Abstract:
A downhole fluid testing system includes a downhole acquisition tool housing configured to be moved into a wellbore, where the wellbore contains fluid that comprises a native reservoir fluid of a geological formation and a contaminant. The system includes a pump to pump fluid through the downhole acquisition tool, a sensor configured to analyze portions of the fluid and obtain a fluid property the fluid from an optical spectrometer, including an optical density, and a controller coupled to the housing to receive a first plurality of measurements over time from the sensor, estimate a future saturation pressure of the fluid at specific time increments via a processor based in part on the first plurality of measurements and a saturation pressure model, and control a flow rate of the pump that causes the flow line pressure to remain above the estimated future saturation pressure plus a value of the associated uncertainty.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
       [0001]    This application claims the benefit of U.S. Patent Application No. 62/315,801 filed on Mar. 31, 2016, which application is expressly incorporated herein by this reference in its entirety. 
     
    
     BACKGROUND 
       [0002]    This disclosure relates to generally to oil and gas exploration systems and, more particularly, to systems and methods for estimating saturation pressure by sampling formation fluids. 
         [0003]    This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present techniques, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light. 
         [0004]    Wells are generally drilled into a surface (land-based) location or ocean bed to recover natural deposits of oil and natural gas, as well as other natural resources that are trapped in geological formations. A well may be drilled using a drill bit attached to the lower end of a “drill string,” which includes a drill pipe, a bottom hole assembly, and other components that facilitate turning the drill bit to create a borehole. Drilling fluid, or “mud,” is pumped down through the drill string to the drill bit during a drilling operation. The drilling fluid lubricates and cools the drill bit, and it carries drill cuttings back to the surface through an annulus between the drill string and the borehole wall. 
         [0005]    For oil and gas exploration, it may be desirable to have information about the subsurface formations that are penetrated by a borehole. More specifically, this may include determining characteristics of fluids stored in the subsurface formations. As used herein, fluid is meant to describe any substance that flows. Fluids stored in the subsurface formations may include formation fluids, such as natural gas or oil. Thus, a fluid sample representative of the formation fluid maybe taken by a downhole tool and analyzed. As used herein, a representative fluid sample is intended to describe a sample that has relatively similar characteristics (e.g., composition and state) to the formation fluid to facilitate determining characteristics of the formation fluid. 
       SUMMARY 
       [0006]    A summary of certain embodiments disclosed herein is set forth below. It should be understood that these aspects are presented merely to provide the reader with a brief summary of these certain embodiments and that these aspects are not intended to limit the scope of this disclosure. Indeed, this disclosure may encompass a variety of aspects that may not be set forth below. 
         [0007]    In a first embodiment, a downhole fluid testing system includes a downhole acquisition tool housing configured to be moved into a wellbore, where the wellbore contains fluid that comprises a native reservoir fluid of a geological formation and a contaminant. The system includes a pump to pump fluid through the downhole acquisition tool, an optical spectrometer comprising at least one sensor. The optical spectrometer is configured to receive a first plurality of measurements output by the at least one sensor and to analyze portions of the fluid to obtain a fluid property of the fluid, including an optical density. The system includes a controller comprising memory circuitry and processing circuitry, where the controller is coupled to the housing to receive the first plurality of measurements over time from the at least one sensor, estimate a future saturation pressure of the fluid and a value of an associated uncertainty within the flow line at specific time increments via the processing circuitry based in part on the first plurality of measurements and a saturation pressure model, and control a flow rate of the pump that causes the flow line pressure to remain above the estimated future saturation pressure plus the value of the associated uncertainty. 
         [0008]    In another embodiment, a downhole fluid testing system, includes a downhole acquisition tool housing configured to be moved into a wellbore in a geological formation, wherein the wellbore or the geological formation, or both, contain fluid that comprises a native reservoir fluid of the geological formation and a contaminant. The system includes a pump configured to pump fluid through the downhole acquisition tool, an optical spectrometer comprising at least one sensor disposed in the downhole acquisition tool housing. The optical spectrometer is configured to receive a first plurality of measurements output by the at least one sensor and to analyze portions of the fluid and obtain a fluid property of the fluid, where the fluid property includes an optical density. The system includes a controller communicatively coupled to a surface level of the housing and the controller is configured to receive the first plurality of measurements over time from the at least one sensor. The controller is configured to estimate a future saturation pressure of the fluid and a value of an associated uncertainty within the flow line at specific time increments via the processing circuitry based at least in part on the first plurality of measurements and a saturation pressure model, and to control a flow rate of the pump that causes the flow line pressure to remain above the estimated future saturation pressure plus the value of the associated uncertainty. 
         [0009]    In a further embodiment, a method includes pumping fluid from outside of a downhole tool through a flow line of the downhole tool with a pump, taking a first plurality of measurements over time using at least one sensor and estimating a future saturation pressure of the fluid within the flow line and a value of its uncertainty at defined time increments via a downhole controller based at least in part on the first plurality of measurements and a first saturation pressure model. The method includes adjusting the flow line pressure to maintain the pressure of the flow line above the estimated future saturation pressure, and using a surface controller at the surface to estimate the future saturation pressure when the flow line pressure goes below a saturation pressure of the flow line, based at least upon the first plurality of measurements and a second saturation pressure model. 
         [0010]    Various refinements of the features noted above may be undertaken in relation to various aspects of the present disclosure. Further features may also be incorporated in these various aspects as well. These refinements and additional features may exist individually or in any combination. For instance, various features discussed below in relation to one or more of the illustrated embodiments may be incorporated into any of the above-described aspects of the present disclosure alone or in any combination. The brief summary presented above is intended to familiarize the reader with certain aspects and contexts of embodiments of the present disclosure without limitation to the claimed subject matter. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0011]    Various aspects of this disclosure may be better understood upon reading the following detailed description and upon reference to the drawings in which: 
           [0012]      FIG. 1  is a schematic diagram of a drilling system including a downhole tool used to sample formation fluid, in accordance with an embodiment of the present techniques; 
           [0013]      FIG. 2  is a schematic diagram of a wireline system including a downhole tool used to sample formation fluid, in accordance with an embodiment of the present techniques; 
           [0014]      FIG. 3  is a schematic diagram of the downhole tool of  FIG. 2  used to determine formation fluid properties, in accordance with an embodiment of the present techniques; 
           [0015]      FIG. 4  is a process flow diagram of a method for controlling a pump in a downhole tool, in accordance with an embodiment of the present techniques; 
           [0016]      FIG. 5  is a plot illustrative of several characteristics of a sample fluid while a sampling-while-drilling operation is performed while a constant flow line pressure is maintained; 
           [0017]      FIG. 6  is a plot illustrative of several characteristics of a sample fluid while a sampling-while-drilling operation is performed while the flow line pressure is controlled, in accordance with an embodiment of the present techniques; 
           [0018]      FIG. 7  is a plot representative of contamination level as a function of pumping time with constant flow line pressure versus controlled flow line pressure, in accordance with an embodiment of the present techniques; 
           [0019]      FIG. 8  is a plot representative of measured saturation pressure versus estimated saturation pressure determined from a saturation pressure model, in accordance with an embodiment of the pressure techniques; 
           [0020]      FIG. 9  is a graphical representation of measured saturation pressure versus estimated saturation pressure determined from the saturation pressure model, in accordance with an embodiment of the pressure techniques; 
           [0021]      FIG. 10  is a flow diagram of a workflow of a pump control system in accordance with an embodiment of the present techniques; 
           [0022]      FIG. 11  is a flow diagram of an initialization phase used to obtain information about the flow line fluid; 
           [0023]      FIG. 12  is a flow diagram of a method for downhole tool control in accordance with an embodiment of the present techniques; 
           [0024]      FIG. 13  is a flow diagram of a method for uphole tool control in accordance with an embodiment of the present techniques; and 
           [0025]      FIG. 14  is a flow diagram of a method for transitioning between downhole tool control and uphole tool control in accordance with an embodiment of the present techniques. 
       
