Patent Publication Number: US-7586087-B2

Title: Methods and apparatus to characterize stock-tank oil during fluid composition analysis

Description:
RELATED APPLICATIONS 
   This patent claims priority from U.S. Provisional Application Ser. No. 60,886,400, entitled “Characterize Stock Tank Oil Using Optical Signals to Improve Downhole Fluid Composition Analysis,” filed on Jan. 24, 2007, and which is hereby incorporated by reference in its entirety. 

   FIELD OF THE DISCLOSURE 
   The present disclosure relates generally to methods and apparatus for making determinations regarding hydrocarbon bearing geological formations and, more particularly, to methods and apparatus to characterize stock-tank oil during fluid composition analysis. 
   BACKGROUND 
   Wells are generally drilled into the ground to recover natural deposits of hydrocarbons and/or other desirable materials trapped in geological formations in the Earth&#39;s crust. A well is drilled into the ground and/or directed to a targeted geological location and/or geological formation by a drilling rig at the Earth&#39;s surface. 
   Once a geological formation of interest is reached in a drilled well, drillers often investigate fluids of the geological formation (i.e., formation fluids) by taking fluid samples from the formation for analysis. In some examples, one or more formation fluid samples are obtained by lowering a fluid sampling tool into the well and withdrawing the fluid samples from an underground formation. One example of a sampling tool is the Schlumberger Modular Formation Dynamics Tester (MDT™). The fluid samples may then be analyzed (e.g., in a laboratory) to determine one or more characteristics of the fluid. Additionally or alternatively, characteristics of a fluid may be measured and/or the fluid may be analyzed (e.g., within the sampling tool itself and/or by a device communicatively coupled to the sampling tool) while the sample is relatively pristine. Moreover, such downhole fluid characterization and/or analysis provides information in substantially real-time in contrast to a laboratory analysis that may require many weeks or months to be completed, and/or surface well site analysis, which may result in undesirable phase transitions as well as the loss of key constituents. if the sampling pressure is above the saturation pressure, the fluid will most likely be in a single phase ensuring that the original composition is being analyzed. For pressures below the saturation pressure, a measurement of the properties of a liquid phase sample taken in the reservoir oil zone, and of an associated gas sample taken above the oil zone, will yield more accurate values than a measurement of the properties of a sample recombined at the surface. Indeed, it may be difficult to retain the sample recombined at the surface. Indeed, it may be difficult to retain the sample in the state in which it existed downhole when it is retrieved and/or removed to the surface. 
   Petroleum oil and gas are essentially a mixture of several hydrocarbon components, the variation of which dictates the characteristics of the fluid, along with some inorganic substances. Different types of reservoir fluids include black oils volatile oils, retrograde condensates, wet gases, and dry gases, and the different fluid types require different considerations for their exploitation, and different properties are used for their description. For example, it is generally agreed that black oils can be described satisfactorily using averaged properties of the oil and gas phases, such as the volumetric factors and gas solubility ratios. volatile oils and retrograde condensates, which are near critical fluids, as well as wet gases all require a more detailed knowledge of the fluid composition because the ultimate recovery will be dictated by the control of the production conditions (e.g., primarily pressure). 
   The analysis of a collected fluid sample provides information about the contents of the fluid, density, viscosity, saturation pressure (e.g., bubble point pressure or dew point pressure), and other important characteristics. This vital information is used for field planning decisions and/or for the optimization of upstream and/or downstream production facilities. Indeed, decisions such as the type of well completion, production procedures and the design of the surface handling and processing facilities are affected by the characteristics of the produced fluids. For example, if fluid in the well is a retrograde condensate, the saturation (dew) pressure, combined with the formation pressure and permeability, dictate the maximum pressure drawdown for production of the fluids, and/or whether an injection scheme for pressure maintenance for liquid vaporization should be implemented. 
   One fluid characteristic of particular interest is the gas-oil-ratio (GOR). The GOR is the ratio of the volume of the gaseous phase in the formation fluid and the volume of liquid hydrocarbons, at standard conditions (e.g., 60 degrees Fahrenheit and 1 atmosphere of pressure). GOR values are typically expressed in units of standard cubic feet of gas per barrel of oil (scf/bbl) at the standard conditions. The GOR, among other formation fluid parameters and/or values, is important in designing the upstream and/or downstream production facilities. for example, if the GOR is high, the surface facilities must be designed to handle a large amount of gas from the well. 
   SUMMARY 
   Example methods and apparatus to characterize stock-tank oil during fluid composition analysis are described. A disclosed example method to characterize a fluid associated with an underground geological formation includes obtaining a sample comprising the fluid associated with the underground geological formation; determining, in a borehole associated with the underground geological formation, a stock-tank oil type for the sample associated with the underground geological formation; and determining a property of the sample associated with the underground geological formation based on the stock-tank oil type. 
   another disclosed example method includes obtaining a sample of the fluid associated with the underground geological formation; detecting in situ indications of absorbance of light by the sample of the fluid; determining a stock-tank oil type for the sample of the fluid associated with the underground geological formation based on the detected indications; and determining a property of the fluid associated with the underground geological formation based on the stock-tank oil type. 
   yet another disclosed example method includes transmitting light to a sample of an underground geological formation; measuring an indication of absorption of the transmitted light by the sample; and comparing the measured indication of absorption to two or more absorptions for respective ones of two or more hydrocarbon types to determine a parameter of the sample, wherein the two or more hydrocarbon types include at least a waxy hydrocarbon and a non-waxy hydrocarbon. 
   A disclosed example apparatus to characterize a fluid associated with an underground geological formation includes a device to obtain a sample of the fluid associated with the underground geological formation; an optical sensor to measure an optical property of the sample of the fluid; and an analyzer to determine a stock-tank oil type for the sample of the fluid based on the optical property. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
       FIG. 1  illustrates a cross-section of an example geological formation testing tool constructed in accordance with the teachings of the invention. 
       FIG. 2  illustrates an example manner of implementing any or all of the example controllers of  FIG. 1 . 
       FIGS. 3 ,  4  and  5  illustrate example optical density value curves for various American Petroleum Institute (API) gravities, types of stock-tank oil (STO) and/or hydrocarbon components. 
       FIG. 6  illustrates example relationships between optical density values at 1690 nanometers (nm) and 1800 nm for different types of STO. 
       FIG. 7  illustrates example optical density value curves for a particular STO separately and when the STO occurs in a “live oil” at different gas-oil-ratios. 
       FIG. 8  illustrates the example optical density value curves of  FIG. 7  after normalization by the optical density at 1740 nm and for methane (C1) content. 
       FIG. 9  illustrates example effects of asphaltene content and n-decane (nC10) content on STO optical density values. 
       FIGS. 10 and 11  illustrate example improvements of downhole fluid composition analysis accuracy that may be achieved when an STO type is determined and then used during composition analysis. 
       FIG. 12  is a flowchart representative of an example process that may be carried out to determine an STO type and then perform downhole fluid composition analysis based on the determined STO type and/or, more generally, to implement any or all of the example apparatus of  FIGS. 1 and 2 . 
       FIG. 13  is a flowchart representative of an example process that may be carried out to perform oil composition analysis for a fluid associated with an underground geological formation. 
       FIG. 14  is a flowchart representative of an example process that may be carried out to estimate the mass ratio of C1 to C2+. 
       FIG. 15  is a flowchart representative of an example process that may be carried out to determine an STO type for fluid associated with an underground geological formation. 
       FIG. 16  illustrates example instructions that may be implemented to determine an STO type for a fluid associated with an underground geological formation. 
       FIG. 17  is a flowchart representative of an example process that may be carried out to compute a mass ratio of two components. 
       FIG. 18  is a flowchart representative of an example process that may be carried out to remove the affect of C1 absorptions. 
       FIG. 19  is a flowchart representative of an example process that may be carried out to compute a mass ratio of C3-5 to C6+. 
       FIGS. 20A and 20  B are flowcharts representative of example processes that may be carried out determine to a CO 2  quality flag. 
       FIG. 21  is a flowchart representative of an example process that may be carried out to compute a mass ratio of CO 2  to all hydrocarbons (C1+). 
       FIG. 22  is a flowchart representative of an example process that may be carried out to refine the estimate of the mass ratio of C1 to C6+. 
       FIG. 23  is a flowchart representative of an example process that may be carried out to compute a mass ratio of C1, C2, C3-5, C6+ and CO 2  to all hydrocarbons plus CO 2 . 
       FIG. 24  is a flowchart representative of an example process that may be carried out to check the results of a fluid composition analysis. 
       FIG. 25  is a flowchart representative of an example process that may be carried out to estimate a gas-oil-ratio (GOR) for a fluid associated with an underground geological formation based on a determined stock-tank oil type. 
       FIG. 26  is a schematic illustration of an example processor platform that may be used and/or programmed to perform any or all of the example processes, the example apparatus and/or the example methods described herein. 
   

