Abstract:
Methods and systems for controlling processes related to the amount of fluid in a container subjected to externally-excited motions. Fluid level sensor measurements in processing tanks on-board boats are confused by ocean waves and swells. A hydrodynamic model of a fluid in a tank can be constructed using non-linear dynamic model algorithms with inputs such as multi-axis accelerations, fluid viscosity, and apparent level measurements. The model can be used to filter-out boat motion disturbances to obtain a corrected level of the fluid in the tank. The corrected fluid level signal can be further processed using a dynamic model of the tank and associated input and output flow rates in a closed loop observer. The methods and systems are especially advantageous for offshore equipment such as cementing and fracturing ships.

Description:
BACKGROUND AND SUMMARY OF THE INVENTION 
   The present application relates to systems and methods for process control, and more particularly to control of processes related to the amount of fluid in a container subject to externally-excited motions, and most especially to control of processes such as storing and blending of fluids and solids when such processes are conducted aboard a waterborne apparatus. 
   The following paragraphs contain some discussion, which is illuminated by the innovations disclosed in this Application, and any discussion of actual or proposed or possible approaches in these paragraphs does not imply that those approaches are prior art. 
   Background: Process Control of Fluid Level 
   Modern hydrocarbon production and processing systems use automated equipment in many aspects of their operations. A key element of such automated operations is the process control system. Such control systems usually include sensors, which in one important function, send a signal back to a process control unit. The signal is usually a communication of a process variable or condition, such as temperature, pressure, fluid or solid flow rate, or fluid level in a container. The process control unit can perform such functions as monitoring the system or unit operations or process variables, making process decisions, energizing and de-energizing equipment, collecting and maintaining data, providing stability to the overall system, and, very importantly, ensuring the system and the unit operations comprising the system operate within desired parameters. 
   Sensors are often placed at specific locations within a production or processing system to provide information necessary for the control of various unit operations. The role of the sensor includes providing accurate and real-time information about a particular process variable or set of variables such that the process control unit can make decisions based on good and accurate information. 
   As an example of the needs and challenges in the accurate sensing and control of processes in the production of hydrocarbons, consider the process of “completing” an off-shore hydrocarbon well-bore. Such work is usually managed and done aboard “service ships,” including the cementing of the well-bore. 
   After drilling of an oil or gas well-bore is finished, the well-bore is “cemented” under carefully-controlled conditions. The first step is to run a steel casing into the well-bore, followed by pumping cement into the annulus between the casing and the cylindrical bore-wall comprised of earth, stone, sand, and/or other subterranean substances and formations. In normal primary well cementing, a hydraulic cement composition is pumped down through the casing, and then (through e.g. a cement shoe at the bottom of the string of casing) up into the annulus. The cement sets in the annulus, forming an annular sheath which not only physically supports and positions the pipe string in the well-bore, but also bonds the exterior surfaces of the pipe string to the walls of the well-bore, thereby blocking the undesirable migration of fluids along the well-bore. The successful cementing of a well-bore is affected by many factors, including cement setting time. 
   Cement setting time is affected by many factors, including weight percent of various components in the mixed cement, such as components which speed or slow the setting time. When mixing the cement prior to pumping the cement down-hole, control of the weight percent level of such time-of-set-regulating components in the final cement mix can be critical to the success of the cementing operation. Too much of, e.g. a cement-set accelerator, can result in setting the cement too quickly and not allowing it to completely fill the annulus. Therefore, the cement as-mixed must be provided within specific cement recipe control parameters. The cement is usually mixed in a blender which receives water, dry cement, dry powders, and/or special additives such as cement-set-time accelerants. Such mixing is often done continuously, rather than by batch. In a continuous mixing system, the blender receives the various material inputs and produces a mixed cement output. Sensors might monitor the flow rate of the water, flow rate of the dry and mixed cement, pressure, viscosity, density, and other measured process variables, and this information can be fed to the process control unit which monitors and then makes decisions to control the cement blending process system. For example, the process control unit might seek to maintain the fluid level in the blender at a constant level. Because the pumping of the cement into the annulus can speed-up, slow down, start, and momentarily stop from time to time, the process control unit will need to adjust the material inputs based on the output being sent down-hole to keep the blender level constant. If the level in the blender goes high as sensed and signaled by a fluid level sensor, the process control system can, for example, either momentarily stop or slow the addition of materials into the blender. 
   In a typical situation, the blender can be sized to hold only about fifteen seconds of mixed cement demand. Thus, if the process control system makes an under-shoot error, or is too slow in responding to a low level measurement signal from the fluid level gauge in the blender, the blender can possibly run empty, and the pump could suck and pump air into the annulus. In another situation in which a low fluid level is sensed, the process control system might over-shoot the addition of a particular component, such as a cement-set accelerant, and seriously jeopardize the success of the cementing operation, because the cement might set-up before the annulus is completely filled. Modern fluid level control systems for the processing industries have been developed to handle many such under-shoot and over-shoot situations. However, most, if not all, have been developed based on the assumption that, for example, the blending process is not moving, or subject to accelerations and decelerations, as will be encountered if the operation is conducted on a ship on a river, lake, sea, or ocean, where it is subject to wave and/or wind actions. So, for example, when a hydrocarbon production maritime service vessel is conducting the cement blending operation, a wave in the ocean will move the ship, and the blender will move with the ship since it is physically attached to the ship, and the fluid in the blender, or in most containers, for that matter, will “slosh”. A significant problem then arises, for example, in the cement blending operation, because the fluid level sensor in the blender can sense a low level when in-fact the blender has the correct amount of mixed cement. For example, the mixed cement might slosh such that the side of the blender where a fluid level sensor is located has a low level and the other side has a high level, at least momentarily. As sloshing continues, the level sensor unknowingly continues to send the changing level signal to the control system, which if not corrected, will begin to make under-shoot and over-shoot errors. 