    
    
     DETAILED DESCRIPTION 
       [0026]    One or more specific embodiments of the present disclosure will be described below. These described embodiments are examples of the presently disclosed techniques. Additionally, in an effort to provide a concise description of these embodiments, features of an actual implementation may not be described in the specification. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions can be made to achieve the developers&#39; specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure. 
         [0027]    When introducing elements of various embodiments of the present disclosure, the articles “a,” “an,” and “the” are intended to mean that there are one or more of the elements. The terms “comprising,” “including,” and “having” are intended to be inclusive and mean that there may be additional elements other than the listed elements. Additionally, it should be understood that references to “one embodiment” or “an embodiment” of the present disclosure are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features. 
         [0028]    Embodiments of this disclosure relate to operating a pump in a downhole tool to capture a fluid sample representative of a formation fluid. This disclosure generally relates to operating a pump in a downhole tool to capture a fluid sample representative of a formation fluid. During oil or natural gas exploration, it may be desirable to measure and/or evaluate the properties of the formations surrounding a borehole. For example, this may include capturing and evaluating a sample of fluid trapped in the formations, which may be referred to as formation fluid. When capturing such a sample, it is desirable that the sample be representative of the formation fluid. More specifically, the sample may have a similar composition and state as the formation fluid. However, in many drilling operations, drilling fluid (e.g., drilling mud) is often pumped into the borehole to facilitate drilling. As the drilling mud is cycled through the drilling process, the filtrate of drilling fluid may seep into the formations and mix with (e.g., contaminate) the formation fluid close to the borehole. In addition, in many fluid sampling operations, a pump is used to pump surrounding fluid into a downhole tool. More specifically, the pump may reduce the pressure in the downhole tool below the pressure in the formation (e.g., formation pressure). Depending on the composition of fluid pumped into the downhole tool, the reduction in pressure may cause a state change (e.g., release of gas, liquid, asphaltene, or the like) if the pressure is reduced below a saturation pressure (e.g., dew point pressure, bubble point pressure, asphaltene onset pressure, or the like). As used herein, the saturation pressure refers to a threshold pressure under an isothermal condition that may cause a state change such as a dew point pressure for a gas (e.g., natural gas), a bubble point pressure for a liquid (e.g., oil), an asphaltene onset pressure for a liquid (e.g., oil), or the like. 
         [0029]    Traditional techniques may capture a contaminated fluid sample (e.g., containing an appreciable amount of drilling fluid filtrate) in a controlled volume and decrease the pressure in the controlled volume to determine the saturation pressure of the contaminated fluid sample. The determined saturation pressure may then be used in a pump equation to determine a pumping rate designed to avoid dropping the pressure in the downhole tool below the saturation pressure. However, these features may be inefficient. For example, because space in a downhole tool is limited, the additional controlled volume capable of decreasing pressure utilized by these techniques may occupy space in the tool that could be used for other purposes. Furthermore, because the properties (e.g., contamination level) of the fluid pumped into a downhole tool may change, a pumping rate determined at one time during pumping may be inaccurate if used at a later time when the contamination level may have changed. For example, when the contamination level and the saturation pressure are high, the pump may be controlled to pump faster than the determined pumping rate obtained from some other contamination level while maintaining the pressure in the downhole tool greater than the saturation pressure. Thus, it may be desirable to provide techniques for operating a pump in a downhole tool to facilitate efficient sampling of the formation fluid when the contamination level and saturation pressure of fluid in the flow line changes during pumping. 
         [0030]    Accordingly, the present disclosure includes a system and method for operating a pump in a downhole tool to capture a fluid sample representative of the formation fluid. More specifically, the present techniques may include: pumping fluid from outside of the downhole tool through a flow line of the downhole tool, taking a measurements within the flow line while pumping the fluid using at least one sensor, estimating a saturation pressure of the fluid with the processor based at least in part on the measurements taken in the flow line and a saturation pressure model, and adjusting an operating parameter of a pump with a controller to maintain pressure in the flow line greater than the estimated saturation pressure. In other words, the saturation pressure of the fluid may be estimated directly from measurements, such as optical density, taken while the fluid is being pumped through the flow line of the downhole tool. For example, in some embodiments, an optical spectrometer may be used to measure the optical density of the fluid in the flow line across several wavelengths. The optical density measurements may be used to obtain compositional information to be employed to model the saturation pressure. In certain embodiments, the optical density measurements may be directly input into the saturation pressure model to provide estimates of saturation pressure. The estimated saturation pressures may then be employed to control the pump to maximize the pumping rate while maintaining the pressure in the flow line greater than the estimated saturation pressure. In certain embodiments, the estimated saturation pressure can be adjusted by a corrective parameter to estimate a future saturation pressure if the flow line pressure goes below the bubble point of the fluid. 
         [0031]    By way of introduction,  FIG. 1  illustrates a drilling system  10  used to drill a well through subsurface formations  12 . A drilling rig  14  at the surface  16  is used to rotate a drill string  18  that includes a drill bit  20  at its lower end. As the drill bit  20  is rotated, a drilling fluid pump  22  is used to pump drilling fluid, commonly referred to as “mud” or “drilling mud,” downward through the center of the drill string  18  in the direction of the arrow  24  to the drill bit  20 . The drilling fluid, which is used to cool and lubricate the drill bit  20 , exits the drill string  18  through ports (not shown) in the drill bit  20 . The drilling fluid then carries drill cuttings away from the bottom of a borehole  26  as it flows back to the surface  16 , as shown by the arrows  28  through an annulus  30  between the drill string  18  and the formation  12 . However, as described above, as the drilling fluid flows through the annulus  30  between the drill string  18  and the formation  12 , the drilling mud may begin to invade and mix with the fluids stored in the formation, which may be referred to as formation fluid (e.g., natural gas or oil). At the surface  16 , the return drilling fluid is filtered and conveyed back to a mud pit  32  for reuse. 