   DETAILED DESCRIPTION 
   As described in greater detail below, determinations regarding hydrocarbon bearing geological formations may be made via the use of a sampling tool such as the Schlumberger Modular Formation Dynamics Tester (MDT™). To facilitate composition analysis of the collected fluids, the sample tool may implement and/or include a module to measure and/or utilize the absorption of light (i.e., optical densities) at one or more wavelengths of interest (e.g., in the visible and/or near infrared (NIR) regions). A collection of one or more optical densities at one or more wavelengths of interest is commonly referred to as an “absorption spectrum.” Example modules include, but are not limited to, the Schlumberger Optical Fluid Analyzer (OFA™), The Schlumberger Live Fluid Analyzer (LFA™), and/or the Schlumberger Composition Fluid Analyzer (CFA™). Details of example sampling tools and/or example fluid analyzer modules may be obtained with reference to commonly owned U.S. Pat. No. 3,859,851 to Urbanosky, U.S. Pat. Nos. 4,860,581and 4,936,139 to Zimmerman et al, U.S. Pat. No. 4,994,671 to Safinya et al., U.S. Pat. No. 5,167,149 to Mullins et al., U.S. Pat. No. 5,201,220 to Mullins et al., U.S. Pat. No. 5,266,800 to Mullins et al., U.S. Pat. No. 5,331,156 to Hines et al., U.S. Pat. No. 6,956,204 to Dong et al., and U.S. Pat. No. 7,081,615 to Betancourt et al, and U.S. Patent Application No. 2006/0243047 to Terabayahsi et al., all of which are hereby incorporated by reference in their entireties. 
   Because different molecules present in a formation fluid exhibit different absorption spectra, the composition of the formation fluid can be determined from the measured optical densities. For example, optical densities may be used to determine a as-oil-ratio (GOR), and/or concentrations and/or mass fractions of methane CH 4  (C1); ethane C 2 H 6  (C2); a group containing propane C 3 H 8 , butane i-C 4 H 10  and/or n-C 4 H 16 , and pentane i-C 5 H 12  and/or n- C 5 H 12  (C3-C5); a group containing hexane C 6 H 14 + and heavier hydrocarbon components (C6+); and/or carbon dioxide (CO 2 ). However, the example methods and apparatus described herein may be more generally applied to any desired groupings, partitioning and/or characterization of fluid components. For example, the grouping C3-5 may be split into two or more separate groups, and/or C2 and C3-5 may be combined into a C2-5 group. Further, if desired, each component of a fluid may be considered separately to potentially increase precision of the modeling. 
   The accuracy of fluid composition analysis may depend upon the type of STO present in a fluid sample, thus, the example methods and/or apparatus described herein estimate, calculate and/or determine the type of STO present in the fluid sample, and use the STO type during subsequent fluid composition analysis. For example, as described below, an STO type may be determined and/or estimated from one or more measured optical densities. As described herein, the measurement of optical densities and/or the determination of STO types are performed in situ (e.g., within and/or nearby a well and/or downhole). However, persons of ordinary skill in the art will readily appreciate that the methods and apparatus described herein to determine and use an STO type to improve the accuracy of fluid composition analysis may be performed elsewhere (e.g., in a laboratory). As used herein, the term “stock-tank oil” refers to the liquid phase of a hydrocarbon after a live oil and/or condensate gas is flashed at standard conditions. Stock tank oils are comprise primarily of C6+ and small amounts of dissolved light hydrocarbons, and/or non-hydrocarbon gases like CO 2  and/or nitrogen. As use herein, the term “live oil” refers to a liquid hydrocarbon that contains dissolved hydrocarbon gases, such as methane and/or ethane. 
     FIG. 1  shows a cross-section of an example geological formation testing tool  101  designed to withdraw, measure characteristics of, and/or analyze a fluid sample present in a geological formation  114 . The example testing tool  101  of  FIG. 1  may be used to, among other things, implement the example fluid characterization methods and apparatus described herein. The example tool  101  is suspended in a borehole (i.e., a well)  110  from the lower end of a conveyance  115  such as wireline or multiconductor cable, that is spooled from the surface However, other types of conveyances  115  may be used. At the surface, the example wireline  115  is typically connected to an example controller and/or processing system  118  that monitors and/or controls the tool  101 . The example controller and/or processing system  118  of  FIG. 1  and/or a controller and/or processing system  116  implemented by and/or within the tool  101  may, additionally or alternatively, perform fluid composition analysis based on one or more measurements (e.g., optical densities) made by and/or within the sampling tool  101  (e.g., by a fluid analyzer module  125 ). As will be appreciated by those skilled in the art, the example controllers  116  and  118  of  FIG. 1  may include one or more microprocessors or other processors or processing units, associated memory, and other hardware and/or software. Example manners of implementing the example controllers  116  and  118  are described below in connection with  FIGS. 2 and 26 . 
   Once at a desired depth, the example tool  101  of  FIG. 1  is used to obtain a formation fluid sample and/or make one or more measurements of a collected and/or passing fluid sample. The example tool  101  has any number and/or type(s) of probes, and/or fluid inlets and/or ports (one of which is designated at reference numeral  120 ), that is selectively extendable from the tool  101 , as well as an anchoring member  121  on the opposite side of the tool  101  that is also selectively extendable. The example probe  120  of  FIG. 1  extends from the tool  101  and seats against the borehole wall  112  so that the probe  120  is in fluid communication with the formation  114 . The example tool  101  may also include one or more pumps (not shown) to pump formation fluids from the formation  114  into the tool  101  and/or to pump formation fluids from the tool  101  into the borehole  110 . 
   Formation fluids sampled by the tool  101  may be contaminated with mud filtrate, that is, the formation fluids may be contaminated with a drilling fluid that seeps into the formation  114  during the drilling process. Thus, when fluids are withdrawn from the formation  114  they may initially include mud filtrate. In some examples, formation fluids are withdrawn from the formation  114  and pumped into the borehole  110  or into a large waste chamber in the tool  101  until the fluid being withdrawn becomes sufficiently clean. A clean sample is one where the concentration of mud filtrate in the sample fluid is acceptably low so that the fluid represents native (i.e., naturally occurring) formation fluids. Once the fluid being withdrawn becomes sufficiently clean, a sample fluid may be analyzed, measured and/or collected for analysis. 
   Formation fluid withdrawn from the formation  114  by the example probe  120  of  FIG. 1  may be passed through a fluid analyzer  125  before it is pumped out of the tool  101  and into the borehole  110  by a pump (not shown) and/or during sample collection. An example fluid analyzer  125  is an optical sensor (e.g., a gas and/or liquid analyzer spectrometer), which measures the absorption of light (e.g., the optical density (OD)) of the sample fluid at several (e.g., ten or twenty) different wavelengths (e.g., in the visible and/or NIR regions). An example set of wavelengths is {445 nanometers (nm), 570, nm, 647 nm, 680 nm, 815 nm, 1070 nm, 1290 nm, 1445 nm, 1500 nm, 1600 nm, 1650 nm, 1671 nm, 1690 nm, 1725 nm, 1760 nm, 1800 nm, 1930 nm, 1985 nm, 2010 nm, 2040 nm}. An example set of more finely spaced wavelengths occurring with a narrower range of wavelengths of interest is {1589 nm, 1603 nm, 1618 nm, 1634 nm, 1649 nm, 1665 nm, 1680 nm, 1695 nm, 1710 nm, 1725 nm, 1740 nm, 1755 nm, 1770 nm, 1784 nm, 1798 nm, 1814 nm}. 
   As described more fully below, measured OD values may be used to determine, calculate and/or estimate a type of STO present in a formation fluid and/or fluid sample, and/or to perform fluid composition analysis based upon an estimated STO type. As illustrated below in connection with  FIGS. 10 and 11 , by estimating an STO type and then using the estimated STO type during subsequent fluid composition analysis and/or GOR value computation, the accuracy of the fluid analysis performed (e.g., by, at and/or nearby the example sample tool  101 ) is substantially improved. While the example methods and apparatus described herein utilize OD values as indicators of light absorption, persons of ordinary skill in the art will readily appreciate that other type(s) of absorption indications may be used. For example, attenuative refractometry values, light emission values, fluorescence values, etc. Moreover, any other types of measurements (e.g., density and/or viscosity) may be used instead of, or in addition to, measured OD values. For example, waxy STO and non-waxy STO have different viscosities and, thus, a measured viscosity may be used to determine an STO type. Further, while the example methods and apparatus describe herein perform STO type determinations and/or perform fluid analysis based on measured OD values for sampled fluids, persons of ordinary skill in the art will readily appreciate that STO type determinations and/or fluid analysis may be performed using other types of measurements performed, and/or measurements taken for other types of samples. For example, the fluorescence of and/or the light refraction of a rock (e.g., the wall  112  of the formation  114 , and/or a core and/or a sample taken from the borehole  110  and/or the formation  114 ) may be used to determine an STO type. 
   Additionally or alternatively, the measured OD values may also be used to determine the level of mud filtrate contamination. For example, because the oil used in an oil-based mud (OBM) is typically lighter in color than the relatively darker native formation fluid, the OD at the color channels increases asymptotically as the formation fluid becomes cleaner. 
   Once the formation fluid being withdrawn through the probe  120  is sufficiently clean (i.e., substantially contaminate free), one or more samples may be taken by pumping the fluid sample into one or more sample chambers  122 ,  123 . The formation fluid and/or the samples may also have one or more OD measurements taken and/or collected by the example fluid analyzer  125 . The term “contaminate free” is used herein to mean a property of the native formation fluid, substantially free of contamination from, for example, mud filtrate. Thus, a contaminate free gas-oil-ratio (GOR) means the GOR of the formation fluid, with no or insignificant effect from for example, the mud filtrate. While it may be difficult in practice to obtain a fluid sample that is completely free of mud filtrate contamination, the goal is to determine the properties of the formation fluid. The term “apparent” is used here in to refer to the value of a measurement taken during a sampling process. Thus, the apparent GOR is the measured value of the GOR of a fluid sample that is collected from the formation. The apparent GOR may be influenced by mud filtrate or other contaminants. 
   Two types of absorption mechanisms contribute to measured optical densities for a fluid sample; electron excitation and molecular vibration mode excitation. Absorption by electron excitation occurs when the energy of incident light is transferred to excite delocalized pi electrons to anti-bonding states. This energy level typically corresponds to light in the visible to near infrared (NIR) range and gives a shade of color as a result. We simply refer this mode of absorption as color hereafter. Oils may exhibit different colors because they have varying amounts of aromatics, resins, and asphaltenes, each of which absorb light in the visible and NIR spectra. So-called “heavy oils” have higher concentrations of aromatics, resins, and asphaltenes, which give them dark colors. So-called “light oils” and condensate, on the other hand, have lighter, yellowish colors because thy have lower concentrations of aromatics, resins, and asphaltenes. 
