ten barrels of oil each, or if one well  110  is producing more oil than another well  110 . As described, the prior art uses one-to-one correspondence between wells and separators for this reason. The present disclosure may allow for the outputs of each well to be characterized with reasonable certainty even where multiple wells are fluidly coupled to the same separator. 
     In  FIGS.  2 A and  2 B , exemplary diagrams depict two operational measurement periods of embodiments of the present disclosure. The measurement periods shown are time periods, however, an artisan will understand that alternative means, such as a number of data points, may be used instead. In  FIG.  2 A , a first time period  201  is shown, wherein one of the wells  110   a  is solitarily coupled to the test separator  122  while the remaining wells  110   b - n  are coupled to the commingle separator  124 . During the first time period  201 , a plurality of precisely accurate output values  203  for well  110   a  are collected, stored, and analyzed via the computer system  160 , the output values  203  used to establish one or more associated interpolated values  205  for well  110   a . Meanwhile, during the first time period  201 , the commingle separator collects collective measurements and data  207 , from the remaining wells, these measurements and data being general to all material flowing through the commingle separator  124  from wells  110   b - n.    
     As shown in  FIG.  2 B , during a second time period  209  (or other measurement period as would be understood), a second well  110   b  is switched to being solitarily coupled to the test separator  122 , while the remaining wells  110   a  and  110   c - n  are coupled to the commingle separator  124 . The test separator  122  collecting precise output values  211  for well  110   b  for generating an associated interpolated value  213  for well  110   b . During this second time period  209 , the commingle separator  124  will collect measurements and data  215  for the remaining wells  110   a  and  110   c - n . As the interpolated value  205  for well  110   a  was already established in the first time period  201 , this interpolated value  205  is then applied to the measurements and data  215  to determine a percentage of the totals that is associated with well  110   a . These measurement periods continue until all wells have been solitarily comingled to the test separator. Further, the process continues to repeat such that the interpolated value for each well may be updated as further data is collected. 
     In an embodiment, the system  100  may make use of the algorithm and/or machine learning processes described herein. In  FIG.  3   , a simplified exemplary output spreadsheet  301  is shown. Here, wells  110   a ,  110   b ,  110   c , and  110   d  are monitored using the test separator  122  and the common or commingle separator  124 . At any given time, the output of only one of the wells  110  is routed to the test separator  122 , while the output of the other wells  110  is collectively routed to the commingle separator  124 . After some period of time and/or a suitable amount of data is collected, the system  100  may use the valves  112  and the well  110  that is being handled by the test separator  122  may be rotated out with one of the wells  110  being routed to the commingle separator  124  (e.g., a well  110   a  that was fluidly coupled to the test separator  122  may be switched over to the commingle separator  124 , and a well  110   b  that was fluidly coupled to the commingle separator  124  may be switched over to the test separator  122 ). This may be accomplished by, for example, using valve  112   a  to switch output of well  110   a , and using valve  112   b  to switch output of well  110   b , to cause the latter to be fluidly coupled to the test separator  122  and the former to be fluidly coupled to the commingle separator  124 . The output of well  110   b  may be now measured using a separator that has a one-to-one correspondence with the well  110   b . In this way, after a period of time, each of the well  110  outputs may eventually be individually measured at the test separator  122 . As shown, the spreadsheet may organize measurements based on time periods  303 , which may be any time period an artisan may deem appropriate, such as measurements reported every hour, every day, or every minute, as examples. Further, while  FIG.  3    illustrates a spreadsheet  301  that illustrate the workings of the system  100  in connection with oil, the artisan will readily understand the teachings are likewise applicable to estimate other outputs (e.g., natural gas, water, et cetera). 
     As shown in  FIG.  3   , in embodiments, the data is divided into columns for Reported Rates  305 , Commingled Separator Measured Rate  307 , Test-Separator Measure Rates  309 , a Total  311 , Well Interpolated Rates  313 , Oil Rate Allocations  315 , and Well Mode  317 .  FIG.  3    shows well  110   a  as well A, well  110   b  as well B, well  110   c  as well C, and well  110   d  as well D. An artisan would understand the exact titles, and layout of data may vary. 
     Accordingly, the spreadsheet  301  may show the reported rates  305  organized by well, and as a total. The reported rates  305  will include a precisely measured rate for the well connected to the test separator  122  and interpolated measured rates for the remaining wells connected to the commingle separator  124  as determined via the well interpolated rates  313 . For example, when well  110   a  is connected to the test separator  122 , the value “X” will be the same as the value “Y” under the test separator measured rates  309 . Further, during time period  1 , the well mode  317  would indicate a “T” as associated with well  110   a . The remaining wells  110   b - d  being there identified with a “C” for indicating connection to the commingle separator  124 . 
