CHARACTERIZATION OF CRUDE OIL BY NEAR INFRARED SPECTROSCOPY

Abstract

A system and a method for calculating and assigning one or more indicative properties (e.g., cetane number, pour point, cloud point, aniline point) of a fraction of an oil sample based on an index calculated and assigned based on near infrared spectroscopy data of the sample.

Claims

1. A system for assigning an indicative property to a fraction of an oil sample based upon near infrared spectroscopy data, the system comprising: a non-volatile memory device that stores calculation modules and data, the data including NIR spectroscopy data indicative of absorbance values of the crude oil solution for peaks detected in a predetermined wavenumber range for the oil sample; a processor coupled to the memory; a first calculation module that calculates a near infrared absorbance index of the fraction from the data indicative of absorbance values; and a second calculation module that calculates and assigns the indicative property of the fraction as a function of the near infrared absorbance index and density of the oil sample.

2. A system for assigning an indicative property to a fraction of an oil sample comprising: a near infrared spectrometer that outputs near infrared spectroscopy data; a non-volatile memory device that stores calculation modules and data, the data including NIR spectroscopy data indicative of absorbance values of the crude oil solution for peaks detected in a predetermined wavenumber range for the oil sample; a processor coupled to the memory; a first calculation module that calculates a near infrared absorbance index of the fraction from the data indicative of absorbance values; and a second calculation module that calculates and assigns the indicative property of the fraction as a function of the near infrared absorbance index and density of the oil sample.

3. A method for operating a computer to assign an indicative property to a fraction of an oil sample based upon near infrared spectroscopy data, the method comprising: entering into the computer near infrared spectroscopy data indicative of absorbance values of the crude oil solution for peaks detected in a predetermined wavenumber range for the oil sample; calculating and assigning a near infrared absorbance index of the fraction from the data indicative of absorbance values; and calculating and assigning the indicative property of a gas oil fraction as a function of the near infrared absorbance index and density of the oil sample.

4. A method for assigning an indicative property to a fraction of an oil sample comprising: obtaining near infrared spectroscopy data indicative of absorbance values of the crude oil solution for peaks detected in a predetermined wavenumber range for the oil sample; entering into a computer the obtained near infrared spectroscopy data; calculating and assigning a near infrared absorbance index of the fraction from the data indicative of absorbance values; and calculating and assigning the indicative property of a gas oil fraction as a function of the near infrared absorbance index and density of the oil sample.

5. The method of claim 3 wherein the oil sample is crude oil.

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

7. The method of claim 3 wherein the indicative property is a cetane number.

8. The method of claim 3 wherein the indicative property is a pour point.

9. The method of claim 3 wherein the indicative property is a cloud point.

10. The method of claim 3 wherein the indicative property is an aniline point.

11. The method of claim 3 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.

12. The method of claim 3 wherein the indicative property is of a gas oil fraction boiling in the nominal range 180-370° C.

13. The method of claim 4, wherein the predetermined wavenumber range is 4,000-12,821 cm.sup.−1.

Description

BRIEF DESCRIPTION OF THE DRAWING

[0022] 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:

[0023] FIG. 1 is a graphic plot of typical near infrared spectroscopy data for three types of crude oil;

[0024] FIG. 2 is a process flow diagram of steps carried out to characterize the API gravity of a crude oil sample, using the system and method herein; and

[0025] FIG. 3 is a block diagram of a component of a system for implementing the invention, according to one embodiment.

DETAILED DESCRIPTION OF INVENTION

[0026] 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 NIR data of a crude oil sample and the density of the crude oil sample.

[0027] 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.

[0028] 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.

[0029] In the system and method herein, spectra are obtained by a suitable known or to be developed near infrared spectroscopy techniques. Infrared energy is the electromagnetic energy of molecular vibration. The energy band is defined for convenience as the near infrared (0.78-2.50 microns), the infrared (or mid-infrared) 2.50-40.0 microns, and the far infrared (40.0-1000 microns). However, even though official standards, textbooks, and the scientific literature generally state that the NIR spectral region extends from 780-2500 nanometers (12821-4000 cm−1), a simple set of liquid phase hydrocarbon spectra demonstrates that the vibrational information characterized by the harmonic vibrations of the C—H stretch fundamental and their corresponding combination bands occurs from approximately 690-3000 nm. The predominant near-infrared spectral features include: the methyl C—H stretching vibrations, methylene C—H stretching vibrations, aromatic C—H stretching vibrations, and O—H stretching vibrations. Minor but still important spectral features include: methoxy C—H stretching, carbonyl associated C—H stretching; N—H from primary amides, secondary amides (both alkyl, and aryl group associations), N—H from primary, secondary, and tertiary amines, and N—H from amine salts.