         [0032]    Furthermore, as illustrated in  FIG. 1 , the lower end of the drill string  18  includes a bottom-hole assembly  34  that may include the drill bit  20  along with various downhole tools (e.g., modules). For example, as depicted, the bottom-hole assembly  34  includes a measuring-while-drilling (MWD) tool  36  and a logging-while-drilling (LWD) tool  38 . The various downhole tools (e.g., MWD tool  36  and LWD tool  38 ) may include various logging tools, measurement tools, sensors, devices, formation evaluation tools, fluid analysis tools, fluid sample devices, and the like to facilitate determining characteristics of the surrounding formation  12  such as the properties of the formation fluid. For example, the LWD tool  38  may include a fluid analysis tool (e.g., an optical spectrometer  39 ) to measure light transmission of the fluid in the flow line, a processor  40  to process the measurements, and memory  42  to store the measurements and/or computer instructions for processing the measurements. 
         [0033]    As used herein, a “processor” or processing circuitry refers to any number of processor components related to the downhole tool (e.g., LWD tool  38 ). For example, in some embodiments, the processor  40  may include one or more processors disposed within the LWD tool  38 . In other embodiments, the processor  40  may include one or more processors disposed within the downhole tool (e.g., LWD tool  38  ) communicatively coupled with one or more processors in surface equipment (e.g., control and data acquisition unit  44  ). Thus, any desirable combination of processors may be considered part of the processor  40  in the following discussion. Similar terminology is applied with respect to the other processors described herein, such as other downhole processors or processors disposed in other surface equipment. 
         [0034]    In addition, the LWD tool  38  may be communicatively coupled to a control and data acquisition unit 44 or other similar surface equipment. More specifically, via mud pulse telemetry system (not shown), the LWD tool  38  may transmit measurements taken or characteristics determined to the control and data acquisition unit  44  for further processing. Additionally, in some embodiments, this may include wireless communication between the LWD tool  38  and the control and data acquisition unit  44 . Accordingly, the control and data acquisition unit  44  may include a processor  46 , memory  48 , and a wireless unit  50 . 
         [0035]    In addition to being included in the drilling system  10 , various downhole tools (e.g., wireline tools) may also be included in a wireline system  52 , as depicted in  FIG. 2 . As depicted, the wireline system  52  includes a wireline assembly  54  suspended in the borehole  26  and coupled to the control and data acquisition unit  44  via a cable  56 . Similar to the bottom-hole assembly  34 , various downhole tools (e.g., wireline tools) may be included in the wireline assembly  54 . For example, as depicted, the wireline assembly  54  includes a telemetry tool  58  and a formation testing tool  60 . In some embodiments, the formation testing tool  60  may take measurements and communicate the measurements to the telemetry tool  58  to determine characteristics of the formation  12 . For example, similar to the LWD tool  38 , the formation testing tool  60  may include a fluid analysis tool (e.g., an optical spectrometer  39 ) to measure light transmission of fluid in the flow line, and the telemetry tool  58  may include a processor  62  to process the measurements and memory  64  to store the measurements and/or computer instructions for processing the measurements. Thus, in some embodiments, the telemetry tool  58  may be included in the formation testing tool  60 . The formation testing tool  60  may be communicatively coupled to the control and data acquisition unit  44  and transmit measurements taken or characteristics determined to the control and data acquisition unit  44  for further processing. 
         [0036]    In other embodiments, features illustrated in  FIGS. 1 and 2  may be employed in a different manner. For example, various downhole tools may also be conveyed into a borehole via other conveyance methods, such as coil tubing or wired drill pipe. For example, a coil tubing system may be similar to the wireline system  52  with the cable  56  replaced with a coiled tube as a method of conveyance, which may facilitate pushing the downhole tool further down the borehole  26 . 
         [0037]    As described above, to facilitate determining characteristics of the formations  12  surrounding the borehole  26 , samples of fluid representative of the formation fluid may be taken. More specifically, the samples may be gathered by various downhole tools such as the LWD tool  38 , a wireline tool (e.g., formation sampling tool  60 ), a coil tubing tool, or the like. To help illustrate, a schematic of the wireline assembly  54 , including the formation sampling tool  60 , is depicted in  FIG. 3 . It should be appreciated that the techniques described herein may also be applied to LWD tools and coil tubing tools. 
         [0038]    To begin sampling the fluids in the formation  12  surrounding the formation sampling tool  60 , the formation sampling tool  60  may engage the formation in various manners. For example, in some embodiments, the formation sampling tool  60  may extend a probe  66  to contact the formation  12 , and formation fluid may be withdrawn into the sampling tool  60  through the probe  66 . In other embodiments, the formation sampling tool  60  may inflate packers  68  to isolate a section of the formation  12  and withdraw fluid into the formation  12  through an opening in the sampling tool between the packers. In a further embodiment, a single packer may be inflated to contact the formation  12 , and fluid from the formation may be drawn into the sampling tool  60  through an inlet (e.g., a drain) in the single packer. 
         [0039]    Once the formation sampling tool  60  has engaged the formation  12 , a pump  70  may extract fluid from the formation by decreasing the pressure in a flow line  72  of the formation sampling tool  60 . As described above, when the pump  70  initially begins to extract fluid from the surrounding formation  12 , the extracted fluid may be contaminated (e.g., contain an appreciable amount of drilling fluid filtrate) and be unrepresentative of the formation fluid. Accordingly, the pump  70  may continue to extract fluid from the formation  12  until it is determined that a representative fluid sample (e.g., single-phase with minimal contamination) may be captured. Various methods are known to determine the contamination level of the fluid in the flow line  72 . One such method is based on analyzing optical spectrometer data, and is described in more detail in U.S. Pat. No. 8,024,125 entitled “Methods and Apparatus to Monitor Contamination Levels in a Formation Fluid,” which is incorporated herein by reference. For example, in certain embodiments, the contamination level may be monitored using a trend model that compares optical densities of the formation fluid at different wavelengths. During the initial pumping process, the pump  70  may expel the extracted fluid back into the annulus  30  at a different location (not shown) from the sample point (e.g., the location of the probe  66 ). A representative fluid sample may be captured in sample bottles  74  in the formation sampling tool  60  when a minimum contamination level is achieved. 
         [0040]    As depicted in  FIG. 3 , the formation sampling tool  60  also includes a fluid analysis tool  75 . The fluid analysis tool  75  may take various measurements on fluid flowing through the flow line  72 , such as optical density or ultrasonic transmission. For example, the fluid analysis tool  75  may be an optical spectrometer  39  that takes optical density measurements by measuring light transmission of fluid as it is pumped through the flow line  72 . In some embodiments, the optical spectrometer  39  may take a plurality of measurements by measuring light transmission across multiple wavelengths. Accordingly, the fluid analysis tool  75  (e.g., optical spectrometer  39 ) may include a light emitter or source  76  and a light detector or sensor  77  disposed on opposite sides of the flow line  72 . More specifically, the fluid analysis tool  75  may determine the proportion of light transmitted through the fluid and detected by the light sensor  77 . 
