Characterization of crude oil by ultraviolet visible spectroscopy

Abstract

A system and a method for calculating and assigning an indicative value, such as cetane number, pour point, cloud point and aniline point, of a fraction of an oil sample based on an index calculated and assigned from ultraviolet visible spectroscopy data of the oil sample.

Claims

1. A system for assigning an indicative property to a fraction of an oil sample based upon ultraviolet visible spectroscopy data, the system comprising: a non-volatile memory device that stores calculation modules and data, the data including ultraviolet visible spectroscopy data indicative of absorbance values at predetermined increments between a predetermined range for the oil sample; a processor coupled to the memory; a first calculation module that calculates a crude oil ultraviolet visible index value of the fraction from the sample's weight and the absorbance values of the spectroscopy data; a second calculation module that calculates and assigns the indicative property for the fraction of the crude oil as a function of the ultraviolet visible index and density of the oil sample.

2. The system as in claim 1 wherein the oil sample is crude oil.

3. The system as in claim 1 wherein the oil sample is obtained from an oil well, stabilizer, extractor, or distillation tower.

4. The system as in claim 1 wherein the indicative property is a cetane number.

5. The system as in claim 1 wherein the indicative property is a pour point.

6. The system as in claim 1 wherein the indicative property is a cloud point.

7. The system as in claim 1 wherein the indicative property is an aniline point.

8. The system as in claim 1, wherein the first calculation module calculates and assigns the ultraviolet visible index with a summation of the absorbance values over the range of wavelengths, divided by the weight of the sample.

9. The system as in claim 1 wherein the second calculation module calculates and assigns the indicative property with a multi-variable polynomial equation with a set of predetermined constant coefficients developed using linear regression wherein the variables are the ultraviolet visible index and the density of the oil sample.

10. The system as in claim 1, wherein the first calculation module calculates and assigns the ultraviolet visible index with a summation of the absorbance values over the range of wavelengths, divided by the weight of the sample, and the second calculation module calculates and assigns the indicative property with a multi-variable polynomial equation with a set of predetermined constant coefficients developed using linear regression wherein the variables are the ultraviolet visible index and the density of the oil sample.

11. A system for assigning an indicative property to a fraction of an oil sample comprising: an ultraviolet spectrometer that outputs ultraviolet visible spectroscopy data; a non-volatile memory device that stores calculation modules and data, the data including ultraviolet visible spectroscopy data indicative of absorbance values at predetermined increments between a predetermined range for the oil sample; a processor coupled to the memory; a first calculation module that calculates a crude oil ultraviolet visible index value of the fraction from the sample's weight and the absorbance values of the spectroscopy data; a second calculation module that calculates and assigns the indicative property for the fraction of the crude oil as a function of the ultraviolet visible index and density of the oil sample.

12. The system as in claim 11, wherein the first calculation module calculates and assigns the ultraviolet visible index with a summation of the absorbance values over the range of wavelengths, divided by the weight of the sample.

13. The system as in claim 11. wherein the first calculation module calculates and assigns the ultraviolet visible index with a summation of the absorbance values over the range of wavelengths, divided by the weight of the sample, and the second calculation module calculates and assigns the indicative property with a multi-variable polynomial equation with a set of predetermined constant coefficients developed using linear regression wherein the variables are the ultraviolet visible index and the density of the oil sample.

14. A method for operating a computer to assign an indicative property to a fraction of an oil sample based upon ultraviolet visible spectroscopy data, the method comprising: entering into the computer ultraviolet visible spectroscopy data indicative of absorbance values at predetermined increments between a predetermined range for the oil sample; calculating and assigning a crude oil ultraviolet visible index value of the fraction from the sample's weight and the absorbance values of the spectroscopy data; and calculating and assigning the indicative property of a gas oil fraction as a function of the ultraviolet visible index and density of the oil sample.

15. The method as in claim 14 wherein the oil sample is crude oil.

16. The method as in claim 3 wherein the oil sample is obtained from an oil well, stabilizer, extractor, or distillation tower.

17. The method as in claim 14 wherein the indicative property is a cetane number.

18. The method as in claim 14 wherein the indicative property is a pour point.

19. The method as in claim 14 wherein the indicative property is a cloud point.

20. The method as in claim 14 wherein the indicative property is an aniline point.

21. The method as in claim 14 wherein plural indicative properties are calculated including at least two indicative properties selected from the group consisting of cetane number, pour point, cloud point and aniline point.