   Molecular vibration absorption is the absorption of a particular frequency of light due to resonance of the chemical bonds in a molecule. While color absorption covers the visible and NIR spectrums, molecular vibration absorption occurs only at specific wavelengths for specific materials. For any given molecule, the wavelength at which vibration absorption occurs is related to the type of chemical bonds and the molecular structure. For example, oils have molecular vibration absorption peaks near wavelengths of 1200 nm, 1400 nm, and 1700 nm. Molecular vibration absorption is a function of the concentration of the particular substance, and it is not necessarily affected by the phase of the substance. For example, the magnitude of a methane absorption resonance peak (near 1670 nm) will be the same, regardless of whether the methane is in the gas phase or dissolved in the oil. In addition to, or instead of, these two types of absorptions, scattering may also effect he measured OD values. For example, incident light can be redirected (e.g., reflected) by particles suspended in a sampled fluid causing light scattering. Scattering may also occur for multiple-phase fluid flows, such as, an oil and water mixture, an oil and gas mixture, and/or a water and gas mixture. For example, incident light can be redirected at phase interfaces, thereby, causing light scattering. 
   One example type of optical sensor is the Schlumberger OFA™ module, which implements a spectrometer to measure the OD of a sample fluid at ten different wavelengths in the NIR and visible range (i.e., in ten different filter-array channels). Another example type of optical sensor is the Schlumberger LFA™ module, which differs from the OFA™ module in that the LFA™ module includes a methane channel at the wavelength of a “methane peak” and an oil channel at the wavelength of an “oil peak.” A “methane peak” is a molecular vibration absorption peak of methane having a wavelength that corresponds to the resonance of the CH bond in a methane molecule. An example methane molecular vibration absorption peak is at a wavelength of about 1670 nm. The molecular vibration absorption occurs independently of the color of the fluid and independently of whether the methane is in the gas phase or dissolved in the formation fluid. Similarly, an “oil peak” is a molecular vibration absorption peak of oil, having a wavelength corresponding to the resonance of the combination of CH 2  and CH 3  groups in an oil molecule. An example oil peak is at a wavelength of about 1720 nm. 
   Yet another example type of optical sensor is the Schlumberger CFA™ module, which includes optical channels at specific frequencies to get a better estimate of the spectrum of gases present in a fluid sample. For example, a typical CFA™ module has a channel that corresponds to the resonance peak for molecular vibration absorption in carbon dioxide CO 2 . A typical CFA™ module is able to determine mass concentrations of methane, non-methane gaseous hydrocarbons, carbon dioxide, and liquid hydrocarbons. 
   While an example downhole sampling tool  101  is illustrated in  FIG. 1 , one or more of the elements, components, modules and/or devices illustrated in  FIG. 1  may be combined, divided, re-arranged, omitted eliminated and/or implemented in any of a variety of ways. Further, the example fluid analyzer  125 , the example controllers  116  and  118  and/or, more generally, the example sampling tool  101  may be implemented by hardware, software, firmware and/or any combination of hardware, software and/or firmware. Further still, the example sampling tool  101  may include elements, components, modules and/or devices instead of, or in addition to, those illustrated in  FIG. 1  and/or may include more than one or any or all of the illustrated elements, components, modules and/or devices. 
     FIG. 2  illustrates an example manner of implementing any or all of the example controllers  116  and  118  of  FIG. 1 . While any of the example controllers  116  and  118  of  FIG. 1  may be represented by  FIG. 2 , for ease of discussion, the device of  FIG. 2  will be referred to as fluid analyzer  116 . The example fluid analyzer  116  of  FIG. 2  receives OD values measured and/or collected by an optical sensor (e.g., any of the example fluid analyzers  125  discussed above in connection with  FIG. 1 ) for a fluid sample  202  collected by an fluid sampler (e.g., the example probe  120  of  FIG. 1 ). As illustrated in  FIG. 2 , the example optical sensor  125  may perform OD measurements using any number of filer channels  210  configured for a first set of wavelengths and/or OD measurements taken by a grating spectrometer  210  configured for a second set of wavelengths. In some examples, the first set of wavelengths (e.g., ten) implemented by the filter channels  210  represent a wider range of wavelengths than the second set of wavelengths (e.g., twenty) implemented by the grating spectrometer  210 . The example fluid analyzer  116  of  FIG. 2  uses one or more OD measurements taken by each of the filter channels  205  and the grating spectrometer  210  to estimate and then use an STO type during fluid composition analysis. However, the fluid analyzer  116  could use a different set of OD measurements taken at different wavelengths (e.g., from just the filter channels  205 ) to estimate and then use an STO type during fluid composition analysis. 
   To correct for water content, the example fluid analyzer  116  of  FIG. 2  includes any type of water fraction corrector  215 . Using any suitable method(s), algorithm(s), equation(s) and/or measurement(s), the example water fraction corrector  215  of  FIG. 2  estimates the water volume fraction, and then uses the water value fraction to correct and/or adjust the OD values measured by the optical sensor  125 . Example methods and apparatus to estimate and/or used water value fraction to correct and/or adjust measured OD values are described in commonly owned U.S. Pat. No. 6,992,768, entitled “Optical Fluid Analysis Signal Refinement,” and which is hereby incorporated by reference in its entirety. 
   To correct for color absorption effects, the example fluid analyzer  116  of  FIG. 2  includes any type of decolorizer  220 . Using any method(s), algorithm(s), equation(s) and/or measurement(s), the example decolorizer  220  of  FIG. 2  computes (e.g., estimates) the amount of color absorption in all channels (i.e., all wavelengths), and then adjusts the water corrected OD values based on the estimated amount of color absorption. Example methods and apparatus to estimate and/or correct for color absorption effects are described in commonly owned U.S. Pat. No. 6,992,768, entitled “Optical Fluid Analysis Signal Refinement.” 
   To correct for scattering effects, the example fluid analyzer  116  of  FIG. 2  includes any type of descatterer  222 . Using any method(s), algorithm(s), equation(s) and/or measurement(s), the example descatterer  222  of  FIG. 2  computers (e.g., estimates) the amount of scattering present in all channels (i.e., all wavelengths), and then adjusts the water corrected and/or color corrected OD values based on the estimated amount of scattering. Example methods and apparatus to estimate and/or correct for scattering effects are described in commonly owned U.S. Pat. No. 6,992,768, entitled “Optical Fluid Analysis Signal Refinement.” 
   To estimate the type of STO present in the fluid sample  202 , the example fluid analyzer  116  of  FIG. 2  include a stock-tank oil analyzer  225 . The example stock-tank oil analyzer  225  of  FIG. 2  uses one or more OD values measured by the optical sensor  125 , and possibly corrected by the example water fraction corrector  215 , the example decolorizer  220  and/or the example descatterer  222 , to determine, calculate and/or estimate the STO type.  FIGS. 3-9  describe example fluid composition characteristics that may be utilized to determine an STO type. Example manners of implementing the example stock-tank oil analyzer  225  of  FIG. 2  are described below in connection with  FIGS. 15 and 16 . 
   To perform composition analysis, the example fluid analyzer  116  of  FIG. 2  includes a composition analyzer  230 . The example composition analyzer  230  of  FIG. 2  uses an STO type estimated by the example stock-tank oil analyzer  225  to identify the components contained in and/or estimate mass ratios of components contained in the fluid sample  202 . An example manner of implementing the example composition analyzer  230  of  FIG. 2  is described below in connection with  FIG. 13 . 
   To calculate (e.g., estimate) a GOR value for the fluid sample  202 , the example fluid analyzer  116  of  FIG. 2  includes a gas-oil-ratio calculator  235 . Based on the composition analysis performed by the composition analyzer  230  and/or the STO type determined by the stock-tank oil analyzer  225 , the example gas-oil-ratio calculator  235  estimate a GOR value for the fluid sample  202 . An example manner of implementing the example gas-oil-ratio calculator  235  of  FIG. 2  is described below in connection with  FIG. 25 . 
   To provide one or more of the values, parameters and/or properties estimated, determined and/or computed by the example fluid analyzer  116  of  FIG. 2 , the fluid analyzer  116  includes any type of reporter(s)  240 . The example reporter  240  of  FIG. 2  collects, receives and/or otherwise obtains values, parameters and/or properties that are estimated, determined and/or computed by the example water fraction corrector  215 , the example decolorizer  220 , the example descatterer  222 , the example stock-tank oil analyzer  225 , the example composition analyzer  230 , and/or the example gas-oil-ratio calculator  235 , and provides and/or outputs the same. For example, the reporter  240  may log, report, store (e.g., in a memory, a memory device and/or a storage device), add to a database and/or data structure, print (e.g., to piece of paper), display (e.g., on a display device), transfer, upload, communicate (e.g., via a communication, a data transfer and/or computer peripheral cable), and/or otherwise provide and/or output the obtained values, parameters, properties. 
   As illustrated below in connection with  FIGS. 10 and 11 , because the example fluid analyzer  116  of  FIG. 2  estimates an STO type for the fluid sample  202  and then uses the estimated STP type during fluid composition analysis and/or GOR value computation, the accuracy of the fluid analysis performed by the example fluid analyzer  116  of  FIG. 2  is substantially improved. 
   While an example manner of implementing any or all of the example controllers  116  and  118  of  FIG. 1  has been illustrated in  FIG. 2 , one or more the elements, processes and devices illustrated in  FIG. 2  may be combined, divided, re-arranged, omitted, eliminated and/or implemented in any of a variety of ways. Further, the example water fraction corrector  215 , the example decolorizer  220 , the example descatterer  222 , the example stock-tank oil analyzer  225 , the example composition analyzer  230 , the example gas-oil-ratio calculator  235 , the example reporter  240  and/or, more generally, the example fluid analyzer  116  may be implemented by hardware, software, firmware and/or any combination of hardware, software and/or firmware. Further still, the example fluid analyzer  116  may include one or more elements, processes and/or devices in addition to, or instead of, those illustrated in  FIG. 2 , and/or may include more than one of any or all of the illustrated elements, processes and devices. 
   Given a set of OD values, the composition of various components of a fluid sample may be estimated. For example, a vector  c  that represents the concentrations of target components (e.g., methane (C1); ethane (C2); a group containing propane, butane, and pentane (C3-C5); a group containing hexane and heavier hydrocarbon components (C6+); and carbon dioxide (CO 2 )) may be estimated by solving the mathematical expression of EQN (1), where  s  is a vector that contains the measured OD values for a set of optical channels (i.e., wavelengths), and {circumflex over (B)} is a response matrix that represents the responses of each optical channel to the target components.
 