         [0041]    Furthermore, as described above, the decrease of pressure in the flow line  72  while extracting fluid from the formation  12  and pumping the fluid through the flow line may cause the fluid to drop below its saturation pressure (e.g., dew point, bubble point, or asphaltene onset). For example, when the pressure in the flow line  72  is dropped below a dew point pressure of a gas (e.g., natural gas), liquid droplets may begin to form. Similarly, when the pressure in the flow line  72  is dropped below a bubble point of a liquid (e.g., oil), gas may be released. As will be described in more detail below, such phase changes and their onset may be detected and determined by the fluid analysis tool  75 . For example, as bubbles begin to form in a liquid (e.g., oil), the fluid analysis tool  75  (e.g., optical spectrometer  39 ) may determine the bubble point of the liquid because the bubbles scatter light and cause light transmission to sharply decrease. 
         [0042]    To facilitate obtaining a representative sample (e.g., single phase and low contamination) of the formation fluid, it is desirable to control the pump  70  to maintain the pressure in the flow line  72  greater than the saturation pressure of fluid in the flow line  72  when the sample is taken. Accordingly, a process  80  for controlling the pump  70  during a sampling process is depicted in  FIG. 4 . 
         [0043]    As will be described in more detail below, the process  80  includes positioning a downhole acquisition tool in a wellbore (process block  82 ). The formation fluid is pumped from outside of the downhole acquisition tool through a flow line of the downhole acquisition tool (process block  84 ) so that the formation fluid properties can be examined. Measurements of the fluid in the flow line can be taken (process block  86 ) to determine certain properties of the fluid and the composition of the fluid in the flow line. Using a saturation pressure model and the properties of the fluid measured, an estimated future saturation pressure can be calculated (process block  88 ). The pressure of the flow line may be adjusted to maintain the pressure of the flow line above the estimated future saturation pressure (process block  90 ). 
         [0044]    An example of the improved contamination level by using the saturation pressure model is illustrated in  FIGS. 5-6  by way of comparison. Specifically,  FIG. 5  illustrates a sampling-while-drilling operation while a constant flow line pressure is maintained. The topmost plot illustrates measured optical density over numerous channels on the Y-axis versus time on the X-axis in minutes (block  92 ). The second plot illustrates an estimated gas to oil ratio, with gas to oil ratio measured in standard cubic feet per stock tank barrel on the Y-axis versus time on the X-axis (block  94 ). The third plot illustrates an estimated saturation pressure while the flow line pressure is controlled, where pressure in psi is on the Y-axis versus time on the X-axis (block  96 ). For example, the flow line pressure is controlled at or approximately 5,750 psi in the example. The fourth plot illustrates an estimated contamination level (block  98 ) in volume percent on the Y-axis and time on the X-axis. The fifth plot illustrates a flowrate and accumulated pumped volume versus simulated pumping time on the X-axis (block  100 ).  FIG. 6  illustrates a sampling-while-drilling operation while the flow line pressure is controlled based on a future estimated saturation pressure plus the associated uncertainty. Here again, the topmost plot illustrates measured optical density over numerous channels on the Y-axis versus time on the X-axis in minutes (block  102 ). The second plot illustrates an estimated gas to oil ratio with gas to oil ratio measured in standard cubic feet per stock tank barrel on the Y-axis versus time on the X-axis (block  104 ). The third plot illustrates an estimated saturation pressure while the flow line pressure is controlled to be above the future estimated saturation pressure plus the uncertainty of the future estimated saturation pressure, using the techniques described herein (block  106 ). The flow line pressure is measured in psi is on the Y-axis versus time on the X-axis. The fourth figure illustrates an estimated contamination level in volume percent on the Y-axis and time on the X-axis (block  108 ). The fifth plot illustrates a flowrate and accumulated pumped volume as a function of simulated pumping time (block  110 ). 
         [0045]    As will be appreciated, a higher flowrate may be reached in the early pumping stages when the flow line pressure is controlled to be above the future estimated saturation pressure and its uncertainty (see  FIG. 6 ) when compared to maintaining a substantially constant flow line pressure (see  FIG. 5 ). As such, the contamination level can be reduced faster when the flow line pressure is maintained to be above the future estimated saturation pressure plus the uncertainty by using the saturation pressure model described herein. Accordingly, the pump operating time is reduced when the saturation pressure model is used to maintain the flow line pressure above the future estimated saturation pressure plus the uncertainty. Put another way, a greater reduction in contamination level can be achieved during a definitive operation time (e.g., during the same amount of operating time). The reduction in time to achieve a desired contamination level is further illustrated in  FIG. 7 . 
         [0046]      FIG. 7  is a plot representative of contamination level as a function of pumping time with constant flow line pressure versus controlled flow line pressure. The contamination level is shown on the Y-axis, and the pumping time is shown on the X-axis. As illustrated, the contamination level when the flow line pressure is controlled using the saturation pressure model, the fluid reaches a lower contamination level in a shorter station time (e.g., line  112 ). For example, a desired reduction in contamination level can be achieved in approximately 160 minutes when the flow line pressure is controlled using the saturation pressure model (e.g., line  112 ). With constant flow line pressure (e.g., without use of the saturation pressure model, line  114 ), the same desired reduction in contamination level is achieved in over 300 minutes. 
       Estimated Future Saturation Pressure Model 
       [0047]    As described above, controlling the flow line pressure by using the saturation pressure model (e.g., the estimated future saturation pressure model) as described herein can reduce the contamination level faster than when the flow line pressure is maintained at or around substantially constant pressure. Controlling the flow line pressure through the saturation pressure model includes maintaining the flow line pressure to be above the future estimated saturation pressure plus the uncertainty. Using the saturation pressure model results in reduced pump operating time to achieve a desired reduction (e.g., target) contamination level. 
         [0048]    As described in detail below, the saturation pressure model uses optical spectrometer data acquired during sampling operations. The saturation pressure model may utilize a variety of different computational methodologies, including but not limited to, multivariate analysis, artificial neural networks, Bayesian networks, support vector machines, and so forth. 
         [0049]    In a first example, the saturation pressure model may be estimated by multivariate analyses. By way of example, a linear regression model including second order terms as described below can be used for estimated the saturation pressure of the flow line fluid: 
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         [0000]    where, ƒ is the estimated saturation pressure from temperature, T, and compositional inputs, {x i }. Coefficients, a i  and b ij , are calibrated against a fluid library. Uncertainty of the estimate derived from the variability of the coefficients is also obtained as the variance of estimate as set forth below: 
         [0000]      Δƒ model   2 =var(ƒ input )= X  cov( W ) X   T    (2)
 