22. The method as in claim 14 wherein the indicative property is of a gas oil fraction boiling in the nominal range 180-370 C.

23. The method as in claim 14 wherein the ultraviolet visible spectroscopy data is obtained from an ultraviolet visible spectroscopy analysis in a wavelength range from 220-400 nm.

24. The method of claim 14, wherein the ultraviolet visible index is calculated and assigned by summation of the absorbance values over the range of wavelengths, divided by the weight of the sample.

25. The system as in claim 14, wherein the second calculation module calculates and assigns the indicative property with a multi-variable polynomial equation with a set of predetermined constant coefficients developed using linear regression wherein the variables are the ultraviolet visible index and the density of the oil sample.

26. The method as in claim 14, wherein the indicative property is calculated and assigned with a multi-variable polynomial equation with a set of predetermined constant coefficients developed using linear regression wherein the variables are the ultraviolet visible index and the density of the oil sample.

27. The method of claim 14, wherein the ultraviolet visible index is calculated and assigned by summation of the absorbance values over the range of wavelengths, divided by the weight of the sample, and the indicative property is calculated and assigned with a multi-variable polynomial equation with a set of predetermined constant coefficients developed using linear regression wherein the variables are the ultraviolet visible index and the density of the oil sample.

28. A method for assigning an indicative property to a fraction of an oil sample comprising: obtaining ultraviolet visible spectroscopy data indicative of absorbance values at predetermined increments between a predetermined range for the oil sample; entering into a computer the obtained ultraviolet visible spectroscopy data; calculating and assigning a crude oil ultraviolet visible index value of the fraction from the sample's weight and the absorbance values of the spectroscopy data; and calculating and assigning the indicative property of a gas oil fraction as a function of the ultraviolet visible index and density of the oil sample.

29. The method of claim 28, further comprising preparing the sample for ultraviolet visible spectroscopy analysis by diluting the sample with a solvent mixture of paraffinic and polar solvents.

30. The method of claim 29, wherein the paraffinic solvent contains from 5-20 carbon atoms.

31. The method of claim 29, wherein the polar solvent is selected based on is Hildebrand solubility factor or by its two-dimensional solubility parameter.

32. The method of claim 31, wherein the polar solvent has a Hildebrand solubility rating of at least 19.

33. The method of claim 31, wherein the two-dimensional solubility factors of the polar solvent are the complexing solubility parameter and the field force solubility parameter.

34. The method of claim 33, wherein the polar solvent's complexing solubility parameter component describes the hydrogen bonding and electron donor acceptor interactions.

35. The method of claim 33, wherein the polar solvent's field force solubility parameter is based on the van der Waals and dipole interactions.

36. The method of claim 29, wherein the paraffinic-to-polar solvent ratio is 70:30 or greater.

37. The method of claim 29, wherein the paraffinic-to-polar solvent ratio is 90:10 or greater.

38. The method of claim 28, wherein the ultraviolet visible index is calculated and assigned by summation of the absorbance values over the range of wavelengths, divided by the weight of the sample.

39. The method as in claim 28, wherein the indicative property is calculated and assigned with a multi-variable polynomial equation with a set of predetermined constant coefficients developed using linear regression wherein the variables are the ultraviolet visible index and the density of the oil sample.

40. The method of claim 28, wherein the ultraviolet visible index is calculated and assigned by summation of the absorbance values over the range of wavelengths, divided by the weight of the sample, and the indicative property is calculated and assigned with a multi-variable polynomial equation with a set of predetermined constant coefficients developed using linear regression wherein the variables are the ultraviolet visible index and the density of the oil sample.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) Further advantages and features of the present invention will become apparent from the following detailed description of the invention when considered with reference to the accompanying drawings, in which:

(2) FIG. 1 is a graphic plot of typical ultraviolet visible spectroscopy data for three types of a crude oil sample solution prepared as described below;

(3) FIG. 2 is a process flow diagram of steps carried out to establish a value for indicative properties of a gas oil fraction, using the system and method herein; and

(4) FIG. 3 is a block diagram of components of a system for implementing the invention according to one embodiment.

DETAILED DESCRIPTION OF INVENTION

(5) A system and method is provided for determining one or more indicative properties of a hydrocarbon sample. Indicative properties (e.g., cetane number, pour point, cloud point and aniline point) of a gas oil fraction in crude oil samples are assigned as a function of data obtained from ultraviolet visible spectroscopy data of a crude oil sample and the density of the crude oil sample.

