PROCESS AND APPARATUS FOR ANALYSIS OF HYDROCARBON SPECIES BY NEAR INFRARED SPECTROSCOPY

Abstract: Hydrocarbon pieces, including preferably aromatic species such as benzene, toluene, xylene, and alkyl benzenes such as ethyl benzene, can be determined by measuring absorption in certain selected wavelengths in the infrared spectra, then manipulating the data, e.g., preferably by taking the first or higher derivative, and applying statistical techniques, preferably multiple linear regression (MLR) to provide an output signal indicative of the concentration of the particular specie. The output signal can be used to control refinery and chemical processes, e.g., gasoline blending, reforming, catalytic cracking, alkylation and isomerization.

Description: Process and Apparatus for Analysis of Hydrocarbon Species by Near Infrared Spectroscopy Prior art teachings of the determination of individual hydrocarbon group types such as paraffins, isoparaffins, aromatics, naphthenes, and olefins (PIANO) can be found in prior literature and patents. A preferred technique is gas liquid chromatography, wherein a sample is injected into an absorbent column swept by an elutriating inert gas, e.g., helium and the elapsed time for arrival at the end of the column is measured for each of the components, e.g., by a flame ionrzation detector, thermal conductivity, or other detector. Conventionally, the percents of each of the individual compounds detected by gas chromatography are grouped under their respective generic classifications in the PIANO classification system, and the relative percentage of each of the compounds (species) is determined in weight percent, volume percent, or mol percent as required. An example of this procedure is that taught by Analytical Automated Specialists, Inc., the detailed analysis of a reformate as shown in Example 11 and Table H. These prior techniques normally require hours. Spectral analysis is a recent development. U.S. 5,349,188 teaches the determination of octane generally, and U.S. 5,349,189 teaches the determination of hydrocarbon groups by group type analysis, e.g., "PIANO". The repeatability, precision and accuracy of spectral analysis would be valuable if it could be applied to speciation (e.g., to determine individually benzene, toluene, xylene, ethyl-benzene, and other desired species). This would be useful in refining the control of reformers which are conventionally controlled by merely measuring octane, or at most, octane and aromatics. By speciation, reformer control could be converted to become more sensitive to individual species. This would be valuable where a reformer is being run for petrochemical products, e.g., xylenes. It would also be valuable where reformulated fuels legislation mandate, maximum content of benzene. By analyzing for the specific species, the control can be more delicately balanced and economics further optimized. The present invention utilizes a combination of selected NIR wavelengths together with mathematical techniques and statistical techniques in which measurements of absorption are made and combines these with multiple regression analysis, or other statistical technique and modeling to differentiate the concentration of individual hydrocarbon species. The invention is particularly preferred for the determination of the concentration of individual aromatic species such as benzene, toluene, xylene, alkyl benzenes and ethyl benzene. Accordingly, the present invention provides a process for the analysis of hydrocarbons to determine component concentration, the improvement comprising in combination: a. measuring at at least one wavelength, the near infrared absorption in the bands of: 1. For benzene: 2100-2160 nanometers (nm) and/or 1600-1670 nm and/or 1780-1858 run; and/or 1120-1260 nm; and/or 850-925 nm; 2. For toluene: 1600-1670 nm and/or 1780-1858 nm and/or 1214-1230 nm; and/or 2000-2160 nm; and/or 860-910 nm; and/or 975-1000 nm; 3. For xylenes: 1320-1530 nm and/or 2000-2040 nm and/or 1600-1670 nm; and/or 1120-1214 nm; and/or 1780-1858 nm; and/or 2100-2160 nm; and/or 850-930 nm; and/or 940-990 nm; and/or 1015-1045 nm; 4. For alkyl benzenes: 1156-1264 nm; and/or 1600-1670 nm; and/or 1214-1230 nm; and/or 1320-1480 nm; and/or 850-900 nm; and/or 1015-1045 nm; and/or 1214-1264 nm, and/or 1970-2040 nm; more preferably 1214-1264 nm and 1970-2040 nm; 5. For n-pentane, n-hexane n-heptane and/or other n-paraffins: 1156-1264 nm; and/or 1320-1480 nm; and/or 1600-1670 nm; and/or 1780-1858 nm; and/or 1940-2100 nm; 6. For isopentane, 2-methyl hexane, 2,2-dimethylbutane, 2,3-dimethylbutane, 2-methylpentane, 3-methylpentane and/or other isoparaffins: 1156-1264 nm; and/or 1320-1500 nm; and/or 1560-1670 nm; and/or 1780-1858 nm, and/or 1900-2160 nm; 7. For methylcyclopentane and/or other naphthenes: 1156-1430 nm; and/or 1780-1858 nm; 8. For isobutylene and/or other olefins: 1132-1214 nm; and/or 1600-1670 nm; b. taking each of the absorbances measured, or a mathematical function thereof; c. performing multiple regression analysis, partial least squares analysis, or other statistical treatment using the above absorbances or functions as individual independent variables, d. assigning and applying weighting constants or their equivalents to said independent variables, e. applying the above steps using known compositions to calibrate the instrument and determine said weighting constants or equivalents, f. repeating said steps with unknown compositions, applying the weighting constants or equivalents determined during said calibration with known compositions to output a signal or signals indicative of one or more specific hydrocarbon species. Brief Description of the Drawings Figure 1 is a plot of a typical catalytic reforming process, with the preferred near infrared spectrometers of the present invention added to control heaters and/or hydrogen recycle. Figure 2 is a diagram of a control system for a continuous catalytic reformer, with feed-forward and feedback, near-infrared control. Figure 3 is a plot of the second derivative spectrum across the NIR range 1000 to 2500 nm for 52 reformate samples. Figure 4 is a control diagram for an on-line blender in a refinery with both feed-forward and feedback, near-infrared (NIR) control. Figure 5 is a control diagram of an isomerization unit in a refinery with both feed-forward and feedback, near-infrared control. Figure 6 is a control diagram of a typical hydrogen fluoride (HF) alkylation unit in a refinery, with both feed-forward and feedback, near-infrared control. Figure 7 is a control diagram of a methyl tert-butyl ether (MTBE) unit in a refinery with feed-forward, near-infrared control. Figure 8 is a typical chromatogram used for PIANO analysis of a reformate by the prior art chromatographic technique, with detector signal plotted on the vertical axis as a function of time (in minutes) on the horizontal axis. Detailed Description The hydrocarbon compositions may flow substantially intermittently or continuously past the point where the measurements are being made. The signal may control a fuel blending system feeding blending components having different benzene contents into a common zone, whereby a fuel product having a desired benzene product is produced, or may control blending of e.g., ethyl benzene or xylene, etc. Signal Processing: The absorbance signal from the measurement of the characteristic hydrocarbon species bands, used either solely or in conjunction with other bands, will preferably be mathematically processed to provide derived signals which are indicative of the concentrations (or property) being measured. Preferred techniques for mathematical processing are absorbance base line off-set corrected absorbance data; taking the first, second, third, fourth or higher derivative of the absorbance spectrum; the technique of dividing the absorbance at one wavelength by another; spectral subtraction; and various combinations of these mathematical techniques. Especially preferred is use of the second derivative. Also valuable are the well-known curve fitting techniques of Savitsky-Golay and Kubelka-Munk, and N-point smoothing (signal averaging). Other types of statistical data treatment comprise principle component analysis/regression (PCA/PCR), partial least squares (PLS), Gauss-Jordan Row reduction, etc. In these techniques, correlations are found among the constituent values of interest and one or more mathematically determined equivalent weighting constants. By equivalent weighting constant we mean to include, among other mathematical constructions known to the art, the wavelength coefficients of multiple linear regression, the factors of partial least squares regression, the scores of principal component regression, or the constants obtained from the Gauss-Jordan Row reduction algorithm. (See Harald Martens and Tormod Naes, Multivariate Calibration, John Wiley & Sons; New York, 1989 [ISBN 471-90979-3], and Honigs, D. E., Heiftje, G. M.; Hirschfeld, T., Applied Spectroscopy, 38(3), 1984, p. 317.) Also any constant obtained from any statistical calibration could be used to calculate