Patent Publication Number: US-7588083-B2

Title: Method and system for scanning tubing

Description:
This application claims benefit of U.S. Provisional Application Ser. No. 60/786,272, filed on Mar. 27, 2006. 
    
    
     FIELD OF THE INVENTION 
     The present invention relates to determining a physical property of a tube that is being inserted into or extracted from an oil well and more specifically to processing information from a tubing scanner using an adaptive or tunable filter implemented via digital signal processing. 
     BACKGROUND 
     After drilling a hole through a subsurface formation and determining that the formation can yield an economically sufficient amount of oil or gas, a crew completes the well. During drilling, completion, and production maintenance, personnel routinely insert and/or extract devices such as tubing, tubes, pipes, rods, hollow cylinders, casing, conduit, collars, and duct into the well. For example, a service crew may use a workover or service rig to extract a string of tubing and sucker rods from a well that has been producing petroleum. The crew may inspect the extracted tubing and evaluate whether one or more sections of that tubing should be replaced due physical wear, thinning of the tubing wall, chemical attack, pitting, or another defect. The crew typically replaces sections that exhibit an unacceptable level of wear and notes other sections that are beginning to show wear and may need replacement at a subsequent service call. 
     As an alternative to manually inspecting tubing, the service crew may deploy an instrument to evaluate the tubing as the tubing is extracted from the well and/or inserted into the well. The instrument typically remains stationary at the wellhead, and the workover rig moves the tubing through the instrument&#39;s measurement zone. 
     The instrument typical measures pitting and wall thickness and can identify cracks in the tubing wall. Radiation, field strength (electrical, electromagnetic, or magnetic), sonic/ultrasonic pulses, and/or pressure differential may interrogate the tubing to evaluate these wear parameters. The instrument typically produces a raw analog signal and outputs a sampled or digital version of that analog signal. 
     In other words, the instrument, typically stimulates a section of the tubing using a field, radiation, or pressure and detects the tubing&#39;s interaction with or response to the stimulus. An element, such as a transducer, converts the response into an analog electrical signal. For example, the instrument may create a magnetic field into which the tubing is disposed, and the transducer may detect changes or perturbations in the field resulting from the presence of the tubing and any anomalies of that tubing. 
     The analog electrical signal output by the transducer can have an arbitrary or essentially unlimited number of states or measurement possibilities. That is, rather than having two discrete or binary levels, typical transducers produce signals that can assume any of numerous levels or values. As the tubing passes through the measurement field of the instrument, the analog transducer signal varies in response to variations and anomalies in the wall of the moving tubing. 
     The transducer and its associated electronics may have a dampened or lagging response that tends to reduce the responsiveness of the signal to tubing wall variations and/or noise. In other words, the instrument may acquire and process analog signals in a manner that steadies or stabilizes those analog signals. In typical conventional instruments, the analog processing remains fixed. That is, any damping or filtering of those signals is generally constant and inflexible. 
     The instrument also typically comprises a system, such as an analog-to-digital converter (“ADC”), that converts the analog transducer signal into one or more digital signals suited for reception and display by a computer. In conventional instruments, those digital signals typically provide a “snapshot” of the transducer signal. Thus, the ADC typically outputs a number, or set of a numbers, that represents or describes the analog transducer signal at a certain instant or moment in time. Since the analog transducer signal describes the section of tubing that is in the instrument&#39;s measurement zone, the digital signal is effectively a sample or a snapshot of a parameter-of-interest of that tubing section. 
     The analog-to-digital conversion typically occurs on a fixed-time basis, for example one, eight, or sixteen times per second. That is, conventional instruments usually acquire measurement samples at a predetermined rate or on a fixed time interval. Meanwhile, the speed of the tubing passing through the measurement zone often fluctuates or changes erratically. That is, the operator and rig may change the extraction speed in an unrepeatable fashion or in a manner that is not known in advance, a priori, or before the speed-change event. 
     Thus, the instrument may output a series of samples or digital snapshots with each sample separated by a tubing length that is not readily determined using conventional technology. The separation between samples might be a millimeter, a centimeter, or a meter of tubing length, for example. The distance between samples may vary, fluctuate, or change erratically as the operator changes the tubing speed. Moreover, the sample data may blur or become smeared when the tubing is moving rapidly. Consequently, fixing the time interval between each snapshot and allowing the tubing speed to vary between snapshots, as occurs in most conventional instruments, can produce data that is difficult to interpret or that fails to adequately characterize the tubing. 
     Another shortcoming of conventional instruments is that they generally provide an insufficient or limited level of processing of the digital samples. When the tubing is moving slowly through the instrument&#39;s measurement zone or is stationary, an operator may incorrectly interpret variation in the digital samples as a wall defect; however, the variation may actually result from signal noise. In other words, at slow tubing speeds, signal spikes due to noise or a random event can be mistaken for a defective tubing condition. 
     Meanwhile, when the tubing is moving quickly through the measurement zone, the tubing motion may blur or smooth signal spikes that are actually due to tubing defects, thereby hiding those defects from operator observation. That is, with conventional instruments, high-speed tubing motion may mask or obscure tubing wall defects. This phenomenon can be likened to the image blurring that can occur when a person takes a photograph of a fast moving car. 
     To address these representative deficiencies in the art, what is needed is an improved capability for evaluating tubing, for example in a petroleum application wherein the tubing is being placed into or drawn from an oil well. A further need exists for processing digital signals, samples, or snapshots of a physical parameter of the tubing. A further need exists for an instrument that can apply a flexible level of processing, filtering, or averaging to a signal from an instrument that is scanning or evaluating the tubing. Yet another need exists for processing instrumentation signals in a manner that smoothes noise while preserving signal structure indicative of valid tubing defects. Still another need exists for converting analog instrumentation or transducer signals into digital signals while accounting or compensating for changes in tubing speed. A capability addressing one or more of these needs would provide more accurate, precise, repeatable, efficient, or profitable tubing evaluations. 
     SUMMARY OF THE INVENTION 
     The present invention supports evaluating an item, such as a piece of tubing or a rod, in connection with placing the item into an oil well or removing the item from the oil well. Evaluating the item can comprise sensing, scanning, monitoring, inspecting, assessing, or detecting a parameter, characteristic, or property of the item. 
     In one aspect of the present invention, an instrument, scanner, or sensor can monitor tubing, tubes, pipes, rods, hollow cylinders, casing, conduit, collars, or duct near a wellhead of the oil well. The instrument can comprise a wall-thickness, rod-wear, collar locating, crack, imaging, or pitting sensor, for example. As a field service crew extracts tubing from the oil well or inserts the tubing into the well, the instrument can evaluate the tubing for defects, integrity, wear, fitness for continued service, or anomalous conditions. The instrument can provide tubing information in a digital format, for example as digital data, one or more numbers, samples, or snapshots. The instrument can digitally process acquired data to improve the data&#39;s fidelity, quality, or usefulness. Subjecting the tubing data to digital signal processing (“DSP”) can promote data interpretation, for example to help a person or a machine better evaluate whether the tubing is acceptable for installation in the oil well. Processing tubing data can comprise applying a flexible level of filtering, smoothing, or averaging to the data, wherein the level changes based on a criterion or according to a rule. The level can vary in response to a change in tubing speed, noise in the raw data, or some other parameter. For example, the instrument can suppress or attenuate signal variations associated with or attributable to noise, random events, or conditions that typically have little or no direct correlation to valid tubing defects. Meanwhile, the instrument can process signals in a manner that preserves signal structures, spikes, or amplitude changes, that are indicative of actual tubing defects. 
     The discussion of processing tubing data presented in this summary is for illustrative purposes only. Various aspects of the present invention may be more clearly understood and appreciated from a review of the following detailed description of the disclosed embodiments and by reference to the drawings and any claims that may follow. Moreover, other aspects, systems, methods, features, advantages, and objects of the present invention will become apparent to one with skill in the art upon examination of the following drawings and detailed description. It is intended that all such aspects, systems, methods, features, advantages, and objects are to be included within this description, are to be within the scope of the present invention, and are to be protected by any accompanying claims. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an illustration of an exemplary system for servicing an oil well that scans tubing as the tubing is extracted from or inserted into the well in accordance with an embodiment of the present invention. 
         FIG. 2  is a functional block diagram of an exemplary system for scanning tubing that is being inserted into or extracted from an oil well in accordance with an embodiment of the present invention. 
         FIGS. 3A and 3B , collectively  FIG. 3 , are a flowchart of an exemplary process for obtaining information about tubing that is being inserted into or extracted from an oil well in accordance with an embodiment of the present invention. 
         FIG. 4  is a flowchart of an exemplary process for filtering data that characterizes tubing in accordance with an embodiment of the present invention. 
         FIGS. 5A and 5B , collectively  FIG. 5 , are a graphical plot and an accompanying table of exemplary raw and filtered data samples in accordance with an embodiment of the present invention. 
         FIG. 6  is a flowchart of an exemplary process for filtering tubing data using an adaptive filter in accordance with an embodiment of the present invention. 
         FIGS. 7A and 7B , collectively  FIG. 7 , are a graphical plot and an accompanying table of tubing data filtered with an exemplary adaptive filter in accordance with an embodiment of the present invention. 
         FIG. 8  is a flowchart of an exemplary process for evaluating a sampling rate of data obtained from a tubing sensor in accordance with an embodiment of the present invention. 
         FIG. 9  is a flowchart of an exemplary process for varying a rate of obtaining data samples from a tubing sensor in accordance with an embodiment of the present invention. 
     