   A conventional approach is to average the fluid level signal over some period of time. However, in the case of ocean swells, for example, the time between swells can easily be fifteen to sixty seconds. Thus, if an averaging process control approach is used based on a sixty second running average to “damp” the effect of the ocean swells, the process control system would be tuned so “slowly” as to miss any “true” or actual fluid level deviations caused by process upsets or changes, since, for example, the blender may hold only fifteen seconds of mixed cement. In this instance, “true” or “actual” is used to mean that the level deviation is due to the process and not due to sloshing caused by accelerations of the container. Thus, averaging, damping, or lagging the control system to account for slow-moving ocean swells is not a completely adequate solution to the problem. 
   Note that a maritime ship, vessel, or apparatus can move in six ways. In this instance, “maritime” refers to waterborne operations conducted on either fresh or salt-water. See  FIG. 1A  for a depiction of each movement of, for example, a ship  100  with a partially filled container of fluid  100 A on it. The ship, and thus the container, can surge (e.g.  104  front to back shifting), heave (e.g.  101  up and down “bobbing”), sway (e.g.  106  side to side shifting), pitch (e.g.  103  front to back rocking), roll (e.g.  102  side to side rolling), and yaw (e.g.  109  rotating about a vertical axis). Each movement can also have a different amplitude, velocity, period, and acceleration or deceleration. For example, rolling of ships up to 30 degrees can occur, and accelerations can approach 0.5 to 1 g. Note that, of course, the motions can be random, variable, or periodic. Because these motions will also affect, for example, the sensed level of fluid in, for example container  100 A, the motions can “confuse” a conventional fluid level control system. 
   Note that other fluid processing operations utilizing fluid level control are also commonly carried-out on-board maritime ships, vessels, or apparatuses, including subterranean reservoir fracturing fluid preparation and well drilling mud operations, as well as simply holding such fluids in tanks, vessels, accumulators, silos, or other such containers. Note also that such ships can vary in size and operate in waters of various degrees of movement. These factors also present the control system with differing and complex control problems. 
   Control systems to account for the motion of physical objects such as tall buildings in the wind or in an earthquake can use a combination of motion sensors and heavy movable weights. For example, as a building begins to sway in one direction, the motion sensor senses the sway and a process control unit sends a signal to a device to move a heavy weight in an opposite direction in an attempt to counter-act the wind or quake force, and thereby reduce the sway. This technique is commonly referred to as “active motion compensation”. One might envision that such a system could be applied to a maritime vessel to stop the six degrees of motion of the vessel itself. However, the size and complexity of the weights or compensating mechanical devices to correct for not just sway, but for the other five motions, represent significant engineering and other kinds of challenges. 
   One might also envision active motion compensation practiced on the fluid container itself, where the container  100 A would be placed on a device or equipped with devices to practice active motion compensation. Again, the size and weight of such containers present engineering and other challenges to account for all six motions. Additionally, the pipes, feeders, pumps, mixers, and other equipment attached to the container or blenders would need to somehow be flexibly connected to the container being moved in response to active motion compensation, which will present additional engineering and other challenges. 
   Additional information related to compensating for noise in fluid height measurements in containers can be found in U.S. patent application Ser. No. 11/029,072, entitled “Methods and Systems for Estimating a Nominal Height or Quantity of a Fluid in a Mixing Tank While Reducing Noise,” filed on Jan. 4, 2005, which is incorporated by reference herein in its entirety. 
   Thus, solving the problem of reliably controlling processes involving fluid level control in containers subjected to externally-excited motions presents challenges, and requires solutions not adequately met by current approaches, and it remains a particular problem in off-shore equipment operations. Finally, there is an increasing need for reduction of uncertainty in the production of petroleum as the value of petroleum continues to rise. 
   Process Control Architecture with Hydrodynamic Correction 
   The present Application discloses new architectures for processes which involve fluid level determination in environments which can be subject to externally-excited motion. Movement of a container can cause fluid therein to slosh, and this can confuse simple measurements of the height of the fluid in the container. The present Application teaches that a hydrodynamic model of in-container fluid motion can be used to remove this source of uncertainty. This architecture can be advantageously implemented in or applied to a wide variety of conventional process control architectures, to improve the fluid amount estimations which would otherwise have been used. 
   In some embodiments (but not necessarily all), the disclosed ideas are used to control equipment operations conducted on-board water-borne apparatus and particularly for mixing operations performed on-board maritime oilfield service vessels. 
   In some embodiments (but not necessarily all), the disclosed ideas are used to enable process control of systems experiencing variable, periodic, or random accelerating and decelerating movements. 
   In some embodiments (but not necessarily all), acceleration inputs are used to provide multi-axis spatial movement measurements of the container and/or the fluid. 
   In some embodiments (but not necessarily all), neural networks or non-linear learning processes can be used to build the hydrodynamic model of the container and fluid. 
   The disclosed innovations, in various embodiments, provide one or more of at least the following advantages:
         Improved process control and operation   Improved unit operations control and performance   Improved control and performance of mixing operations   Improved measurement accuracy and reduced measurement uncertainty   Improved measurements of fluid levels in containers when the fluid is sloshing in the container       

