Abstract:
A processor accepts sensor data about a geological formation from a sensor. The sensor data is such that processing the sensor data using a processing technique to estimate a parameter of the geological formation without a constraint, whose value is not yet known, produces a plurality of non-unique estimates of the parameter. The processor accepts more than two time-displaced images of fluid sampled from the geological formation. The time displacements between the images are substantially defined by a mathematical series. The processor processes the images to determine the constraint. The processor processes the sensor data using the processing technique constrained by the constraint to estimate the parameter of the geological formation. The processor uses the estimated parameter to affect the drilling of a well through the geological formation.

Description:
Analysts examine fluids extracted from geological formations to estimate the properties of the geological formation and the economic value of the fluids being produced. The fluids may be analyzed by formation testing tools that are deep within a well. The fluid being extracted and analyzed may contain contaminants or multiple phases. Analyzing such fluids, and in particular, detecting multiple phases in a fluid and the effect those multiple phases can have on the estimation of properties of the geological formation, can be a challenge. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  illustrates a drilling system. 
         FIG. 2  is a block diagram of a formation testing tool. 
         FIG. 3  is a block diagram of an analysis section within a formation testing tool. 
         FIGS. 4-10  are block diagrams of imaging devices. 
         FIG. 11  is a diagram illustrating the timing of images taken by an imaging device. 
         FIG. 12  is a data flow diagram of a system that analyzes fluid within a context. 
         FIG. 13  is a block diagram of a system that analyzes fluid within a context. 
         FIG. 14  is a block diagram of a system that includes a remote operating system. 
     
    
    