    
    
     Many aspects of the invention can be better understood with reference to the above drawings. The components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of exemplary embodiments of the present invention. Moreover, in the drawings, reference numerals designate like or corresponding, but not necessarily identical, elements throughout the several views. 
     DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS 
     The present invention supports processing information or data that describes or characterizes a tubing parameter, such as pitting, wall thickness, wall cracks, or some other indication of tubing quality or integrity. Processing tubing data can enhance the utility, usefulness, or fidelity of the data, for example helping determine whether a piece of tubing remains fit for continued service. Thus, an oilfield service crew can make efficient, accurate, or sound evaluations of how much life, if any, remains in each joint of tubing in a string of tubing. 
     A method and system for processing tubing data will now be described more fully hereinafter with reference to  FIGS. 1-9 , which show representative embodiments of the present invention.  FIG. 1  depicts a workover rig moving tubing through a tubing scanner in a representative operating environment for an embodiment the present invention.  FIG. 2  provides a block diagram of a tubing scanner that monitors, senses, or characterizes tubing and flexibly processes acquired tubing data.  FIGS. 3-9  show flow diagrams, along with illustrative data and plots, of methods related to acquiring tubing data and processing acquired data. 
     The invention can be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those having ordinary skill in the art. Furthermore, all “examples” or “exemplary embodiments” given herein are intended to be non-limiting, and among others supported by representations of the present invention. 
     Moreover, although an exemplary embodiment of the invention is described with respect to sensing or monitoring a tube, tubing, or pipe moving though a measurement zone adjacent a wellhead, those skilled in the art will recognize that the invention may be employed or utilized in connection with a variety of applications in the oilfield or another operating environment. 
     Turning now to  FIG. 1 , this figure illustrates a system  100  for servicing an oil well  175  that scans tubing  125  as the tubing  125  is extracted from or inserted into the well  175  according to an exemplary embodiment of the present invention. 
     The oil well  175  comprises a hole bored or drilled into the ground to reach an oil-bearing formation. The borehole of the well  175  is encased by a tube or pipe (not explicated shown in  FIG. 1 ), known as a “casing,” that is cemented to down-hole formations and that protects the well from unwanted formation fluids and debris. 
     Within the casing is a tube  125  that carries oil, gas, hydrocarbons, petroleum products, and/or other formation fluids, such as water, to the surface. In operation, a sucker rod string (not explicitly shown in  FIG. 1 ), disposed within the tube  125 , forces the oil uphole. Driven by strokes from an uphole machine, such as a “rocking” pump jack, the sucker rod moves up and down to communicate reciprocal motion to a downhole pump (not explicitly shown in  FIG. 1 ). With each stroke, the downhole pump moves oil up the tube  125  towards the wellhead. 
     As shown in  FIG. 1 , a service crew uses a workover or service rig  140  to service the well  175 . During the illustrated procedure, the crew pulls the tubing  125  from the well, for example to repair or replace the downhole pump. The tubing  125  comprises a string of sections, each of which may be referred to as a “joint,” that typically range in length from 29 to 34 feet (about 8.8 to 10.3 meters). The joints screw together via unions, tubing joints, or threaded connections. 
     The crew uses the workover rig  140  to extract the tubing  125  in increments or steps, typically two joints per increment. The rig  140  comprises a derrick or boom  145  and a cable  105  that the crew temporarily fastens to the tubing string  125 . A motor-driven reel  110 , drum, winch, or block and tackle pulls the cable  105  thereby hoisting or lifting the tubing string  125  attached thereto. The crew lifts the tubing string  125  a vertical distance that approximately equals the height of the derrick  145 , typically about sixty feet or two joints. 
     More specifically, the crew attaches the cable  105  to the tubing string  125 , which is vertically stationary during the attachment procedure. The crew then lifts the tubing  125 , generally in a continuous motion, so that two joints are extracted from the well  175  while the portion of the tubing string  125  below those two joints remains in the well  175 . When those two joints are out of the well  175 , the operator of the reel  110  stops the cable  105 , thereby halting upward motion of the tubing  125 . The crew then separates or unscrews the two exposed joints from the remainder of the tubing string  125  that extends into the well  175 . A clamping apparatus grasps the tubing string  125  while the crew unscrews the two exposed joints, thereby preventing the string  125  from dropping into the well  175  when those joints separate from the main string  125 . 
     The crew repeats the process of lifting and separating two-joint sections of tubing from the well  175  and arranges the extracted sections in a stack of vertically disposed joints, known as a “stand” of tubing. After extracting the full tubing string  125  from the well  175  and servicing the pump, the crew reverses the step-wise tube-extraction process to place the tubing string  125  back in the well  175 . In other words, the crew uses the rig  140  to reconstitute the tubing string  125  by threading or “making up” each joint and incrementally lowering the tubing string  125  into the well  175 . 
     The system  100  comprises an instrumentation system for monitoring, scanning, assessing, or evaluating the tubing  125  as the tubing  125  moves into or out of the well  175 . The instrumentation system comprises a tubing scanner  150  that obtains information or data about the portion of the tubing  125  that is in the scanner&#39;s sensing or measurement zone  155 . Via a data link  120 , an encoder  115  provides the tubing scanner  150  with speed, velocity, and/or positional information about the tube  125 . That is, the encoder  115  is mechanically linked to the reel  110  to determine motion and/or position of the tubing  125  as the tubing  125  moves through the measurement zone  155 . 
     As an alternative to the illustrated encoder  115 , some other form of positional or speed sensor can determine the derrick&#39;s block speed or the rig engine&#39;s rotational velocity in revolution per minute (“RPM”), for example. 
     Another data link  135  connects the tubing scanner  150  to a computing device, which can be a laptop  130 , a handheld, a personal communication device (“PDA”), a cellular system, a portable radio, a personal messaging system, a wireless appliance, or a stationary personal computer (“PC”), for example. The laptop  130  displays data that the tubing scanner  150  has obtained from the tubing  125 . The laptop  130  can present the tubing data graphically, for example in a trend format. The service crew monitors or observes the displayed data on the laptop  130  to evaluate the condition of the tubing  125 . The service crew can thereby grade the tubing  125  according to its fitness for continued service, for example. 
     The communication link  135  can comprise a direct link or a portion of a broader communication network that carries information among other devices or similar systems to the system  100 . Moreover, the communication link  135  can comprise a path through the Internet, an intranet, a private network, a telephony network, an Internet protocol (“IP”) network, a packet-switched network, a circuit-switched network, a local area network (“LAN”), a wide area network (“WAN”), a metropolitan area network (“MAN”), the public switched telephone network (“PSTN”), a wireless network, or a cellular system, for example. The communication link  135  can further comprise a signal path that is optical, fiber optic, wired, wireless, wire-line, waveguided, or satellite-based, to name a few possibilities. Signals transmitting over the link  135  can carry or convey data or information digitally or via analog transmission. Such signals can comprise modulated electrical, optical, microwave, radiofrequency, ultrasonic, or electromagnetic energy, among other energy forms. 