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The disclosed innovations will be described with reference to the accompanying drawings, which show important sample embodiments of the invention and which are incorporated in the specification hereof by reference. 
       FIG. 1  shows one embodiment of the present innovations. 
       FIG. 1A  shows possible motions of a maritime vessel due to sea-state. 
       FIG. 2  shows one embodiment of an off-shore hydrocarbon well site with various maritime vessels that can experience externally-excited motion, in which some or all of the present innovations can be applied to. 
       FIG. 3  shows one embodiment of a blending process that can be practiced on-board maritime vessels, to which some or all of the present innovations can be applied to. 
       FIG. 4  is a state block diagram showing one embodiment of a process control modeling and training system and method of the present innovations for controlling processes. 
       FIG. 5  is a state block diagram showing a preferred embodiment of the present innovations of a process control system and method which can be a component in a larger process control system for controlling processes. 
   

   DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
   The numerous innovative teachings of the present Application will be described with particular reference to the presently preferred embodiment (by way of example, and not of limitation). 
   Physical System and Model 
     FIG. 2  shows a non-limiting embodiment of some possible components of an exemplary off-shore hydrocarbon well site  200  to which the present innovations can be applied. On the surface of the water, many different components are possible. In one embodiment of the present innovations, a crew ship  201  can be present. In one embodiment of the present innovations, drilling ship  203  can be present and such a ship has a drilling mud preparation processing operation on-board to which some or all of the present innovations can be applied. In one embodiment of the present innovations, fracturing ship  205  can be present and has a fracturing fluid preparation processing operation to which some or all of the present innovations can be applied. In one embodiment of the present innovations, cementing ship  207  can be present and has a cement mixing processing operation, as previously generally described, to which some or all of the present innovations can be applied. In one embodiment of the present innovations, a barge  209  can be present which can contain one or more processing operations to which some or all of the present innovations can be applied. The barge can also be subject to experiencing some or all of the motions of  FIG. 1A . In one embodiment of the present innovations, a platform  211  can be present which can contain one or more processing operations to which some or all of the present innovations can be applied. A floating or securing means  213  is shown. Platform  211  can still be subject to experiencing some or all of the motions depicted in  FIG. 1A , even though said securing means is present. In one embodiment of the present innovations, one or more processing operations can be conducted on the same ship. An exemplary well-bore  217  is depicted beneath the floor  215  of the water body. In one embodiment of the present innovations, combinations of the various service ships can be present at the well site. 
     FIG. 3  shows a non-limiting example of a cement blending process  300  as one example of a physical process to which the present innovations can be applied to, or embodied in. Blender  301  can be a blender with a mixer to stir the water, cement, and e.g. an accelerant. Water can enter via flow stream  302  and can be controlled by process control unit  316  via water control valve  304 . Dry cement can enter via flow stream  305  and can be controlled by process control unit  316  via cement flow control device  306 . Cement-setting accelerant can enter via flow stream  307  and can be controlled by process control unit  316  via accelerant flow control device  308 . The fluid level  311  in blender  301  can be sensed by sensor  310 . Mixed cement can exit the blender via flow stream  312  and can be pumped down-hole by pump  314 . Pump  314  can be controlled by process control unit  316  via pump flow control device  315 . Process control unit  316 , in one embodiment, can communicate with external system  318 . External system  318  can, in one embodiment, perform a wide variety of operations and functions, including interacting with the operation and control functions of process control unit  316 . 
     FIG. 1  shows one embodiment of the present innovations in which a container of fluid  10  is subjected to externally excited motions, such as the motions experienced on-board a water-borne vessel experiencing different sea-states as shown in  FIG. 1A . In one embodiment, container  10  can be blender  301  in  FIG. 3 . The amount of fluid in the container can be monitored by action  20 . In one embodiment, the amount can be monitored by measuring the fluid level in container  10 . The movement of the container of fluids can be monitored by action  30 . In one embodiment, the movement of the container can be monitored by measuring the acceleration of the container using a multi-axis accelerometer, or combination of accelerometers. The results of actions  20  and  30  can be combined using a hydrodynamic model of the container to generate a resultant output in action  40 . In one embodiment, the resultant output can be a refined measurement of the actual fluid level in the container. The resultant output can be outputted in action  50 . In one embodiment, the output is a control signal that is further processed. 
   In one embodiment of the present innovations, the hydrodynamic model provides a calculation of the true vertical height of a fluid at a particular point or points in the container, at a particular time in the history of a container of fluid subject to externally-excited motions. The model can receive one or more measured variables, such as the measured vertical height of the sloshing fluid, accelerations of the container, and viscosity of the fluid, and then calculate one or more intermediate variables, and/or calculate and output one or more outputs, such as a calculation of the true height of the level of fluid in the container by removing the momentary fluid height effects due to the aforementioned sloshing. 