values for unknown samples. Examples 7 and 9 use multiple linear regression and Examples 8 and 10 use partial least squares. This invention will find its greatest application in the petroleum refining industry and can be used to monitor the amounts of individual aromatic species in gasoline and middle distillate fuels (e.g., benzene content of gasoline). Another preferred application is to feed the maximum allowable benzene content for reformulated fuel regulations into gasoline blending systems using a blending program such as Ashland Petroleum's BOSS Blend Optimization and Scheduling System, Chevron's GINO (Gasoline In-line Optimization), Oil Systems, Inc. MG Blend, or other similar blending optimization programs. Other applications of the invention include various catalytic processes, such as catalytic reforming, where a knowledge of feedstock composition and product composition is preferably used to determine reactor severity, e.g., the hydrogen uptake, temperature, pressure or unit space velocity in the reforming zone. Moreover, the same analysis can be used to predict octane from the reforming step in any of the various modes of octane measurement: pump octane, motor octane, or research octane. Example 1 shows a reformer operating under near infrared analysis to control the severity of the reforming (temperature, H 2 :HC and/or unit space velocity) or moisture in the feed. Catalytic isomerization improves octane number by the conversion of normal paraffins to their isomers. A knowledge of feedstock composition and product composition is preferably used to determine the catalyst activity, the space velocity, the reactor temperature, and the n-paraffin recycle. N-pentane and n-hexane can be determined in the feed and product and used to monitor conversion efficiency to isopentane and isohexanes, which results in increased octane. Process conditions can be adjusted to optimize the formation of isoparaffins. Also, using a feed-forward control system, the optimum space velocity, and/or temperature, and/or unreacted n-paraffin recycle rate can be determined. The amount of product and cracking that occurs during the reaction to form light gases can be predicted using the feed-forward NIR. A multiplexed or multistreamed on-line NIR can be configured so that the feed and product speciation and octane numbers can be deteπnined by a single NIR which alternatively switches between the feed and product streams. Moreover, moisture, which deactivates some catalysts, can be determined in the feed to alert the operators of this problem. The invention can also be applied to catalytic alkylation which involves the reaction of low-molecular-weight olefins with an isoparaffin to form higher-molecular-weight isoparaffins with increased octane numbers and decreased Reid Vapor Pressure. Two commonly used alkylation processes use either sulfuric or hydrofluoric acid as catalysts. Solid acidic catalyst can also be used. An on-line NIR with closed-loop control can be used to optimize octane and yield, and to minimize polymerization. The envisioned control system would be capable of adjusting the temperature, acid/hydrocarbon ratio, and isoparaffm/olefin ratio, based on NIR measurements in the feed or product streams. A specific application of near-infrared, feed-forward control of alkylation can be deduced from discussions by C. J. Ryskamp, N. F. McGee and P. C. Badavas in Hydrocarbon Processing 65(11): 113-118, wherein it is stated that alkylate octane number increases, and acid consumption decreases, with increasing isobutane/olefin ratio. However, there is a tradeoff in the form of higher deisobutanizer distillation costs which are the result of the increase in isobutane recycle required to increase the ratio of isobutane to olefin. Therefore, from an economic standpoint, it is often not practical to maximize the isobutane/olefin ratio, but rather to operate at an optimum ratio which can be lower than the maximum attainable ratio. Consequently, control of this parameter is of utmost importance. Calculation of the isobutane/olefin ratio requires knowledge of the percent isobutane in the olefin charge stream, the isobutane makeup stream and the isobutane recycle stream. Gas chromatographs are often used to determine these parameters. However, as stated above, chromatography is a slow process in comparison to an on-line spectrophotometric method such as NIR. Therefore, it is advantageous to incorporate NIR according to the invention for feed-forward control in these streams. A multiplexed or multistreamed on-line NIR can be configured so that the feed and product speciations, and octane numbers can be determined by a single NIR which alternates between the feed and product streams. The feed forward NIR can determine the purity of the olefin and isoparaffin feeds, and predict the optimum temperature, acid/hydrocarbon ratio and isoparaffm/olefin ratio, for a given acid catalyst purity and water content. At these conditions, the feed-forward NIR can predict product yields of LPG grade propane liquid, normal butane liquid, C5 + alkylate, and polymers. Finally, alkylate quality can be verified by NIR speciation in a feedback on-line mode. Discussions by G. L. Funk and J. A. Feldman in Hydrocarbon Processing 62(11): 92-95 state that octane contributions of alkylate product are often predicted by aid of an Alkylate Quality Factor which is a function of the volume fraction of isobutane in the reactor effluent and which can be calculated according to results obtained by the invention. The invention will find many applications of hydrocarbon species analysis outside of the petroleum industry. An example is the monitoring of individual isomer concentration (e.g., ortho-xylene) during solvent purification in the chemical industry. Also, the invention can be used to monitor the purity of various streams, the concentration changes which occur during a chemical reaction, and even impurity concentration of hydrocarbon constituents. Analytical Equipment: Near infrared (NIR) spectrometers, Fourier Transform near infrared (FTNIR) spectrometers, and modified near infrared spectrometers of conventional design may be used with the invention. Preferred modes of operation are transmission, reflectance, and transflectance. More preferred are transmission and transflectance. Most preferred is transflectance. Suitable spectrometers are the NIR Systems Models 5000 and 6500 (both bench top and on-line versions); LT Industries Model 1200; and the Guided Wave Model 300 Series; and the Perkin Elmer PIONIR models 1024 and 1024P. The spectrometer can be operated in a quality control lab, on a batch basis(receiving signals, e.g., by a sample feeding arrangement), or, more preferably, on a continuous basis in which the fluid to be measured flows through a cell or in which a probe immersed in the flowing fluid transmits optically through a fiber-optic cable to the spectrophotometer. The techniques for sampling, measuring, and signal processing can be conventional and are well known to those skilled in the art. Blending Systems: Blending systems for use with the present invention to provide blends having desired species analysis can be of conventional design, usually involving the use of proportioning pumps or automatic control valves which control the addition rate for each of a series of components fed from different tanks or other sources. A computer receiving the output signal from the spectrophotometer can readily process the information to not only provide the target species analysis or octane number in the finished blended hydrocarbon, e.g., gasoline, but also to provide the target blend at minimum cost, given the relative costs and octane or species analysis enhancement values of the components being fed to the blending system. The present invention permits the determination of species analysis components which have previously been determined only by laboratory analysis or by relatively long slow gas chromatography techniques. The invention permits this determination of different components to be made simultaneously and nearly continuously, providing on-line (or at-line) analysis without the need to return samples to control labs in refineries. Examples of preferred blending systems include systems wherein said signal controls a fuel blending system feeding blending components having different benzene compositions into a common zone, whereby a product having a desired benzene composition is produced. Examples of preferred systems include systems wherein the hydrocarbons being monitored are involved in a chemical reaction. Examples of preferred systems include systems said signal is used to control the severity of said catalytic cracking step by adjusting catalyst: oil ratio, temperature, or recycle of naphtha or other cracked product. Example 1 (Invention Controlling Fixed Bed Catalytic Reformer) Figure 1 shows schematically the process flow of a typical semi-regenerative catalytic reforming unit. Fixed-bed reforming units containing typical reforming catalysts are shown in series as 100, 110 and 120. The operation