(6) The correlations provide information about gas oil and/or naphtha indicative properties without fractionation/distillation (crude oil assays) and will help producers, refiners, and marketers to benchmark the oil quality and, as a result, valuate the oils without performing the customary extensive and time-consuming crude oil assays. The currently used crude oil assay method is costly in terms of money and time. It costs about $50,000 US and takes two months to complete one assay. With the method and system herein, the crude oil can be classified as a function of NMR data, and thus decisions can be made for purchasing and/or processing.

(7) The systems and methods are applicable for naturally occurring hydrocarbons derived from crude oils, bitumens, heavy oils, shale oils and from refinery process units including hydrotreating, hydroprocessing, fluid catalytic cracking, coking, and visbreaking or coal liquefaction. Samples can be obtained from various sources, including an oil well, stabilizer, extractor, or distillation tower.

(8) In the system and method herein, spectra are obtained by a suitable known or to be developed UV-visible spectrophotometry techniques UV-visible spectrophotometry is carried out on a sample of crude oil according to the method and system herein to provide unique information about aromatic and heteroaromatic compounds which absorb strongly in the UV region (200 nm-400 nm). Specific individual aromatic compounds and components have maxima at well-defined wavelengths. Wavelength maxima of known aromatic compounds and components are evaluated and extracted from the UV spectra of crude oils. These maxima are used to formulate indices for the aromatic content of the crude oil. These indices are used to assign one or more indicative properties of the oil, e.g., cetane number, pour point, cloud point and aniline point. Importantly, this information can be obtained relatively rapidly and inexpensively from a UV-visible scan as compared to the prior art assay methods described above.

(9) FIG. 2 shows a process flowchart in a method according to one embodiment herein. Crude oil samples are prepared and analyzed by ultraviolet visible spectrophotometry between 200-500 nm, in certain embodiments between 220-400 nm. In step 210, a crude oil sample is weighed.

(10) In step 220, solutions are prepared by dissolving a sample of the crude oil in a two-part solvent system of a paraffinic solvent having from 5-20 carbon atoms and a polar solvent, e.g., at a ratio of 90:10% v/v. In certain embodiments, effective paraffinic solvents include iso-octane. In certain embodiments, effective polar solvents include dichloromethane.

(11) The use of a polar solvent prevents precipitation of asphaltenes from the crude oil sample and ensures that all solutions are translucent for the measurement. The polar solvents are selected based on their Hildebrand solubility factors or their two-dimensional solubility parameters. The overall Hildebrand solubility factor is a well known measure of polarity and has been calculated for numerous compounds. See, for example, the Journal of Paint Technology, Vol. 39, No. 505 (February 1967). The solvents can also be described by their two-dimensional solubility parameter. See, for example, I. A. Wiehe, Polygon Mapping with Two-Dimensional Solubility Parameters, I&EC Research, 34, 661-673 (1995). The complexing solubility parameter component, which describes the hydrogen bonding and electron donor-acceptor interactions, measures the interaction energy that requires a specific orientation between an atom of one molecule and a second atom of a different molecule. The field force solubility parameter, which describes the van der Waals and dipole interactions, measures the interaction energy of the liquid that is not destroyed by changes in the orientation of the molecules.

(12) The UV absorbance of the crude oil solutions is determined, for instance, in a conventional one cm quartz cell. The absorbance values of the samples are summed at predetermined increments (e.g., even numbers, odd number, or increments of any number) between a predetermined range, e.g., between 200-500 nm, in certain embodiments between 220-400 nm to calculate the characterization index.

(13) In step 230, one or more samples of crude oil in dilute solution are analyzed by UV-visible spectrophotometry over the wavelengths 200-500 nm, in certain embodiments 220-400 nm.

(14) In step 240, the density and spectra data are entered into a computer. In step 250, the CUVISI is calculated.

(15) Equation (1) shows a crude oil ultraviolet visible index, CUVISI.

(16) $\begin{array}{cc}\mathrm{CUVISI}=\underset{i=L}{\overset{H}{.Math.}}\left({\mathrm{Absorbance}}_{\left(\mathrm{Ni}-220\right)}/x^{*}10\right);& \left(1\right)\end{array}$

(17) where:

(18) Absorbance=absorbance value of the prepared crude oil sample solution at a specific wavelength over the range L to H at intervals of N, whereby in certain embodiments L is between about 200 nm and 220 nm and H is between 400 nm and 500 nm, and N is between 1 and 3, and x is the weight of the sample used, in mg.