     The laptop  130  typically comprises hardware and software. That hardware may comprise various computer components, such as disk storage, disk drives, microphones, random access memory (“RAM”), read only memory (“ROM”), one or more microprocessors, power supplies, a video controller, a system bus, a display monitor, a communication interface, and input devices. Further, the laptop  130  can comprise a digital controller, a microprocessor, or some other implementation of digital logic, for example. 
     The laptop  130  executes software that may comprise an operating system and one or more software modules for managing data. The operating system can be the software product that Microsoft Corporation of Redmond, Wash. sells under the registered trademark WINDOWS, for example. The data management module can store, sort, and organize data and can also provide a capability for graphing, plotting, charting, or trending data. The data management module can be or comprise the software product that Microsoft Corporation sells under the registered trademark EXCEL, for example. 
     In one exemplary embodiment of the present invention, a multitasking computer functions as the laptop  130 . Multiple programs can execute in an overlapping timeframe or in a manner that appears concurrent or simultaneous to a human observer. Multitasking operation can comprise time slicing or timesharing, for example. 
     The data management module can comprise one or more computer programs or pieces of computer executable code. To name a few examples, the data management module can comprise one or more of a utility, a module or object of code, a software program, an interactive program, a “plug-in” an “applet,” a script, a “scriptlet,” an operating system, a browser, an object handler, a standalone program, a language, a program that is not a standalone program, a program that runs a computer, a program that performs maintenance or general purpose chores, a program that is launched to enable a machine or human user to interact with data, a program that creates or is used to create another program, and a program that assists a user in the performance of a task such as database interaction, word processing, accounting, or file management. 
     Turning now to  FIG. 2 , this figure illustrates a functional block diagram of a system  200  for scanning tubing  125  that is being inserted into or extracted from an oil well  175  according to an exemplary embodiment of the present invention. Thus, the system  200  provides an exemplary embodiment of the instrumentation system shown in  FIG. 1  and discussed above, and will be discussed as such. 
     Those skilled in the information-technology, computing, signal processing, sensor, or electronics arts will recognize that the components and functions that are illustrated as individual blocks in  FIG. 2 , and referenced as such elsewhere herein, are not necessarily well-defined modules. Furthermore, the contents of each block are not necessarily positioned in one physical location. In one embodiment of the present invention, certain blocks represent virtual modules, and the components, data, and functions may be physically dispersed. Moreover, in some exemplary embodiments, a single physical device may perform two or more functions that  FIG. 2  illustrates in two or more distinct blocks. For example, the function of the personal computer  130  can be integrated into the tubing scanner  150  to provide a unitary or commonly-housed hardware and software element that acquires and processes data and displays processed data in graphical form for viewing by an operator, technician, or engineer. 
     The tubing scanner  150  comprises a rod-wear sensor  205  and a pitting sensor  255  for determining parameters relevant to continued use of the tubing  125 . The rod-wear sensor  205  assesses relatively large tubing defects or problems such as wall thinning. Wall thinning may be due to physical wear or abrasion between the tubing  125  and the sucker rod that is reciprocates therein, for example. Meanwhile, the pitting sensor  255  detects or identifies smaller flaws, such as pitting stemming from corrosion or some other form of chemical attack within the well  175 . Those small flaws may be visible to the naked, eye or may have microscopic features, for example. Pitting can occur on the inside surface of the tubing  125 , the so-called “inner diameter,” or on the outside of the tubing  125 . 
     The inclusion of the rod-wear sensor  205  and the pitting sensor  255  in the tubing scanner  150  is intended to be illustrative rather than limiting. The tubing scanner  150  can comprise another sensor or measuring apparatus that may be suited to a particular application. For example, the instrumentation system  200  can comprise a collar locator, a device that detects tubing cracks or splits, a temperature gauge, a camera, a hydrostatic fester, etc. In one exemplary embodiment of the present invention, the scanner  150  comprises or is coupled to an inventory counter, such as one of the inventory counting devices disclosed in U.S. Patent Application Publication Number 2004/0196032. 
     The tubing scanner  150  also comprises a controller  250  that processes signals from the rod-wear sensor  205  and the pitting sensor  255 . The exemplary controller  250  has two filter modules  225 ,  275  that each, as discussed in further detail below, adaptively or flexibly processes sensor signals. In one exemplary embodiment, the controller  250  processes signals according to a speed measurement from the encoder  115 . 
     The controller  250  can comprise a computer, a microprocessor  290 , a computing device, or some other implementation of programmable or hardwired digital logic. In one exemplary embodiment, the controller  250  comprises one or more application specific integrated circuits (“ASICS”) or DSP chips that perform the functions of the filters  225 ,  275 , as discussed below. The filter modules  225 ,  275  can comprise executable code stored on ROM, programmable ROM (“PROM”), RAM, an optical disk, a hard drive, magnetic media, tape, paper, or some other machine readable medium. 
     The rod-wear sensor  205  comprises a transducer  210  that outputs an electrical signal containing information about the section of tubing  125  that is in the measurement zone  155 . As discussed above, the transducer  210  typically responds to the flux density or flux uniformity in the measurement zone  155  adjacent the tube  125 . Sensor electronics  220  amplify or condition that output, signal and feed the conditioned signal to the ADC  215 . The ADC  215  converts the signal into a digital format, typically providing samples or snapshots of the wall thickness of the portion of the tubing  125  that is situated in the measurement zone  155 . 
     The rod-wear filter module  225  receives the samples or snapshots from the ADC  215  and digitally processes those signals to facilitate machine- or human-based signal interpretation. The communication link  135  carries the digitally processed signals  230  from the rod-wear filter module  225  to the laptop  130  for recording and/or review by one or more members of the service crew. The service crew can observe the processed data to evaluate the suitability of the tubing  125  for ongoing service. 
     Similar to the rod-wear sensor  205 , the pitting sensor  255  comprises a pitting transducer  260 , sensor electronics  270  that amplify the transducer&#39;s output, and an ADC  265  for digitizing and/or sampling the amplified signal from the sensor electronics  270 . Like the rod-wear filter module  225 , the pitting filter module  275  digitally processes measurement samples from the ADC  265  and outputs a signal  280  that exhibits improved signal fidelity for display on the laptop  130 . 
     Each of the transducers  210 ,  260  generates a stimulus and outputs a signal according to the tubing&#39;s response to that stimulus. For example, one of the transducers  210 ,  260  may generate a magnetic field and detect the tubing&#39;s effect or distortion of that field. In one exemplary embodiment, the pitting transducer  260  comprises field coils that generate the magnetic field and Hall effect sensors or magnetic “pickup” coils that detect field strength. 
     In one exemplary embodiment, one of the transducers  210 ,  260  may output ionizing radiation, such as gamma rays, incident upon the tubing  125 . The tubing  125  blocks or deflects a fraction of the radiation and allows transmission of another portion of the radiation. In this example, one or both of the transducers  210 ,  260  comprises a detector that outputs an electrical signal with a strength or amplitude that changes according to the number of gamma rays detected. The detector may count individual gamma rays by outputting a discrete signal when a gamma ray interacts with the detector, for example. Ultrasonic or sonic energy can also be used to probe the tubing  125 . 