[0030] Qualitative and quantitative near infrared (NIR) spectroscopic methods typically require the application of multivariate calibration algorithms and statistical methods (i.e. chemometrics) to model NIR spectral response to chemical or physical properties of the samples used for calibration. The NIR method relies on the spectra-structure correlations existing between a measured spectral response caused by the harmonics of the fundamental vibrations occurring at infrared frequencies. These harmonic vibrations occur at unique frequencies depending upon the quantity of absorber (analyte), type of absorbing molecules present within the sample, and the sample thickness. Quantitative methods are possible where changes in the response of the near infrared spectrometer are proportional to changes in the concentration of chemical components, or in the physical characteristics (scattering/absorptive properties) of samples undergoing analysis

[0031] Near infrared spectroscopy is used where multicomponent molecular vibrational analysis is required in the presence of interfering substances. The near infrared spectra consist of overtones and combination bands of the fundamental molecular absorptions found in the mid infrared region. Near infrared spectra consist of generally overlapping vibrational bands that may appear non-specific and poorly resolved. The use of chemometric mathematical data processing and multiple harmonics can be used to calibrate for qualitative of quantitative analysis despite these apparent spectroscopic limitations. Traditional near infrared spectroscopy has been most often used for analysis of lignin polymers (2270 nm), paraffins and long alkane chain polymers (2310 nm), glucose based polymers such as cellulose (2336 nm), amino acid polymers as proteins (2180 nm), carbohydrates (2100 nm), and moisture (1440 and 1940 nm). When analyzing synthetic and natural materials NIR spectroscopy has shown unprecedented industrial success in multiple applications. The basic uses of near infrared spectroscopy have been for process control, quality assessment, identification of raw materials and process byproducts, and chemical quantitative analysis of complex mixtures.

[0032] Note that a near infrared spectrum consists in the convolution of the measuring instrument function with the unique optical characteristics of the sample being measured (i.e. the sample is an active optical element of the spectrometer). The reference values are those chemical or physical parameters to be predicted using the NIR spectroscopic measurements. A spectrum may, or may not, contain information related to the sample chemistry measured using any specific reference method. Spectra-structure correlation provides a basis for the establishment of a known cause and effect relationship between instrument response and reference (analyte) data, in order to provide a more scientific basis for multivariate-based near infrared spectroscopy. When performing multivariate calibrations, analytically valid calibration models require a relationship between X (the instrument response data or spectrum), and Y (the reference data). The use of probability alone tells us only if X and Y ‘appear’ to be related. If no cause-effect relationship exists between spectra-structure correlation and reference values the model will have no true predictive importance. Thus, knowledge of cause and effect creates a basis for scientific decision-making.

[0033] Factors affecting the integrity of the teaching samples used to calibrate spectrophotometers for individual NIR applications include the variations in sample chemistry, the physical condition of samples, and the measurement conditions. Teaching Sets must represent several sample ‘spaces’ to include: compositional space, instrument space, and measurement condition (sample handling and presentation) space. Interpretive spectroscopy is a key intellectual process in approaching NIR measurements if one is to achieve an analytical understanding of these measurements.

[0034] Near-infrared (NIR) spectroscopy has been employed for the characterization of products derived from petroleum, such as gasoline and diesel fuel, with considerable success. The intrinsic capacity of the NIR spectrum to obtain information on the different types of C—H bonds as well as other chemical bonds of interest (such as S—H and N—H) has been proved to be valuable in the prediction of quality parameters such as octane number, ethanol content, MTBE (methyl tert-butyl ether) content, distillation points, Reid vapor pressure and aromatic and saturated contents in gasoline. The information present in the NIR spectrum can be successfully applied to assign quality parameters for gas oil fractions such as cetane number, pour point, cloud point and aniline point.