of the unit is generally as described in Gary and Handwerk, Petroleum Refining, Marcel Dekker, third edition, 1994 under catalytic reforming and isomerization. Referring to Figure 1 , naphtha charge 90 is pumped through heat exchanger 95 into heater 98 which heats it to 496-524°C (925-975 °F) and to a first fixed bed reforming unit 100 which contains a conventional reforming catalyst, effluent from reformer 100 moves sequentially through heater 108, reactor 110 and heater 118 and reactor 120. The reformed product moves on to hydrogen separator 125 and fractionating column 135 which produces as bottoms a reformate stream high in aromatics. Hydrogen recycle compressor 130 compresses hydrogen from hydrogen separator 125 to mix with the naphtha charge 90. NIR analyzer 140 samples the effluent from the reformer, analyzes it based on calibrations shown in Table A, which sets forth for each specie, the constants k(0), k(l), k(2), k(3), in the equation below and the wavelengths at which absorption is measured together with the correlation, R and the NIR standard error of estimate as compared to the primary method shown: Concentration of Species = k(0) + k(l) x (d 2 A dλ 2 ) λl + k(2) x (d 2 A/dλ 2 ) λ2 + k(3) x (d 2 A/dλ 2 ) λ3 Where k(0) = bias coefficient k(n) = coefficient for wavelength λn (d 2 A/dλ 2 ) λn = second derivative of absorbance at wavelength λn for n = 1, 2 and 3 (wavelengths λl, λ2, and λ3) Reforming makes aromatic species. The lower the aromatics content analyzed by NIR instrument 140, the higher the temperature of heaters 98, 108 and 118 must be to increase the "severity" of the reforming process and increase the aromatics in the product stream. Isomerization and thermal cracking occur to some degree during reforming. NIR 140 can also be used to measure isoparaffin content and olefin content. According to the invention, a near-infrared (NIR) instrument 140 with closed-loop control capability and operating according to the techniques described above, is placed "at line" so that it measures a portion of the reformate product, analyzes it for aromatics and/or octane or other parameter. Noting any differences between the measured value and the desired value, the NIR closed-loop control unit 140 sends a signal to the heaters 98, 108, and 118 to increase or decrease their temperature or the temperature of any one of them. By increasing the temperature, the "severity" of the reforming process is increased which tends to increase the aromatics and/or octane number of the finished reformate product. Alternatively, (or additionally) the signal from NIR unit 140 can be used to control the hydrogen recycle compressor 130. NIR instrument 140 can also be used to monitor catalyst performance as determined by product composition at a given severity. Additionally, or alternatively, a different NIR instrument 92 (or the same NIR instrument 140 multiplexed for either multistreaming or multiplexing with fiber optics so as to analyze both the naphtha charge 90 and the reformate product), measures the naphtha charge and by "feed forward" predicts the temperature and hydrogen pressure which will be needed for heaters 98, 108 and 118, and hydrogen recycle compressor 130 in order to provide the desired product yield and level of aromatics in the reformate product being analyzed. As an additional precaution, the NIR units can also analyze for H 2 0 to determine the presence of deleterious moisture which can otherwise deactivate the reformer catalyst. The invention controls the aromatics species and/or octane number of the reformate more closely than similar methods employing gas chromatography because the NIR instrument can analyze and respond in less than about one minute, providing close control and fast response. If a specific aromatic species such as benzene is especially desired to be increased or nr imized in the reformate product, that specific species can be measured and the unit controlled based on the measured value. Similarly, space velocity can be increased in response to the NIR unit signal in order to reduce the severity of the reforming operation and reduce the aromatics in the produced reformate. Example 2 (Invention Controlling A Continuous Catalytic Reformer) Figure 2 is a diagram of a control system for a continuous catalytic reformer with both feed-forward and feedback, near-infrared (NIR) control. A UOP-type continuous catalytic reformer (CCR) unit is controlled by the NIR instruments of the present invention. In Figure 2, R is the reactor, H is the heater, RS is the catalytic regeneration section, LPS is the low pressure separator, HPS is the high pressure separator, C is the hydrogen compressor, and DBU is the debutanizer. Naphtha feed is pumped through heater H and then to reactor R which contains recirculating catalyst. Regenerator RS continuously regenerates the catalyst by burning off carbon, reducing and acidifying the catalyst, and then retaming it to the top of reactor R. The product is removed from reactor R to low-pressure separator LPS which removes hydrogen from the product. The removed hydrogen is compressed by hydrogen compressor C. The product is then directed to high-pressure separator HPS which removes additional hydrogen, a portion of which is recombined with the naphtha feed. Product from high-pressure separator HPS is directed to debutanizer DBU which removes butane and lighter hydrocarbons. The bottom fraction from debutanizer DBU is sampled and analyzed by feedback analyzer NIR1 which in turn is used in a feedback mode to control the feed rate, the temperature of heater H and the hydrogen recycle from high-pressure separator HPS. Feed-forward NIR analyzer NIR2 is also used to sample the naphtha feed for control of the feed rate, the temperature of heater H and the hydrogen recycle from high-pressure separator HPS. By use of feed-forward control in this configuration, the severity of the reforming process is adjusted based on the concentrations of aromatic-forming species (such as naphthenes) in the feeds. In this way, aromatics in the product is controlled based on the chemical properties of the feedstocks. In addition, feed-forward NIR analyzer NIR2 alerts the operator to excessive amounts of undesirable species in the feed. NIR2 may be the same instrument as NIR1 or a different NIR instrument, with feed-forward and feedback functions operating in a multiplexing or multistreaming mode. According to the invention, NIR analyzers NIR1 and NIR2 sample the feed and the stabilizer bottoms, and analyze them based on calibrations such as those shown in Table A, which sets forth the constants k(0), k(l), k(2), k(3), and the wavelengths at which absorption is measured together with the correlation, R and the NIR standard error of estimate as compared to the primary method shown. Figure 3 shows typical second-derivative spectra used for calibrations such as those shown in Table A. Typical analyses of reformate are shown in Table B, with comparison of the NIR results with results by the primary method (GC-PIANO). Example 3 (Invention Controlling a Fuel Blender) Figure 4 is a control diagram for a typical on-line blender in a refinery, with both feed-forward and feedback, near-infrared (NIR) control, as described by W. T. Welch in the Proceedings of the National Petroleum Refiners Association (NPRA), National Fuels and Lubricants Meeting, FL-93-114, 1993. In Figure 4, the use of multistreaming, whereby the component streams are switched sequentially to a single probe using valves, is illustrated; however, multiplexing, whereby a probe is located at each control point; or a combination of both; can also be used. In a multistreaming operation such as that illustrated in Figure 4, components 410, 420, 430, 440, 450 and 460 are sequentially routed to the sample cell or sample probe of NIR 470 which analyzes each stream for properties or components of interest (e.g. , benzene). A signal for each stream (proportional to vol% benzene) is then transmitted to optimizing software such as GINO. The GINO software, resident in blending computer 480, then continuously optimize and update the blend recipe, then downloads the updated recipe to Blend Ratio Control (BRC) software which is resident in Distributed Control System (DCS) 490. The BRC software is capable of controlling DCS 490 which in turn adjusts the position of valves 405, 415, 425, 435, 445, and 455 to change the flow rates of components 410, 420, 430, 440, 450 and 460, respectively. Another NIR 500 can also be used in a feedback mode. A slip stream 465 of the finished blend is directed to the sample probe or sample cell of NIR 500, which analyzes the finished blend for benzene and other properties of interest. DCS 490 then receives the feedback signal from NIR 500 in the same manner as it receives the feed-forward signals from NIR 470. The DCS 490 is configured to allow direct control of valves 405, 415, 425, 435, 445 and 455 by the feedback control loop to override the recipe established by the feed-forward control loop when necessary. NIR 500 may be the same instrument as NIR 470, with feed-forward