(19) Equations (2) through (5) show, respectively, the cetane number, pour point, cloud point and aniline point of gas oils boiling in the range 180-370 C. that can be predicted from the density and ultraviolet visible spectroscopy index (CUVISI) of crude oils. In step 260, the cetane number is calculated. In step 270, the pour point is calculated. In step 280, the cloud point is calculated. In step 290, the aniline point is calculated. While FIG. 2 shows steps 260 through 290 performed sequentially, they can be performed in any order, and in certain embodiments fewer than all can be calculated and assigned.
Cetane Number (CET)=K.sub.CET+X1.sub.CET*DEN+X2.sub.CET*DEN.sup.2+X3.sub.CET*DEN.sup.3+X4.sub.CET*(CUVISI/100)+X5.sub.CET*(CUVISI/100).sup.2+X6.sub.CET*(CUVISI/100).sup.3+X7.sub.CET*DEN*(CUVISI/100)(2);
Pour Point (PP)=K.sub.PP+X1.sub.PP*DEN+X2.sub.PP*DEN.sup.2+X3.sub.PP*DEN.sup.3+X4.sub.PP*(CUVISI/100)+X5.sub.PP*(CUVISI/100).sup.2+X6.sub.PP*(CUVISI/100).sup.3+X7.sub.PP*DEN*(CUVISI/100)(3);
Cloud Point (CP)=K.sub.CP+X1.sub.AP*DEN+X2.sub.CP*DEN.sup.2+X3.sub.CP*DEN.sup.3+X4.sub.CP*(CUVISI/100)+X5.sub.CP*(CUVISI/100).sup.2+X6.sub.CP*(CUVISI/100).sup.3+X7.sub.CP*DEN*(CUVISI/100)(4);
Aniline Point (AP)=K.sub.AP+X1.sub.AP*DEN+X2.sub.AP*DEN.sup.2+X3.sub.AP*DEN.sup.3+X4.sub.AP*(CUVISI/100)+X5.sub.AP*(CUVISI/100).sup.2+X6.sub.AP*(CUVISI/100).sup.3+X7.sub.AP*DEN*(CUVISI/100)(5);
where:
DEN=density of the crude oil sample;
CUVISI=crude oil UV visible index;
and K.sub.CET, X1.sub.CET-X7.sub.CET, K.sub.PP, X1.sub.PP-X7.sub.PP, K.sub.CP, X1.sub.CP-X7.sub.CP, K.sub.AP, and X1.sub.AP-X7.sub.AP are constants that were developed using linear regression techniques,

(20) An exemplary block diagram of a computer system 300 by which indicative property calculation modules can be implemented is shown in FIG. 3. Computer system 300 includes a processor 310, such as a central processing unit, an input/output interface 320 and support circuitry 330. In certain embodiments, where the computer 300 requires direct human interaction, a display 340 and an input device 350 such as a keyboard, mouse or pointer are also provided. The display 340, input device 350, processor 310, input/output interface 320 and support circuitry 330 are shown connected to a bus 360 which also connects to a memory unit 370. Memory 370 includes program storage memory 380 and data storage memory 390. Note that while computer 300 is depicted with the direct human interface components of display 340 and input device 350, programming of modules and importation and exportation of data can also be accomplished over the interface 320, for instance, where the computer 300 is connected to a network and the programming and display operations occur on another associated computer, or via a detachable input device, as are well known in the art for interfacing programmable logic controllers.

(21) Program storage memory 380 and data storage memory 390 can each comprise volatile (RAM) and non-volatile (ROM) memory units and can also comprise hard disk and backup storage capacity, and both program storage memory 380 and data storage memory 390 can be embodied in a single memory device or separated in plural memory devices. Program storage memory 380 stores software program modules and associated data, and in particular stores a crude oil UV visible index (CUVISI) calculation module 381 and one or more indicative property calculation modules 382-385 such as a cetane number calculation module 382, a pour point calculation module 383, a cloud point calculation module 384, and an aniline point calculation module 385. Data storage memory 390 stores data used and/or generated by the one or more modules of the present invention, including but not limited to density of the crude oil sample, UV absorbance data or portions thereof used by the one or more modules of the present system, and calculated indicative properties generated by the one or more modules of the present system.

(22) The calculated and assigned results in accordance with the systems and methods herein are displayed, audibly outputted, printed, and/or stored to memory for use as described herein.