     FIG. 4  shows a state block diagram of one embodiment of the present innovations. As a non-limiting example of one embodiment of the present innovations, the application of the state block diagram of  FIG. 4  will be discussed in reference to the physical mixing system embodied in  FIG. 3 . One skilled in the art with the benefit of the present Application will realize other kinds of physical systems to which the present innovations can be applied to, or embodied in. 
   To build a hydrodynamic model of blender  301 , four inputs  402 - 1 ,  2 ,  3 , and  4  can be inputted to a neural network (“NN”) or any non-linear dynamic system model learning algorithm (system  404 ). In one embodiment, the learning system can receive a real-time measurement of the viscosity of the fluid in blender  301  (e.g. input  402 - 1 ). In one embodiment, the learning system can receive motion sensing inputs along two axes (e.g. inputs  402 - 2  and  402 - 3 ). In one embodiment, the learning system can receive an input of a vertical height measurement of the fluid in blender  301  (e.g. input  4 ). The output of system  404  can be a system  406  comprising a trained or learned system model of the effects of externally-excited motion on fluid level in blender  301 . 
   In one embodiment,  FIG. 4  can represent a training system for algorithm  404 . The system of  406  can be a trained algorithm. For example, blender  301  can be filled half-way with a model fluid of a known rheology, including a known viscosity. Blender  301 , being on-board, for example, ship  207 , can experience the motions of  FIG. 1A . In training mode, the actual cement mixing process, for example, might not be operating. Instead, the motion in both axes would occur and the sensed height in the container would vary as the model fluid sloshed within blender  301 . The learning algorithm  404  can learn through neural network techniques or any non-linear modeling techniques the relationship between the motion represented by inputs  2  and  3 , and the sensed level, input  4 . In learning, for example, viscosity can be varied by changing fluids and repeating the learning process. Or, the viscosity of the model fluid can be varied randomly in some way to present the algorithm with opportunities to learn the effects of dynamic viscosity behavior in combination with the aforementioned motions. Or, the container can be filled to various levels and the learning process repeated such that the algorithm learns sloshing dynamics as affected by the true height of fluid in blender  301 . Other learning methods are also possible as would be appreciated by one skilled in the art of non-linear modeling. 
     FIG. 5  is a preferred embodiment of the present innovations that, in one embodiment, can be used in a larger process control system for controlling processes. In  FIG. 5 , the trained system model  406  of  FIG. 4  can be adapted and utilized for a motion filtering or canceling function in system hydrodynamic correction block  512  to effect “hydrodynamic correction.” 
   As a non-limiting example of one embodiment of the present innovations, the application of the system and method of  FIG. 5  will be discussed in reference to the physical mixing system embodied in  FIG. 3 . One skilled in the art with the benefit of the present application will realize other kinds of physical systems to which the present innovations can be applied to, or embodied in. 
   In the operation of the system and method of  FIG. 5  during control of the exemplary blending operations, it can receive a sensed or measured vertical fluid height input  502  as a measured process variable of the fluid level of a container, such as blender  301  as sensed by sensor  310 . Measured fluid height  502  can be, during sea-board operation, “truly” rising and falling due to real process effects such as changes in demand from pump  314 , or from changes in inputted material volumes in streams  302 ,  305 , and/or  307 , as previously described. However, measured fluid height  502  can be “falsely” rising and falling due to sloshing caused by the sea-state motions of  FIG. 1A . Thus, a first step in  FIG. 5  can be to perform a hydrodynamic correction function  516  on the sensed fluid height measurement  502  to remove the “false” rising and falling from the measurement. 
   In one embodiment, the hydrodynamic correction function  516  can include a summation block  511 , a controller  510  with a control function, one or more acceleration measurements, e.g. acceleration along an x-axis  504 , and e.g. acceleration along a y-axis  506 , a fluid viscosity measurement  508 , and a trained system hydrodynamic model  406  as part of hydrodynamic correction block  512 . In one embodiment, controller  510  can be a PID (proportional-integral-derivative) controller. In one embodiment, acceleration measurements  504  and  506  can be made by a multi-axis accelerometer. In one embodiment, viscosity measurement  508  can be made by a viscometer. 
   Sensed fluid height measurement  502 , which includes effects of sloshing, can be positively fed to the hydrodynamic correction function  516  via summation block  511 . Control signal  514  can be negatively fed to summation block  511 . The output of block summation  511  is signal  511 A as can be inputted to controller  510 . Control signal  511 A can be considered as an error function, ε error , also referred to as e(t). The error function can be calculated as the difference between a measured variable, such as sensed fluid height  502  in one embodiment, and an estimated variable, such as signal  514 , which in one embodiment can represent an estimate of the height of the fluid in blender  301  with the effects of sloshing removed. 
   Thus, control signal  511 A can be a first estimation of the height error, which can then be used to drive the estimation of the fluid height without the effects of sloshing through the use of controller  510  and correction block  512 . In a preferred embodiment, controller  510  is a PID controller, which has controller constants K P , K D , and K I , which are the controller gain constants for the proportional, derivative, and integral functions, respectively. 
   The temporal response of a PID controller can be given by Equation 1:
 