     Processes of exemplary embodiments of the present invention will now be discussed with reference to  FIGS. 3-9 . An exemplary embodiment of the present invention can comprise one or more computer programs or computer-implemented methods that implement functions or steps described herein and illustrated in the exemplary flowcharts, graphs, and data sets of  FIGS. 3-9  and the diagrams of  FIGS. 1 and 2 . However, it should be apparent that there could be many different ways of implementing the invention in computer programming, and the invention should not be construed as limited to any one set of computer program instructions. Further, a skilled programmer would be able to write such a computer program to implement the disclosed invention without difficulty based on the exemplary system architectures, data tables, data plots, and flowcharts and the associated description in the application text, for example. 
     Therefore, disclosure of a particular set of program code instructions is not considered necessary for an adequate understanding of how to make and use the invention. The inventive functionality of any claimed process, method, or computer program will be explained in more detail in the following description in conjunction with the remaining figures illustrating representative functions and program flow. 
     Certain steps in the processes described below must naturally precede others for the present invention to function as described. However, the present invention is not limited to the order of the steps described if such order or sequence does not alter the functionality of the present invention in an undesirable manner. That is, it is recognized that some steps may be performed before or after other steps or in parallel with other steps without departing from the scope and spirit of the present invention. 
     Turning now to  FIG. 3 , this two-part figure illustrates a flowchart of a process  300  for obtaining information about tubing  125  that is being inserted into or extracted from an oil well  175  according to an exemplary embodiment of the present invention. While Process  300 , which is entitled Obtain Pitting Data, describes conducting a tubing evaluation using the pitting sensor  225 , the underlying method can be applied to various sensors and monitoring devices, including the rod-wear sensor  205  shown in  FIG. 2  and discussed above. 
     At Step  305 , the oil field service crew arrives at the well site with the tubing scanner  150  and the workover rig  140 . The crew places the tubing scanner  150  at the wellhead, typically via a detachable mount, and locates the derrick  145  over the well  175 . As illustrated in  FIG. 1 , a portion of the tubing  125  is disposed in the measurement zone  155  of the tubing scanner  150 , while another portion, suspended below, extends in to the well  175 . 
     At Step  310 , the service crew applies power to the tubing scanner  150  or turns it “on” and readies the derrick  145  to begin lifting the tubing string  125  out of the well  175  in two-joint steps or increments. 
     At Step  315 , the pitting sensor electronics  270  receives electrical energy from a power source (not explicitly shown in  FIG. 2 ) and, in turn, supplies electrical energy to the pitting transducer  260 . The pitting transducer  260  generates a magnetic field with flux lines through the wall of the tubing  125 , running generally parallel to the longitudinal axis of the tubing  125 . 
     At Step  320 , the pitting transducer  260  outputs an electrical signal based on the tubing&#39;s presence in the sensor&#39;s measurement zone  155 . More specifically, Hall effect sensors, magnetic field-strength detectors, or pickup coils measure magnetic field strength at various locations near the tubing  125 . The electrical signal, which may comprise multiple distinct signals from multiple detectors, carries information about the tubing wall. More specifically, the intensity of the transducer signal correlates to the amount of pitting of the section of the tubing  125  that is in the measurement zone  155 . The output signal is typically analog, implying that, it can have or assume an arbitrary or virtually unlimited number of states or intensity values. 
     At Step  325 , the pitting sensor electronics  270  receives the analog signal from the pitting transducer  260 . The electronics  270  conditions the signal for subsequent processing, typically via applying amplification or gain to heighten signal, intensity and/or to create a more robust analog signal. 
     At Step  330 , the ADC  265  receives the conditioned analog signal from the sensor electronics  270  and generates a corresponding digital signal. The digitization process creates a digital or discrete signal that is typically represented by one or more numbers. The ADC  265  generally operates on a time basis, for example outputting one digital signal per second, sixteen per second, or some other number per second or minute, such as 10, 32, 64, 100, 1000, 10,000, etc. The ADC  265  can be viewed as sampling the analog signal from the transducer  260  at a sample rate. Each output signal or sample can comprise bits transmitted on a single line or on multiple lines, for example serially or in a parallel format. 
     Each digital output from the ADC  265  can comprise a sample or snapshot of the transducer signal or of the extent of pitting of the tubing  125 . Thus, the ADC  265  provides measurement samples at predetermined time intervals, on a repetitive or fixed-time basis, for example. 
     In one exemplary embodiment of the present invention, the ADC  265  provides functionality beyond a basic conversion of analog signals into the digital domain. For example, the ADC  265  may handle multiple digital samples and process or average those samples to output a burst or package of data. Such a data package can comprise a snapshot or a sample of tubing pitting, for example. 
     Thus, in one exemplary embodiment, the ADC  265  outputs a digital word at each sampling interval, wherein each word comprises a measurement of the signal intensity of the ADC&#39;s analog input. As discussed below, the filter module  275  filters or averages those words. And in the alternative exemplary embodiment, the ADC  265  not only implements the analog-to-digital conversion, but also performs at least some processing of the resulting digital words. That processing can comprise accumulating, aggregating, combining, or averaging multiple digital words and feeding the result to the filter module  275 . The filter module  275 , in turn, processes the results output from the ADCs  265 , for example via adaptive filtering. 
     At Step  335 , the pitting filter module  275  of the controller  250  receives the digital signals from the ADC  265  and places those signal in memory, for example a short-term memory, a long-term memory, one or more RAM registers, or a buffer. As discussed above, the pitting filter module  275  typically comprises executable instructions or software. 
     Thus, while the tubing  125  remains vertically stationary in the measurement zone  155  of the pitting sensor  255 , the ADC  265  provides a series or steam of digital samples, typically aligned on a recurring timeframe. 
     At Step  340 , the service crew raises the tubing string  125  to expose two joints or thirty-foot pieces of tubing  125  from the well  175 . The service crew stops the vertical motion of the tubing  125  when the two joints are sufficiently out of the well  175  to facilitate separation of those joints from the full tubing string  125 . 
     The service crew typically lifts the tubing string  125  in a continuous motion, keeping the tubing string  125  moving upward until the two joints have achieved an acceptable height above the wellhead. In other words, in one increment of tube extraction, the tubing string  125  starts at a rest, progresses upward with continuous, but not necessarily uniform or smooth, motion and ends at a rest. The upward motion during the increment may contain speed variations, fluctuations, or perturbations. In each step, the operator of the reel  110  may apply a different level of acceleration or may achieve a different peak speed. The operator may increase and decrease the speed in ramp-up/ramp-down fashion, for example. 
     At Step  345 , the pitting sensor ADC  265  continues outputting digital samples to the pitting filter module  275 . Thus, the pitting sensor  255  can output digitally formatted measurements at regular time intervals. In one exemplary embodiment, the duration of each interval can remain fixed while the extraction speed changes and while the tubing&#39;s progress ceases between each extraction increment. In one exemplary embodiment, the ADC  265  continues outputting samples whether the tubing  125  is moving or is stopped. 