     DETAILED DESCRIPTION 
     For the purposes of this application, a “phase” of matter is defined as “a homogenous part of a system, separated from other parts by physical boundaries.” L INUS  P AULING , G ENERAL  C HEMISTRY  at 9 (Dover Publications 1988). For example, in the context of the fluids in an oil well, oil, gas, and water are different phases. In a system in which a fluid is experiencing laminar flow, each layer of flow is, in one embodiment, considered a phase. 
     An example environment  100 , illustrated in  FIG. 1 , includes a derrick  105  from which a drill string  110  is suspended in a borehole  112 .  FIG. 1  is greatly simplified and for clarity does not show many of the elements that are used in the drilling process. In one embodiment, the volume within the borehole  112  around the drill string  110  is called the annulus  114 . In one embodiment, the drill string includes a bit  115 , a variety of actuators and sensors, shown schematically by element  120 , a formation testing tool  125 , and a telemetry section  130 , through which the downhole equipment communicates with a surface telemetry system  135 . In one embodiment, a computer  140 , which in one embodiment includes input/output devices, memory, storage, and network communication equipment, including equipment necessary to connect to the Internet, receives data from the downhole equipment and sends commands to the downhole equipment. 
     The equipment and techniques described herein are also useful in a wireline or slickline environment. In one embodiment, for example, a formation testing tool may be lowered into the borehole  112  using wired drillpipe, wireline, coiled tubing (wired or unwired), or slickline. In one embodiment of a measurement-while-drilling or logging-while-drilling environment, such as that shown in  FIG. 1 , power for the formation testing tool is provided by a battery, by a mud turbine, through a wired pipe from the surface, or through some other conventional means. In one embodiment of a wireline or slickline environment, power is provided by a battery or by power provided from the surface through the wired drillpipe, wireline, coiled tubing, or slickline, or through some other conventional means. 
     In one embodiment, the drilling equipment is not on dry land, as shown in  FIG. 1  but is in a wetland or at sea. In such an environment, the derrick  105  (or another piece of equipment that performs the function of the derrick) is located on a drilling platform, such as a semi-submersible drilling rig, a drill ship, or a jack-up drilling rig. The drill string  110  extends from the derrick  105  through the water, to the sea floor, and into the formation. 
     A more detailed, but still simplified, schematic of an embodiment of the formation testing tool  125  is shown in  FIG. 2 . In one embodiment, the formation testing tool  125  includes a power telemetry section  202  through which the tool communicates with other actuators and sensors  120  in the drill string, the drill string&#39;s telemetry section  130 , and/or directly with the surface telemetry system  135 . In one embodiment, the power telemetry section  202  is also the port through which the various actuators (e.g. valves) and sensors (e.g., temperature and pressure sensors) in the formation testing tool  125  are controlled and monitored. In one embodiment, the power telemetry section  202  includes a computer that exercises the control and monitoring function. In one embodiment, the control and monitoring function is performed by a computer in another part of the drill string (not shown) or by the computer  140  on the surface. 
     In one embodiment, the formation testing tool  125  includes a dual probe section  204 , which extracts fluid from the reservoir, and delivers it to a channel  206  that, in one embodiment, extends from one end of the formation testing tool  125  to the other. In one embodiment, the channel  206  can be connected to other tools. In one embodiment, the formation testing tool  125  also includes an analysis section  208 , which includes sensors to allow measurement of properties, such as temperature and pressure, of the fluid in the channel  206 . In one embodiment, the formation testing tool  125  includes a flow-control pump-out section  210 , which includes a high-volume bidirectional pump  212  for pumping fluid through the channel  206 . In one embodiment, the formation testing tool  125  includes two multi-chamber sections  214 ,  216 . 
     In one embodiment, the dual probe section  204  includes two probes  218 ,  220  which extend from the formation testing tool  125  and press against the borehole wall, as shown in  FIG. 1 . Returning to  FIG. 2 , probe channels  222 ,  224  connect the probes  218 ,  220  to the channel  206 . The high-volume bidirectional pump  212  can be used to pump fluids from the reservoir, through the probe channels  222 ,  224  and to the channel  206 . Alternatively, a low volume pump  226  can be used for this purpose. Two standoffs or stabilizers  228 ,  230  hold the formation testing tool  125  in place as the probes  218 ,  220  press against the borehole wall, as shown in  FIG. 1 . In one embodiment, the probes  218 ,  220  and stabilizers  228 ,  230  are retracted when the tool is in motion and are extended to sample the formation fluids. 