[0035] FIG. 2 shows a process flowchart of steps in a method according to one embodiment herein. In step 210, a crude oil sample is weighed. In step 220, crude oils were analyzed by near infrared spectroscopy, e.g., in accordance with the instructions of the equipment manufacturer. No dilution or special preparation is required.

[0036] Equation (1) shows a near infrared absorbance index (NIRA):

[00001]$\begin{array}{cc}\mathrm{NIRA}=\underset{i=4,000}{\overset{12,821}{.Math.}}.Math..Math.({\mathrm{Absorbance}}_{\left(i\right)}/10,000& \left(1\right)\end{array}$

[0037] where:

[0038] Absorbance=absorbance value of the crude oil solution for peaks detected over a predetermined wavenumber range, e.g., over the range 4,000 cm.sup.−1 to 12,821 cm.sup.−1.

[0039] The indicative properties (i.e., the cetane number, pour point, cloud point and aniline point) of the gas oil fraction, e.g., boiling in the range of 150-400° C. and in certain embodiments in the range of 180-370° C., are assigned as a function of the density of whole crude oil and the near infrared absorbance index (NIRA) of crude oil. That is,

Indicative Property=f(density.sub.crude oil,NIRA.sub.crude oil)  (2)

[0040] Equations (3) through (6) are detailed examples of this relationship, respectively showing the cetane number, pour point, cloud point and aniline point that can be predicted from the density and near infrared spectroscopy of crude oils.

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*NIRA+X5.sub.CET*NIRA.sup.2+X6.sub.CET*NIRA.sup.3+X7.sub.CET*DEN*NIRA  (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*NIRA+X5.sub.PP*NIRA.sup.2+X6.sub.PP*NIRA.sup.3+X7.sub.PP*DEN*NIRA  (4)

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*NIRA+X5.sub.CP*NIRA.sup.2+X6.sub.CP*NIRA.sup.3+X7.sub.CP*DEN*NIRA  (5)

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*NIRA+X5.sub.AP*NIRA.sup.2+X6.sub.AP*NIRA.sup.3+X7.sub.AP*DEN*NIRA  (6)

[0041] where:

[0042] DEN=density of the crude oil sample at 15° C.;

[0043] NIRA=near infrared absorbance (derived from near infrared spectra);

[0044] and K.sub.CET, X1.sub.CET-X7.sub.CET, K.sub.PP, X1.sub.PP-X7.sub.PP, K.sub.AP, X1.sub.CP-X7.sub.CP, K.sub.AP, and X1.sub.AP-X7.sub.AP are constants.

[0045] In step 250, the cetane number is calculated. In step 260, the pour point is calculated. In step 270, the cloud point is calculated. In step 280, the aniline point is calculated.

[0046] 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.

[0047] 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 near infrared absorbance index (NIRA) 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 density of the oil sample, NIR spectroscopy 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.

[0048] 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.

[0049] 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.

[0050] The computing device 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

[0051] 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 give in Table 3:

TABLE-US-00003 TABLE 3 Cetane Number Cloud (CET) Pour Point (PP) Point (CP) Aniline Point (AP) K −181844.7 −1373741.5 −567845.2 760795.9 X1 576360.4 4551764.5 1890384.7 −2548841.4 X2 −593268.7 −4984097.0 −2082457.0 2831541.0 X3 196815.2 1802114.2 758773.6 −1042818.6 X4 −14874.9 −43934.6 −15153.0 14832.5 X5 1230.5 5414.9 2411.3 −2461.4 X6 −916.9 −3397.2 −1430.5 1412.8 X7 16450.1 47134.2 15879.7 −15424.7

[0052] A sample of Arabian medium crude with a density of 0.8828 Kg/l was analyzed by near infrared spectroscopy. The spectra data is presented in Table 4 and is shown in FIG. 1 as the sample with an API gravity of 28.8°. The near infrared spectroscopy index (NIRA) is calculated by summing the absorbances of the detected peaks and then dividing by 10,000, with the value in the example calculated as 0.7576.