and feedback functions operating in a multiplexing or multistreaming mode. Example 4 (Invention Controlling an Isomerization Unit with Pentane Recycle) Figure 5 is a control diagram of a typical isomerization unit in a refinery, as shown in Gary and Handwerk, Petroleum Refining, Marcel Dekker, third edition, 1994; with near-infrared control having both feed-forward and feedback control. In Figure 5, the feed stream 500 first goes to deisopentanizer 520 which removes the low-boiling isopentane product 680 as the overhead fraction. The bottom fraction 530 is then directed to dryer 540 combined with recycle hydrogen 550, to which makeup hydrogen 560 is added from dryer 570 as needed. The combined stream is directed through economizing heat exchanger 580 to heater 590, then to reactor 600, then to water cooler 610 and then to hydrogen separator 620 for separation of recycle hydrogen 550 from the product stream, which is then directed to stabilizer 630. Propane and light gases are removed from stabilizer 630 as the overhead fraction 670. The bottoms from stabilizer 630 are then directed to splitter 640 for separation of pentanes 650 as the overhead fraction, from product hexanes 660 which are removed as the bottom fraction. Pentanes 650 are recycled to deisopentanizer 520. Feed-forward control is accomplished by the use of NIR 510 to analyze feed 500, recycle pentanes 650 and/or the combined stream composed of both. Use of NIR 510 to speciate paraffins in these streams, more preferably pentanes and hexanes, can provide the refiner with important real-time information for optimization of reactor temperature, feed rate and recycle rate. Feedback control is typically accomplished for both product hexanes 660 and isopentane product 680 by NIR 690. By tracking the amounts of unreacted normal hexanes in product hexanes 660 and unreacted normal pentane in isopentane product 680, product quality is continuously monitored. Similar to the blender operation, the feedback control loop is configured with capability to override the feed-forward control loop. NIR 510 may be the same instrument as NIR 690, with feed-forward and feedback functions operating in a multiplexing or multistreaming mode. Example 5 (Invention Controlling a Hydrogen Fluoride (HF) Alkylation Unit) Figure 6 is a control diagram of a typical hydrogen fluoride (HF) alkylation unit in a refinery, as shown in Gary and Handwerk, Petroleum Refining, Marcel Dekker, third edition, 1994; with both feed-forward and feedback near-infrared control. In Figure 6, olefin feed 700 and isobutane feed 710 are directed through dryers A and B, respectively, combined with each other and then with HF acid recycle 720 before reaching acid settler C, which disengages the hydrocarbon overhead fraction 730 and immediately recycles the acid 720 through acid cooler D. Overhead fraction 730 arrives at depropanizer G which removes propane 740 as the overhead fraction and directs it to propane accumulator H, from which any remaining HF is removed in stripper J and propane caustic treater P. The bottom fraction 750 from depropanizer G is directed to deisobutanizer accumulator K, which separates this stream into isobutane overhead fraction 760 and bottom fraction 770. Isobutane 760 is recycled and combined with feed streams 700 and 710. The bottom fraction 770 is then directed to debutanizer M which removes n-butane 780 as overhead from alkylate bottom fraction 790. Feed-forward control of the isobutane/olefin ratio is accomplished by sampling olefin feed stream 700, isobutane feed or makeup stream 710 and isobutane recycle stream. The three streams are directed to NIR 800 in a multistreaming mode, or, alternatively, sampled using separate probes or flow cells in a multiplexing mode. NIR 800 the analyzes the streams for percent isobutane. This value, in combination with flow measurements and the predetermined optimum isobutane/olefin ratio, allows calculation of the flow rate of olefin feed stream 700 required to maintain the desired ratio. Feed-forward control of temperature, acid/hydrocarbon ratio and isoparaffm/olefin ratio can also be accomplished by using the NIR values for percent isobutane in olefin feed 700 and isobutane feed 710 as previously mentioned. Feedback control can involve the determination of the composition of the isobutane content in hydrocarbon overhead 730 from reactor C as well as the composition of alkylate product 790. The percent isobutane in hydrocarbon overhead 730 is used to calculate the previously-mentioned quality factor which is used to predict the contribution of the alkylate product 790 to octane numbers in blends. NIR 800 may be the same instrument as NIR 810, with feed-forward and feedback functions operating in a multiplexing or multistreaming mode. Example 6 (Invention Controlling a Methyl Tertiary Butyl Ether (MTBE) Unit) Figure 7 is a control diagram of a typical methyl tert-butyl ether (MTBE) unit in a refinery, as shown in Gary and Handwerk, Petroleum Refining, Marcel Dekker, third edition, 1994; with both feed-forward and feedback near-infrared control. A useful application of on-line feed-forward control involves a critical calculation of Isobutylene to methanol ratio. Referring to Figure 7, a UOP design, excess methanol is used to obtain almost complete conversion of the isobutylene. Isobutylene feed 700 and methanol feed 710 are combined with recycle methanol 820 and directed through cooler 720 to the top of primary reactor 730. Most of the effluent from reactor 730 is recycled but a small amount is directed to proprietary (Koch Engineering) Reaction with Distillation (RWD) column 740 which contains a catalyst section just above the feed inlet and serves as a secondary reactor. MTBE product 750 is withdrawn from the bottom of RWD column 740. Unreacted methanol and isobutylene pass through the catalyst-containing section of RWD column 740 and are converted to additional MTBE which also withdrawn from the bottom. The overhead fraction of RWD column 740, consisting mostly of unreacted methanol vapor and butanes from feed stream 700, is split into recycle stream 760 and methanol recovery stream 770. Methanol is extracted with water from recovery stream 770 in water wash column 780. Raffmate 790, consisting mainly of unreacted butanes, is used as feed for other processes. Extract 800 is distilled in tower 810, the water being recycled to wash column 780 and the distilled methanol directed to recycle methanol stream 820. NIR 830 is used in a feed-forward control loop to monitor the composition of isobutylene feed 700 the combined isobutylene/methanol stream being fed to primary reactor 730. By measuring flow rates, the amounts of butanes, butenes and isobutylenes in isobutylene feed stream 700, and percent methanol and isobutylene in combined stream 840, the methanol/isobutylene ratio can be calculated and used to control the flow of isobutylene. The methanol/isobutylene ratio is a critical parameter in this process because it is desirable to use a small excess of methanol. MTBE purity can be monitored using NIR 850. NIR 830 and NIR 850 can be a single instrument in a multiplexing or multistreaming mode. Other ether manufacturing steps (TAME, ETBE, diisopropyl, ether, etc.) can be similarly controlled. Example 7 (Speciation of Aromatics For Reformer Control According to the Invention Using MLR) Fifty-two samples of hydrocarbons are used for calibration according to the techniques of the present invention. Calibration results are shown in Table A, for PIANO and for speciation of individual compounds. Debutanizer bottoms, obtained from the bottom of the fractionating tower which removes components lighter than butane as overheads, are used as calibration samples. All samples are analyzed by gas liquid chromatography by a procedure taught by Analytical Automation Specialists, Inc., "The Detailed Analysis of Petroleum Naphthas, Reformates, Gasoline and Condensates by High-Resolution Gas chromatography", operators manual, P. O. Box 80653, Baton Rouge, Louisiana 70898, with results as shown in Table G. The NIR instrument used for the invention was an NIRSy stems on-line Model 5000 , near infrared spectrophotometer measuring all of the 52 samples. Wavelengths used and the range of volume percents is shown in Table A. The samples were selected so as to represent an increasing concentration of each of the species or components so that the entire range was covered. A multiple linear regression analysis was performed on the second derivative of the absorbances measured at the indicated wavelengths. Also shown in Table A are the regression coefficients, the multiple coefficients of correlation, and the standard errors of the estimate (calculated for this calibration set by conventional well-known statistical techniques). Eight samples are used as a prediction set for prediction of species and component concentrations in unknown samples. Again, the second derivatives of the absorbances are used as the independent variables in the multiple linear regression equations obtained from the calibration set. Results are shown in