 u ( t )= K   P   e ( t )+ K   D ( de/dt )+ K   I   ∫e ( t ) dt   (1)
 
   where e(t) is the error function. 
   The temporal response of a PID controller can be also transformed into the frequency domain through the use of a Laplace transform. The Laplace transform of the temporal response of a PID controller can be given by Equation 2:
 
 U ( s )=( K   P   +K   D   s +( K   I   /s ))× E ( s )  (2)
 
   By adjusting or tuning the PID controller constants appropriately as known to one skilled in the art, noise and oscillations can be removed from the fluid height estimation while tracking the nominal value of the fluid height in the container, with the effects of sloshing on the fluid height removed. 
   The fluid height error function can thus be processed through controller  510  to output control signal  510 A to input into hydrodynamic correction block  512 . 
   In one embodiment, acceleration inputs for two axes, x via  504  and y via  506 , can be inputted to correction block  512  as they are measured, along with the cement viscosity measurement  508  from sensor  313 . 
   In another embodiment, acceleration inputs for three axes can be used, where a third axis, z, has been previously incorporated into hydrodynamic model  406 . 
   In other embodiments, additional acceleration measurements can be used. 
   Hydrodynamic correction block  512  can feed the inputs into trained hydrodynamic model  406  to calculate the “false” component of the height measurement as caused by the sloshing. Correction block  512  can then filter or cancel the effect of the externally-excited motion from the control signal  510 A by subtracting the calculated false height component, resulting in a hydrodynamically-corrected height signal  512 A. 
   In one embodiment, control signal  514  as a control loop can be closed around the sensed fluid height  502  and control signal  512 A. To that effect, control signal  512 A can be fed-back as control signal  514  and can be negatively summed in summation block  511 , as previously described. 
   A next step in  FIG. 5  can be to further process control signal  512 A in a closed loop observer  530 , which acts as a dynamic model of the physical mixing process to further correct the control signal, and estimated fluid height, to remove the effects of true volume changes in the blender  301 , caused by the process as well as additional noise and oscillations in the associated signals. 
   The physical system and mass balance of  FIG. 3  can be modeled mathematically using the law of mass conservation in a control volume, which can be represented for blender  301  by Equation 3:
 