     At Step  350 , the pitting filter module  275  filters or averages the samples that it receives from the pitting ADC  265 . The pitting filter module  275  can implement the filtering via DSP or some other form of processing the signals from the pitting sensor  255 . As will be discussed in further detail below, the pitting filter module  275  can apply a flexible amount of filtering based on an application of a rule or according to some other criterion. For example, the digital signals from the pitting sensor  255  can receive a level of averaging, wherein the level varies according to tubing speed. 
       FIGS. 4 and 5  respectively present a flowchart and an accompanying dataset of an exemplary embodiment of Step  350 , as Process  350 , which is entitled Filter Data. In the exemplary embodiment of  FIGS. 4 and 5 , Process  350  conducts data processing in an iterative manner. More specifically and as discussed in further detail below, Process  350  typically runs or executes in parallel with and/or in coordination with certain other steps of Process  300 . Thus, Process  300  avoids remaining “stuck” in the iterative loop of  FIG. 4 . 
     At Step  355 , the tubing scanner  150  forwards the digitally processed tubing samples to the laptop  130 . The laptop  130  displays the data, typically in the form of one or more graphs, plots, or trends, for the service crew&#39;s observation. 
     At Step  360 , a member of the crew views and interprets the data displayed on the laptop  130 . The operator, or an engineer or technician, typically grades or classifies each joint of extracted tubing according to pitting damage, wall thickness, and/or another factor. The operator may classify some tubing joints as unfit for continued service, while grading other sections of tubing  125  as marginal, and still others as having pristine condition. The operator may use a system of color codes, for example. In one exemplary embodiment, the grading is automatic, autonomous, or computer-implemented. 
     At inquiry Step  365 , the service crew determines whether the current extraction increment completes the tubing&#39;s extraction from the well  175 . More specifically, the operator may determine if the pump attached to the bottom of the tubing string  125  is near the wellhead. If all tubing joints have been removed, Process  300  ends. If tubing  125  remains downhole, Process  300  loops back to Step  340  and repeats Step  340  and the steps that follow. In that case, the service crew continues to extract tubing  125 , and the tubing scanner  150  continues to evaluate the extracted tubing  125 . 
     After servicing the pump and/or the well, the crew incrementally “makes up” and inserts the tubing string  125  into the well  175  to complete the service job. In one exemplary embodiment of the present invention, the tubing scanner  150  scans the tubing  125  while inserting the tubing  125  into the well  175 , effectively conducting many of the steps of Process  300  in reverse. In one exemplary embodiment of the present invention, pitting and rod-wear data is collected while the tubing  125  moves uphole, and the tubing  125  is monitored for cracks as the tubing  125  moves downhole. 
     Turning now to  FIGS. 4 and 5 ,  FIG. 4  illustrates a flowchart of a process  350  for filtering data that characterizes tubing  125  according to an exemplary embodiment of the present invention.  FIG. 5  illustrates a graphical plot  500  and an accompanying table  550  of raw data samples  555  and filtered data samples  560 ,  565  according to an exemplary embodiment of the present invention. As discussed above,  FIGS. 4 and 5  illustrate an exemplary embodiment of Step  350  of Process  300 . 
     At Step  405 , the pitting filter module  275  begins processing the digital samples  555  that it received at Step  345  of Process  300 . The table  550  of  FIG. 5B  provides simulated digital samples  555  as an example. The pitting filter module  275  places the samples  555  in a buffer, a memory array, or some other storage facility. For example, a memory device may hold one sample  555  per table cell or per memory register. 
     At Step  410 , the encoder  115  measures the speed of the tubing  125  and outputs the speed measurement to the pitting filter module  275  via the communication link  120 . Thus, the pitting filter module  275  has access to information about the speed of the tubing  125  throughout each extraction increment. As discussed above, the tubing&#39;s extraction speed may fluctuate, may change in an uncontrolled manner, or may be erratic. 
     At Step  415 , the pitting filter module  275  compares the measured tubing speed to a speed threshold. The speed threshold can be a setting input by an operator, technician, or engineer via the laptop  130 . Alternatively, the speed threshold can be software generated, for example derived from an assessment of the pitting sensor&#39;s performance and/or responsiveness. Moreover, the speed threshold can be determined empirically or based on a calibration procedure, a standardization process, a rule, or some protocol or procedure. 
     The flow of Process  350  branches at inquiry Step  420  according to whether the measured speed is greater that the speed threshold. If the measured speed is greater than the speed threshold, then Step  425  follows Step  420 . If the measured speed is not greater than the speed threshold, then Step  430  follows Step  420 . After executing one of Step  430  and  425 , Process  350  loops back to Step  405  and continues digitally processing sensor samples  555 . Step  430  applies a greater level of filtering or averaging than Step  425  applies. 
     Thus, at lower speeds, the pitting filter module  275  applies more filtering than it applies at higher speeds. In other words, the pitting filter module  275  applies greater smoothing or averaging in response to a tubing speed decrease or in response to the tubing speed dropping below a threshold or a limit. 
     As discussed above, Process  300  typically executes Step  350  without waiting for the flow of Process  350  to exit the iterative loop shown in  FIG. 4 . For example, Process  350  may run in the background, with Process  300  obtaining output from Process  350  on an as-needed basis. Moreover, Process  300  may stop and start Process  350 , as Step  350 , for example causing Process  350  to perform a predetermined number of iterative cycles or halting its execution after achieving some computational result. 
     In an alternative exemplary embodiment of the present invention, Step  420  is adapted, relative to the version illustrated on  FIG. 4 , to compare the current speed to a band or a range of speeds. If the current speed is above the band, then Step  425  follows Step  420  as a first filtering mode. If the current speed is below the band, then, Step  430  follows Step  425  as a second filtering mode. If the current speed is within the band, then Process  350  selects another step (not explicitly illustrated in the flowchart of  FIG. 4 ) as a third filtering mode. 
     In one embodiment, that third filtering mode may alternatively provide a level of filtering somewhere between the filtering of the first mode and the filtering of the second mode. The third filtering mode can also comprise a refined filtering approach or a user-selected level of filtering, for example. 
     The third filtering mode may alternatively comprise the last filtering mode used prior to the speed entering the band. In other words, the speed band has an upper speed threshold at the top of the band and a lower speed threshold at the bottom of the band. If the current speed is greater than the upper speed threshold, the filter module  275  applies the first filtering mode. If the current speed then drops below the upper speed threshold without falling below the lower speed threshold, the filter module  275  continues applying the first filtering mode. If the current speed then drops below the lower threshold (from within the band), the filter module  275  applies the second filtering mode. If the speed then increases back into the band, the filter module  275  continues applying the second filtering mode until the speed increases above the band. Thus, in this embodiment, the filter module  275  can be viewed as using a “dead band” as a criterion for selecting a filtering mode or state. 
     Referring now to the flowchart  FIG. 4 , at Step  425 , which executes in response to the tubing speed being above the speed threshold, the pitting filter module  275  applies a first level of filtering or averaging to the raw data  555 . In one exemplary embodiment, the digital signal processing of Step  425  comprises averaging a number “N” of the samples  555 . The number “N” may be set to one or two, for example. 
     For example, as shown in the table  550  of  FIG. 5B , the pitting filter module  275  can average two of the samples  555  using the computation or equation shown immediately below. In this computation “FS i ” denotes the current filtered sample  560 , “S i ” denotes the current raw sample  555 , and “S i-1 ” denotes the raw sample  555  acquired immediately before the current raw sample  555 .
 