     The reported rates  305  for wells  110   b - d  will be based off of the commingled separator measured rate  307  as analyzed via the well interpolated rates  313 . Here, the total  311  is the total of all wells, including the commingled separator measured rate  307  and the test separator measure rate  309 . And lastly, the oil rate allocations  315  will show a percentage of totals for each well. For example, when well  110   a  is coupled to the test separator  122 , the associated oil rate allocations  315  will be 100%. The remaining wells  110   b - d  being coupled to the commingle separator  124 , the associated oil rate allocations  315  for B, C, and D would sum to 100%. The oil rate allocations  315  further showing a percentage of the total commingled separator measured rate  307  for the remaining wells  110   b - d . These percentages may then be applied against the total measured value at the commingle separator  124  to calculate the portion of the measured total attributable to each of the wells  110   b ,  110   c , and  110   d    
     As each well  110   a - n  is solitarily coupled to the test separator  122 , the spreadsheet  301  will continue to gain data and the well interpolated rates  315  may further adapt to provide more accurate reported rates  305 . Because each well was coupled to the test separator  122  at a prior point in time, actual prior data for each well is available. This data of each well from the prior point in time may be used to interpolate the current data of each well fluidly coupled to the commingle separator  124 . 
     The interpolated value for a well  100  (e.g., well  110   b ) fluidly coupled to the commingle separator  124  may be determined by, for example, finding the average measured output for that well  110  while it was being directly measured by the test separator  122  for a period of time (e.g., four hours, six hours, et cetera). In some cases, as discussed herein, the interpolated value may be different than an average yield of the well while it was coupled to the test separator  122 . 
     Turning now to an example scenario, the interpolated values of wells  110   b ,  110   c , and  110   d  for rows  1  through  4  are twenty, twenty-one, and twenty-three barrels, respectively. These values were all interpolated from actual data (i.e., data that was previously obtained while each of these wells  110   b ,  110   c , and  11   d  were coupled to the test separator  122 ). The total interpolated value of these three wells  110  is equal to sixty-four barrels (i.e., 20+21+23=64). With this total interpolated value, the percentage or ratio of the total that is made up by each of the wells  110  may be found. In this case, wells  110   b ,  110   c , and  110   d  make up 31.25%, 32.81%, and 35.94%, respectively, of the total interpolated value. These percentages may then be applied against the total measured value at the commingle separator  124  to calculate the portion of the measured total attributable to each of the wells  110   b ,  110   c , and  110   d . In row  1  of the spreadsheet  301 , this would result in wells  110   b ,  110   c , and  110   d  providing 20.31, 21.33, and 23.36 barrels of oil, respectively, of an example measured total of sixty-five barrels. Thus, for the first row of  FIG.  2 A , the reported values for wells  110   a ,  110   b ,  110   c , and  11   d  may come out to be 15.00 (as measured),  20 . 31  (as interpolated), 21.33 (as interpolated), and 23.36 (as interpolated) barrels of oil, respectively. This process may be repeated as many times as desired. For example, the process may be carried out another three times while well  110   a  is fluidly connected to the test separator  122 . 
     After a suitable amount of data is collected (e.g., after four hourly data points), the system  100  may use the valves  112  to rotate out the well coupled to the test separator  122 . In this example, at row  5  of the spreadsheet  301 , well  110   b  may be switched to the test separator  122 , and well  110   a  may be switched to the commingle separator  124  (together with wells  110   c  and  110   d  which were already fluidly coupled to the commingle separator  124 ). This may be accomplished by, for example, using valve  112   a  to switch output of well  110   a , and using valve  112   b  to switch output of well  110   b , to cause the latter to be fluidly coupled to the test separator  122  and the former to be fluidly coupled to the commingle separator  124 . The output of well  110   b  may be now measured using a separator that has a one-to-one correspondence with the well  110   b . Using the data collected in rows one through four when well  110   a  was fluidly coupled to the test separator  122 , the output value for well  110   a  may be interpolated. In this case, example measured values of fifteen, ten, twelve, and ten may be averaged (or otherwise computed, as discussed herein) to yield an interpolated value of 11 barrels for well A at the example time (row  5 ). The output values of each of the wells  110  may then be determined using the techniques described above, using the newly measured data of well  110   b  and the interpolated values of well  110   a.    