  s ={circumflex over (B)}  c   EQN (1)
 
The response matrix {circumflex over (B)} depends upon the type of STO present in a fluid sample. However, in many fluid composition analysis methods and apparatus currently employed, the STO type is unknown, imprecisely known and/or inaccurately known and, thus, the response matrix {circumflex over (B)} used to perform fluid composition analysis for any particular fluid sample may be inaccurate. In such circumstances, any resulting fluid composition analysis may be likewise wholly or partially inaccurate.
 
     FIGS. 3 ,  4 ,  5 ,  7 ,  8  and  9  illustrate example fluid composition characteristics that may be recognized, utilized, employed and/or taken advantage of to determine an STO type for a fluid sample.  FIG. 3  illustrates example OD values as a function of wavelength and STO American Petroleum Institute (API) gravity. As illustrated in  FIG. 3 , the spectrum of STO can vary significantly depending upon its type. Moreover, because of the large spectrum variation around channels 1650 nm and 1710 nm, not knowing the STO type may have a profound impact on the detection of light hydrocarbons (C1 through C5, i.e., C1-5) having main absorptions that fall in this band of wavelengths. 
   After a live oil is flashed, most volatile hydrocarbon components (C1-5) vaporize into their gaseous phase. In fact, substantially all of C1, C2 and CO 2  are in the gaseous phase after flashing. Thus, a flashed STO contains mainly non-volatile hydrocarbons (C6+). From the point of NIR spectroscopy, the major hydrocarbon components in STO may be classified into three types:
         Saturated long-chain alkane with no or few branches. Wax is representative of hydrocarbons of this type, which are primarily straight long-chain alkanes with few branches, usually from C17 to C90+. For this type of hydrocarbon, the molecule structure is dominated by —CH 2 — group, so its NIR spectroscopy shows strong character of —CH 2 — absorption, like that of n-decane (nC10).   Saturated alkane with lots of branches. Typically, the more branches an alkane has, the more —CH 3  groups in molecule, so the branched alkanes contain more —CH 3  groups than the wax type of hydrocarbons. The molecular structures of the straight-chain nC10 and a branched C10 are shown below. Although both compounds have the same formula, C 10 H 22 , their molecular structures are significantly different, and the ratio of —CH 3  to —CH 2 — group varies from 1:5 for the straight-chain C10 to 3:1 for the branched C10. Therefore, the NIR spectroscopy of the branched alkanes shows more characters of —CH 3  absorption in addition to —CH 2 — absorption properties.       

   
     
       
       
           
           
       
     
       
       
         
           Aromatics hydrocarbons including resins and asphaltenes that contain benzene rings in their molecules. Because of the effect of the combined benzene rings, the NIR spectroscopy of asphaltene can be different than both the waxy and branched-alkane types of hydrocarbons. 
         
       
     
  
     FIG. 4  illustrates example OD values for a very waxy STO and a non-waxy volatile STO. The waxy STO shows the characteristics of —CH 2 — absorption, which substantially matches nC10 spectrum. On the other hand, the non-waxy volatile STO shows more characteristics of —CH 3  group, which substantially matches the spectrum of a diesel that contains large amount of branched alkanes. 
     FIG. 5  illustrates example OD values for sixteen different types of STOs. A first thick curve  505  represents waxy STO and a second thick curve  510  represents diesel. The two curves  505  and  510  represent two extreme cases of STO spectrum; waxy type (—CH 2 —) and branched-alkane type (—CH 3 ). The spectra of almost all other types of STO are between these two extreme cases, depending on the contents of wax and branched-alkane. The waxy type STO has strong absorptions at channels ranging from 1725 nm to 1814 nm and weak absorption at channels ranging from 1650 nm to 1710 nm. On the other hand, the branched-alkane type STO has weaker absorptions from 1725 nm to 1814 nm and stronger absorptions from 1650 nm to 1710 nm, which is opposite to the waxy type STO. 
     FIG. 6  shows the relationship between the channels 1690 nm and 1800 nm, as the STO type varies from the waxy type to the branched-alkane type. As illustrated in the examples of  FIGS. 5 and 6 , the STO type may be determined from the channels 1725 nm to 1814 nm, and the absorptions of the STO channels 1650 nm to 1710 nm may be determined and then used into account for composition analysis. 
   During fluid analysis and/or measurement (e.g., downhole), only OD values for the live oil are available. However, the spectrum of the live oil may be substantially different than the spectrum of the STO.  FIG. 7  illustrates example OD values for a particular STO, and two live oils formed from the combination of the same STO and gas at different GOR values. 
   To determine an STO type based on a live-oil spectra, the live-oil spectra may be normalized by channel 1740 nm and for C1 content.  FIG. 8  illustrates the example live-oil spectra of  FIG. 7  after normalized by channel 1740 nm and for C1 content. Example instructions that may be carried out to normalize by channel 1740 nm and for C1 content is described below in connection with  FIG. 16 . In the illustrated example of  FIG. 8 , the normalized live-oil spectra are substantially similar for channels 1725 nm to 1814 nm, even when the content of C1 to C5 is more than 40 percent by weight. Therefore, as shown in  FIG. 8 , an STO type may be identified from channels ranging from 1725 nm to 1814 nm of the normalized live-oil spectrum. 
   For example, an STO type may be determined for a fluid sample using the following process:
     1. Define normalized spectra of waxy and branched alkane STO, and define STO_TYPE values as:
       a. STO_TYPE=1 for a “pure” waxy oil   b. STO_TYPE=0 for a “pure” branched alkane   
       2. Normalize measured live oil spectrum by channel 1740 nm and for C1 content   3. Use Channels 1725 nm to 1814 nm to compute STO_TYPE of the live oil so that
 
 OD[λ]   Live-oil   =OD[λ]   Waxy-STO   ×STO _TYPE+ OD[λ]   Branched-alkane-STO ×(1 −STO _TYPE)
 
where λ are the channel wavelengths ranging between 1725 nm to 1814 nm, OD[λ] Live-oil  is the normalized measured live oil spectrum from the previous step, OD[λ] Waxy-STO  is a normalized pre-defined waxy STO spectrum, and OD[λ] Branched-alkane-STO  is a normalized pre-defined branched-alkane STO spectrum.
   

