Abstract

On-line Nuclear Magnetic Resonance (NMR) analyzers are beneficial in chemical and petroleum industries for qualitative and quantitative analyses of physical properties of process streams. NMR selectively specifies and quantifies hydrogen atoms with regard to the molecular structure of substances and their presence in mixtures. Its linear spectral response enables chemometrics to easily perform accurate linear correlation between provided spectral data and the physical properties to be determined. NMR process analyzers are applicable to opaque and transparent solutions alike. This is highly beneficial for its application in process control in chemical process and petroleum industries.

Stability, reliability and accuracy are basic requirements for successful implementation of process analyzers. Previous generations of NMR process analyzers had significant issues moving from the lab to hostile production environments.  This was predominately caused by a high sensitivity towards temperature fluctuations in production locations and input streams.

Process streams are characterized by different temperatures and flow properties. It is up to the analyzer and the sampling system to eliminate any interference of these on analytical results.

A thorough failure analysis of the first and second generation production units was the foundation on which the third generation on-line NMR process analyzer was developed. The challenge was to reduce its sensitivity towards the influence of temperature variations of process streams and to improve its reliability. This was achieved by entirely re-innovating its hardware and software. The third generation includes a new design of the magnet with an increase of the bore size to 30 mm and a newly developed measuring probe.  Manually wrapped shim coils were replaced by new state of the art PCB cards. As a result of these improvements, enhanced long and short term stability, reduced sensitivity towards temperature variations, smaller footprint, improved SNR ratio, and improved sensitivity has been achieved.

The third generation is distinct from its previous generations by its low susceptibility towards temperature fluctuations, its high stability and its reduced cost of maintenance. Reliable measurements of transparent, dense and opaque process streams can be conducted without any impact from temperature differences between different streams. It can therefore benefit the chemical plants and refineries in their efforts to effectively monitor and control their entire processes. It prevents production of off-spec and borderline products and avoids the need for reprocessing. This in turn will definitely have its output on the plant economics.

Introduction

At present, refinery streams are predominately monitored by discrete process analyzers, based on standard ASTM methods, and/or optical spectrometry based process analyzers, such as NIR/FTIR. Standard method analyzers are not dependent on crude quality and other factors. However, their response time is longer and their maintenance is expensive. Various optical spectroscopy analyzers require close attention to the modeling efforts and are restricted to measuring transparent fluids only. Their reliability depends of the accuracy of the chemometric model, as well as the impact of the presence of hetero-atomic molecules which are present at fluctuating concentrations depending of the crude oil origin.

Principle of NMR Analyzers

NMR technology is based on the influence of differences in alignment of nuclei in the presence of a magnetic field. When a group of spinning nuclei with an odd number of protons, is placed in a static magnetic field, each nucleus aligns with the magnetic field. By its spinning, small magnetic fields are formed that oppose the externally applied field, which reduce the effective magnetic field at the nucleus. Neighboring protons, atoms and chemical bonds influence the magnetic field differently for each proton. This phenomenon results in a shifting of the spectral signal differently for each proton (chemical shift). The chemical structure of different species in molecules can be identified, while its spectral response correlates linearly with the proton concentrations. NMR spectrometry is a fundamental method. It focuses on molecular structures of the substances in the mixture. In combination with the proper chemometrics accurate quantification of physical properties is achieved.

This is in contrast to optical spectroscopic methods, which are based on the determination of «fingerprints» of substances.  Its accuracy is affected by the impact of weak analytical signal variance of overtone and combination band vibrations, heavy overlapping spectral bands, of non carbon or hydrogen atoms and a lack of linear spectral response.

The introduction of Fourier transform (FT) in NMR spectrometry increased its sensitivity to measure low concentrations. Multiple scans of the spectrum reduce the signal to noise ratio. Spectral resolution improved as compared to continuous wave NMR spectrometers of similar magnetic strength.

The concept of NMR process analyzers is based on the assignment and quantification of the different types of hydrogen atoms of organic molecules or water, which are present in distillates or in crude oils. The linear spectral response correlates accurately with the hydrogen atom assigned to molecular species of the substances which are present in a composition.