(23) It is to be appreciated that the computer system 300 can be any general or special purpose computer such as a personal computer, minicomputer, workstation, mainframe, a dedicated controller such as a programmable logic controller, or a combination thereof. While the computer system 300 is shown, for illustration purposes, as a single computer unit, the system can comprise a group/farm of computers which can be scaled depending on the processing load and database size, e.g., the total number of samples that are processed and results maintained on the system. The computer system 300 can serve as a common multi-tasking computer.

(24) Computer system 300 preferably supports an operating system, for example stored in program storage memory 390 and executed by the processor 310 from volatile memory. According to the present system and method, the operating system contains instructions for interfacing the device 300 to the calculation module(s). According to an embodiment of the invention, the operating system contains instructions for interfacing computer system 300 to the Internet and/or to private networks.

EXAMPLE

(25) Exemplary constants K.sub.CET, X1.sub.CET-X7.sub.CET, K.sub.PP, X1.sub.PP-X7.sub.PP, K.sub.CP, X1.sub.CP-X7.sub.CP, K.sub.AP, and X1.sub.AP-X7.sub.AP were developed using linear regression techniques and are given in Table 3:

(26) TABLE-US-00003 TABLE 3 Cetane Pour Cloud Aniline Property Number (CET) Point (PP) Point (CP) Point (AP) K 472522.2 551951.6 72809.6 168599.5 X1 1629297.3 1914678.7 253698.1 553283.7 X2 1858806.6 2198029.9 291533.9 598770.2 X3 707220.4 842964.0 112071.8 213228.6 X4 13648.8 15981.5 3122.3 4138.5 X5 17763.9 24751.5 4976.9 562.7 X6 7241.0 10000.1 2006.9 239.6 X7 656.8 4616.8 1040.9 5250.3

(27) The instrument is allowed to warm up for 30 minutes prior to analysis and is auto-zeroed without cells in both sample and reference beams. The reference cell is filled with the solvent mixture then placed in the reference beam. Solutions of the crude oil sample solutions prepared as described above are successively placed in a clean quartz sample cell and the spectra are recorded against the reference solvent blank. The spectra are recorded at a scan speed of 100 nm/min with a fast response time.

(28) A sample of Arabian medium crude with a density of 0.8828 Kg/l was analyzed by UV-Visible spectroscopy. The spectra data, normalized to 10 mg/L, is shown in Table 4:

(29) TABLE-US-00004 TABLE 4 Wave Length Absor., nm 220 2.9442 222 2.8301 224 2.8296 226 2.8382 228 2.8341 230 2.8014 232 2.7397 234 2.6512 236 2.5278 238 2.3901 240 2.2547 242 2.1199 244 1.9885 246 1.8776 248 1.7951 250 1.7386 252 1.7024 254 1.6845 256 1.6781 258 1.6789 260 1.6737 262 1.6580 264 1.6311 266 1.5994 268 1.5665 270 1.5242 272 1.4714 274 1.4128 276 1.3549 278 1.3037 280 1.2559 282 1.2120 284 1.1722 286 1.1353 288 1.1002 290 1.0706 292 1.0416 294 1.0107 296 0.9769 298 0.9436 300 0.9194 302 0.9003 304 0.8711 306 0.8393 308 0.8026 310 0.7688 312 0.7390 314 0.7111 316 0.6869 318 0.6640 320 0.6436 322 0.6252 324 0.6074 326 0.5912 328 0.5746 330 0.5561 332 0.5368 334 0.5175 336 0.4980 338 0.4781 340 0.4590 342 0.4454 344 0.4302 346 0.4162 348 0.4042 350 0.3910 352 0.3786 354 0.3650 356 0.3525 358 0.3407 360 0.3288 362 0.3173 364 0.3069 366 0.2963 368 0.2870 370 0.2787 372 0.2711 374 0.2642 376 0.2574 378 0.2524 380 0.2468 382 0.2425 384 0.2394 386 0.2371 388 0.2359 390 0.2360 392 0.2351 394 0.2342 396 0.2314 398 0.2258 400 0.2174

(30) Equation (1) is applied and the data recorded in Table 4 for the sample of Arab medium crude oil produces a CUVISI of 94.9748.