   In addition to the waxy and branched-alkane contents, asphaltene content in STO also affects its spectrum.  FIG. 9  shows example OD values for a waxy STO, another waxy STO but with much more asphaltene and nC10 that contains no asphaltene. As illustrated in  FIG. 9 , as the asphaltene content increases, the absorption increases at channels 1650 nm to 1680 nm where C1 has the major absorption peak. If the effect illustrated in  FIG. 9  is not corrected, a derived C1 content and/or a derived GOR value may be inaccurate. 
   Asphaltene molecules may cause color absorptions from the visible (400 nm to 700 nm) to the NIR regions. As shown in  FIG. 9 , the greater the asphaltene content of an oil, the strong its color absorptions. Thus, in some examples, the asphaltene effects on channels 1650 nm to 1680 nm are identified and corrected on the basis of the color absorptions. 
     FIGS. 10 and 11  illustrate example improvements of downhole fluid composition analysis accuracy that may be achieved when an STO type is determined and then used during composition analysis.  FIG. 10  illustrates example accuracy results achievable when an STO is not determined and used during analysis.  FIG. 11  illustrates example accuracy results achievable when an STO is determined and then used during composition analysis. In the examples of  FIGS. 10 and 11 , the absolute errors in the estimate of C1 content are displayed for various fluid samples. As illustrated in  FIGS. 10 and 11 , determining an STO type and using the same during composition analysis greatly improves the average absolute error of the composition analysis (e.g., from approximately 3 percent to less than 0.5 percent). 
     FIG. 12  is a flowchart representative of an example process that may be performed to implement the example sampling tool  101  of  FIG. 1 .  FIG. 13  is a flowchart representative of an example process that may be performed to implement any or all of the example fluid analyzers  116  and  118  of  FIGS. 1  and/or  2 .  FIG. 14  is a flowchart representative of an example process that may be carried out to estimate a mass ratio of C1 to C2 (i.e., C2, C3, . . . ).  FIG. 15  is a flowchart representative of an example process that may be performed to implement the example stock-tank oil analyzer  225  of  FIG. 2 .  FIG. 16  depicts example instructions that may be carried out to determine an STO type.  FIG. 17  is a flowchart representative of an example process that may be carried out to compute a mass ratio of two components.  FIG. 18  is a flowchart representative of an example process that may be carried out to remove the effect(s) of C1 absorptions.  FIG. 19  is a flowchart representative of an example process that may be carried out to compute a mass ratio of C3-5 to C6+.  FIGS. 20A and 20B  are flowcharts representative of example processes that may be carried out to determine a CO 2  quality flag.  FIG. 21  is a flowchart representative of an example process that may be carried out to computer a mass ratio of CO 2  to all hydrocarbons (C1+).  FIG. 22  is a flowchart representative of an example process that may be carried out to refine the estimate of the mass ratio of C1 to C6+.  FIG. 23  is a flowchart representative of an example process that may be carried out to compute mass ratios of C1, C2, C3-5, C6+ and CO 2  to all hydrocarbons plus CO 2 .  FIG. 24  is a flowchart representative of an example process that may be carried out to check the results of a fluid composition analysis.  FIG. 25  is a flowchart representative of an example process that may be carried out to estimate a gas-oil-ratio (GOR) for a fluid associated with an underground geological formation based on a determined stock-tank oil type. 
   The example processes of  FIGS. 12 ,  13 ,  14 ,  15 ,  17 ,  18 ,  19 ,  20 A,  20 B,  21 ,  22 ,  23 , and/or  24 , and/or the example instructions of  FIG. 16  may be carried out by a processor, a controller and/or any other suitable processing device. For example, the example processes of  FIGS. 12 ,  13 ,  14 ,  15 ,  17 ,  18 ,  19 ,  20 A,  20 B,  21 ,  22 ,  23 , and/or  24 , and/or the example instructions of  FIG. 16  may be embodied in coded instructions stored on a tangible medium such as a flash memory, a read-only memory (ROM) and/or random-access memory (RAM) associated with a processor (e.g., the example processor  2605  discussed below in connection with  FIG. 26 ). Alternatively, some or all of the example operations of  FIGS. 12 ,  13 ,  14 ,  15 ,  17 ,  18 ,  19 ,  20 A,  20 B,  21 ,  22 ,  23 , and/or  24 , and/or the example instructions of  FIG. 16  may be implemented using any combination(s) of application specific integrated circuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)), field programmable logic device(s) (FPLD(s)), discrete logic, hardware, firmware, etc. Also, one or more the example operations of  FIGS. 12 ,  13 ,  14 ,  15 ,  17 ,  18 ,  19 ,  20 A,  20 B,  21 ,  22 ,  23 , and/or  24 , and/or the example instructions of  FIG. 16  may be implemented manually or as any combination of any of the foregoing techniques, for example, any combination of firmware, software, discrete logic and/or hardware, Further although the example processes of  FIGS. 12 ,  13 ,  14 ,  15 ,  17 ,  18 ,  19 ,  20 A,  20 B,  21 ,  22 ,  23 , and  24  are described with reference to the examples of  FIGS. 12 ,  13 ,  14 ,  15 ,  17 ,  18 ,  19 ,  20 A,  20 B,  21 ,  22 ,  23 , and/or  24 , persons of ordinary skill in the art will readily appreciate that many other methods of implementing the processes of  FIGS. 12 ,  13 ,  14 ,  15 ,  17 ,  18 ,  19 ,  20 A,  20 B,  21 ,  22 ,  23 , and/or  24 , and/or the example instructions of  FIG. 16  may be employed. for example, the order of execution of the blocks may be changed, and/or one or more of the blocks described may be changed, eliminated, sub-divided, or combined. Additionally, persons of ordinary skill in the art will appreciate that any or all of the example operations of  FIGS. 12 ,  13 ,  14 ,  15 ,  17 ,  18 ,  19 ,  20 A,  20 B,  21 ,  22 ,  23 , and/or  24 , and/or the example instructions of  FIG. 16  may be carried out sequentially and/or carried out in parallel by, for example, separate processing threads, processors, devices, discrete logic, circuits, etc. 
   The example process of  FIG. 12  begins with a fluid analyzer (e.g., any of the example fluid analyzers  116  and  118  of  FIGS. 1  and/or  2 ) collecting OD values for a fluid sample (block  1205 ). The fluid analyzer (e.g., the example water fraction corrector  215  of  FIG. 2 ) computes (e.g., estimates) the water volume fraction and then corrects for water content (block  1210 ). The fluid analyzer (e.g., the example decolorizer  220 ) performs decolorization of the water content corrected OD values (block  1215 ). The fluid analyzer (e.g., the example descatterer  222 ) then performs descattering of the water content corrected and/or color corrected OD values (block  1217 ). 
   The fluid analyzer estimates a mass ratio of C1 to C6+ by, for example, carrying out the example process of  FIG. 17  for an assumed STO type (block  1220 ). The fluid analyzer then determines if the fluid sample should be analyzed for oil or gas (block  1222 ). For example, the fluid analyzer may use the mass ratio of C1 to C6+ computed at block  1220  to determine whether to analyze for oil or gas. In particular, if the mass ratio of C1 to C6+ is greater than a threshold, the fluid sample is analyzed for gas. If the fluid sample is to be analyzed for oil (block  1222 ), the fluid analyzer performs oil composition analysis by, for example, carrying out the example process of  FIG. 13  (block  1225 ). If a result of the analysis performed at block  1225  confirms that the sample was principally composed of oil (block  1230 ), control proceeds to block  1255 . if the result indicates that the sample was not principally composed of oil (block  1230 ), the fluid analyzer performs gas composition analysis (block  1235 ). 
   Returning to block  1222 , if the fluid sample is to be analyzed for gas (block  1222 ), the fluid analyzer performs gas composition analysis (block  1240 ). If a result of the analysis performed at block  1240  confirms that the sample was principally composed of gas (block  1245 ), control proceeds to block  1255 . If the result indicates that the sample was not principally composed of gas (block  1245 ), the fluid analyzer performs oil composition analysis by, for example, carrying out the example process of  FIG. 13  (block  1250 ). 
   Continuing at block  1255 , the fluid analyzer computers a GOR value by, for example, carrying out the example process of  FIG. 25  (block  1255 ). The fluid analyzer then computes any type of quality flag that indicates the accuracy of the fluid analysis by performed by the fluid analyzer (block  1260 ). For example, the fluid analyzer may compare one or more computer values with one or more thresholds. The fluid analyzer (e.g., the example reporter  240  of  FIG. 2 ) provides (e.g., outputs, logs, reports, stores, communicates, etc.) one or more values that were computed, estimated and/or determined by the fluid analyzer (block  1265 ). control then exits from the example process of  FIG. 12 . 