     This process may be continually repeated. Each of the wells  110  may periodically (or after varying intervals of time) be fluidly coupled to the test separator  122  so that actual measurements of these wells are taken, and subsequently, the actual measurements of each well may be used to interpolate the output of that well when that well is coupled to the commingle separator  124 . 
     It will readily be understood by an artisan that spreadsheet  301  is merely exemplary; in other embodiments, other means of data presentation may be used, varying time periods or other means may be used. The amount of data points used for each cycle, or period before the test separator  122  switches to another well  110 , may be user selected and/or determined by the computing system  160 . For example, each cycle may last three data points, four data points, six data points, ten data points, twenty-four data points, etc., and may even be changed during system  100  operation. 
     While the interpolated value used in  FIG.  3    may be a direct average of the previously measured cycle of values for a given well, other embodiments may employ different methods to find the interpolated value. For instance, any suitable type of interpolation method may be used to arrive at the interpolated value using the data measured at the test separator  122 . In some embodiments, the interpolation value may be biased by user and/or computing system  160  selected settings. For instance, the direction and/or magnitude of rounding numbers may be modified. As another example, the computing system  160  may be configured to recognize a trend of the data and modify the final interpolated value accordingly. For example, in an instance where actual measured values of well  110   a  are fifteen, ten, twelve, and ten the computing system  160  may have recognized that the values measured were fifteen, ten, twelve, and ten, and recognized that the output of well  110   a  was trending downwards. In response, the computing system  160  may modify the interpolated value of 11.75 (average) down to eleven since, over the course of the next several cycles of data points, it would be likely that the observed trend would continue and well  110   a  may output less than an average of 11.75 barrels during that time. In embodiments, however, averaging of the well output while it was coupled to the test separator  122  may be a primary (or at least one) mechanism employed for interpolation. 
     In some embodiments, the interpolated value may be modified (e.g., by the computing system  160 ) in response to and based on a recognized operating condition. For example, if well  110   a  is being measured by the test separator  122 , and wells  110   b ,  110   c , and  110   d  are being collectively measured by the commingle separator  124  and the measured values for well  110   a  for a time period are zero, zero, two, six, five, six, seven, and seven barrels of oil. This averages out to a value of 4.13, however, a value of seven is chosen as the interpolated value of well  110   a  after its cycle is complete and the test separator  122  begins measuring well  110   b . The interpolated value may be modified to seven in this case because the computing system  160  may recognize that well  110   a  is in a “startup” condition and therefore sharply trending upwards. In response to a determination of this startup condition, the computing system  160  may modify the interpolation value found by truncating the data set measured to eliminate the low flow values, by selecting the largest or last data point measured, et cetera. Other methods of modifying the interpolated values found in response to various operating conditions are contemplated herein and part of the disclosure, such as modifying interpolated values in light of detected blockage conditions, over-pressured conditions, wind-down conditions, user input, et cetera. 
     Using the above-described techniques and their embodiments, a plurality of wells  110  may be accurately monitored using a plurality (e.g., a relatively smaller plurality) of separators  120 . The artisan may recognize that any suitable number of wells  110  may be used with any suitable number of separators  120 , so long as at least one test separator  122  is used to periodically (or after irregular intervals of time) measure the output of each well on a one-to-one basis. In embodiments, the test separator  122  and commingle separator  124  may be functionally identical (i.e., the commingle separator may be converted to a test separator by fluidly coupling a solitary well thereto). In embodiments, and depending on the number of wells, multiple test separators and/or commingle separators may be employed. While barrels of oil are used as the data point in exemplary embodiments herein, it is to be understood that other values and materials may likewise be employed. For example, alternately or in addition, pressure, temperature, and/or flow rate may be used. The artisan would also understand that while these techniques, methods, and systems are illustrated using oil, these same techniques, systems, and methods may be applied towards monitoring other materials, such as water, proppants (e.g., sand), and/or natural gas. 
       FIG.  4    is a functional block diagram of the computing system  160  which may be used to implement the various flowback monitoring system embodiments and methods according to the different aspects of the present disclosure. The computing system  160  may be, for example, a smartphone, a laptop computer, a desktop computer, a flexible circuit board, or other computing device whether now known or subsequently developed. In embodiments, the computing system is housed at least in part within one or more of the separators  120 ; in other embodiments, the computing system is remote from the separators  120  and in data communication therewith. The computing system  160  comprises a processor  162 , the memory  164 , a communication module  166 , and a dataport  168 . These components may be communicatively coupled together by an interconnect bus  169 . A user may interact with the computing system  160  via the HMIs  126   a ,  126   b  located at the separators  120 , for example. The artisan will understand the HMIs  126   a ,  126   b  may comprise input and output devices, e.g., a touch screen, a keyboard, a display, et cetera. 