Table B. The NIRSy stems computer program supplied with the apparatus (NIR Spectral Analysis Software) was used for multiple regression analysis, although SAS or another well-known statistical program could be used as well. These programs multiply the second derivative of each absorbance at each wavelength by its respective weighting constant, then sum the products to provide a weighted value which is characteristic of the predicted percent of each respective species or component. It can be seen that the actual standard error of prediction shows excellent correlation between the model and the actual concentrations in samples not in the calibration set. Table B (reformate) shows that the invention measures concentration of species with accuracy comparable to the slow GC PIANO method, but at much faster control response times. Example 8 (The Invention Using Species Analysis and Partial Least Squares) The same 52 samples analyzed in Example 6 with multiple linear regression (MLR) results shown in Table B, were reprocessed using partial least squares regression equations (PLS). Results are shown in Table C for each species commonly requiring analysis in refinery practices. As shown under column "R", the correlation coefficients are as good or better than those obtained according to the invention using the multiple linear regression (Example 7, Table A). NIR values for all of the constituents approach the accuracy of the primary method, GC PIANO, while avoiding the man-hour requirements and delayed control response of the GC PIANO analysis. In general, GC PIANO requires approximately 3-4 hours for an analysis while an on-line NIR analysis of the same constituents with automatic input to a conventional Distributed Control System (DCS) or similar control device, requires only about thirty seconds. Thus the invention provides a substantially faster control response. Example 9 (Speciation of Aromatics For Blender Control Using Multiple Linear Regression According to the Invention) One hundred forty-three samples of hydrocarbons are used for calibration according to the techniques of the present invention. Calibration results are shown in Table D, for PIANO and for speciation of individual aromatic compounds. All samples are analyzed by gas liquid chromatography by a procedure taught by Analytical Automation Specialists, Inc., "The Detailed Analysis of Petroleum Naphthas, Reformates, Gasoline and Condensates by High-Resolution Gas chromatography", operators manual, P. O. Box 80653, Baton Rouge, Louisiana 70898, with typical results as shown in Table H. The instrument used for this example of the invention is a Perkin Elmer PIONIR 1024P, near infrared spectrophotometer measuring all of the samples. Wavelengths used and the range of volume percents is shown in Table D. The samples are selected so as to represent an increasing concentration of each of the species or components so that the entire range was covered. A multiple linear regression analysis was performed on the second derivative of the absorbances measured at the indicated wavelengths. Also shown in Table D are the regression coefficients, the multiple coefficients of correlation, and the standard errors of the estimate (calculated for this calibration set by conventional well-known statistical techniques). Example 10 (Speciation of Aromatics For Blender Control Using Partial Least Squares According to the Invention) One hundred thirty-four samples analyzed in Example 9 with multiple linear regression (MLR) results shown in Table D, were reprocessed using partial least squares regression equations (PLS). Results are shown in Table E for each species commonly requiring analysis in refinery practices. As shown under column "R", the correlation coefficients are as good or better than those obtained according to the invention using the multiple linear regression (Example 9, Table D). NIR values for all of the constituents approach the accuracy of the primary method GC PIANO, while avoiding the man-hour requirements of the GC PIANO analysis. In general, GC PIANO requires approximately 3-4 hours for an analysis. On the other hand, an on-line NIR analysis of the same constituents with automatic input to a DCS or similar control device, requires only about thirty seconds. Thus the invention provides a substantially faster control response. Nine samples were used as a prediction set for prediction of species and component concentrations in unknown samples. Again, the second derivatives of the absorbances are used as the independent variables in the PLS regression equations obtained from the calibration set. Results are shown in Table F. The NIRSystems computer program was used for partial least squares analysis, although SAS or another well-known statistical program could be used as well. It can be seen that the actual standard error of prediction shows excellent correlation between the model and the actual concentrations in samples not in the calibration set. Table F (gasoline) shows that the invention measures concentration of species with accuracy comparable to the slow GC PIANO method by a much faster control response time. Example 11 (Comparative with Species Analysis Using Conventional Gas Liquid Chromatography) Table H is a typical PIANO analysis report as performed using PIANO Software Version 6.06 Serial Number P-0182U (Analytical Automation Specialists, Inc.) The chromatogram for a reformate, shown in Figure 8, was obtained using a Hewlett-Packard Model 5890 temperature-programmed gas chromatograph with a flame ionization detector and a Supelco Petrocol DH capillary column (fused silica, 100 M x 0.25 mm i.d., df=0.5 uM). Chromatographic conditions were adjusted according to the standard methods established by the instrument manufacturer and Analytical Automation Specialists, Inc. Table H contains detailed speciation of many paraffins, isoparaffins, aromatics, naphthenes and olefins by this method. Thus it is seen that this prior art method is useful for the determination of individual species as well as compound types, and can serve as the primary method for calibration of the near-infrared instruments used in the present invention. However, as shown in Figure 8, this method is slow. Figure 8 shows an elutriation time for the last fractions of 142 min or over two hours. The PIANO method is thus seen to be too slow for efficient use in closed-loop control for many refinery processes. Example 12 (Commercial Test) Four of the equations from this work are used on-line in conjunction with the on-line near-IR InfraTane ® system located at Ashland 's Catlettsburg, Kentucky refinery. The four equations were the MLR equations for total aromatics, olefins, benzene, and toluene. As an added package for quality assurance, the unit has a protofuel system installed. A protofuel is a sample of a particular fuel or stream with known varying amounts of analytes. There are three protofuels included in this system. The system is designed to run these protofuels to monitor the equations, based upon set tolerance limits. If the equations need to be adjusted, the system does that automatically. It also has the capability to run one protofuel only. This is used where there may be a question about the prediction of the stream and a quick check on the calibration is requested. The three protofuels that were initially collected had concentrations of total aromatics, benzene, toluene, and olefins too close together. These were too similar because the initial collection times were based only upon the octane numbers of the stream. It was desired to have concentrations over a large range. One of the three protofuels was kept. The other two new protofuels, the ranges for all analytes, except benzene, were sufficient enough for use. In the case of benzene, spectra of several grab samples were collected off-line. The stream has primarily been used for gasoline blending. The stream is primarily being monitored for its research octane number and benzene content (Table I). A weekly check sample is obtained for benzene analysis by ASTM D 3606. This method agrees extremely well with GC-PIANO. However, the results of this sample and a standard are completed in approximately one hour. This is faster than the GC-PIANO method, and since only one analyte is being monitored, it is more efficient for this purpose. The only analyte from this work that is being closely monitored at this time is benzene. These results show that the goal of being able to determine benzene within 0.21 % by volume has been achieved. In this six month period, the difference between the on-line near-IR exceeded 0.21 % by volume one time, with a standard error of prediction of 0.12% by volume over this six month period. Every five months, the lamp is replaced with a new lamp because the life of the lamps are estimated at six months. Instead of running all the calibration samples again, the MLR calibrations can be transferred for use with the new lamp, since, technically, changing a lamp is similar to changing an instrument. The calibrations are transferred via Maggard's method. The equations