 FS   i =( S   i   +S   i-1 )/2
 
     As shown in the plot  510  of the level-one-filtered data samples  560 , the level-one filtering suppresses or smoothes some of the peaks present in the raw data plot  505 , while retaining the raw data plot&#39;s general structure. 
     If the tubing  125  is moving rapidly, low filtering or no filtering may be appropriate. The motion of the tubing through the measurement zone  155  can, itself, smooth the data  555 . In other words, in many circumstances, spikes present in raw data  555  obtained from a fast-moving tubing  125  can be attributable to valid tubing conditions, may be of interest to the operator, and may bear on grading the tubing  125 . 
     At Step  430 , which Process  350  executes in response to the tubing speed being below the speed threshold, the pitting filter module  275  applies a second, higher level of filtering or averaging to the raw data  555 . In one exemplary embodiment, the digital signal processing of Step  430  comprises averaging a number “M” of the samples  555 , wherein M is greater than N (M&gt;N). The number “M” may be set to three, for example. 
     For example, as shown in the table  550  of  FIG. 5B , the pitting filter module  275  can average three of the samples  555  using the following computation:
 
 FS   i =( S   i   +S   i-1   +S   i-2 )/3
 
     The symbols of this equation follow the same conventions of the equation of Step  425 , discussed above. As shown in the plot  515  of the level-two-filtered data samples  565 , the level-two filtering further suppresses or smoothes the peaks present in the raw data plot  505 . 
     With the tubing string  125  moving very slowly or stopped, level-two suppression can suppress high-frequency components of the raw data  555 . Such spikes could be attributed to noise, an extraneous effect, or some influence that is not directly related to grading the tubing  125 . In one embodiment of the present invention, Process  350  applies a third level of suppression when the tubing string  125  is stopped. That third level can further smooth signal spikes, for example by setting M to five, ten, or twenty. 
     Process  350  may be viewed as an exemplary method for changing the filtering in response to a speed event or a noise event. While Process  350  provides two discrete levels of filtering, other exemplary embodiments may implement more filtering levels, such as three, ten, one hundred, etc. In one exemplary embodiment, the number of levels is large enough to approximate continuity, to be continuous, or to provide an essentially unlimited number of levels. 
     In one exemplary embodiment, Process  350  can be viewed as a rule-based method for digitally processing signals. Moreover, Process  350  can be viewed as a method for filtering the output of the pitting sensor  255  using two filtering modes, wherein a specific mode is selected based on an event related to signal integrity, fidelity, noise, or quality. 
     In one exemplary embodiment of the present invention, the motion of the tube  125  provides a first filtering or signal averaging, and the pitting filter module  275  provides a second filtering or signal averaging. Thus, the total filtering is the aggregate or net of the first filtering and the second filtering. A computer-based process can adjust that second filtering to offset or compensate for changes in the first filtering due to speed variations. In response to the computer adjustments of the second filtering, the net filtering may remain relatively constant or uniform despite fluctuations in tubing speed. 
     In one exemplary embodiment, the tubing scanner  150  flexibly filters sensor signals while the signals are in the analog domain. For example, the pitting sensor electronics  270  can comprise an adaptive filter that applies a variable amount of analog filtering to analog signals from the pitting transducer  260 . That is, the sensor electronics  270  can process the analog pitting signal using a time constant that is set according to encoder input, speed, noise, or some other criterion, rule, or parameter. Accordingly, adaptive filtering can occur exclusively in the digital domain, exclusively in the analog domain, or in both the analog and the digital domain. 
     Turning now to  FIGS. 6 and 7 ,  FIG. 6  illustrates a flowchart of a process  600  for filtering tubing data  555  using an adaptive filter according to an exemplary embodiment of the present invention.  FIG. 7  illustrates a graphical plot  700  and an accompanying table  750  of raw tubing data  555  and adaptively filtered tubing data  760 ,  765  according to an exemplary embodiment of the present invention. 
     Although Process  600 , which is entitled Weighted Average Filtering, will be discussed with exemplary reference to the pitting sensor  255 , the method is applicable to the rod-wear sensor  205  or to some other sensing device that monitors tubing. 
     In one exemplary embodiment of the present invention, Process  600  can be implemented as Step  350  of Process  300 , discussed above and illustrated in  FIG. 3 . That is, Process  300  can execute Process  600  as an alternative to executing Process  350  as illustrated in  FIGS. 4 and 5  and discussed above. 
     Process  600  outputs filtered signal samples  565 ,  760 ,  765  that are each a weighted composite of four raw signal samples  755 . 
     At Step  605 , the pitting filter module  275  computes a current processed sample  565  as a weighted average of a present, or current sample and three earlier samples. That is, the output is based on the most recently acquired sample and the three immediately-preceding samples, wherein three is an exemplary rather than restrictive number of samples. 
     For example, the pitting filter module  275  can apply the following computation to the raw data  555  as a basis for generating each filtered sample output (FS i )  565  in a series of outputs  565 :
 