     The processor  162  may include any processor used in smartphones and/or other computing devices, including an analog processor (e.g., a Nano carbon-based processor) or a digital processor. In certain embodiments, the processor  162  may include one or more other processors, such as one or more microprocessors, and/or one or more supplementary co-processors, such as math co-processors. 
     The memory  164  may include both operating memory, such as random access memory (RAM), as well as data storage, such as read-only memory (ROM), hard drives, optical, flash memory, or any other suitable memory/storage element. The memory  164  may include removable memory elements, such as a CompactFlash card, a MultiMediaCard (MMC), and/or a Secure Digital (SD) card. In certain embodiments, the memory  164  includes a combination of magnetic, optical, and/or semiconductor memory, and may include, for example, RAM, ROM, flash drive, and/or a hard disk or drive. The processor  162  and the memory  164  each may be located entirely within a single device, or may be connected to each other by a communication medium, such as a USB port, a serial port cable, a coaxial cable, an Ethernet-type cable, a telephone line, a radio frequency transceiver, or other similar wireless or wired medium or combination of the foregoing. For example, the processor  162  may be connected to the memory  164  via the dataport  168 . 
     The communication module  166  may be configured to handle communication links between the computing system  160  and other external devices or receivers, and to route incoming/outgoing data appropriately. For example, inbound data from the dataport  168  may be routed through the communication module  166  before being directed to the processor  162 , and outbound data from the processor  162  may be routed through the communication module  166  before being directed to the dataport  168 . The communication module  166  may include one or more transceiver modules configured for transmitting and receiving data, and using, for example, one or more protocols and/or technologies, such as GSM, UMTS (3GSM), IS-95 (CDMA one), IS-2000 (CDMA 2000), LTE, FDMA, TDMA, W-CDMA, CDMA, OFDMA, Wi-Fi, WiMAX, 5G, or any other protocol and/or technology. 
     The dataport  168  may be any type of connector used for physically interfacing with a smartphone, computer, and/or other devices, such as a mini-USB port or an IPHONE®/IPOD® 30-pin connector or LIGHTNING® connector. In other embodiments, the dataport  168  may include multiple communication channels for simultaneous communication with, for example, other processors, servers, and/or client terminals. 
     The memory  164  may store instructions for communicating with other systems, such as a computer. The memory  164  may store, for example, a program (e.g., computer program code) adapted to direct the processor  162  in accordance with the embodiments described herein. The instructions also may include program elements, such as an operating system. While execution of sequences of instructions in the program causes the processor  162  to perform the process steps described herein, hard-wired circuitry may be used in place of, or in combination with, software/firmware instructions for implementation of the processes of the present embodiments. Thus, unless expressly noted, the present embodiments are not limited to any specific combination of hardware and software. 
     In embodiments, the memory  164  includes software  161 . The software  161  may contain machine-readable instructions configured to be executed by the processor  162 . The software  161  may, for example, process data obtained from the sensor  128 . In embodiments, the software  161  may cause the computing system  160  to dynamically respond to a reading obtained by the sensor  128 . For example, the software  161  may direct the valves  112  to close in response to a sensor  128  determination that dangerous operating conditions are present. As another example, the software  161  may direct the valves  112  to switch which of the wells  110  is connected to the test separator  122  and which of the wells  110  are connected to the commingle separator  124 . 
     In embodiments, the memory  164  may contain a machine learning system or program configured to carry out one or more of the techniques and methods described herein. As an example, a machine learning program may be used by the computing system  160  to recognize various operating conditions of the system  100 , and to formulate a response to said detections (e.g., by modifying the interpolated value calculated from the measured data set). The machine learning analysis may be provided on behalf of any number of machine learning algorithms and trained models, including but not limited to deep learning models (also known as deep machine learning, or hierarchical models) that have been trained to perform image recognition tasks. Machine learning is used to refer to the various classes of artificial intelligence algorithms and algorithm-driven approaches that are capable of performing machine-driven (e.g., computer-aided) identification of trained structures, and deep learning is used to refer to a multiple-level operation of such machine learning algorithms using multiple levels of representation and abstraction. The artisan will understand that the role of the machine learning algorithms that are applied, used, and configured as described may be supplemented or substituted by any number of other algorithm-based approaches, including variations of artificial neural networks, learning-capable algorithms, trainable object classifications, and other artificial intelligence processing techniques. 