are then slope and bias adjusted for all parameters, except benzene, using the three protofuels. The benzene equation is adjusted using a set of samples ran off-line. Near infrared spectroscopy can be used as a quantitative technique using multiple linear regression and partial least squares regression for determining the concentration of hydrocarbon groups and individual hydrocarbons amongst a complex mixture of hydrocarbons. Models have been generated and presented here for total aromatics, benzene, toluene, total xylenes and individual xylene isomers, ethylbenzene, total paraffins, n- hexane, n-heptane, total isoparaffins, isopentane, 2-methylhexane, total naphthenes, methylcyclopentane, and total olefins. Techniques have been successfully applied on-line, and in the laboratory, and are performing well. The standard error of performance over a six month period for the on-line prediction of the benzene concentration of a reformate stream was determined to be 0.21 % by volume. The technique described here serves as a faster method of analysis. The near-IR technique takes less than a minute to perform the operation, and results of several analytes are determined simultaneously. The primary methods of gas chromatography can take in excess of three hours to perform. Therefore, near-IR is a fast method of providing reliable data. This faster analysis can enhance the economics concerning analysis time and can be used on-line for advanced control of a refinery process. TABLE A. Multiple Linear Regression Equations for Reformate Using Second Derivative Data in the 1 100 - 2500 nm Range. TABLE A. Multiple Linear Regression Equations for Reformate Using Second Derivative Data in the 1 100 - 2500 nm Range. Table B Comparison of NIR Results with GC PIANO Results For Reformates in the 1100 500 nm Range using MLR Equations Table B continued Comparison of NIR Results with GC PIANO Results For Reformates in the 1100 500 nm Range using PLS Equations TABLE C. Partial Least Squares Regression Equations for Reformate Using Second Derivative Data in the 1 100 - 2500 nm Range. Table D Multiple Linear Regression Equations for Gasoline Using Second Derivative Data in the 800-1100 nm Range Compound Primary Wavelengths (nm) 2 NIR Volume % Method Range Average k(0) k(1) k(2) k(3) 1 2 3 R R STD ERROR Total Aromatics GC-PIANO 15807 - 53948 27 184 5997 849956 2093227 -941 626 1064 854 8795 0983 0966 1 35 Benzene GC-PIANO 0209 - 3464 1 021 5957 -223324 14679 -282507 886 9145 871 0894 0799 0208 Toluene GC-PIANO 1 103 - 16 177 4418 -48597 875582 577698 1586754 8845 8925 9895 0907 0823 0909 Total Xylenes GC PIANO 3869 - 17 130 6685 -10873 118346 414531 2652921 920 879 868 0882 0777 0955 m-Xylene GC-PIANO 1 942- 9108 3250 -15071 148824 618061 849797 906 973 868 0803 0644 0599 p-Xylene GC-PIANO 0742 - 3773 1 333 -0891 331 087 47028 -218 752 8675 9065 857 5 0785 0616 0265 o-Xylene GC-PIANO 1 133 - 4728 2 102 1 238 -66080 -98546 -174507 9545 8805 9645 0967 0935 0 186 Ethylbenzene GC-PIANO 0444 - 4 110 1 193 -0229 -316535 -474 194 343881 1028 861 8875 0664 0441 0329 I i -1 Table E Partial Least Squares Regression Equations for Gasoline Using Second Derivative Data In the 800-1100 nm Range w Compound Primary 2 NIR Volume % Method Range Average Wavelength Range Factors R R STD ERROR H Total Aromatics GC-PIANO 15807-53948 27184 840-900,1050-1075 3 0985 0969 12455 ►—< H Benzene GC-PIANO 0209 - 3464 1021 850 - 925 9 0935 0874 01723 H Toluene GC-PIANO 1103- 16177 4418 860-910,975-1000 6 0918 0842 0749 W Total Xylenes GC-PIANO 3869- 17130 6685 850 - 930 9 0923 0852 08112 m-Xylene GC-PIANO 1942-9108 3250 850 - 925 , 965 - 990 7 0864 0747 05271 w OO w p-Xylene GC-PIANO 0742 - 3773 1333 850 - 925 10 0881 0776 02141 H o-Xylene GC-PIANO 1133-4728 2102 865 - 900 , 940 - 975 8 0975 095 01652 Ethylbenzene GC-PIANO 0444-4110 1193 850-900,1015-1045 9 0844 0712 02494 Table F. Comparison Between GC-PIANO and NIR Results for Gasolines In the 800-1100 nm Range Using PLSR. Sample TOTAL AROMATICS BENZENE TOLUENE TOTAL XYLENES NIR GC-PIANO Λ NIR GC-PIANO Λ NIR GC-PIANO Λ NIR GC-PIANO Δ CAT-15 46 261 45 742 0 519 0 720 0 611 0 109 1 757 2 961 -1 204 11 067 10 460 0 607 CAT- 2 6 16 234 16 615 -0 381 0 854 0649 0 205 2 328 3 397 -1 069 4 412 4 004 0 408 CAT-4 2 21 188 21 476 -0 288 1 039 0 828 0 211 3 506 3 929 -0 423 5 764 5 37 2 0 392 3 CAT-86 24 050 25 780 -1 730 0 761 0 860 -0 099 3 756 4 966 -1 210 5 835 5 930 -0 095 CAT-99 24 174 22 954 1 220 0 891 1 010 -0 119 4 797 2 515 2 282 2 843 6 248 -3 405 CAT-118 28 510 29 440 -0 930 1 031 0 937 0 094 3 625 4 258 -0 633 7 192 7 040 0 152 CAT- 139 26 936 27 984 -1 048 0 904 0 615 0 289 7 695 10 2 -2 5U5 6 340 5 078 1 262 CAT-150 28 539 27 664 0 875 2 254 1 982 0 272 8 107 7 508 0 599 8 102 7 546 0 556 CAT-163 20 481 19 927 0 554 0 761 1 113 -0 352 5 387 3 877 1 510 4 919 6 103 -1 184 AVERAGES -0 134 0 068 -0 295 -0 145 Std Error of Prediction 1 001 0 227 1 531 1 397 I m-XYLENE p-XYLENE o-XYLENE ETHYLBENZENE VO I NIR GC-PIANO Λ NIR GC-PIANO Δ NIR '- PIANO Δ NIR GC Δ CAM 5 5 027 4 450 0 577 1 846 1 762 0 084 4 119 4 248 -0 129 1 613 1 V7 0 236 CAT-26 2 345 2 041 0 304 0 930 0 825 0 105 1 008 1 138 -0 130 0 914 0 847 0 067 CAT-42 2 807 2 718 0 119 1 206 1 099 0 107 1 587 1 555 0 032 1 406 1 034 0 372 CAT-86 2 771 2 918 -0 147 1 109 1 211 -0 102 1 696 1 801 -0 105 0 975 1 098 -0 123 CAT-99 1 588 3 106 -1 518 1 178 1 288 -0 110 2 118 1 854 0 264 0 381 1 191 -0 810 CAT-118 3 621 3 389 0 232 1 448 1 371 0 077 2 246 2 280 -0 034 1 743 1 226 0 017 CAM 39 3 661 2 409 1 252 1 409 0 955 0 454 1 969 1 714 0 255 1 1U9 0 789 0 400 CAM 50 2 997 3 911 -0 914 1 622 1 664 -0 042 2 155 1 971 0 184 1 596 1 722 -0 126 CAT-163 1 797 3 097 -1 300 0 765 1 378 -0613 1 324 1 628 -0 304 1 253 1 427 -0 174 AVERAGES -0 155 -0 004 0 004 -0 016 Std Error of Prediction 0 930 0 283 0 196 0 367 Table G GC-PIANO Results Listing Selected Specialions Table G GC PIANO Results Listing Selecled Specialions TABLE H. P.I.A.N.O. ANALYSIS by Analytical Automation Specialists, Inc. Licensed to: Ashland Petroleum Co. - Catlettsburg, KY Sample: LPCCR Acquired on: 05-03-1994 File: K524.ATB Normalized to 100% RI Data File, product Processed 254 Peaks Gas Chromatograph: Inj Temp Sample Size Det Temp_ Split Ratio Carrier Gas Helium Carrier Pressure_ Column Supe'.co DH-100 100M Installed on Conditions 35 deg C Rate 2 Methane set to 7 00 min. Sample LPCCR Acquired on 05-03-1994 Composite Report Hydrocarbon Totals bv Group Type Type Wt % Vol% Mol % Total Paraffins 7 321 8 831 8 355 Total Iso-paraffins 19 136 22 798 20 739 Total Naphthenes 1 490 1 578 1 531 Total Aromaucs 69913 64474 67429 Total Olefins 1 246 1 435 1 412 Total C1 + 0431 0455 0 224 Total Unknowns 0 463 0429 0 309 Total 100000 100000 100000 Totals bv Carbon Number Group Wt % Vol % Mol % Ave Mw Ave Sp Gr Methane 0 000 0 000 0000 0000 0000 Ethane 0000 0000 0 000 0000 0000 Propane 0 000 0000 0000 0000 0000 Butanes 0 193 0270 0 343 58071 0575 Pentanes 2 305 2 961 3 304 72009 0626 Hexanes 13 324 14 974 16 474 83467 0716 Heptanes 27 312 28401 29 468 95649 0773 Octanes 27 334 26 114 26 307 107228 0842 Nonaries 20 307 18 800 17 410 120369 0869 Dccancs 5 401 4 938 4163 133870 0880 Cl l s 2 189 1 953 1533 147351 0902 T l2 s 0 740 0 706 0464 164560 0844 CP's 0000 0 000 0000 0000 0000 C14+ 0 431 0455 0224 Unknowns 0463 0429 0309 Total 100000 100000 100000 104444 0797 Sample LPCCF Acquired on 05-03-1994 TVDCS bv Carbon Number Wt% Vol % Mol •/. Paraffins Cl 0000 0000 0000 C2 0000 0000 0000 C3 0000 0000 0000 C4 0148 0206 0263 C 0874 1122 1250 C6 2840 3463 1400 C7 2620 3082 2698 C8 0701 0803 0634 C9 0129 0145 0104 CIO 0009 0010 0007 Cll 0000 0000 0000 C12 0000 0000 0000 C13 0000 0000 0000 Iso- araffins C4 0040 0058 0071 S 1276 1656 1825 CC, 5766 7054 6905 C7 8913 10469 9175 C8 2613 2981 2363 C9 0369 0409 0300 C10 0012 0014 0009 Cll 0041 0044 0027 C12 0106 0113 0064 C.3 0000 0000 0000 C6 4034 3692 5329 C7 14652 13592 16410 C8 23381 21655 22727 C9 19711 18148 16927 C10 5373 4907 4143 Cl 2149 1909 1506 C12 0613 0571 0387 C13 0000 0000 0000 Naphthenes C5 0052 0056 0076 C6 0356 0381 0436 C7 0339 0364 0357 C8 0617 0651 0563 C9 0097 0098 0080 CIO 0006 0007 0005 ll 0000 0000 0000 C12 0021 0021 0013 C13 0000 0000 0000 Olefins C2 0000 0000 0000 C3 0000 0000 0000 C4 0005 0007 0009 C5 0104 0127 0153 C6 0328 0384 0403 C7 0788 0893 0828 C8 0022 0024 0020 C9 0000 0000 0000 CIO 0000 0000 0000 Cil 0000 0000 0000 C12 0000 0000 0000 cπ 0000 0000 0000 Sample LPCCR Acquired on 05-03-1994 Components Listed in Chromatographic Order pk# Min Index Component .Area Wt% Vol % Mol % Grp Shift 1 767 3679 i-Bulane 4449 0040 0058 0071 14 210 2 791 3903 Butene- 1 Λsobutvlene 272 0002 0003 0004 04 091 3 803 4000 n-Bulane 16477 0148 0206 0263 P4 000 4 815 4097 t-Butene-2 1 6 0001 0002 0002 04 058 5 835 4241 c-Butene-2 152 0001 0002 0002 04 021 6 892 4568 3-Met vlbutene-l 261 0002 0003 0003 05 119 7 932 4747 ι-Pemane 142853 1276 1656 1825 15 022 8 969 4887 pentfflie-1 476 0004 0005 0006 OS 002 9 987 4952 2-Methvlbutene-l 2405 0021 0026 0031 05 022 10 1002 5000 n-Pentane 97816 0874 1122 1250 P5 000 11 1025 5073 t-Pentene-2 