 FS   i =0.33· S   i +0.33 ·S   i-1 +0.33 ·S   i-2 +0.0 ·S   i-3  
 
     In this equation, “FS i ” denotes the current filtered sample, “S i ” denotes the current raw sample  555 , and “S i-1 ,” “S i-2 ,” and “S i-3 ” denote the three samples  555  that arrive in series at the pitting filter module  275  in advance of the current sample  555 .  FIG. 5A , discussed above, provides a plot  515  and a data table  565  of the results of this equation. In other words, the computation of Step  430  of Process  350  provides an equivalent computation to the computation of Step  605  of Process  600 . 
     At Step  610 , the pitting filter module  275  uses the computation of Step  605  to produce a predetermined or a selected number of outputs, such as ten or one hundred, for example. Process  600  can implement Step  610  by iterating Step  605  a fixed number of times or for a fixed amount of time. In one exemplary embodiment of the present invention, Process  600  iterates Step  605  until an event occurs; until the signal exhibits a predetermined characteristic, such as a frequency content; or until a signal processing objective, such as a stabilization criterion, is met. 
     At Step  615 , the encoder  115  determines the tubing speed and forwards that speed to the pitting filter module  275 . 
     At inquiry Step  620 , the pitting filter module  275  applies a rule to the tubing speed, specifically determining whether the speed has increased, decreased, or remained steady, for example for a period of time. The period of time can comprise a fixed time, a configurable time, or an amount of time that varies according to a rule. 
     Determining whether the speed remains steady can comprise determining whether the speed remains within a speed region or a band of acceptable speeds. That is, the determination of inquiry Step  620  can be based on whether the actual speed is between two levels or thresholds. The determination of Step  620  can further comprise evaluating whether the speed is uniform, constant, consistent, smooth, or within a band of normalcy, for example. 
     If the speed is steady, as determined at Step  620 , Process  600  iterates Steps  605   610 ,  615 , and  620  thereby using, or continuing to use, the equation of Step  605  to digitally process incoming sensor samples. 
     If the pitting filter module  275  determines that the speed has decreased rather than remained constant, then Process  600  executes Step  625  following Step  620 . At Step  625 , the filtering module  225  applies a filtering computation to the raw data  555  that increases the weight of older samples  555  or that includes a contribution of older samples  555 . For example, the pitting filter module  275  may use the following computation:
 
 FS   i =0.4 ·S   i +0.3· S   i-1 +0.2· S   i-2 +0.1 ·S   i-3  
 
     The results  765  of this equation are tabulated in table  750  and presented graphically via the trace  715  (arbitrarily labeled “Level 4 Filtering”) of the plot  700 . The symbols of this equation follow the same notational conventions of the equation of Step  605 , discussed above. 
     At Step  630 , the pitting filter module  275  generates multiple filtered output samples  765  using the computation of Step  625 . The number of generated samples can be ten, fifty, one hundred, or one thousand, for example. Process  600  can iterate Step  625  to achieve Step  630 . The number of iterations can be based on time, output, or a number of cycles. In one exemplary embodiment of the present invention, Process  600  iterates Step  625  until an event occurs, until the filtered signal exhibits a predetermined characteristic, such as a frequency content, or until meeting a signal processing objective, such as a stabilization criterion. 
     Following Step  630 , Process  600  loops back to Step  615  to check the tubing speed and to inquire, at Step  620 , whether the tubing speed is increasing, decreasing, or remaining constant. 
     If the pitting filter module  275  determines, at Step  620 , that the tubing speed is increasing rather than decreasing or remaining constant, then Step  635  follows Step  620 . At Step  635 , the pitting filter module  275  increases the contribution of the more recent samples  555  in the filtering computation. For example, the pitting filter module  275  might apply the following computation to the raw data samples  555 :
 
 FS   i =0.8· S   i +0.2 ·S   i-1 +0.0· S   i-2 +0.0 ·S   i-3  
 
     The row  760  of the table  750  provides a representative output of this computation using the raw sensor data  555 . The trace  710 , arbitrarily labeled “Level 3 Filtering” shows the filtered data  760  in graphical form. This computation follows the same symbolic notation of the equations of Steps  605  and  625 , which are discussed above. 
     At Step  640 , the pitting filter module  275  applies the computation of Step  635  to the incoming data samples  555 , executing at each new data element  555 , to generate the filtered output samples  760 . The pitting filter module  275  can generate either a fixed or a flexible number of filtered samples  760 , such as ten, fifty, one hundred, ten thousand, etc. Process  600  can repeat or iteratively execute Step  635  to achieve Step  640 . The number of iterations can be based on time or a number of cycles. In one exemplary embodiment of the present invention, Process  600  repeats Step  635  until an event occurs, or until the filtered signal exhibits a predetermined characteristic, such as a frequency content, or until meeting a signal processing objective, such as a stabilization criterion. 
     Following the execution of Step  640 , Process  600  loops back to Step  615 , obtains a fresh speed measurement, executes inquiry Step  620  to determine whether a speed change event has occurred, and proceeds accordingly. 
     Turning now to  FIG. 8 , this figure illustrates a flowchart of a process  800  for evaluating a sampling rate of data obtained from a tubing sensor according to an exemplary embodiment of the present invention. The tubing sensor can be the tubing scanner  150 , the pitting sensor  255 , the rod-wear sensor  205 , a collar locator, an inventory counter, an imaging apparatus, or some other monitoring or evaluating device or detection system, for example. 
     Process  800 , which is entitled Assess Speed, will be described in the exemplary situation of the controller  250  performing certain of the method&#39;s steps. However, in an alternative embodiment, software executing on the laptop  130  implements various steps of Process  800 . 
     Moreover, the instrumentation system  200 , which comprises the laptop  130  and the controller  250 , can perform Process  800  as an adjunct, complement, or supplement to the adaptive filtering of Process  350  or Process  600 . Alternatively, the instrumentation system  200  can perform Process  800 , or a similar process, as an alternative to performing Process  350  or Process  600 . Process  800  can proceed with or without the filter modules  225 ,  275  performing digital signal processing tasks. 
     At Step  805 , an engineer or some other person, tests the system  200  on various tubes to identify the tubing scanner&#39;s performance characteristics at various tubing speeds. Test pieces of tubing can have assorted defects, pits, cracks, and rod-wear conditions that are representative of real-world situations. That is, the tubing scanner  150  can be characterized by scanning standard pieces of tubing  125  that, have well-defined defects. The testing can comprise moving tubes, each at a known stage of deterioration, at various speeds though the measurement zone  155  of the tubing scanner  150 . 
     The engineer uses the empirical results of those tests to specify, define, or establish a sampling threshold for operating the tubing scanner  150 . That is, the engineer specifies a minimum number of samples per unit length of tubing  125  that the tubing scanner  150  should acquire to obtain reliable or interpretable data. The engineer may also use the testing as a basis to specify a tubing speed limit, for example. 
     At Step  810 , the controller  250  determines the actual sampling rate of the ADC  265  and the ADC  215 . That is, during a routine service call, as illustrated in  FIG. 1  and discussed above, the controller  250  determines the data sampling rate or data capture rate of the tubing scanner  200 . The controller  250  may obtain this information by polling the ADCs  215 ,  265 , or by measuring the passage of time between incoming samples, for example. The units of the sampling rate may be “samples per second,” for example. 
     At Step  815 , the encoder  115  measures the speed and provides the speed measurement to the controller  250 . 
     At Step  820 , the controller  250  determines the number of acquired samples that the ADCs  215 ,  265  are supplying on a length basis. That is, the controller  250  computes, based on the time between each sample and the speed of the tubing  125 , how many samples that the tubing scanner  150  is producing in a given length of tubing  125 . 
     Software executing on the controller  250  can compute the number of samples per meter of tubing as the sample rate (in samples per second) divided by the tubing speed (in meters per second). Thus, the controller  250  might employ the following equation to evaluate whether the tubing scanner  150  is generating a sufficient or adequate number of data samples per unit length of tubing:
 