         [0000]      where, X=[T, T 2 , x i , x i x j ], W=[a T ,b T ,a i , b ij ], i,j∈CO 2 ,C 1 ,C 2 ,C 3 ,C 4 ,C 5 ,C 6+ 
 
         [0050]    An expected value of W can be obtained using a resampling technique, such as through using subsets of available data or drawing randomly with replacement from a set of data points (e.g., bootstrapping). The expected value of the coefficients is utilized in eq. (1) and therefore, the estimate from eq. (1) is the expected value of the saturation pressure. The uncertainty associated with the temperature and the estimate of the composition obtained by means of optical spectrometry can be determined using the following equation: 
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                         ∑ 
                         k 
                       
                        
                       
                         
                           ∑ 
                           l 
                         
                          
                         
                           
                             
                               ∂ 
                               f 
                             
                             
                               ∂ 
                               
                                 X 
                                 k 
                               
                             
                           
                            
                           
                             
                               ∂ 
                               f 
                             
                             
                               ∂ 
                               
                                 X 
                                 l 
                               
                             
                           
                            
                           Δ 
                            
                           
                               
                           
                            
                           
                             X 
                             k 
                           
                            
                           Δ 
                            
                           
                               
                           
                            
                           
                             X 
                             l 
                           
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   3 
                   ) 
                 
               
             
           
         
       
     
         [0000]    where, ΔX k  denotes uncertainty of the inputs. Consequently, the uncertainty of the estimate combined eq. (2) and (3) is represented as follows: 
         [0000]      Δƒ 2 =Δƒ model   2 +Δ input   2    (4)
 
         [0051]    In a second example, the saturation pressure may be estimated by using an artificial neural network (ANN) based model. In this example, the ANN is based on eight input variable including Temperature (7), weight fraction of CO 2 , C 1 , C 2 , C 3 , C 4 , C 5 , and C 6 . In this example, the eight input variables were validated against the saturation pressures of a portion (e.g., 70%) of randomly selected samples in a fluid library and validated against the remaining (e.g., 30%) of the samples in the fluid library. The input variables were connected to a hidden layer (e.g., system layers) by nine nodes with weights and biases. In the hidden layer, sigmoidal functions were employed as the activation function. This ANN is represented using an equation as set forth below: 
         [0000]    
       
         
           
             
               
                 
                   
                     
                       f 
                        
                       
                         ( 
                         X 
                         ) 
                       
                     
                     = 
                     
                       
                         ∑ 
                         j 
                       
                        
                       
                         
                           w 
                           j 
                           
                             ( 
                             1 
                             ) 
                           
                         
                          
                         
                           
                             g 
                             j 
                           
                           ( 
                           
                             
                               ∑ 
                               i 
                             
                              
                             
                               
                                 w 
                                 ij 
                                 
                                   ( 
                                   0 
                                   ) 
                                 
                               
                                
                               
                                 x 
                                 i 
                               
                             
                           
                           ) 
                         
                          
                         
                           ( 
                           
                             
                               i 
                               ≤ 
                               8 
                             
                             , 
                             
                               j 
                               ≤ 
                               9 
                             
                           
                           ) 
                         
                       
                     
                   
                   , 
                   
                     
 
                   
                    
                   
                     
                       where 
                        
                       
                           