   The example process of  FIG. 13  may be carried out to perform oil composition analysis. The example process of  FIG. 13  computes (e.g., estimates) an STO type and then uses the estimated STO type during subsequent composition analysis. the example process of  FIG. 13  determines the composition of a fluid sample sequentially, from the simplest component (e.g., C1) to the most complex component (e.g., C6+), and also estimates CO 2  concentration separately from other hydrocarbons. 
   The example process of  FIG. 13  begins with a composition analyzer (e.g., the example composition analyzer  230  of  FIG. 2 ) computing (e.g., estimating) a mass ratio of C1 to C2+ (i.e., C2, C3, . . . ) by, for example, carrying out the example process of  FIG. 14  (block  1305 ). The example process continues with a stock-tank oil analyzer (e.g., the example stock-tank oil analyzer  225  of  FIG. 2 ) determining (e.g., estimating) an STO type by, for example, carrying out the example process of  FIG. 15  and/or by carrying out the example instructions of  FIG. 16  (block  1310 ). 
   The composition analyzer estimates a mass ratio of C1 to C6+ by, for example, carrying out the example process of  FIG. 17  (block  1315 ). The composition analyzer then removes the effects of C1 absorption by, for example, carrying out the example process of  FIG. 18  (block  1320 ). The composition analyzer next computes a mass ratio of C2 to C6+ (block  1325 ) and a mass ratio of C3-5 to C6+ (block  1330 ) by, for example, carrying out the example process of  FIG. 17  and  FIG. 19 , respectively. 
   The composition analyzer computes a flag indicative of the quality (e.g., estimated accuracy) of the CO 2  determination by, for example, carrying out the example processes of  FIGS. 20A and 20B  (block  1335 ). The composition analyzer computes a mass ratio of CO 2  to all hydrocarbons (C1+) by, for example, carrying out the example process of  FIG. 21  (block  1340 ). The composition analyzer then refines the mass ratio of C1 to C6+ computed at block  1315  by, for example, carrying out the example process of  FIG. 22  (block  1345 ). 
   The composition analyzer computes respective mass ratios of C1, C2, C3-5, C6+ and CO 2  to all hydrocarbons plus CO 2  by, for example, carrying out the example process of  FIG. 23  (block  1350 ). The composition analyzer computes a flag that indicates whether oil or gas was the primary component of the fluid sample by, for example, carrying out the example process of  FIG. 24  (block  1355 ). Control then exits from the example process of  FIG. 13 . 
   The example process of  FIG. 14  may used to compute (e.g., estimate) a mass ratio of C1 to C2+. The example process of  FIG. 14  begins with a composition analyzer (e.g., the example composition analyzer  230  of  FIG. 2 ) computing a color absorption factor that represents the overall absorption of color at a number of wavelengths (e.g., 1070, 1290, 1500 and 1600 nm) (block  1405 ). Using any suitable method(s) and/or algorithm(s), the composition analyzer computes a response matrix  B  based on the color absorption factor for a set of filter-array channels (e.g., 1650 nm and 1725 nm after normalization by filter-array channel 1600 nm) (block  1410 ), inverts the matrix (block  1415 ), solves for the C1 and C20+ content based on the measured OD values for the filter-array channels (block  1420 ), and computes a mass ratio of R_FS based on the computed C1 and C2+ content values (block  1425 ). 
   Likewise, the composition analyzer computes a second response matrix {circumflex over (B)} based on the color absorption factor for a set of grating channels (e.g., 1649 nm and 1725 nm after normalization by grating channel 1589 nm) (block  1430 ), inverts the second matrix (block  1435 ), solves for the C1 and C2+ content based on the measured OD values for the grating channels (block  1440 ), and computes a mass ratio R_GS based on the computed C1 and C2+ content values (block  1445 ). The composition analyzer then computes the average of the computed mass ratios R_FS and R_GS. Control then exits from the example process of  FIG. 14 . 
   The example process of  FIG. 15  may used to determine (e.g., estimate) an STO type. The example process of  FIG. 15  begins with a stock-tank oil analyzer (e.g., the example stock-tank oil analyzer  225  of  FIG. 2 ) normalizing a live oil spectrum by channel 1740 nm and for C1 content by, for example, carrying out the example instructions  1605  of  FIG. 16  (block  1505 ). The stock-tank oil analyzer then computes (e.g., estimates) the STO type by, for example, solving the example mathematical expression of EQN (1) and/or carrying out the example instructions  1610  of  FIG. 16  (block  1510 ). Control then exits from the example process of  FIG. 15 . 
   The example process of  FIG. 17  may be used to compute (e.g., estimate) a mass ratio of two components (e.g., C1 to C6+, C2 to C6+, C2-5 to C6+, etc.). The example process of  FIG. 17  begins with a composition analyzer (e.g., the example composition analyzer  230  of  FIG. 2 ) computing a response matrix based on a color absorption factor and an STO type (block  1705 ). For example, the STO type may be used to scale a response value of the response matrix based upon the percentage of waxy STO versus branched-alkane type STO present in the fluid sample. 
   The composition analyzer inverts the response matrix (block  1710 ), solves for the component  1  content (e.g., C1 content) and component  2  content (e.g., C6+ content) based on the measured OD values for a channel (e.g., filter-array, grating and/or otherwise) (block  1715 ), and computes a mass ratio based on the computed component  1  and component  2  content values (block  1720 ). The composition analyzer adds the computed mass ratio to a sum of mass ratios (block  1725 ). 
   If more channels remain to be processed (block  1730 ), control returns to block  1715  to process the next channel. If all channels have been processed (block  1730 ), an average mass ratio is computed by dividing the sum of mass ratios by the number of channels processed (block  1735 ). Control then exits from the example process of  FIG. 17 . 
   Persons of ordinary skill in the art will readily appreciate that the example process of  FIG. 17  may be used to determine mass ratios for various combinations of components. Moreover, the particular channels used to compute one mass ratio (e.g., C1 to C6+) may be different than the channels used to compute a different mass ratio (e.g., C3-5 to C6+). Further, a response matrix used and/or values used to compute the response matrix at block  1705  may depend upon the particular components being analyzed by the example process of  FIG. 17 . Such response matrices and/or values used to compute the same may be determined analytically (e.g., computed using mathematical equations) and/or determined experimentally (e.g., by taking one or more measurements of fluid samples having known compositions and/or characteristics). Further still, differences of each channel (e.g., at wavelengths of 1649 nm, 1725 nm, etc.) to a common base channel (e.g., at 1600 nm or 1589 nm) may be used when solving for component  1  and component  2  content. 
   The example process of  FIG. 18  may be used to remove C1 absorptions. The example process of  FIG. 18  begins with a composition analyzer (e.g., the example composition analyzer  230  of  FIG. 2 ) computing (e.g., estimating) the amount of C1 absorption (CA) at, for example, filter-array channel 1650 nm using the following mathematical expression (block  1805 ). 
                 CA   =           (       FSOD_DC   ⁡     [   1650   ]       -     FSOD_DC   ⁡     [   1600   ]         )     *       MR       C   ⁢           ⁢     1   /   C     ⁢           ⁢   2     +         1   +     MR       C   ⁢           ⁢     1   /   C     ⁢           ⁢   2     +           *   C   ⁢           ⁢   1   ⁢   _f   ⁢     _FS   ⁡     [   1650   ]           (           MR       C   ⁢           ⁢     1   /   C     ⁢           ⁢   2     +         1   +     MR       C   ⁢           ⁢     1   /   C     ⁢           ⁢   2     +           *   C   ⁢           ⁢   1   ⁢   _f   ⁢     _FS   ⁡     [   1650   ]         +       1     1   +     MR       C   ⁢           ⁢     1   /   C     ⁢           ⁢   2     +           *     (       OD_FS1650   ⁢   _f   ⁢           ⁢   1     -     STO_TYPE   *   OD_FS1650   ⁢   _f   ⁢           ⁢   2       )         )       ⁢             EQN   ⁢           ⁢     (   2   )                 
where C1_f_FS[] characterizes C1 absorption at particular wavelengths, OD_FS1650_f1 equals 0.03, OD_FS1650_f2=0.01, FSOD_DC[] values represent decolorized filter-array channel OD values, STO_TYPE is a value representative of an STO type value, and MR C1/C2+  is a mass ratio of C1 to C2+. The values of C1_f_FS[] may be determined analytically (e.g., computed using mathematical equations) and/or determined experimentally (e.g., by taking one or more measurements of fluid samples having known compositions and/or characteristics).
 