(31) Applying equation (2) and the constants from Table 3,
Cetane Number (CET)=K.sub.CET+X1.sub.CET*DEN+X2.sub.CET*DEN.sup.2+X3.sub.CET*DEN.sup.3+X4.sub.CET*(CUVISI/100)+X5.sub.CET*(CUVISI/100).sup.2+X6.sub.CET*(CUVISI/100).sup.3+X7.sub.CET*DEN*(CUVISI/100)=(472522.2)+(1629297.3)(0.8828)+(1858806.6)(0.8828).sup.2+(707220.4)(0.8828).sup.3+(13648.8)(94.9748/100)+(17763.9)(94.9748/100).sup.2+(7241.0)(94.9748/100).sup.3+(656.8)(0.8828)(94.9748/100)=59

(32) Applying equation (3) and the constants from Table 3,
Pour Point (PP)=K.sub.PP+X1.sub.PP*DEN+X2.sub.PP*DEN.sup.2+X3.sub.PP*DEN.sup.3+X4.sub.PP*(CUVISI/100)+X5.sub.PP*(CUVISI/100).sup.2+X6.sub.PP*(CUVISI/100).sup.3+X7.sub.PP*DEN*(CUVISI/100)=(551951.6)+(1914678.7)(0.8828)+(2198029.9)(0.8828).sup.2+(842964.0)(0.8828).sup.3+(15981.5)(94.9748/100)+(24751.5)(94.9748/100).sup.2+(10000.1)(94.9748/100).sup.3+(4616.8)(0.8828)(94.9748/100)=9 C.

(33) Applying equation (4) and the constants from Table 3,
Cloud Point (CP)=K.sub.CP+X1.sub.CP*DEN+X2.sub.CP*DEN.sup.2+X3.sub.CP*DEN.sup.3+X4.sub.CP*(CUVISI/100)+X5.sub.CP*(CUVISI/100).sup.2+X6.sub.CP*(CUVISI/100).sup.3+X7.sub.CP*DEN*(CUVISI/100)=(72809.6)+(253698.1)(0.8828)+(291533.9)(0.8828).sup.2+(112071.8)(0.8828).sup.3+(3122.3)(94.9748/100)+(4976.9)(94.9748/100).sup.2+(2006.9)(94.9748/100).sup.3+(1040.9)(0.8828)(94.9748/100)=11 C.

(34) Applying equation (5) and the constants from Table 3,
Aniline Point (AP)=K.sub.AP+X1.sub.AP*DEN+X2.sub.AP*DEN.sup.2+X3.sub.AP*DEN.sup.3+X4.sub.AP*(CUVISI/100)+X5.sub.AP*(CUVISI/100).sup.2+X6.sub.AP*(CUVISI/100).sup.3+X7.sub.AP*DEN*(CUVISI/100)=(168599.5)+(553283.7)(0.8828)+(598770.2)(0.8828).sup.2+(213228.6)(0.8828).sup.3+(4138.5)(94.9748/100)+(562.7)(94.9748/100).sup.2+(239.6)(94.9748/100).sup.3+(5250.3)(0.8828)(94.9748/100)=66 C.

(35) Accordingly, as shown in the above example, indicative properties including cetane number, pour point, cloud point and aniline point can be assigned to the crude oil samples without fractionation/distillation (crude oil assays).

(36) In alternate embodiments, the present invention can be implemented as a computer program product for use with a computerized computing system. Those skilled in the art will readily appreciate that programs defining the functions of the present invention can be written in any appropriate programming language and delivered to a computer in any form, including but not limited to: (a) information permanently stored on non-writeable storage media (e.g., read-only memory devices such as ROMs or CD-ROM disks); (b) information alterably stored on writeable storage media (e.g., floppy disks and hard drives); and/or (c) information conveyed to a computer through communication media, such as a local area network, a telephone network, or a public network such as the Internet. When carrying computer readable instructions that implement the present invention methods, such computer readable media represent alternate embodiments of the present invention.

(37) As generally illustrated herein, the system embodiments can incorporate a variety of computer readable media that comprise a computer usable medium having computer readable code means embodied therein. One skilled in the art will recognize that the software associated with the various processes described can be embodied in a wide variety of computer accessible media from which the software is loaded and activated. Pursuant to In re Beauregard, 35 USPQ2d 1383 (U.S. Pat. No. 5,710,578), the present invention contemplates and includes this type of computer readable media within the scope of the invention. In certain embodiments, pursuant to In re Nuijten, 500 F.3d 1346 (Fed. Cir. 2007) (U.S. patent application Ser. No. 09/211,928), the scope of the present claims is limited to computer readable media, wherein the media is both tangible and non-transitory.

(38) The system and method of the present invention have been described above and with reference to the attached figure; however, modifications will be apparent to those of ordinary skill in the art and the scope of protection for the invention is to be defined by the claims that follow.