[0053] Applying equation 3 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*NIRA+X5.sub.CET*NIRA.sup.2+X6.sub.CET*NIRA.sup.3+X7.sub.CET*DEN*NIRA

=(−181844.7)+(576360.4)(0.8828)+(−593268.7)(0.8828).sup.2+(196815.2)(0.8828).sup.3+(−14874.9)(0.7576)+(1230.5)(0.7576).sup.2+(−916.9)(0.7576).sup.3+(16450.1)(0.8828)(0.7576)

=59

[0054] Applying equation 4 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*NIRA+X5.sub.PP*NIRA.sup.2+X6.sub.PP*NIRA.sup.3+X7.sub.PP*DEN*NIRA

=(−1373741.5)+(4551764.5)(0.8828)+(−4984097.0)(0.8828).sup.2+(1802114.2)(0.8828).sup.3+(−43934.6)(0.7576)+(5414.9)(0.7576).sup.2+(−3397.2)(0.7576).sup.3+(47134.2)(0.8828)(0.7576)

=−9° C.

[0055] Applying equation 5 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*NIRA+X5.sub.CP*NIRA.sup.2+X6.sub.CP*NIRA.sup.3+X7.sub.CP*DEN*NIRA

=(−567845.2)+(1890384.7)(0.8828)+(−2082457.0)(0.8828).sup.2+(758773.6)(0.8888).sup.3+(−15153.0)(0.7576)+(2411.3)(0.7576).sup.2+(−1430.5)(0.7576).sup.3+(15879.7)(0.8828)(0.7576)

=−10° C.

[0056] Applying equation 6 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*NIRA+X5.sub.AP*NIRA.sup.2+X6.sub.AP*NIRA.sup.3+X7.sub.AP*DEN*NIRA

=(760795.9)+(−2548841.4)(0.8828)+(2831541.0)(0.8828).sup.2+(−1042818.6)(0.8828).sup.3+(14832.5)(0.7576)+(−2461.4)(0.7576).sup.2+(1412.8)(0.7576).sup.3+(−15424.7)(0.8828)(0.7576)

=66° C.

[0057] 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).

[0058] 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.

[0059] 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 Nuuten, 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.

[0060] 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.