1591 0014 0017 0020 05 013 12 1052 5156 c-Pentene-2 1079 0009 0011 0014 05 045 13 1069 5205 2-Methvlbutene-2 5848 0051 0062 0075 05 075 14 1134 5370 2,2-Dunethvlbutane 59789 0531 0658 0636 16 031 15 1216 5543 Cvclopentene 310 0003 0003 0004 05 046 16 1232 5580 4-Methvlpentene- 1 938 0008 0010 0010 06 040 17 1241 5597 3-Methvlpentene- 1 1341 0012 0014 0014 06 032 18 12 ->S 5660 Cvclopentane/MTBE 5974 0052 0056 0076 N5 021 19 1283 5674 2,3-Dιmethvlbutane 61481 0546 0664 0654 16 036 20 1294 5692 2,3-Dιmet vlbutene-l 867 0008 0009 0009 06 046 21 1306 5715 2-Methvlpentane 297308 2643 3254 3164 16 028 22 1390 5851 3-Methvlpentane 230156 2046 2477 2450 16 015 23 1417 5891 2-Methvlpentene- 1 5244 0045 0053 0056 06 041 24 1423 59C0 Hexene-1 1439 0012 0015 0015 06 042 25 1496 6000 n-Hexane 319475 2840 3463 3400 P6 000 26 1507 6017 t-Hexene-3 2749 0024 0028 0029 06 021 2" 1516 6030 c-Hexene-3 1098 0010 0011 0012 06 033 28 1526 6044 t-Hexene-2 5616 0049 0057 0060 06 013 29 1543 6068 2-Meth\ lpeτttene-2 8605 0075 0087 0092 06 003 30 1567 6102 2-Methvl-c-pentene-2 6403 0056 0064 0068 06 020 31 1583 6125 013 400 0003 0004 0004 06 021 32 1595 6140 c-Hexene-2 3117 0027 0031 0033 06 018 33 1642 6200 8724 0076 0087 0080 07 029 34 1677 6246 49513 0440 0525 0453 17 006 35 1697 6270 37270 0323 0347 0396 N6 010 36 1727 6307 55146 0489 0584 0503 17 035 37 Γ J 6344 249 0002 0002 0002 07 015 38 1775 6362 223-Tnmeth%lbutane 7563 0067 0078 0069 17 035 39 1833 6425 017 443 0004 0004 0004 07 021 40 1874 6467 ,4-Dιrneιhvlpentene- 1 2038 0018 0020 0019 07 014 41 1908 6502 Benzene 500525 4034 3692 5329 A6 029 42 1931 6524 3-Met Nlhexene-l 775 0007 0008 0007 07 006 43 1962 6555 50314 0446 0517 0459 17 033 44 1977 6569 754 0007 0008 0007 07 013 45 1995 6586 3763 0033 0034 0040 N6 044 46 2016 6605 2-Methvl-t-hexene-3 3037 0026 0031 0028 07 026 47 2054 6640 2-Ethvl-3-methvlbutene- 1 1348 0012 0013 0012 07 028 48 2080 6663 4-Methvl-t/c-hexene-2 7163 0062 0071 0065 .07 012 49 2099 6679 307650 2726 3231 2808 17 011 50 2117 6695 117233 1039 1202 1070 17 005 Sample LPCCR Acquired or i 05-03-1994 pk# Min Index Component Area Wt % Vol % Mol % Grp Shift 51 21 48 672 1 1 , 1 -Dimethvlcvclopentane 364S 0 032 0 034 0 033 N7 0 10 52 22 01 6764 3-Methvl exane 380066 3 297 3 860 3 396 17 0 03 53 22 39 679 5 3,4-Dιmethyl-c-petnene-2 2941 0 026 0029 0 027 θ7 0 14 54 22 75 682 3 1 c,3-Dunethvlcvclopentane 7125 0062 0066 0065 N7 0 19 55 23 10 685 0 lt,3-Dιmethylcyclopentane 7458 0 065 0070 0 068 N7 0 15 56 23 25 686 1 3-Elhylpentane 42171 0 374 0431 0 385 17 0 15 57 23 45 687 6 1 t^-Dimethylcyclopentane 11563 0 100 0 107 0 105 N7 0 02 58 23 58 688 5 •> 1306 0 012 0012 0 012 UNK 59 23 68 6892 2,2,4-Tπmethylpentane 3953 0 035 0 041 0 032 17 0 24 60 24 42 6M 5 3-Methyl-c-hexene-3 4067 0 035 0040 0 037 07 0 20 61 24 91 697 9 t-Heptene-3 6861 0 060 0 068 0 063 07 0 25 62 25 23 700 0 n-Heptane 295632 2 620 3 082 2 698 P7 0 00 63 25 48 702 0 c-Heptene-3 16668 0 145 0 165 0 152 07 0 16 64 25 63 703 1 2-Methvl-2-hexene (S47 4 0056 0063 0 059 07 0 02 63 25 89 705 1 3-Methyl-t-hexene-3 5063 0 044 0 051 0 046 07 0 40 66 26 13 706 9 3-Ethvlpentene-2 3323 0 029 0 032 0 030 07 0 21 67 26 60 710 3 c-Heptene-2 9259 0 080 0 091 0 084 07 0 29 68 27 23 714 8 2,3-Dιmethvlpentene-2 7669 0 067 0 073 0 070 07 0 03 69 28 09 720 7 1 c^-Dimethvlcvclopentane 3919 0 034 0 037 0 036 N7 0 31 70 28 22 721 6 Methylcvclohexane 2377 0 021 0 022 0 022 N7 0 10 71 2 8 71 724 8 1 , 1 ,3-Tπmethvlcvclopentane 17637 0 153 0 164 0 141 N8 003 72 30 24 734 5 Ethylcyclopentane 3042 0 026 0 028 0 028 N7 0 14 73 30 51 736 2 2,2,3-Trunethyrρentane 17101 0 151 0 170 0 137 18 0 00 30 85 738 2 2,4-Dιmethvlhexane 31104 0275 0 316 0249 18 001 31 82 743 9 3133 0 027 0 029 0 025 N8 0 10 76 32 08 74 ; 4 14585 0 129 0 146 0 117 18 0 19 — 32 76 7 49 2 365 0003 0 004 0 003 UNK "• X 32 93 750 1 1 ι,2c,3-Tπmethylcvclopentane 901 0 008 0008 0 007 N8 0 01 -"> 33 | 4 751 3 039 2672 0 023 0 025 0 024 07 0 02 XII 33 38 752 6 1 185 0 002 0 002 0 002 UNK X I 33 6V 754 3 2 3 391 0 003 0 004 0 003 18 0 06 x: '4 i 758 6 Toluene 1807049 14 652 13 592 16 410 A7 0 31 83 34 ^ 759 8 2,3,3-Tnmethylpentane 1978 0 017 0 019 0 018 18 0 02 X4 35 : 7 762 4 043 1265 0 011 0012 0012 07 008 X^ 3^8 24150 0 213 0 241 0 193 18 0 39 86 3t> 00 3983 0 035 0 040 0 032 18 0 47 n 36 20 2164 0 019 0 020 0 017 N8 0 15 88 36 99 70288 0 621 0 716 0 561 18 0 06 89 37 27 34877 0 308 0 352 0 278 18 0 27 90 37 43 7233 0 064 0072 0 058 18 0 45 91 37 53 773 4 3 ,4-Dιmethv lhexane 5956 0 053 0 059 0 048 18 0 02 92 38 01 775 6 1 ,3c-Dιmethvlcvclohexane 523 0 005 0005 0 004 N8 0 11 93 38 44 777 6 84 68 0 743 0 846 0 671 18 0 19 94 38 63 778 5 22668 0 197 0205 0 181 N8 046 95 40 60 787 1 2304 0 020 0 023 0 016 19 0 03 96 40 79 787 9 923 0 008 0 008 0 007 N8 0 01 97 41 21 789 6 1198 0 010 0 01 1 0 010 N8 042 98 41 45 790 6 1707 0 015 0 015 0 014 N8 0 34 99 41 64 791 4 777 0007 0007 0 006 N8 002 100 41 86 792 3 458 0 004 0 004 0 004 UNK Sample LPCCR Acq [lured on 05-03- 1994 pk# Mm Index Component Area Wt% Vol % Mol % Grp Shift 101 4201 7930 2,2,4-Tπmethvlhexane 1495 0013 0014 0011 19 005 102 4239 7945 1 t,2-Dιmethvcyclohexane 1737 0015 0016 0014 N8 046 103 4266 7956 t-Octene-4 1338 0012 0013 0011 08 016 104 4322 7978 1 c,2c,3-Trunethvlcvclopentane 4238 0037 0038 0034 N8 002 105 4351 7989 113-Dιmethylcvclohexane 513 0004 0005 0004 N8 000 106 4379 8000 n-Octane 79373 0701 0803 0634 P8 000 107 4453 8038 1 c,4-Dunethvlcvclohexane 1256 0011 0011 0010 N8 004 108 4487 8056 Octene-2 1145 0010 0011 0009 08 002 109 4520 8073 l-Propylcyclopemane 1898 0016 0017 0015 N8 002 110 4619 8123 7 646 0006 0006 0005 UNK 111 4718 8171 2,3,4-Tπmethvlhexane 786 0007 0008 0006 19 055 112 4746 8184 N2 415 0004 0004 0003 N8 050 113 4799 8209 N3 3238 0028 0032 0023 N8 053 114 4893 8253 2 , 3 ,4-Tπmethvlhexane 2574 0023 0023 0021 19 04] 115 4931 8270 2,2-Dιmethylheptane 384 0003 0003 0003 19 063 116 5025 8313 N4 691 0006 0007 0005 N8 051 117 5049 8324 2^,3-Tπmethvlhexane 1858 0016 0019 0013 19 038 118 5208 8393 n-Propylcvclopentane 5538 0048 0050 0044 N8 031 119 5243 8408 2 ,6-Dιmethvlheptane 2651 0023 0026 0019 19 038 120 5455 8496 Ethylbenzene 483323 3970 3683 3859 A8 044 121 5712 8598 m-Xvlene 1118209 9186 8549 8929 A8 008 122 5738 8608 p-Xvlene 479767 3941 3682 3831 A8 008 123 5762 8617 2 , 3-Dιmethvlheptane 2974 0026 0029 0021 19 004 124 5812 8636 764 0007 0007 0005 19 024 125 5836 8646 1084 0010 0011 0008 19 025 126 5906 8672 1763 0016 0017 0013 19 003 127 5997 8705 8562 0075 0084 0061 19 001 128 6027 8716 2-Methvloctane 10493 0093 0104 0074 19 007 129 6171 8768 3 Ethvlheptane 4120 0036 0040 0029 19 009 no 6214 8783 1 , 1 ,2-TπmetiιΛ l clohexane 11224 0097 0098 0080 N9 051 131 6313 8818 o-Xvlene 764897 6283 5741 6108 A8 006 82 6868 9000 n-Nonane 14631 0129 0145 0104 P9 031 83 7048 9120 l-Propvlbenzene 59966 0496 0463 0426 A9 002 84 7599 9465 n-Propvlbenzene 149718 1238 1155 1063 A9 008 85 7741 9550 1 -Me'h\ 1-3-ethvlbenzene 471635 3899 3628 3348 A9 039 86 7770 9567 1 -Methv 1-4-ethv lbenzene 225755 1867 1743 1603 A9 047 87 7864 9622 1,3,5-Tπmetvlbenzene 156035 1290 1199 1108 A9 015 88 8010 9706 254048 2100 1918 1803 A9 006 89 8041 9723 790 0007 0008 0005 no 027 90 8144 9781 749 0006 0007 0005 N10 045 141 8163 9792 118 614 0005 0006 0004 no 001 142 8203 9814 t-Butvlbenzene 1727 0014 0013 0011 A9 060 143 8251 9841 1 ,24-Tπmethvlbenzene 796682 6629 6088 5692 A9 002 144 8463 9956 t-Butvlbenzene 9659 0080 0076 0062 A10 001 145 8500 9976 10410 0087 0081 0067 A10 035 146 8546 10000 n-Decane 1043 0009 0010 0007 P10 000 147 8621 10068 1,23-Tπmethvlbenzene 230262 1904 1712 1635 A9 010 148 8648 10092 1 -Methv 1-3-ι-propvlbenzene 30053 0250 0233 0192 A10 019 149 8689 10129 1 -Methvl-4-ι-propvlbenzene 10426 0087 0081 0067 A10 008 150 8759 10190 2,3-Dιh\droιndene 33119 0274 0228 0239 A9 006 Sample LPCCR Acq luire on 05-03- 1994 161 9349 10694 s-C5Ps/l,3-DM-4-EtBz 58098 0484 0453 0337 All 005 162 9376 10716 I3S 506 0004 0005 0003 111 009 163 9417 10750 1 J-Dijnethvl-4-ethvlbenzene 101805 0846 0778 0651 A10 028 164 9482 10802 1 '-Eιmsthvl-2-ethvlbenzene 9568 0080 0072 0061 A10 016 165 9505 10821 194 0002 0002 0001 UNK 166 9527 10839 217 0002 0002 0001 UNK 167 9620 10911 1 -Methvl-4-t-butvlbenzene 4097 0034 0032 00 2 4 All 015 168 9635 10926 1 ^-Dunethyl-3-ethvlbenzene 36891 0307 0276 0 2 36 A10 007 169 9689 10968 1547 0014 0012 0011 UNK 170 9710 10985 1701 0015 0014 0012 UNK 171 9755 11028 1 -LUιvι-4-ι-propylbenzene 2712 0023 0020 0016 All 040 172 9769 11044 12 ,4 ,5-Teιramethvlbenzene 54991 0457 0414 0351 A10 010 173 9786 11062 1141 0010 0009 0008 UNK 174 9806 11084 (2-Methvlbutyl) benzene 86584 0722 0652 0503 All 038 175 9836 11116 256 0002 0002 0002 UNK 176 9869 11152 1323 0012 0011 0008 UNK 177 9895 11180 ) 465 0004 0004 0003 UNK 178 9921 11208 1 -t-Buιvl-2-Methvιbenzene 352 0003 0003 0002 All 001 179 9977 11268 5-Mι.thylιndan 18099 0151 0136 0105 All 051 180 10031 11325 143 5258 0046 0049 0028 112 055 181 10043 11338 2338 0021 0022 0013 UNK 182 10059 11355 A3 9058 0076 0068 0053 All 052 183 10079 1137 j 1 -Ethvl-2-n-propv lbenzene 17848 0149 0134 0104 All 002 184 