   The composition analyzer then removes the C1 absorption from each measured channel (block  1810 ). For example, for decolorized filter-array channels FSOD_DC orig [], C1 absorption (CA) (e.g., computed using EQN (2)) may be removed using the mathematical expression shown below, where of C1_f_FS[] characterizes C1 absorption at particular wavelengths, and the subscripts orig and new represent decolorized filter-array channel OD values pre and post C1 absorption correction, respectively. 
                     FSOD_DC   new     ⁡     [   i   ]       =         FSOD_DC   orig     ⁡     [   i   ]       -     FSOD_DC   ⁡     [   1600   ]       -       CA   *   C   ⁢           ⁢   1   ⁢   _f   ⁢     _FS   ⁡     [   i   ]           C   ⁢           ⁢   1   ⁢   _f   ⁢     _FS   ⁡     [   1650   ]                     EQN   ⁢           ⁢     (   3   )                 
Control then exits from the example process of  FIG. 18 .
 
   The example process of  FIG. 19  may be used to compute (e.g., estimate) a mass ratio of C3-5 to C6+. The example process of  FIG. 19  begins with a composition analyzer (e.g., the example composition analyzer  230  of  FIG. 2 ) computing (e.g., estimating) the mass ratio of C2-5 to C6+ by, for example, carrying out the example process of  FIG. 17  (block  1905 ). The composition analyzer then computes the mass ratio of C3-5 to C6+ by computing a difference of the computed mass ratio of C2-5 to C6+ and a computed mass ratio of C2 to C6+ (e.g., computed at block  1325  of  FIG. 13 ) (block  1910 ). Control then exits from the example process of  FIG. 19 . 
   The example processes of  FIGS. 20A and 20B  may be used to determine (e.g., compute) a flag indicative of the quality (e.g., estimated accuracy) of the CO 2  determination. The example process of  FIG. 20A  begins with a composition analyzer (e.g., the example composition analyzer  230  of  FIG. 2 ) computing a first flag CO2_Q1 based on a water fraction value by, for example, carrying out the example process of  FIG. 20B  (block  2005 ). Water fraction values may be computed using, for example, the effective flow stream (EFS) model. An example method for computing water fraction values is described in the paper entitled “In-Situ Optical Fluid Analysis as an Aid to Wireline Formation Sampling,” by Smits et al, published in SPE Formation Evaluation, June 1995, pp. 91-98, and incorporated herein by reference in its entirety. The composition analyzer then computes a second flag CO 2 _Q 2  based upon a water difference value by, for example, carrying out the example process of  FIG. 20B  (block  2010 ). The composition analyzer then selects the minimum of the CO2_Q1 and CO2_Q2 flags (block  2015 ). The thresholds used at blocks  2005  and  2010  may be different. For example, the flag CO2_Q1 may be determined using a first set of thresholds and the flag CO2_Q2 may be determined using a second set of thresholds. Control then exits from the example process of  FIG. 20A . 
   The example process of  FIG. 20B  begins with a composition analyzer (e.g., the example composition analyzer  230  of  FIG. 2 ) comparing a value (e.g., a water fraction value or a water difference value) with a first threshold (e.g., 0.025) (block  2020 ). If the value is less than the first threshold (block  2020 ), the flag is set to HIGH (block  2025 ). If the value equals or exceeds the first threshold (block  2020 ), the value is compared to a second threshold (e.g. 0.05) (block  2030 ). If the value is less than the second threshold (block  2030 ), the flag is set to MEDIUM (block  2035 ). If the value equals or exceeds the second threshold (block  2030 ), the value is compared to a third threshold (e.g., 0.1) (block  2040 ). If the value is less than the third threshold (block  2040 ), the flag is set to LOW (block  2045 ). If the value equals or exceeds the third threshold (block  2040 ), the flag is set to NO COMPUTE (block  2050 ). Once the flag is set, control returns from the example process of  FIG. 20B  to, for example, the example process of  FIG. 20A  at block  2005  and/or block  2010 . Persons of ordinary skill in the art will readily appreciate that the threshold values used at blocks  2020 ,  2030  and/or  2040  may depend and/or be selected based on the type of value (e.g., water fraction or water difference) being used by the example process of  FIG. 20B  to determine the quality flag. 
   The example process of  FIG. 21  may be used tom compute (e.g., estimate) a mass ratio of CO 2  to all hydrocarbons. The example process of  FIG. 21  begins with a composition analyzer (e.g., the example composition analyzer  230  of  FIG. 2 ) computing hydrocarbon concentration factors for a filter-array channel (e.g., at 1725 nm) and a grating channel (e.g., at 1725 nm) (block  2105 ). For example, a hydrocarbon concentration factor for the 1725 nm filter-array channel (f HYD ) can be computed using EQN (4), where STO_Type is a value representative of an STO type FSOD_DC[] values represent decolorized filter-array channel OD values, MR C1/C6 , is a mass ratio of C1 to C6+, MR C2/C6 +  is a mass ratio of C2 to C6+, and MR C3-5/C6 + is a mass ratio of C3-5 to C6+. 
             
               EQN   ⁢           ⁢     (   4   )                 
The composition analyzer then computes an average hydrocarbon concentration factor from the factors computed at block  2105  (block  2110 ).
 
   Using any suitable algorithm(s) and/or method(s), the composition analyzer next computes the concentrations of the various components (e.g., C1, C2, C3, C6, etc.) (block  2115 ) and computes the total concentration of hydrocarbons based on the partial concentrations (block  2120 ). The composition analyzer also computes the concentration of CO 2  (block  2125 ). For example, the composition analyzer may remove the absorptions of hydrocarbons from two difference channels (e.g., FSOD[2010]−FSOD[1985] and FSOD[2010]−FSOD[2040]) to estimate the concentration of CO 2  for the two difference channels. Based on the partial concentrations computed at block  2115  and the concentrations of CO 2  for the two difference channels, the composition analyzer computes the mass ratio of CO 2  to all hydrocarbons (block  2130 ). For example, the mass ratio of CO 2  to C1+ may be computed using the following mathematical equation. 
                 =         0.3   ×   2.2   ×     +     0.7   ×   2.1   ×           ρ     C   ⁢           ⁢   1       +     ρ     C   ⁢           ⁢   2       +     ρ       C   ⁢           ⁢   3     -   5       +     ρ       C   ⁢           ⁢   6     +                   EQN   ⁢           ⁢     (   5   )                 
where the values of ρ x  are the various partial concentrations, ρ CO2     —     2010−1985  is the CO 2  concentration computed from the difference channel FSOD[2010]−FSOD[1985], and ρ CO2     —     2010−2040  is the CO 2  concentration computed from the difference channel FSOD[2010]−FSOD[2040]. Control then exits from the example process of  FIG. 21 .
 
   The example process of  FIG. 22  may be used to refine the mass ratio of C1 to C6+ (e.g., computed at block  1315  of  FIG. 13 ). The example process of  FIG. 22  begins with a composition analyzer (e.g., the example composition analyzer  230  of  FIG. 2 ) using any suitable algorithm(s) and/or method(s) to remove the effects of C2 absorption from a grating channel at 1665 nm (block  2205 ). The composition analyzer then computes the mass ratio of C1 to C6+ based on the grating channel at 1665 nm with C2 absorptions removed by, for example, carrying out the example process of  FIG. 17  (block  2210 ). Control then exits from the example process of  FIG. 22 . 
   The example process of  FIG. 23  may be used to compute the mass ratio of C1, C2, C3-5, C6+ and CO 2  to all hydrocarbons plus CO 2 . The example process of  FIG. 23  begins with a composition analyzer (e.g., the example composition analyzer  230  of  FIG. 2 ) computing (e.g., estimating) the mass ratio of C1 to all hydrocarbons plus CO 2  using, for example EQN (6) (block  2305 ), and the mass ratio of C2 to all hydrocarbons plus CO 2  using, for example EQN (7) (block  2310 ). The composition analyzer then computes the mass ratio of C3-5 to all hydrocarbons plus CO 2  using, for example EQN (8) (block  2315 ), the mass ratio of C6 to all hydrocarbons plus CO 2  using, for example EQN (9) (block  2320 ), and the mass ratio of CO 2  to all hydrocarbons plus CO 2  using, for example EQN (10) (block  2325 ). In the example equations EQN(6), EQN(7), EQN(8), EQN(9) and EQN(10),), MR C1/C6+  is a mass ratio of C1 to C6+, MR C2/C6+  is a mass ratio of C2 to C6+, MR C3-5/C6+  is a mass ratio of C3-5 to C6+, MR CO2/C6+  is a mass ratio of CO 2  to C6+, and MR CO2/C1+  is a mass ratio of CO 2  to C1+. Control then exits from the example process of  FIG. 23 . 
   
     
       
         
           
             
               
                 
                   R 
                   
                     C 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     1 
                   
                 
                 = 
                 
                   
                     MR 
                     
                       
                         C 
                         ⁢ 
                         
                             
                         
                         ⁢ 
                         
                           1 
                           / 
                           C 
                         
                         ⁢ 
                         
                             
                         
                         ⁢ 
                         6 
                       
                       + 
                     
                   
                   
                     
                       ( 
                       
                         1 
                         + 
                         
                           MR 
                           
                             
                               C 
                               ⁢ 
                               
                                   
                               
                               ⁢ 
                               
                                 1 
                                 / 
                                 C 
                               
                               ⁢ 
                               
                                   
                               
                               ⁢ 
                               6 
                             
                             + 
                           
                         
                         + 
                         
                           MR 
                           
                             
                               C 
                               ⁢ 
                               
                                   
                               
                               ⁢ 
                               
                                 2 
                                 / 
                                 C 
                               
                               ⁢ 
                               
                                   
                               
                               ⁢ 
                               6 
                             
                             + 
                           
                         
                         + 
                         
                           MR 
                           
                             
                               C 
                               ⁢ 
                               
                                   
                               
                               ⁢ 
                               3 
                             
                             - 
                             
                               
                                 5 
                                 / 
                                 C 
                               
                               ⁢ 
                               
                                   
                               
                               ⁢ 
                               6 
                             
                             + 
                           
                         
                       
                       ) 
                     
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     
                       ( 
                       
                         1 
                         + 
                         
                           MR 
                           
                             
                               
                                 
                                   CO 
                                   2 
                                 
                                 / 
                                 C 
                               
                               ⁢ 
                               
                                   
                               
                               ⁢ 
                               1 
                             
                             + 
                           
                         
                       
                       ) 
                     
                   
                 
               
             
             
               
                 EQN 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 
                   ( 
                   6 
                   ) 
                 
               
             
           
           
             
           
             
               
                 EQN 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 
                   ( 
                   7 
                   ) 
                 
               
             
           
           
             
           
             
               
                 EQN 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 
                   ( 
                   8 
                   ) 
                 
               
             
           
           
             
           
             
               
                 EQN 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 
                   ( 
                   9 
                   ) 
                 
               
             
           
           
             
           
             
               
                 EQN 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 
                   ( 
                   10 
                   ) 
                 
               
             
           
         
       
     