ρ w {dot over (V)} w +ρ c {dot over (V)} c −ρ 12 {dot over (V)} 12 +{dot over (m)} D ={dot over (ρ)} 12   h   1   A   1 +ρ 12 {dot over (h)} 1   A   1   (3)
 
where ρ w  is the density of water in stream  302 , ρ c  is the dry cement density in stream  306 , ρ 12  is the density of the mixed cement exiting blender  301  in stream  312 , A 1  is the cross-sectional area of blender  301 , h 1  is the fluid level in blender  301  as measured by fluid level sensor  310 , {dot over (h)} 1  is the change in height level per unit time in blender  301 , {dot over (V)} w  is the volumetric flow rate of the water in stream  302 , {dot over (V)} c  is the volumetric flow rate of cement in stream  305 , {dot over (V)} 12  is the volumetric discharge flow rate of blender  301  as stream  312 , and {dot over (ρ)} 12  is the change in density of the mixed cement in blender  301  per unit time. The parameter {dot over (m)} D  represents the sum of all disturbances accounting for unknown mass rate inputs into the system such as the input mass rate of air. The derivation of Equation 3 assumes instantaneous mixing such that any change in the relative proportions of {dot over (V)} w  and {dot over (V)} c  is instantaneously realized in the resulting value of the slurry density in blender  301 . With this simplification ρ 12  now represents the density of all the slurry in blender  301  at any given moment.
 
   The physical system and mass balance can also be modeled mathematically by volume conservation assuming that both the water and the cement added to the system are incompressible. This model can be represented for blender  301  by Equation 4:
 
{dot over (V)} w +{dot over (V)} c −{dot over (V)} 12 +{dot over (V)} D ={dot over (h)} 1   A   1   (4)
 
The parameter {dot over (V)} D  in Equation 4 represents the “volumetric disturbance flow rate,” which is herein defined as the sum of the flow rates of inputs, e.g., air, into the mixing process other than the primary materials being mixed. The term {dot over (V)} 12 , is predominantly a function of h 1  as indicated by the following
 
Equation 5:
 
{dot over (V)} 12   =F ( h   1 )  (5)
 