     One embodiment of the analysis section  208 , illustrated in  FIG. 3 , includes an analysis section channel  305  that connects to the channel  206 . The analysis section channel  305  may be in series with the channel  206  or it may be in parallel with the channel  206 . In the former case, in one embodiment, all fluids that flow through the channel  206  also flow through the analysis section channel  305 . In the latter case, in one embodiment, valves (not shown) at the end of the analysis section channel  305  allow fluids to be sampled from the channel  206  and sent through the analysis section  208 . 
     In one embodiment, fluids flow through the analysis section channel  305  in the direction shown by the arrows in the analysis section channel  305  in  FIG. 3 . 
     In one embodiment, the analysis section  208  includes a pump  310  connected in line with the analysis section channel  305 . The pump  310  has an inlet side  310 A, through which fluids are received by the pump, and an outlet side  310 B, through which fluids are expelled by the pump. In one embodiment, the pump  310  operates in the opposite direction. In one embodiment, the pump  310  is reversible. In one embodiment, the pump creates a pressure difference between the fluids on the inlet side  310 A and the outlet side  310 B. In one embodiment, the amount of the pressure difference can be adjusted. In one embodiment, the pressure difference is controlled by a processor  315 . 
     In one embodiment, the processor  315  is housed within the analysis section  208  and is dedicated to the operation of the analysis section  208 . In one embodiment, the processor  315  is a processor in another part of the drill string (not shown). In one embodiment the processor  315  is the processor  140  on the surface. In one embodiment, the processor  315  is a microprocessor. In one embodiment, the processor  315  is a microcontroller. In one embodiment, the processor  315  is a programmable logic array. In one embodiment, the processor  315  is formed from discrete logic elements. 
     In one embodiment, the analysis section  208  includes an inbound choke valve  320  that, under the control of the processor  315 , variably restricts or cuts off the flow of fluids. 
     In one embodiment, the analysis section  208  includes an optical subsystem  325 . In one embodiment, the optical subsystem includes a light source  325 A, an optical mask  325 B, and an imaging device  325 C. In addition, in one embodiment, the analysis section channel  305  includes windows made of a material, such as sapphire, that is at least partially transparent to the light omitted by the light source  325 A. Consequently, light emitted by the light source  325 A passes through the analysis section channel  305 , through any fluid flowing through the analysis section channel  305 , through the optical mask  325 B, and is imaged by the imaging device  325 C. In one embodiment, a second optical mask (not shown) is placed between the light source  325 A and the analysis section channel  305 . 
     In one embodiment, the light source  325 A emits light in the infra-red spectrum. In one embodiment, the light source  325 A emits light in the visible spectrum. In one embodiment, the light source  325 A emits light in the ultra-violet spectrum. In one embodiment, the light source  325 A can emit light over all, or some subset of all, of these ranges. In one embodiment, the frequency range of the light emitted by the light source  325 A is controllable by the processor  315 . 
     In one embodiment, the optical mask  325 B is a piece of hardware. In one embodiment, the optical mask  325 B is controlled by the processor  315 . In one embodiment, the optical mask is software or firmware executed by the processor  315 . In one embodiment, the optical mask is a multivariate optical element (“MOE”) capable of performing spectroscopy on the light emitted by the light source  325 A and transmitted through the fluids passing through the analysis section channel  305 . 
     In one embodiment, the optical mask  325  includes pattern recognition capabilities. In one embodiment, the optical mask can use the pattern recognition capabilities to detect bubbles, particles of sand or other contaminants in the fluid, differences in phases in the fluids, and other similar patterns. 
     In one embodiment, the optical mask  325  includes a holographic filter that provides high attenuation over a narrow bandwidth. 
     In one embodiment, the optical mask  325  provides enhanced phase detection and enhanced inhomogeneity detection. In one embodiment, the optical mask  325  includes a filter, a cross polarizer, and/or a Moiré filter. 
     In one embodiment, the imaging device  325 C is a camera that is capable of operating at the high temperatures (in excess of 200 degrees Centigrade) encountered in the drilling environment. In one embodiment, the imaging device  325 C includes a thermopile array, such as that manufactured by Heimann Sensor GmbH, Memstech, and Devantech. 
     In one embodiment, the processor  315  controls the imaging device  325 C and receives and processes images from the imaging device  325 C. 