   
   The example process of  FIG. 24  may be used to check that fluid sample was correctly analyzed for oil or gas. The example process of  FIG. 24  begins with a composition analyzer (e.g., the example composition analyzer  230  of  FIG. 2 ) computing and then comparing to a threshold the ratio of the mass ratio of C1 to all hydrocarbons to the mass ratio of C6 to all hydrocarbons (block  2405 ). If the ratio exceeds the threshold (block  2405 ), the fluid sample is selected for gas analysis (block  2410 ). If the ratio does not exceed the threshold (block  2405 ), the fluid sample is selected for oil analysis (block  2415 ). 
   If the average of the OD values taken at 1725 nm, after correction for water fraction, is less than a cutoff (e.g., 0.1) (block  2420 ), the fluid sample is selected for gas analysis (block  2425 ). Once a selection for oil or gas analysis has been made, control exits form the example process of  FIG. 24 . 
   The example process of  FIG. 25  may be used to compute a gas-oil-ratio based on STO type. The example process of  FIG. 25  begins with a composition analyzer (e.g., the example composition analyzer  230  of  FIG. 2 ) computing (e.g., estimating) the amount of C1-5 in the live oil (block  2505 ), and computing the C3-5 molecular weight (block  2510 ). The composition analyzer then computes the fraction of vaporized C3-5 present in the fluid sample (block  2515 ), and revises the amount of C1-5 in the live oil (block  2520 ). 
   The composition analyzer continues by computing the fraction of vaporized C6+ (block  2525 ) and computing the density of the stock-tank oil (block  2530 ). Based on the STO type, the composition analyzer updates the fraction of vaporized C3-5 and vaporized C6+ (block  2535 ). For example, the fraction of vaporized C3-5 and vaporized C6+ may be computed using the mathematical expressions of EQN (11) and EQN (12). In equation EQN(11), STO_Type is a value representative of an STO type. In equation EQN (12), Raw_Color is a value representative of fluid coloration. For example, it may be computed as a sum of the filter channels at 1070 nm, 1290 nm and 1500 nm after subtraction of the filter channel at 1600 nm. Based on the vaporized fractions, the composition analyzer computes the GOR for the fluid sample using, for example, EQN (13) (block  2540 ). In equations EQN(11), EQN(12) and EQN(13), the values R x  represent mass ratios of respective components to all hydrocarbons plus CO 2  and may be computed, for example, by using EQN(6), EQN(7), EQN(8), EQN(9) and/or EQN(10). Control then exits from the example process of  FIG. 25 . 
   
     
       
         
           
             
               
                 
                   η 
                   
                     
                       R_C 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       3 
                     
                     - 
                     5 
                   
                 
                 = 
                 
                   
                     ( 
                     
                       1 
                       - 
                       
                         3.15 
                         
                           100 
                           × 
                           
                             ( 
                             
                               
                                 
                                   R 
                                   
                                     C 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     1 
                                   
                                 
                                 16.04 
                               
                               + 
                               
                                 
                                   R 
                                   
                                     C 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     2 
                                   
                                 
                                 30.07 
                               
                             
                             ) 
                           
                         
                       
                     
                     ) 
                   
                   × 
                   
                     ( 
                     
                       1 
                       - 
                       
                         0.1280 
                         × 
                         STO_Type 
                       
                     
                     ) 
                   
                 
               
             
             
               
                 EQN 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 
                   ( 
                   11 
                   ) 
                 
               
             
           
           
             
               
                 
                   η 
                   
                     
                       R_C 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       6 
                     
                     + 
                   
                 
                 = 
                 
                   0.0314 
                   × 
                   
                     ( 
                     
                       
                         
                           R 
                           
                             C 
                             ⁢ 
                             
                                 
                             
                             ⁢ 
                             1 
                           
                         
                         16.04 
                       
                       + 
                       
                         
                           R 
                           
                             C 
                             ⁢ 
                             
                                 
                             
                             ⁢ 
                             2 
                           
                         
                         30.07 
                       
                       + 
                       
                         
                           
                             R 
                             
                               
                                 C 
                                 ⁢ 
                                 
                                     
                                 
                                 ⁢ 
                                 3 
                               
                               - 
                               5 
                             
                           
                           69.82 
                         
                         × 
                         
                           η 
                           
                             
                               C 
                               ⁢ 
                               
                                   
                               
                               ⁢ 
                               3 
                             
                             - 
                             5 
                           
                         
                       
                       + 
                       
                         
                           R 
                           
                             CO 
                             2 
                           
                         
                         44 
                       
                     
                     ) 
                   
                   × 
                   
                     ( 
                     
                       1 
                       + 
                       
                         1.166 
                         × 
                         Raw_Color 
                       
                     
                     ) 
                   
                 
               
             
             
               
                 EQN 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 
                   ( 
                   12 
                   ) 
                 
               
             
           
           
             
               
                 GOR 
                 = 
                 
                   113076 
                   × 
                   
                     
                       
                         
                           R 
                           
                             C 
                             ⁢ 
                             
                                 
                             
                             ⁢ 
                             1 
                           
                         
                         16.04 
                       
                       + 
                       
                         
                           R 
                           
                             C 
                             ⁢ 
                             
                                 
                             
                             ⁢ 
                             2 
                           
                         
                         30.07 
                       
                       + 
                       
                         
                           
                             R 
                             
                               
                                 C 
                                 ⁢ 
                                 
                                     
                                 
                                 ⁢ 
                                 3 
                               
                               - 
                               5 
                             
                           
                           69.82 
                         
                         × 
                         
                           η 
                           
                             
                               R_C 
                               ⁢ 
                               
                                   
                               
                               ⁢ 
                               3 
                             
                             - 
                             5 
                           
                         
                       
                       + 
                       
                         
                           
                             R 
                             
                               
                                 C 
                                 ⁢ 
                                 
                                     
                                 
                                 ⁢ 
                                 6 
                               
                               + 
                             
                           
                           110.0 
                         
                         × 
                         
                           η 
                           
                             
                               R_C 
                               ⁢ 
                               
                                   
                               
                               ⁢ 
                               6 
                             
                             + 
                           
                         
                       
                       + 
                       
                         
                           R 
                           
                             CO 
                             2 
                           
                         
                         44.0 
                       
                     
                     
                       
                         
                           R 
                           
                             
                               C 
                               ⁢ 
                               
                                   
                               
                               ⁢ 
                               3 
                             
                             - 
                             5 
                           
                         
                         ⁢ 
                         
                             
                         
                         ⁢ 
                         
                           ( 
                           
                             1 
                             - 
                             
                               η 
                               
                                 
                                   R_C 
                                   ⁢ 
                                   
                                       
                                   
                                   ⁢ 
                                   3 
                                 
                                 - 
                                 5 
                               
                             
                           
                           ) 
                         
                       
                       + 
                       
                         
                           R 
                           
                             
                               C 
                               ⁢ 
                               
                                   
                               
                               ⁢ 
                               6 
                             
                             + 
                           
                         
                         ⁢ 
                         
                             
                         
                         ⁢ 
                         
                           ( 
                           
                             1 
                             - 
                             
                               η 
                               
                                 
                                   R_C 
                                   ⁢ 
                                   
                                       
                                   
                                   ⁢ 
                                   6 
                                 
                                 + 
                               
                             
                           
                           ) 
                         
                       
                     
                   
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   
                     ( 
                     
                       scf 
                       ⁢ 
                       
                         / 
                       
                       ⁢ 
                       stb 
                     
                     ) 
                   
                 
               
             
             
               
                 EQN 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 
                   ( 
                   13 
                   ) 
                 
               
             
           
         
       
     
   
     FIG. 26  is a schematic diagram of an example processor platform  2600  that may be used and/or programmed to implement any portion of the example sampling tool  101  and/or the fluid analyzers  116  and  118  described herein. For example, the processor platform  2600  can be implemented by one or more general purpose processors, processor cores, microcontrollers, etc. 
   The processor platform  2600  of the example of  FIG. 26  includes at least one general purpose programmable processor  2605 . The processor  2605  executes coded instructions  2610  and/or  2612  present in main memory of the processor  2605  (e.g., within a RAM  2615  and/or a ROM  2620 ). The processor  2605  may be any type of processing unit, such as a processor core, a processor and/or a microcontroller. The processor  2605  may execute, among other things, the example processes of  FIGS. 12 ,  13 ,  14 ,  15 ,  17 ,  18 ,  19 ,  20 A,  20 B,  21 ,  22 ,  23 ,  24  and/or  25 , and/or the example instructions of  FIG. 16  to implement any or all of the example sampling tool  101  and/or the example fluid analyzers  116  and  118  described herein. The processor  2605  is in communication with the main memory (including a ROM  2620  and/or the RAM  2615 ) via a bus  2625 . The RAM  2615  may be implemented by DRAM, SDRAM, and/or any other type of RAM device, and ROM may be implemented by flash memory and/or any other desired type of memory device. Access to the memory  2615  and  2620  may be controlled by a memory controller (not shown). The RAM  2615  may be used to store and/or implement, for example, measured OD values. 
   The processor platform  2600  also includes an interface circuit  2630 . The interface circuit  2630  may be implemented by any type of interface standard, such as a USB interface, a Bluetooth interface, an external memory interface, serial port, general purpose input/output, etc. One or more input devices  2635  and one or more output devices  2640  are connected to the interface circuit  2630 . The input devices  2635  and/or output devices  2640  may be used to receive measured OD values and/or to output result(s) of fluid composition analyses. 
   Although certain example methods, apparatus and articles of manufacture have been described herein, the scope of coverage of this patent is not limited thereto. On the contrary, this patent covers all methods, apparatus and articles of manufacture fairly falling within the scope of the appended claims either literally or under the doctrine of equivalents.