     The computing system  160  may be in data communication with a remote storage  30  over a network  20 . The network  20  may be a wired network, a wireless network, or comprise elements of both. In embodiments, the network  20  may communicatively link one or more components of the flowback monitoring system  100 . For example, the sensor  128  may be communicatively linked to the computing system  160  via the network  20  for the exchange of information therebetween. The remote storage  30  may be, for example, the “cloud” or other remote storage in communication with other computing systems. In embodiments, data (e.g., readings obtained by the sensors  128  and the separators  120 , and the dynamic responses of the computing system  160  thereto) may be stored in the remote storage  30  for analytics. 
       FIG.  5    is a flowchart depicting a method  200  of operating the flowback monitoring system  100 , in an example embodiment. First, at step  202 , well  110  outputs may be measured using the separators  120 . For example, the output of one well  110  may be directly measured at test separator  122 , while the total output of the other wells  110  may be measured at the commingle separator  124 . Next, at step  204 , interpolated values of the wells (interpolated as described herein) may be used, along with the measurements of the commingle separator  124 , to calculate the contribution ratio of each well to the commingle separator  124 . Then, at step  206 , the calculated ratios may be applied against the actual measured collective total at the commingle separator  124  to estimate the individual output of each of the comingled wells  110 . At step  208 , each of the well  110  output values found may be reported (e.g., to a client, to a database, et cetera). 
     Once a cycle is complete, or at an otherwise determined point of time, the valves  112  may be used to switch which well  110  is feeding its output to the test separator  122 , at step  210 . In operation, one well  110  may transfer from the test separator  122  to the commingle separator  124 , while a different well  110  may generally simultaneously transfer from the commingle separator  124  to the test separator  122 . Then, at step  212 , an interpolated value for the well  110  which was previously coupled to the test separator  122  is determined. This value may be found as described above, such as through interpolation methods (e.g., smart linear averaging). At step  214 , the determined interpolated value found in step  212  may be modified. For example, the computing system  160  may recognize an operating condition (e.g., a startup condition), and modify the interpolated value from step  212  in response. 
     Each of the steps  202  through  208  may be repeated as many times as desired to complete a “cycle.” For instance, steps  202  through  208  may be repeated four times, as shown in  FIG.  2 A , to complete a cycle before initiating step  210 . Likewise, steps  210  through  214  may be repeated as many times as desired. For example,  FIG.  2 A  shows a scenario where steps  210  through  214  are executed five times, once after each cycle of steps  202  through  208  are completed. 
     It is to be understood that the steps of the method  200  need not be carried out in the exact order as described, that some steps may occur simultaneously with other steps, that some steps may be optional, and that each of these combinations of carrying out the method  200  are within the scope of the present disclosure. For example, the step of modifying the interpolated value in response to a detected operating condition (e.g., step  214 ) may be skipped where no operating condition is detected. As another example, one or more wells  110  may be offline when the method  200  is started, and thus the method  200  may be modified to accommodate additional wells. 
     As mentioned above, using the flowback monitoring system  100  to deliver extraction information to a user may advantageously avoid some or all of the issues normally associated with operating a plurality of flowback wells. For instance, the number of separators required to operate the plurality of wells may be reduced. In other words, cost and logistical complications may be minimized because there may be less separators than there are wells. 
     While flowback well applications were primarily used herein to provide context for the various flowback monitoring system functions, the artisan would understand that the systems  100  disclosed herein may be adapted to other suitable application functions, and that such adaptions are within the scope of the present disclosure. 
     The artisan will understand that the flowback monitoring system  100  disclosed herein may include or have associated therewith electronics (e.g., the computing system  160 , the sensors  128 , et cetera). The electronics may be used to control and modify the operation of the flowback monitoring system  160  (e.g., to change the timing of the system  100 , to turn the system  100  on and off, to dynamically control the system  100  in response to a sensor  128 /separator  120  detection, et cetera). In some example embodiments, the processor or processors may be configured through particularly configured hardware, such as an application specific integrated circuit (ASIC), field-programmable gate array (FPGA), etc., and/or through execution of software to allow the diving tank apparatus  100  to function in accordance with the disclosure herein. 
     Many different arrangements of the various components depicted, as well as components not shown, are possible without departing from the spirit and scope of the present disclosure. Embodiments of the present disclosure have been described with the intent to be illustrative rather than restrictive. Alternative embodiments will become apparent to those skilled in the art that do not depart from its scope. A skilled artisan may develop alternative means of implementing the aforementioned improvements without departing from the scope of the present disclosure.