     In one embodiment, the analysis section  208  includes an outbound choke valve  330  that, under the control of the processor  315 , variably restricts or cuts off the flow of fluids. In one embodiment, the processor  315  controls and optionally receives status from the outbound choke valve  330  and the inbound choke valve  320 . 
     In one embodiment, the analysis section  208  includes an instrument package  335  that includes one or more of a temperature sensor to measure the temperature of fluids flowing through the analysis section channel  305 , a pressure sensor to measure the pressure in the fluid flowing through the analysis section channel  305 , and other similar sensors. 
     While  FIG. 3  shows a particular arrangement of the components in the analysis section  208 , it will be understood that the components can be placed in different configurations and orders. For example, in one embodiment the instrument package  335  is placed between the optical subsystem  325  and the outbound choke valve  330 . In one embodiment, one of the inbound choke valve  320  and the outbound choke valve  330  is not present. 
     In one embodiment, illustrated in  FIG. 4 , the light source  325 A is a single light source, and the imaging device  325 C is a single imaging device, such as a camera or a thermopile array. In one embodiment, illustrated in  FIG. 5 , the light source  325 A consists of two (or more) sources of light, each source covering a different frequency range (e.g., visible and infra-red, or infra-red and ultra-violet, etc.), and the imaging device  325 C includes two (or more) imaging devices, one sensitive to one frequency range and the other sensitive to another frequency range. In one embodiment, illustrated in  FIG. 6 , the light source  325 A consists of two sources of light and the imaging device  325 C is as discussed with respect to  FIG. 5 . In the embodiment shown in  FIG. 6 , the light source  325 A is on the same side of the analysis section channel  305  and the light reflects off a mirrored surface that is either part of a wall of the analysis section channel  305  or is separate from and outside the analysis section channel  305 . In one embodiment, illustrated in  FIG. 7 , the light source  325 A includes two sources of light and the imaging device  325 C consists of two imaging devices, as discussed with respect to  FIG. 5 , and two optical masks  705 ,  710  are present. 
     In one embodiment, shown in  FIG. 8 , light pipes  805 ,  810  carry light from the analysis section channel  305  to the imaging device  325 C. In one embodiment, shown in  FIG. 9 , the imaging device  325 C includes a large number (only four are shown) of imaging devices and a large number (only three are shown) of light pipes  805 ,  810 ,  815  to convey light from the analysis section channel  305  to the imaging device  325 C. 
     In another arrangement for collecting images, illustrated in  FIG. 10 , parabolic reflecting mirrors  1005  and  1010  collect the light from the light source  325 A and direct it to the imaging device  325 C. The parabolic reflecting mirrors  1005  and  1010  are designed so that each compensates for the deformations that the other will experience because of heat in the down-hole data collection locations. Further, the mounts  1015  and  1020  are designed so that each offsets heat-caused distortions to the other. 
     In one embodiment, the collected images are a series of a plurality of substantially-equally-spaced images. In one embodiment, the collected images include more than 2 images. In one embodiment, the collected images include more than 10 images. In one embodiment, the collected images include more than 100 images. In one embodiment, each image is of light detectable in the visible light spectrum. In one embodiment, each image is of light detectable in the infra-red spectrum. In one embodiment, each image is of light detectable in the ultra-violet spectrum. In one embodiment, each image is of light detectable in the infra-red, visible, and ultra-violet spectrums. 
     In one embodiment, illustrated in  FIG. 11 , the series of images is collected at substantially equally intervals.  FIG. 11  shows two sets  1105  and  1110  of five images being collected over a period of time. The interval  1115  between the collection images (only one such interval is labeled) is substantially (i.e., in one embodiment within 10 percent, in one embodiment within 5 percent, in one embodiment within 1 percent) the same. In one embodiment, the rate at which the images are collected is similar to the frames per second (“FPS”) specification that is associated with video cameras. In one embodiment, the images are collected at a rate on the order of 50 or 60 images per second. While two sets  1105  and  1110  of 5 images are shown being collected in  FIG. 11 , it will be understood that the number of sets and the number of images per set can be much larger than shown. Further, it will be understood that the images can be taken continuously, rather than in discrete sets as shown. 
     In one embodiment, the series of images is collected at intervals that can be defined by a linear series, such as that shown in  FIG. 11 . That is, in one embodiment, the times at which the images are collected are defined by the following equation:
 