no. of samples per meter=(no. of samples per sec)/(tubing speed in meters per sec.)
 
     At inquiry Step  825 , the controller  250  determines whether the actual, computed sampling rate is greater than the sampling threshold specified at Step  805 . If the actual sampling rate is greater than the threshold, then at Step  825 , Process  800  loops to Step  810 . Thereafter, Process  800  continues monitoring the sampling rate to evaluate whether an adequate number of samples are being obtained from the tubing  125 . 
     If the ADCs  215 ,  265  operate at a fixed sampling rate, then inquiry Step  825  can be viewed as assessing whether the tubing speed is within a range of acceptability. 
     If, at Step  825 , the controller  250  determines that the tubing scanner is obtaining an insufficient number of samples of the tubing  125 , then execution of Step  830  follows Step  825 . At Step  830 , the controller  250  takes corrective action to the under sampling condition. The controller  250  can alert the operator of the reel  110  to slow down. In one exemplary embodiment, the controller  250  automatically slows the rotational speed of the reel  110 , for example via a feedback loop. 
     In one exemplary embodiment, the controller  250  may instruct the service crew to lower one or more sections of the tubing  125  back into the well  175 , for example to re-scan a section from which an insufficient number of samples have been collected. Alternatively, the crew may elect to physically mark a section of the tubing  125  that has been identified as being associated with data of suspect quality. In one exemplary embodiment, the controller  250  sends notification to the laptop  130  that certain data is questionable or may not be reliable. The laptop  130  can mark the suspect data as potentially unreliable and can present a label on a graph of the data to highlight any suspect data. Moreover, a graphing capability, such as provided by the data management module discussed above, of the laptop  130  may overlay a confidence indicator upon the graphical data. The overlay may indicate the relative or absolute confidence of various portions of the graph according to the sampling rate. 
     In one exemplary embodiment of the present invention, the controller  250  sends a feedback signal to the ADCs  215 ,  265  upon an occurrence of a sampling rate incursion. That is, the controller  250  notifies the ADCs  215 ,  265  to increase their respective sampling rates if a section of tubing  125  is under sampled. The controller  250  can also increase the sampling rate of the ADCs  215 ,  265  if the number of samples per unit length is trending towards an unacceptable value. 
     Following Step  830 , Process  800  ends. Process  800  can be viewed as a method for taking corrective action if the tubing scanner  150  fails to collect an adequate or sufficient number of measurement samples from a section of the tubing  125 . 
     Turning now to  FIG. 9 , this figure illustrates a flowchart of a process  900  for varying a rate of obtaining data samples from a tubing sensor according to an exemplary embodiment of the present invention. Process  900 , which is entitled Vary Sample Rate, illustrates a method through which the tubing scanner  150  can adjust a rate of sample acquisition based on a rule or an application of a criterion. 
     At Step  905 , an engineer specifies a target sampling rate on a length basis. As discussed above, the engineer can conduct testing to evaluate the number of samples that the tubing scanner  150  should collect from each unit length of the tubing  125  to ensure adequate data representation. 
     The analysis can proceed according to the principles of the Nyquist Theorem. In accordance with that theorem, the sampling should be greater than the Nyquist rate to avoid aliasing. In other words, the tubing  125  should be sampled at a frequency that is at least twice the frequency of any variation in the tubing  125  that may be relevant to evaluating or grading the tubing  125 . 
     For example, if the tubing scanner  150  is to reliably detect tubing wall variations that are one millimeter in length and larger, then the minimum acceptable sampling rate might be specified as two samples per millimeter. 
     Moreover, the engineer may specify a band or range of acceptable sampling rates, wherein rates above or below the specified band are unacceptable. The sampling rate criterion can be based upon sensor resolution, for example to provide data with adequate resolution to discern features relative to a quality assessment. 
     At Step  910 , the controller  250 , or a software program executing thereon, computes the actual sampling rate on a length basis according to the time span between each sample and the speed of the tubing  125 . The computation can proceed as discussed above with reference to Step  820  of Process  800 , for example. 
     At inquiry Step  915 , the controller  250  compares the actual length-based sampling rate, determined at Step  910 , to the specifications defined at Step  905 . Step  915  branches the flow of Process  900  according to whether the actual sampling rate is above, below, or within a range of acceptable values. 
     If the sampling rate is with the acceptable range, then Process  900  avoids altering the sampling rate and, via iterating Steps  910  and  915 , continues monitoring the sampling rate to ensure that it remains within the acceptable range. 
     If the sampling rate is too low, then Process  900  executes Step  920 . At Step  920 , the controller  250  transmits a signal or command to either or both of the ADCs  215 ,  265 . In response to that signal or command, the signaled ADC  215 ,  265  increases the sampling rate, typically by shortening the time between each sample acquisition. 
     If the controller  250  determines that the sampling rate is too high at Step  915 , then execution of Step  925  follows execution of Step  915 . At Step  915 , the controller  250  signals the appropriate ADCs  215 ,  265  to decrease the sampling rate on a time basis. That is, one or both of the ADCs  215 ,  265  lengthen the time between each sample. One motivation to avoid an excessively high sampling rate is to conserve memory, computer processing resources, or communication bandwidth of the sampled data. 
     Following execution of either of Steps  920  and  925 , Process  900  loops back to Step  910  and continues monitoring the sampling rate to ensure compliance with specifications or operating parameters. 
     In summary, an exemplary embodiment of the present invention can help provide information and/or operating conditions that aid in assessing whether a piece of tubing  125  is fit for continued oilfield service. 
     From the foregoing, it will be appreciated that an embodiment of the present invention overcomes the limitations of the prior art. Those skilled in the art will appreciate that the present invention is not limited to any specifically discussed application and that the embodiments described herein are illustrative and not restrictive. From the description of the exemplary embodiments, equivalents of the elements shown therein will suggest themselves to those skilled in the art, and ways of constructing other embodiments of the present invention will suggest themselves to practitioners of the art. Therefore, the scope of the present invention is to be limited only by any claims that may follow.