                       
                        
                       
                         g 
                          
                         
                           ( 
                           t 
                           ) 
                         
                       
                     
                     = 
                     
                       2 
                       
                         1 
                         + 
                         
                           e 
                           
                             - 
                             t 
                           
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   5 
                   ) 
                 
               
             
           
         
       
     
         [0052]    Note that the biases (b) in the hidden and the output layers are, respectively, absorbed into the weights, w (0)  and w (1) . Using the ANN saturation pressure model described above, the estimation results calculated from the ANN saturation pressure model can be compared. Turning now to  FIG. 8 , the bubble point estimation of a fluid as estimated from the ANN saturation pressure model is plotted on the Y-axis in psi against the bubble points calculated from laboratory analysis in psi on the X-axis. Using the ANN saturation pressure model, a standard deviation of approximately 170 psi between the estimated bubble point and the laboratory analyzed can be observed. 
         [0053]    The uncertainty is derived based on variability of weights in the neural networks. However, variability of weights in the hidden layer is not considered, and the variability is assumed to be absorbed into the variability of weights in the output layer. Consequently, the uncertainty of the prediction originated from the neural network model is approximately given: 
         [0000]      Δƒ 2 ≈g cov(w (1) )g T    (6)
 
         [0054]    In a similar manner on the multivariate model (e.g., first example) described above, uncertainty originated from estimated composition is also obtained. To adjust for uncertainty, a parameter, a, is introduced and applied to weight fraction of C 6+  (x C6+ ) which is one of the inputs to the model, as set forth below: 
         [0000]      x C6+ →(1+α)x C6+    (7)
 
         [0055]    This adjustment implies to tune molecular weight of C 6+  component (MW C6− ). As the summation of the components in weight fraction should be equal to one, inputs of weight fraction should be normalized by the summation after the tuning parameter is applied, thus: 
         [0000]    
       
         
           
             
               
                 
                   
                     
                       x 
                       i 
                     
                     → 
                     
                       
                         x 
                         i 
                       
                       
                         
                           
                             ∑ 
                             i 
                           
                            
                           
                             x 
                             i 
                           
                         
                         + 
                         
                           
                             ( 
                             
                               1 
                               + 
                               α 
                             
                             ) 
                           
                            
                           
                             x 
                             
                               
                                 C 
                                  
                                 
                                     
                                 
                                  
                                 6 
                               
                               + 
                             
                           
                         
                       
                     
                   
                   , 
                   
                     
 
                   
                    
                   
                     
                       x 
                       
                         
                           C 
                            
                           
                               
                           
                            
                           6 
                         
                         + 
                       
                     
                     → 
                     
                       
                         
                           ( 
                           
                             1 
                             + 
                             α 
                           
                           ) 
                         
                          
                         
                           x 
                           
                             
                               C 
                                
                               
                                   
                               
                                
                               6 
                             
                             + 
                           
                         
                       
                       
                         
                           
                             ∑ 
                             i 
                           
                            
                           
                             x 
                             i 
                           
                         
                         + 
                         
                           
                             ( 
                             
                               1 
                               + 
                               α 
                             
                             ) 
                           
                            
                           
                             x 
                             
                               
                                 C 
                                  
                                 
                                     
                                 
                                  
                                 6 
                               
                               + 
                             
                           
                         
                       
                     
                   
                   , 
                   
                     
 
                   
                    
                   
                     i 
                     ∈ 
                     
                       CO 
                       2 
                     
                   
                   , 
                   
                     C 
                     1 
                   
                   , 
                   
                     C 
                     2 
                   
                   , 
                   
                     C 
                     3 
                   
                   , 
                   
                     C 
                     4 
                   
                   , 
                   
                     C 
                     5 
                   
                 
               
               
                 
                   ( 
                   8 
                   ) 
                 
               
             
           
         
       
     
         [0056]    When bubbles start emerged and light scattering is observed at time, t, the saturation pressure of the flow line fluid, P sat (t), should be nearly equal to the flow line pressure, P FL (t). 
         [0000]      P sat (t)≈P FL (t)   (9)
 
         [0057]    The parameter, α, is to be adjusted to be satisfied: 
         [0000]      α′=arg min α   {P   FL (t)− {tilde over (P)}   sat ( t, X (α))}(0&lt;α&lt;1)   (10)
 
         [0058]    Where α′ is the adjusted parameter, {tilde over (P)} sat  is the estimated saturation pressure at time, t, and X (α) is the input to the model with the adjustment parameter, α, as set forth below: 
         [0000]    
       
         
           
             
               
                 
                   
                     X 
                      
                     
                       ( 
                       α 
                       ) 
                     
                   
                   = 
                   
                     
                       [ 
                       
                         T 
                         , 
                         
                           x 
                           i 
                           ′ 
                         
                         , 
                         
                           x 
                           
                             
                               C 
                                
                               
                                   
                               
                                
                               6 
                             
                             + 
                           
                           ′ 
                         
                       
                       ] 
                     
                      
                     
                         
                     
                      
                     
                       ( 
                       
                         
                           i 
                           ∈ 
                           
                             CO 
                             2 
                           
                         
                         , 
                         
                           C 
                           1 
                         
                         , 
                         
                           C 
                           2 
                         
                         , 
                         
                           C 
                           3 
                         
                         , 
                         
                           C 
                           4 
                         
                         , 
                         
                           C 
                           5 
                         
                       
                       ] 
                     
                   
                 
               
               
                 
                   ( 
                   11 
                   ) 
                 
               
             
             
               
                 
                   
                     
                       x 
                       i 
                       ′ 
                     
                     = 
                     
                       
                         x 
                         i 
                       
                       
                         
                           
                             ∑ 
                             i 
                           
                            
                           
                             x 
                             i 
                           
                         
                         + 
                         
                           
                             ( 
                             
                               1 
                               + 
                               α 
                             
                             ) 
                           
                            
                           
                             x 
                             
                               
                                 C 
                                  
                                 
                                     
                                 
                                  
                                 6 
                               
                               + 
                             
                           
                         
                       
                     
                   
                   , 
                   
                     
 
                   
                    
                   
                     
                       x 
                       
                         
                           C 
                            
                           
                               