 t   n   =n·i; n= 1  . . . m  
         where:   t n  is the times at which the images are collected;   i is the time interval (or time displacement) between the times that images are collected;   m is the number of images collected in a segment; and   n is an index.       

     In one embodiment, the series of images is collected at intervals that can be defined by a non-linear series. That is, in one embodiment, the times at which the images are collected are defined by the following equation:
 
 nlt   n   =f ( n );  n= 1  . . . m  
         where:   nlt n  is the times at which the images are collected;   m is the number of images collected in a segment;   n is an index; and   f(n) is an non-linear non-random function.       

     For example, in one embodiment, the times at which the images are collected are defined by the following equation:
 
 nlt   n   =i   n   ; n= 1  . . . m  
         where:   nlt n  is the times at which the images are collected;   m is the number of images collected in a segment;   n is an index; and   i is a constant (e.g., “2”).       

     In this example, if:
         i=2 and m=5,
 
the times at which the images are collected are:
   nlt 1 =2;   nlt 2 =4;   nlt 3 =8;   nlt 4 =16; and   nlt 5 =32.       

     In the linear example, the time displacement between samples is the same. In the non-linear example, the time displacement between samples is defined by the non-linear function. That is, in the example just given, the time displacement between nlt 1  and nlt 2  is 2 seconds, the time displacement between nlt 2  and nlt 3  is 4 seconds, the time displacement between nlt 3  and nlt 4  is 8 seconds, and the time displacement between nlt 4  and nlt 5  is 16 seconds. 
     It will be understood that f(n) can be any non-linear non-random function. It will be understood that multiple segments of images can be collected or that a given segment can include a very large number of images. It will also be understood that the images can be collected at times substantially equal to t n  and nlt n , where “substantially equal” in this context is defined to mean, in one embodiment, within 10 percent of the most recent interval, in another embodiment, within 20 percent of the most recent interval, and in another embodiment, within 50 percent of the most recent interval. 
     The images collected by the optical subsystem  325  are used to identify a context which constrains a transformation or inversion of the data collected by other sensors into an answer, as illustrated in  FIG. 12 . In one embodiment, the images are used to identify a constraint set from a database of constraint sets  1205 . For example, in one embodiment, the database of constraint sets  1205  includes entries that correspond to fluids with various sizes and densities of particulate matter in a fluid. The entries in the database of constraint sets  1205  would include constraints that would be used to constrain the transform or inversion. 
     As can be seen at the bottom of  FIG. 12 , sensor data is transformed or inverted to produce an answer. For example, U.S. Pat. No. 7,434,457 to Goodwin, et al. (hereinafter “Goodwin”) describes measuring the resonant frequency of a movable element immersed in a fluid. The use of the resonant frequency to determine the density and viscosity of the fluid is an example of a “transform” or “inversion” as used in this application. See Goodwin at col. 4, lines 52-55. Goodwin&#39;s transformation uses “constants c and k” that are “determined by calibrating the sensor using fluids of known density and viscosity.” Id. at col. 4, lines 37-40. 
     In one embodiment, the images collected by the optical subsystem  325  are used to identify a context in which a transform, such as the transform described in Goodwin, is to operate. A context is defined to be a set of conditions that cause a transform to change or be constrained. For example, the transform in Goodwin may have one set of constants for use when the fluids being measured are a single phase, i.e., free of laminar flow and contaminants. A second set of constants may be used when the fluid is experiencing laminar flow. A third set of constants may be used when the fluid contains gas. A fourth set of constants may be used when the fluid contains solid particles, such as sand. The conditions of the fluid being measured are the contexts. The images collected by the optical subsystem  325  are used to identify the context and thereby constrain the transform to produce an accurate answer. 
     One embodiment of a system to perform such an analysis, illustrated in  FIG. 13 , includes a camera  1305 , which in one embodiment is a device such as one of those shown in  FIGS. 4-10 . In one embodiment, images from the camera  1305  are used by a context analyzer  1310  to identify a context. In one embodiment, the context analyzer  1310  is a function performed by the processor  315 . In one embodiment, the context analyzer  1310  is performed by a processor that is separate from processor  315  but that communicates with processor  315  in order to perform some or all of the operations associated with collecting images. In one embodiment, the function of the context analyzer  1310  is performed by a processor in another part of the drill string (not shown). In one embodiment the function of the context analyzer  1310  is performed by the processor  140  on the surface. 