   Additional information related to physical system dynamic models can be found in U.S. patent application Ser. Nos. 11/323,831 and 11/323,323, both filed on Dec. 30, 2005. 
   In one embodiment, the closed loop observer as a dynamic model of the physical mixing system and its mass balance can include a summation block  516 , a controller  517  with a control function, one or more feed forward input parameters  518 , one or more feed forward output parameters  520 , a summation block  522  and a container characteristics function  523 . 
   To further refine the estimate of the height of the fluid level in blender  301 , hydrodynamically corrected control signal  512 A can be positively fed to the dynamic blender model  530  via summation block  516 . Control signal  527  can be negatively fed to block  516 . The output of block  516  can be signal  516 A as input to controller  517 .  516 A can be considered an error function, ε error , also referred to as e(t), as described previously. The error function can be calculated as the difference between a measured variable, such as signal  512 A in one embodiment, and an estimated variable, such as signal  527 , in one embodiment. 
   Thus, signal  516 A can be another, more refined fluid height error estimation, which can then be used to drive the estimation to the nominal container height through the use of controller  517 . In a preferred embodiment, controller  517  is a PID controller, which has controller constants and temporal responses as previously described 
   By adjusting the PID controller constants appropriately as known to one skilled in the art, noise and oscillations can be removed from the container height estimation while tracking the nominal value of the fluid height in the container. 
   One skilled in the art of process control with the benefit of this disclosure will recognize that the methods, devices, and systems of the present innovations can be applied to digital signals, as well as analog signals. The digital signals can be processed using digital transform functions, including but not limited to, Z transforms, Fast Fourier Transforms, and wavelet transforms. 
   In other embodiments, the variables can be other physical parameters such as the volume, quantity of fluid, or surface area of the fluid in the container. 
   In one embodiment, feed forward input parameters  518  can include measured material inputs into, for example, blender  301 , such as streams  302 ,  305 , and/or  307 . 
   In one embodiment, feed forward output parameters  520  can include mixed cement output  312  out of, for example, blender  301 . 
   The summation block  522  can be positively fed with the feed forward input parameters  518  and the output of controller  517  as control signal  517 A, and can be negatively fed with the feed forward output parameters  520 . 
   The container characteristics function  523  can take into account the dimensions of the container, such as its cross section area. The container characteristics function  523 , in one embodiment, can include block  524  which represents the function of the inverse of the container cross sectional area to convert the rate of any change of fluid volume in the container to rate of change of fluid height in the container. Block  526  can be included to effect an integration process with respect to time, converting the rate of change of fluid height in the container to the actual fluid height  528 . 
   It should be noted that the container cross sectional area does not need to be constant. These methods and systems are not affected by changes in the cross section of the container as long as those changes are known a priori. 
   By addition of a feed forward function to the dynamic model, the performance can be improved, especially when the feed forward is used together with a traditional feedback function. In one embodiment, since sensors can have inaccuracies and noise, control loop  527  can be closed around the hydrodynamically corrected control signal  526 A and the actual fluid height  528 . 
   The result can be an output of the true height of the fluid in the container  528 , which can now be utilized by process control unit  316  as a reliable measurement of the height of the fluid in the container, essentially free of errors due to externally-excited motion such as depicted in  FIG. 1A . 
   In another embodiment, controllers  510  and/or  517  can be a proportional-integral (“PI”) controller. 
   In another embodiment, controller  510  and/or  517  can be a proportional (“P”) controller. 
   In another embodiment, controller  510  and/or  517  can be a proportional-derivative (“PD”) controller. 
   In another embodiment, controller  510  and/or  517  can be a non-linear controller. 
   According to a disclosed class of innovative embodiments, there is provided a process control method, comprising the actions of monitoring the amount of a fluid in a container, monitoring movements of said fluid and/or said container, and combining results of said monitoring actions using a hydrodynamic model of said container to generate a resultant output. 
   According to a disclosed class of innovative embodiments, there is provided a process control method, comprising the actions of measuring the amount of a fluid in a container which is subject to externally-excited motion, measuring a spatial movement parameter of said fluid and/or said container, modifying the result of an amount-measuring action to more closely represent the actual amount of said fluid using said spatial movement measurements as an input to a hydrodynamic model of the behavior of said fluid, and controlling a process using the hydrodynamic model. 
   According to a disclosed class of innovative embodiments, there is provided a process control system comprising a connection to at least one measured variable input which is related to the amount of fluid in said container, a connection to at least one spatial parameter measurement of said fluid and/or said container, and at least one output, derived from said measured variable input as modified by a hydrodynamic model of fluid motion in said container, which has reduced dependency on the hydrodynamics of motion of the fluid in the container. 
   According to a disclosed class of innovative embodiments, there is provided a process control system comprising a hydrodynamic model of the level of a fluid within a container subject to externally-excited motion during operation, a system to monitor at least accelerations of said fluid and said container, and a logic circuit which uses at least a first determination of said level and said accelerations to calculate a second determination of said level. 
   According to a disclosed class of innovative embodiments, there is provided a process control system, comprising means for receiving measurements related to the amount of a fluid in a container, means for monitoring movements of said fluid and/or said container, and means for using said measurements and a hydrodynamic model which simulates said container to generate modified measurements. 