10100 11398 1 -Methvl-3-n-butvlbenzene 1602 0013 0012 0009 All 053 185 10124 ι 23 13-Dι-ι-propvlbenzene 44895 0376 0340 0239 A12 052 186 10173 11474 n-Penr. lbenzene 1581 0013 0012 0009 All 046 187 10190 11492 'l M 2-(4-MP 2464 0021 0021 0013 N12 058 188 10221 11524 2956 0026 0026 0016 UNK 189 10263 11568 1 -Metlrt 1-2-n-ouιvlbenzene 5735 0048 0043 0033 All 072 190 10280 11585 1 ,4-Dι-ι-nropylbenzene 7151 0060 0054 0038 A12 060 191 10319 11626 1 ,2,3,4-Tetrahvdronaphthalene 301 0003 0002 0002 A10 055 192 10347 11654 AU66 11170 0093 0073 0072 A10 002 193 10365 11673 Naphthalene 36309 0302 0237 0243 A10 194 10 195 10491 11801 160 0001 0002 0001 UNK 196 10515 11825 147 4108 0036 0039 0022 112 073 197 10554 11864 452 0004 0004 0002 UNK 198 10567 11877 A48 11907 0105 0112 0063 A12 on 199 10583 11892 i ,3-Dι-n-propvlbenzene 8111 0068 0061 0043 A12 007 200 10665 11974 8048 0071 0064 0045 UNK Sample LPCCR Acquired on 05-03-1994 pk# Mm Index Component Area Wt % Vol % Mol % Grp Shift 201 10749 12071 9 1462 0013 0012 0008 UNK 202 10819 12157 9 1761 0016 0014 0010 UNK 203 10865 12213 9 991 0009 0008 0006 UNK 204 10889 12243 9 3684 0033 0030 0021 UNK 205 10910 12268 9 215 0002 0002 0001 UNK 206 10972 12343 9 253 0002 0002 0001 UNK 207 10982 12355 9 376 0003 0003 0002 UNK 208 11023 12404 9 3615 0032 0029 0020 UNK 209 11057 12444 1-Methvl-4-n-penrvlbenzene 510 0004 0004 0003 A12 072 210 11077 12468 9 380 0003 0003 0002 UNK 211 11140 12543 9 2006 0018 0016 0011 UNK 212 11173 12583 9 762 0007 0006 0004 UNK 213 11213 12629 ? 175 0002 0001 0001 UNK 214 11247 12670 9 296 0003 0002 0002 UNK 215 11297 12728 9 11928 0106 0096 0067 UNK 216 11369 12811 2-Methvlnaphthalene 30612 0256 0201 0184 All 030 217 11407 12856 9 547 0005 0004 0003 UNK 218 11499 12962 1-Methvlnaphthalene 21214 0177 0140 0128 All 005 219 11757 14000 C14+ 262 0002 0002 0001 + 000 220 11905 14000 C14+ 435 0004 0004 0002 + 000 221 11999 14000 C14+ 359 0003 0003 0002 + 000 222 12152 14000 C14+ 2642 0024 0024 0012 + 000 223 12167 14000 C14+ 973 0009 0009 0004 + 000 224 12179 14000 C14+ 741 0007 0007 0003 + 000 222 12238 14000 C14+ 3450 0030 0032 0016 + 000 226 12252 14000 C14+ 2730 0024 0025 0012 + 000 227 12347 14000 C14+ 8524 0075 0079 0039 + 000 228 12375 14000 C14+ 4270 0037 0039 0019 + 000 229 12495 14000 C14+ 3360 0029 0031 0015 + 000 230 12511 14000 C14+ 1132 0010 0010 0005 + 000 231 12601 14000 C14+ 3530 0031 0033 0016 + 000 gi 12-71 14000 C14+ 595 0005 0006 0003 + 000 83 12839 14000 C14+ 787 0007 0007 0004 + 000 84 12913 14000 C14+ 282 0002 0003 0001 + 000 ' 5 12957 14000 C14+ 1339 0012 0012 0006 + 000 12989 14000 C14+ 262 0002 0002 0001 + 000 87 13023 14000 C14+ 905 0008 0008 0004 + 000 88 13074 14000 C14+ 579 0005 0005 0003 + 000 89 13106 14000 C14+ 1262 0011 0012 0006 + 000 90 13146 14000 C14+ 1178 0010 0011 0005 + 000 241 13249 14000 C14+ 1178 0010 0011 0005 + 000 242 13279 14000 C14+ 1107 0010 0010 0005 + 000 243 13353 14000 C14+ 670 0006 0006 0003 + 000 244 13368 14000 C14+ 554 0005 0005 0003 + 000 245 13379 14000 C14+ 1259 0011 0012 0006 + 000 246 13474 14000 C14+ 1433 0013 0013 0007 + 000 247 13523 14000 C14+ 340 0003 0003 0002 + 000 248 13553 14000 C14+ 567 0005 0005 0003 + 000 249 13593 14000 C14+ 155 0001 0001 0001 + 000 250 13608 14000 C14+ 267 0002 0002 0001 + 000 Sample LPCCR Acquired on 05-03-1994 pk# Mm Index Component Area Wt % Vol % Mol % Grp Shift 251 13638 14000 C14+ 309 0003 0003 0001 + 000 252 13728 14000 C14I- 777 0007 0007 0004 + 000 253 14067 14000 C14->- 338 0003 0003 0002 + 000 254 141 69 14000 C14-t 631 0006 0006 0003 + 000 Table I Volume Benzene % DIFFERENCE DATE TIME D3606 ON-LINE d3606 - NIR NIR 8/30/95 1545 2.700 2.780 -0.080 9/08/95 15 00 2.830 2.740 0.090 9/12/95 09.00 2.630 2.520 0.110 9/19/95 10-15 2.920 2.990 -0.070 9/26/95 09.00 2.260 2.200 0.060 0/02/95 13 35 4 190 4.050 0.140 0/10/95 13 50 2.600 2.643 -0.043 0/17/95 10 00 4.194 4.231 -0.037 0/26/95 07 30 1.890 1.870 0.020 1/06/95 09 05 1 920 1.840 0.080 1/09/95 22 32 2.520 2 540 -0.020 1/14/95 10 30 2.569 2.608 -0.039 1/21/95 07 50 2.150 2.196 -0.046 1/28/95 14 00 2.510 2.355 0.155 2/05/95 10 00 2.260 2.000 0.260 2/12/95 09 30 1.900 1.840 0.060 1/05/96 0700 1.617 1.492 0.125 1/12/96 15 05 2.340 2.530 -0.190 1/26/96 1445 2.200 2.280 -0.080 2/01/96 15 00 2.415 2.230 0.185 2/06/96 13 30 2.540 2 370 0 170 2/13/96 14 00 1.210 1.290 -0080 2/23/96 13 20 1 700 1 870 -0.170 2/27/96 14 30 1.990 2.030 -0.040 SEP 0 118

Claims: CLAIMS 1. A process for the analysis of hydrocarbons to determine component concentration, the improvement comprising in combination: a. measuring at at least one wavelength, the near infrared absorption in the bands of: 1. For benzene: 2100-2160 nanometers (nm) and/or 1600-1670 nm and/or 1780-1858 nm; and/or 1120-1260 nm; and/or 850-925 nm; 2. For toluene: 1600-1670 nm and/or 1780-1858 nm and/or 1214-1230 nm; and/or 2000-2160 nm; and/or 860-910 nm; and/or 975-1000 nm; 3. For xylenes: 1320-1530 nm and/or 2000-2040 nm and/or 1600-1670 nm; and/or 1120-1214 nm; and/or 1780-1858 nm; and/or 2100-2160 nm; and/or 850-930 nm; and/or 940-990 nm; and/or 1015-1045 nm; 4. For alkyl benzenes: 1156-1264 nm; and/or 1600-1670 nm; and/or 1214-1230 nm; and/or 1320-1480 nm; and/or 850-900 nm; and/or 1015-1045 nm; and/or 1214-1264 nm, and/or 1970-2040 nm; more preferably 1214-1264 nm and 1970-2040 nm; 5. For n-pentane, n-hexane n-heptane and/or other n-paraf fins: 1156-1264 nm; and/or 1320-1480 nm; and/or 1600-1670 nm; and/or 1780-1858 nm; and/or 1940-2100 nm; 6. For isopentane, 2-methyl hexane, 2 ,2-dimethylbutane , 2,3 -dimethylbutane , 2-methylpentane, 3-methylpentane and/or other isoparaffins: 1156-1264 nm; and/or 1320-1500 nm; and/or 1560-1670 nm; and/or 1780-1858 nm, and/or 1900-2160 nm; 7. For methylcyclopentane and/or other naphthenes: 1156-1430 nm; and/or 1780-1858 nm; 8. For isobutylene and/or other olefins: 1132-1214 nm; and/or 1600-1670 nm; b. taking each of the absorbances measured, or a mathematical function thereof; c. performing multiple regression analysis, partial least squares analysis, or other statistical treatment using the above absorbances or functions as individual independent variables, d. assigning and applying weighting constants or their equivalents to said independent variables, e. applying the above steps using known compositions to calibrate the instrument and determine said weighting constants or equivalents, f. repeating said steps with unknown compositions, applying the weighting constants or equivalents determined during said calibration with known compositions to output a signal or signals indicative of one or more specific hydrocarbon species. 2. A process according to Claim 1 wherein said composition includes ethyl-benzene and wherein said bands are 1156-1214 nm, 1600-1670 nm, and 1214-1230 nm or 1230-1264. 3. A process according to Claim 1 wherein said composition includes benzene and wherein said bands are 2100-2160 nm, 1600-1670 nm, and 1780-1858 nm. 4. A process according to Claim 1 wherein said composition includes toluene and wherein said bands are 1600-1670 nm, 1780-1858 nm, and 1214-1230 nm. 5. A process according to Claim 1 wherein said statistical treatment comprises partial least squares analysis over the length of each band, of wavelengths, or of a portion thereof. 6. A process according to Claim 1 wherein said mixture flows substantially intermittently or continuously past the point of measuring said absorbance. 7. A process according to Claim 1 wherein a second derivative of said absorbance is computed. 8. A process according to Claim 1 wherein said mathematical converting comprises a baseline off-set correction. 9. A process according to Claim 1 wherein said mathematically converting comprises partial least squares analyses, principle component regression, Gauss-Jordan Row reduction, or multiple linear regression. 10. A process according to Claim 1 wherein said signal is used to control at least one process selected from the group of: a. fuel blending system feeding blending components having different benzene compositions into a common zone, whereby a product having a desired benzene composition is produced, a reformer, and wherein said signal is used to control the severity of said reformer step by adjusting throughput, hydrogen uptake, temperature, or unit space velocity, c. a catalytic cracking step, and wherein said signal is used to control the severity of said catalytic cracking step by adjusting catalyst: oil ratio, temperature, or recycle of naphtha or other cracked product, d. an alkylation step, and wherein said signal is used to control isoparaffin: olefin ratio, e. an ether manufacturing step, and wherein said signal is used to control alcohol :isoolefm ratio, and f. an isomerization step, and wherein said signal is used to control isoparaffm:normal paraffin ratio.

Inventors: BLEDSOE ROY ROGER, MAGGARD STEVEN M, SUMNER MICHAEL B, WELCH WILLIAM T, WILT BRIAN K, BLEDSOE, ROY, ROGER, MAGGARD, STEVEN, M., SUMNER, MICHAEL, B., WELCH, WILLIAM, T., WILT, BRIAN, K.
Applicants: ASHLAND INC, ASHLAND INC.
Application year: 1997
Main classification: G01N21
IPC codes: G01N21, G01N33