     In one embodiment, the context analyzer  1310  provides a context to a constraint analyzer  1315 . In one embodiment, the function of the constraint analyzer  1315  is performed by a processor dedicated to that task. In one embodiment, the function of the constraint analyzer  1315  is performed by the same processor that performs the function of the context analyzer  1310 . In one embodiment, the function of the constraint analyzer  1315  is performed by a processor in another part of the drill string (not shown). In one embodiment the function of the constraint analyzer  1315  is performed by the processor  140  on the surface. In one embodiment, the function of the constraint analyzer  1315  is to identify a set of one or more constraints to be applied to a transform or inversion given the context provided by the context analyzer  1310 . In one embodiment, the constraint analyzer  1315  identifies constraints through an analysis of the context. In one embodiment, the constraint analyzer  1315  identifies a constraint set or sets by accessing a database or file of constraint sets  1320  that provides constraint set(s) when queried by context. In one embodiment, the database or file of constraint sets  1320  that provides constraint set(s) when queried using the images provided to the context analyzer  1310 . 
     In one embodiment, the constraint set or sets is provided by the constraint analyzer  1315  to a sensor data analyzer  1325 , which uses the constraint set or sets to modify a transform or inversion of sensor data  1330  to produce an answer  1335 . 
     In one embodiment, the context analyzer  1310  identifies a context that includes phase change conditions. In one embodiment, pressure on fluid flowing through the analysis section channel  305  can be controlled using inbound choke valve  320  or outbound choke valve  330 . In one embodiment, a bubble point for a fluid flowing through the analysis section channel  305  is identified by lowering the pressure until bubbles are identified in the images provided by the imaging device  325 C (e.g., camera  1305 ). Further, in one embodiment, asphaltene onset pressure for a fluid flowing through the analysis section channel  305  is identified by lowering pressure on the fluid until asphaltene particles are identified in the fluid. 
     In one embodiment, a dew point in a transparent fluid flowing through the analysis section channel  305  is identified by lowering pressure on the fluid until the images produced by the imaging device  325 C are generally black, indicating that the dew point has been reached. Increasing the pressure causes the images to clear up and two phases to be present: (1) a gas, and (2) an oily liquid. In one embodiment, adhesion of droplets to the window into the analysis section channel  305  hint at wetability and hence phase (oily or aqueous) of the fluid. 
     In one embodiment, the optical mask  325 B is a light polarizing filter on both sides of the analysis section channel  305 . In one embodiment, the light polarizing filter allows the enhanced detection of solids, including hydrates and salts precipitating from the aqueous phase. In one embodiment, waxes are detected in the oily phases as pinpoints of bright light. In one embodiment, the light polarizing filters act as illumination intensity controls. In one embodiment, mineral solids are highly enhanced in polarized systems. 
     In one embodiment, the perforating system is controlled by software in the form of a computer program on a computer readable media  1405 , such as a CD or DVD, as shown in  FIG. 14 . In one embodiment a computer  1410 , which may be the same as or included in the processor  315  (see  FIG. 3 ) or may be the computer  140  on the surface (see  FIG. 1 ), reads the computer program from the computer readable media  1405  through an input/output device  1415  and stores it in a memory  1420  where it is prepared for execution through compiling and linking, if necessary, and then executed. In one embodiment, the system accepts inputs through an input/output device  1415 , such as a keyboard, and provides outputs through an input/output device  1415 , such as a monitor or printer. In one embodiment, the system stores the results of calculations in memory  1420  or modifies such calculations that already exist in memory  1420 . 
     In one embodiment, the results of calculations that reside in memory  1420  are made available through a network  1425  to a remote real time operating center  1430 . In one embodiment, the remote real time operating center  1430  makes the results of calculations available through a network  1435  to help in the planning of oil wells  1440  or in the drilling of oil wells  1440 . 
     The word “coupled” herein means a direct connection or an indirect connection. 
     The text above describes one or more specific embodiments of a broader invention. The invention also is carried out in a variety of alternate embodiments and thus is not limited to those described here. The foregoing description of the preferred embodiment of the invention has been presented for the purposes of illustration and description. It is not intended to be exhaustive or to limit the invention to the precise form disclosed. Many modifications and variations are possible in light of the above teaching. It is intended that the scope of the invention be limited not by this detailed description, but rather by the claims appended hereto.