                           
                            
                           6 
                         
                         + 
                       
                       ′ 
                     
                     → 
                     
                       
                         
                           ( 
                           
                             1 
                             + 
                             α 
                           
                           ) 
                         
                          
                         
                           x 
                           
                             
                               C 
                                
                               
                                   
                               
                                
                               6 
                             
                             + 
                           
                         
                       
                       
                         
                           
                             ∑ 
                             i 
                           
                            
                           
                             x 
                             i 
                           
                         
                         + 
                         
                           
                             ( 
                             
                               1 
                               + 
                               α 
                             
                             ) 
                           
                            
                           
                             x 
                             
                               
                                 C 
                                  
                                 
                                     
                                 
                                  
                                 6 
                               
                               + 
                             
                           
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   12 
                   ) 
                 
               
             
           
         
       
     
         [0059]    An example of estimating the saturation pressure using the saturation pressure model with and without the adjustment parameter, α, is set forth below in  FIG. 9 .  FIG. 9  is a graphical representation of measured saturation pressure versus estimated saturation pressure determined from a saturation pressure model, with and without tuning the model. The adjustment parameter was developed to enable the estimated saturation pressure to approach (e.g., get close) to the laboratory measured saturation pressure. In one example, the parameter, a, was adjusted based on the saturation pressure at 7.2% contaminated crude oil. Here, the estimated saturation pressure before the adjustment is ˜5246 psi in comparison with 5750 psi measured by a PVT laboratory. 
         [0060]    Using the adjusted parameter, the saturation pressure of same crude oil (but at a different contamination level) was estimated. Before the adjustment the estimated saturation pressure is ˜5520 psi in comparison with ˜6110 psi laboratory measure saturation pressure. After the adjustment, the saturation pressure of 0.6% contaminated crude oil is estimated to be 5924 psi with the adjusted parameter, which is obtained from the 7.2% contaminated crude oil. Accordingly, adjusting the estimated saturation pressure with the adjustment parameter, α, results in an improved (e.g., more accurate) estimate of saturation pressure of the sample. 
       Flow Line Pressure Control Model 
       [0061]      FIG. 10  is a flow diagram of a workflow of a pump control system in accordance with an embodiment of the present techniques. Optical density data at specified wavelength channels can be acquired almost continuously (block  110 ). For example, the optical density data may be obtained at approximately 2 Hz, 4 Hz, 6 Hz, and so forth. Once the optical density data is obtained, the pump control system determines whether or not light scattering is observed (block  112 ). The optical density data should indicate light scattering if the flow line pressure is below the saturation pressure of the fluid present in the flow line. The scattering may be detected using the technique described in U.S. application Ser. No. 13/693782, “Scattering Detection from Downhole Optical Spectra,” which is assigned to Schlumberger Technology Corporation and is incorporated by reference herein in its entirety for all purposes. If no indication of the light scattering is observed, the composition of the flow line fluid and its uncertainty are estimated, and the saturation pressure (Psat) and its uncertainty (dPsat) are estimated (block  114 ). 
         [0062]    If the optical density data indicates crossing below the saturation pressure, the estimated composition by the adjustment parameter, α, in eq. (8) (block  116 ). The adjustment parameter, α, uses the most recent valid estimated composition and assumes the saturation pressure is nearly equal to the flow line pressure (block  118 ). An adjustment to the is made to the saturation pressure model by including the obtained parameter, α, for the following saturation pressure estimations as long as the value is valid (e.g., until the next parameter adjustment, block  120 ). If the estimated saturation pressure is valid, the estimated saturation pressure is fed into the pressure control system (e.g., pump control model, block  122 ) to maintain the flow line pressure above the saturation pressure plus a value of its uncertainty. This process is continued until the sampling operation is complete at the sampling station. One example of the pressure control system is described in U.S. Pat. No. 9,115,567, “Method and Apparatus for Determining Efficiency of a Sampling Tool,” which is assigned to Schlumberger Technology Corporation and is incorporated by reference herein in its entirety for all purposes. 
         [0063]      FIG. 11  is a flow diagram of an initialization phase used to obtain information about the flow line fluid. The initialization phase may use (e.g., acquire) initial values of the formation fluid pressure and the mobility of the flow line to begin. Once the initialization phase begins, a pump may be started at a relatively low (e.g., ˜1 cm 3 /s) pump flow rate (block  130 ). During the initialization phase, a minimum pump flow volume may be set to maintain a desired pump flow rate. For example, the minimum pump flow volume may be set to greater than 1 pump out module (POM) stroke. After the minimum pump flow volume is set, optical densities of the fluid may be obtained (block  134 ). Using the techniques described above with respect to  FIG. 10 , a determination is made whether the fluid remains above the saturation pressure or whether the fluid has gone below the saturation pressure (block  136 ). 
         [0064]    If the optical density data acquired and techniques described herein indicated that the fluid has gone below the saturation pressure, the saturation pressure model is recalibrated (block  138 ). The saturation pressure model uses the most recent valid estimated composition to recalibrate. Once the saturation pressure model is re-calibrated, the saturation pressure model again computes the estimated saturation pressure of the flow line fluid and the saturation pressure of the flow line fluid (block  140 ). Then, the saturation pressure model commands the pump flow rate to pump fluid at a rate such that the pressure of the flow line fluid in the probe (e.g., downhole tool) remains greater than the estimated saturation pressure plus the uncertainty (block  142 ). If the fluid has stayed above the saturation pressure, the initialization phase is complete (block  144 ). The initialization phase may be followed by downhole tool control and/or uphole tool control as described below with respect to  FIGS. 12 and 13 . 