TABLE-US-00004 TABLE 4 cm.sup.−1 Absorb. 12493 3.61 12489 3.56 12485 3.52 12482 3.48 12478 3.51 12474 3.56 12470 3.57 12466 3.56 12462 3.58 12458 3.6 12455 3.6 12451 3.65 12447 3.74 12443 3.72 12439 3.68 12435 3.67 12431 3.63 12428 3.6 12424 3.57 12420 3.51 12416 3.5 12412 3.57 12408 3.59 12404 3.54 12401 3.57 12397 3.68 12393 3.7 12389 3.63 12385 3.58 12381 3.58 12377 3.57 12374 3.57 12370 3.57 12366 3.56 12362 3.55 12358 3.56 12354 3.56 12350 3.54 12347 3.51 12343 3.5 12339 3.53 12335 3.6 12331 3.64 12327 3.59 12323 3.54 12320 3.57 12316 3.68 12312 3.68 12308 3.57 12304 3.5 12300 3.48 12296 3.5 12293 3.6 12289 3.66 12285 3.64 12281 3.69 12277 3.7 12273 3.62 12269 3.56 12266 3.53 12262 3.56 12258 3.63 12254 3.74 12250 3.88 12246 3.79 12242 3.7 12239 3.64 12235 3.55 12231 3.48 12227 3.47 12223 3.46 12219 3.45 12215 3.44 12212 3.42 12208 3.47 12204 3.61 12200 3.73 12196 3.67 12192 3.6 12188 3.6 12185 3.61 12181 3.59 12177 3.61 12173 3.66 12169 3.65 12165 3.62 12161 3.62 12158 3.59 12154 3.55 12150 3.56 12146 3.6 12142 3.59 12138 3.57 12134 3.62 12131 3.7 12127 3.73 12123 3.7 12119 3.62 12115 3.57 12111 3.59 12107 3.64 12104 3.62 12100 3.57 12096 3.55 12092 3.54 12088 3.53 12084 3.52 12080 3.53 12077 3.6 12073 3.72 12069 3.76 12065 3.74 12061 3.72 12057 3.71 12053 3.72 12050 3.77 12046 3.78 12042 3.7 12038 3.62 12034 3.64 12030 3.8 12026 3.98 12023 3.98 12019 3.87 12015 3.77 12011 3.7 12007 3.71 12003 3.79 11999 3.89 11996 3.88 11992 3.76 11988 3.66 11984 3.63 11980 3.65 11976 3.7 11972 3.78 11969 3.83 11965 3.78 11961 3.69 11957 3.64 11953 3.64 11949 3.69 11945 3.74 11942 3.73 11938 3.73 11934 3.8 11930 3.87 11926 3.89 11922 3.9 11918 3.95 11915 4.06 11911 4.15 11907 4.06 11903 3.94 11899 3.88 11895 3.9 11891 3.92 11888 3.92 11884 4.02 11880 4.12 11876 4.15 11872 4.16 11868 4.13 11864 4.03 11861 4.03 11857 4.28 11853 4.47 11849 4.29 11845 4.1 11841 4.16 11837 4.25 11834 4 11830 3.96 11826 4.01 11822 4.01 11818 4.01 11814 4.01 11810 4.05 11807 4.12 11803 4.17 11799 4.24 11795 4.37 11791 4.18 11787 4.09 11783 4.3 11780 4.27 11776 4.19 11772 4.12 11768 4.18 11764 4.13 11760 4.04 11756 4.05 11753 4.05 11749 4.15 11745 4.25 11741 4.26 11737 4.15 11733 4.17 11729 4.32 11726 4.35 11722 4.32 11718 4.21 11714 4.03 11710 4.08 11706 4.12 11702 4.02 11699 3.96 11695 4.12 11691 4.32 11687 4.4 11683 4.23 11679 4.22 11675 4.29 11672 4.46 11668 4.58 11664 4.41 11660 4.19 11656 4.11 11652 4.1 11648 4.15 11645 4.27 11641 4.2 11637 4.02 11633 4.08 11629 4.14 11625 4.07 11621 4.05 11618 4.11 11614 4.11 11610 4.11 11606 4.07 11602 4.11 11598 4.21 11594 4.15 11591 4.05 11587 3.99 11583 3.98 11579 4.05 11575 4.15 11571 4.21 11567 4.21 11564 4.4 11560 4.54 11556 4.37 11552 4.18 11548 4.18 11544 4.2 11540 4.16 11537 4.16 11533 4.14 11529 4.09 11525 4.05 11521 3.99 11517 3.94 11513 3.98 11510 4.03 11506 4.03 11502 4.04 11498 4.1 11494 4.21 11490 4.33 11486 4.28 11483 4.42 11479 4.27 11475 4.21 11471 4.1 11467 4.12 11463 4.13 11459 4.07 11456 4.16 11452 4.15 11448 4.07 11444 4.09 11440 4.18 11436 4.28 11432 4.2 11429 4.1 11425 4.22 11421 4.38 11417 4.25 11413 4.15 11409 4.05 11405 4.01 11402 4.11 11398 4.2 11394 4.26 11390 4.3 11386 4.11 11382 4.01 11378 4.05 11375 4.04 11371 4.02 11367 3.97 11363 3.93 11359 3.93 11355 3.99 11351 4.09 11348 4.18 11344 4.19 11340 4.16 11336 4.16 11332 4.07 11328 3.96 11324 3.94 11321 3.95 11317 4.01 11313 4.07 11309 4 11305 3.89 11301 3.84 11297 3.88 11294 3.97 11290 4.03 11286 3.99 11282 3.89 11278 3.86 11274 3.87 11270 3.85 11267 3.83 11263 3.85 11259 3.85 11255 3.84 11251 3.82 11247 3.82 11243 3.82 11240 3.81 11236 3.78 11232 3.75 11228 3.75 11224 3.83 11220 3.95 11216 4 11213 3.93 11209 3.82 11205 3.79 11201 3.87 11197 3.95 11193 3.89 11189 3.79 11186 3.72 11182 3.74 11178 3.79 11174 3.81 11170 3.8 11166 3.8 11162 3.78 11159 3.74 11155 3.68 11151 3.63 11147 3.62 11143 3.64 11139 3.66 11135 3.64 11132 3.61 11128 3.6 11124 3.64 11120 3.65 11116 3.63 11112 3.6 11108 3.56 11105 3.54 11101 3.53 11097 3.52 11093 3.5 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