   According to a disclosed class of innovative embodiments, there is provided a mixing process system comprising a mixing process or equipment subjected to externally-excited motions wherein said mixing process or equipment receives at least one input fluid flow stream and has at least one output fluid flow stream and a process control system acting on said mixing process or equipment wherein said control system reduces the effect of said motions on the results of the mixing process. 
   Modifications and Variations 
   As will be recognized by those skilled in the art, the innovative concepts described in the present Application can be modified and varied over a range of applications, and accordingly the scope of patented subject matter is not limited by any of the specific exemplary teachings given. It is intended to embrace all such alternatives, modifications and variations that fall within the spirit and broad scope of the appended claims. 
   The methods and systems of the present Application can operate across a wide range of processing situations and conditions. One of ordinary skill in the art, with the benefit of this disclosure, will recognize the appropriate use of the methods and systems for a chosen application of a given or dynamic set of operating parameters, including process pressure, process temperature, process flow rate, fluid composition, flow stream composition, presence of gases, use of flow stream conditioning operations, flow stream pipe locations fro sensors, slip-stream installation of measurement devices versus full-stream installation versus insertion installation, ambient temperature, or other conditions. 
   Optionally, the methods and systems of the present Application can be configured or combined in various schemes. The combination or configuration depends partially on the required measuring precision and accuracy and the operational envelope of the process. One of ordinary skill in the art, with the benefit of this disclosure, will recognize the appropriate combination or configuration for a chosen application. 
   Optionally, the methods and systems of the present application can also measure the density of the fluid whose level is being controlled. 
   Optionally, flags such as a particular process variable out of range which can define the reliability of the data or provide variables to use for process control. One of ordinary skill in the art, with the benefit of this disclosure, will recognize the appropriate additional measurements that would be beneficial for a chosen application. Optionally, such measurements taken by the methods and systems of the present Application can also be sent to the external system  318  for processing or use. For example, if the fluid level exceeds a certain amount, this fact could be used to flag improper data during a system upset. Fluid viscosity having a large standard deviation beyond a preset level might be used for the same flagging determination. 
   Optionally, fluid viscosity or rheologic property temperature compensation can be employed used to adjust for shifts in temperature using reference data sets relating temperature change to total fluid viscosity change, or curves fitted to such reference data. 
   Optionally, because the viscosity changes of different fluid compositions or recipes can vary from application to application, or across different embodiments, different reference data sets or curves or hydrodynamic models fitted to such data sets can be employed, maintained, or stored in unit  316  or external system  318 . One of ordinary skill in the art, with the benefit of this disclosure, will recognize the appropriate systems to employ for such temperature compensation methods. 
   Optionally, blenders of various types can be used including propeller, ribbon, paddle, baffle, tumble, turbine, helical, jet, eduction, etc. as known to a person having ordinary skill in the art of blending. 
   Optionally, containers of various types can be used including pressure vessels, vacuum vessels, vertical vessels, horizontal vessels, open tanks, closed tanks, cone tanks, cone-bottom tanks, etc. as known to a person having ordinary skill in the art of process vessel selection or design. 
   Optionally, the methods and systems of the present innovations can be applied to a plurality of containers in series or parallel. 
   Optionally, the methods and systems of the present innovations can be applied to containers having a fluid which contains desirable additives which modify the fluid&#39;s rheologic properties. 
   Optionally, the methods and systems of the present innovations can be applied wherein the nominal quantity of a fluid in a container is estimated. 
   Optionally, fluid level measurements of height, amount, weight, load cell force, or physical fluid level gauging can be employed. 
   Optionally, position, velocity, and force can be employed, along with acceleration for motion sensing. 
   Optionally, the methods of the present application can also be embodied in a set of instructions that can be used on a general purpose desktop or laptop computer or microprocessor system, or external system  318 . The set of instructions can comprise input instructions that receives data from unit  316 . Similarly, the input instructions can accept instructions from a user via one or more input devices, such as a keyboard, mouse, touchpad, or other input device. The instructions can also implement the methods of the present innovations or any part thereof to generate, for example, an updated transform for the system model  512  and closed loop observer  530 . The instructions can cause the computer or microprocessor system to display information, such as the results of the methods of the present innovations, to a user, through a display monitor, printer, generated electronic file, or other such device. The instructions can also cause the computer or microprocessor system to transmit the results to a distant user via modem, cable, satellite, cell link, or other such means. For such digital communications, RS-422 or RS-485 can optionally be used to allow links from unit  316  or external system  318  to multiple external units or locations. Optionally, a 4-20 milliamp analog output signal can be used to allow external processing of the system measurements. 
   Optionally, the methods of the present invention can also be embodied in a computer readable medium. 
   The preferred embodiment uses fluid level sensing. Various technologies can be used to sense the fluid level, including differential pressure sensors, capacitance probes, sonar probes, radar probes, and mechanical level devices such as floats or the like. 
   In some embodiments (but not necessarily all), the hydrodynamic model can incorporate fluid movements caused by mixing processes. 
   None of the description in the present application should be read as implying that any particular element, step, or function is an essential element which must be included in the claim scope: THE SCOPE OF PATENTED SUBJECT MATTER IS DEFINED ONLY BY THE ALLOWED CLAIMS. Moreover, none of these claims are intended to invoke paragraph six of 35 USC section 112 unless the exact words “means for” are followed by a participle. 
   The claims as filed are intended to be as comprehensive as possible, and NO subject matter is intentionally relinquished, dedicated, or abandoned.