         [0065]      FIG. 12  is a flow diagram of a method for downhole tool control in accordance with an embodiment of the present techniques. The downhole tool control may generally be started upon completion of the initialization phase, or when initialized by an operator or controller. The method of downhole tool control described herein computes mobility from the last full pump stroke (block  150 ). Computing mobility of the flow line fluid may provide data to enable the controller or operator to assess the resistance of mobility of the flow line fluid and other factors affecting the fluid sampling. The method of downhole tool control includes using a previous estimate of the saturation pressure and its uncertainty to extrapolate to the next time interval (e.g., 15 seconds, 60 seconds) to calculate a future saturation pressure and its uncertainty (block  152 ). The method of downhole tool control includes controlling the pump flow rate such that the pressure of the fluid in the probe (e.g., downhole tool) remains greater than the estimated saturation pressure at the next time interval, plus the uncertainty (block  154 ). The method of downhole tool control includes acquiring optical density data (block  156 ) to determine whether the flow line fluid has stayed above the saturation pressure or whether the flow line fluid has gone below the saturation pressure (block  158 ). 
         [0066]    If the flow line fluid has gone below the saturation pressure, the method of downhole tool control includes recalibrating the saturation pressure model (e.g., the first saturation pressure model) (block  160 ). The saturation pressure model uses the most recent valid estimated composition to recalibrate. Once the saturation pressure model is re-calibrated, the saturation pressure model again computes the estimated saturation pressure of the flow line fluid and the saturation pressure of the flow line fluid (block  162 ). Then, the saturation pressure model commands the pump flow rate to pump flow line fluid at a rate such that the pressure of the flow line fluid in probe (e.g., downhole tool) remains greater than the estimated saturation pressure plus the uncertainty (block  164 ). The method of downhole tool control includes storing the results of the data (block  166 ). For example, the data stored may include data indicating the estimated saturation pressure of the flow line fluid dropped below the saturation pressure, the saturation pressure of the flow line at certain time intervals, other sample data, or any combination thereof. The method of downhole tool control includes sending the event message (e.g., indication of the saturation pressure of the flow line fluid dropping below the estimated saturation pressure plus its uncertainty of the flow line fluid) to the surface for reporting (block  168 ). The method of downhole tool control includes generating a progress report for transmission of the event message to the surface (block  170 ). The method of downhole tool control includes storing the results to generate the progress report (block  176 ). An operator or controller may take control of the downhole tool from the surface at any time during the method described herein. For example, an operator may wish to manually control the downhole tool from the surface upon receiving notice of an event message. 
         [0067]    If the pressure of the flow line fluid has remained above the saturation pressure, the method of downhole tool control includes continuing to compute the composition of the flow line fluid (block  172 ). The method of downhole tool control includes continuing to compute the saturation pressure and the estimated saturation pressure plus its uncertainty at the next time interval (block  174 ). The method of downhole tool control includes storing data such as the saturation pressure and estimated saturation pressure and its uncertainty (block  176 ). 
         [0068]      FIG. 13  is a flow diagram of a method for uphole tool control in accordance with an embodiment of the present techniques. The uphole tool control may generally be started upon completion of the initialization phase, or when initialized by an operator or controller. The method of uphole tool control described herein computes mobility from the last full pump stroke (block  180 ). Computing mobility of the flow line fluid may provide data to enable the controller or operator to assess the resistance of mobility of the flow line fluid and other factors affecting the fluid sampling. The method of uphole tool control includes using a previous estimate of the saturation pressure and its uncertainty to extrapolate to the next time interval (e.g., 4.5 minutes) to calculate future saturation pressure and its uncertainty at the next time interval (block  182 ). The method of uphole tool control includes controlling the pump flow rate such that the pressure of the flow line fluid in the probe (e.g., downhole tool) remains greater than the estimated saturation pressure plus the uncertainty at the next time interval (block  184 ). The method of uphole tool control includes analyzing optical density data (block  186 ) to determine whether the pressure of the flow line fluid has remained above the saturation pressure or whether the pressure of the flow line fluid has gone below the saturation pressure (block  188 ). 
         [0069]    If the pressure of the flow line fluid has gone below the saturation pressure, the method of uphole tool control includes recalibrating the saturation pressure model (e.g., the second saturation pressure model) (block  190 ). The saturation pressure model uses the most recent valid estimated composition to recalibrate. Once the saturation pressure model is re-calibrated, the saturation pressure model again computes the estimated saturation pressure of the flow line fluid and the saturation pressure of the flow line fluid (block  192 ). Then, the saturation pressure model commands the pump flow rate to pump fluid at a rate such that the pressure of the flow line fluid in the probe (e.g., downhole tool) remains greater than the estimated saturation pressure plus the uncertainty (block  194 ). 
         [0070]    If the flow line fluid has remained above the saturation pressure, the method of uphole tool control includes determining if the operator or controller will attempt to control the pressure of the flow line from the surface (block  196 ). If the operator or controller determines no surface control will be utilized, the flow line may be controlled using the downhole control methods described herein with respect to  FIG. 12 . If the operator or controller determines surface control will be utilized, the method of uphole tool control includes analyzing a next transmitted composition (block  198 ). The method of uphole tool control includes computing the saturation pressure and the estimated saturation pressure at the next time interval (block  200 ). The method of uphole tool control includes storing data from the computed saturation pressure and estimated saturation pressure (block  202 ). The stored data may be used to re-calibrate the surface saturation pressure model in the event that the saturation pressure of the flow line fluid drops below the estimated saturation pressure plus its uncertainty. 
         [0071]      FIG. 14  is a flow diagram of a method for transitioning between downhole tool control and uphole tool control in accordance with an embodiment of the present techniques. The method  210  includes pumping a fluid from outside the downhole tool through a flow line of the downhole tool with a pump (block  212 ). The method  210  includes taking a first plurality of measurements over time using one or more sensors (block  214 ). The method  210  includes estimating a future saturation pressure of the fluid within the flow line at defined time increments with a downhole tool controller based at least in part on the first plurality of measurements and a first saturation pressure model (block  216 ). The method  210  includes adjusting the flow line pressure to maintain the pressure of the flow line above the estimated future saturation pressure and its uncertainty (block  218 ). The method  210  includes using a surface controller to estimate the future saturation pressure when the flow line pressure goes below a current saturation pressure of the flow line, based at least in part on the first plurality of measurements and a second saturation pressure model (block  220 ). 
         [0072]    The specific embodiments described above have been shown by way of example, and it should be understood that these embodiments may be susceptible to various modifications and alternative forms. It should be further understood that the claims are not intended to be limited to the particular forms disclosed, but rather to cover modifications, equivalents, and alternatives falling within the spirit and scope of this disclosure.