NMR spectral peaks are influenced by the nature of neighboring chemical carbon-carbon bonds and neighboring non-carbons in the molecular structure. It enables the assessment of the chemical character of the substance, present crude oil or distillates. Assignment can be made to indentify whether these molecules are linear or branched paraffins, olefins, and mono-aromatics, poly-aromatics, hetero-cyclic, naphthenic, acids, oxygenates and water, as shown in Figure 1 [1]. This is the principle on which the first NMR analyzer has been developed.

Figure 1. Clarity of various hydrogen types in gasoline NMR spectra [1].

Applications of 3rd Generation NMR Process Analyzer in Process Control

Introduction of the third generation NMR process analyzers opens a new road to accurate and reliable process control of chemical processes, refinery streams and blending processes. In contrast to other optical spectrometry based technologies, such as NIR analyzers, NMR analyzers are not dictated by the need for transparency of the process streams, such as refinery streams, to be analyzed. NMR technology can be implemented without any restriction to transparent, dense and opaque process streams alike. However, due to the lack of stability, accuracy and reliability of the first and second generation NMR analyzers, many end users, predominately in refineries, were skeptical about moving these systems out of the lab and integrating these analyzers in their process control schemes. Elimination of these obstacles has been accomplished in the third generation NMR analyzers, which is required for successful implementation in the refining and process industries.

NMR technology is applicable to any process stream where organic molecules are involved. It enables the correlation between physical properties of process feed and product streams. It provides an effective tool to improve the ability to make real-time adjustment of the process conditions, which is a major requirement or optimized utilization of a process unit.

Physical properties of a process streams are an accumulation of physical properties and concentrations of each individual component present.

Optical methods, such as NIR/FT-IR spectrometry, have the advantage of being able to measure at locations far from the analyzer, through installed fixed field probes or flow cells which are connected to the analyzer by fiber optics.  Sample switching, by an optical multiplexer, occurs almost instantaneous.  However its application is restricted by the transparency of the process stream. Furthermore, NIR/FT-IR spectrometry is based on «fingerprints» of chemical compositions, without specification to molecular structures. Overlapping and weak spectral bands and the lack of linear spectral response dictate chemometric models to include a wide range of expectable compositions in the model to enhance its accuracy.

In contrast, NMR precisely distinguishes between of molecular structures and the nature of chemical bonds involved. Quantification of hydrogen atoms according to the spectral signal enables quantitative and qualitative assessment of molecular structures with a high certainty. In combination with its linear response chemometrics accurately correlates between spectral data and physical properties.

A basis on «fingerprints» and a lack of linear response in optical spectrometric methods requires the chemometric model to include all possible variation in order to correlate between spectral data and quantification of physical properties.  The linear response of NMR enables extrapolation to quantify physical properties also of compositions, are not included in the calibration curve of the chemometric model.

Various hetero-atomic substances are present at different levels in crude oils, depending on its origin. These substances partially distill alongside distillation products. If they are not included in the chemometric model, crude oil switching will affect the accuracy the analytical results due to non-consistent light absorption in the NIR/FT-IR region. However, as a fundamental method, the accuracy in NMR spectrometry is not affected by the presence of these       hetero-atomic molecules. Assessment can be made specifically for hydrocarbon molecules only. This is extremely important for its application in crude oil distillation to analyze crude oil, naphtha, diesel, kerosene and heavy distillates, vacuum distillates and bottom products.

Figure 4 illustrates the application of NMR process analyzers in a crude distillation unit of a refinery. Light distillates can be measured by NIR/FT-IR or NMR analyzers. Monitoring of kerosene and diesel can also be performed by both, but under the restrictions that process streams are transparent, and that crude switching is omitted. Otherwise, NMR is the method of preference. Heavy distillates, vacuum distillates and bottom product can only be monitored by NMR.

Figure 4. Implementation of NIR/FT-IR and NMR Analyzers in Crude Oil Distillation


Full monitoring of all refinery streams is essential to the most efficient performance of the crude unit. However, temperature differences between distillate streams prevented previous generation of NMR analyzers to switch between the distillate streams without losing accuracy. The enhanced temperature insulation between magnet and probe in the third generation eliminated these drawbacks.

Analysis of feed and product streams by the same analytical method and the same analyzer is the preferred strategy to accurately correlate between physical properties of process streams. Boiling ranges of different distillates partially overlap. Efficient and stringent adjustment of the temperature profile in the distillation to optimize cut points between distillates increases its production capacity of the most required distillates. It enables the optimization of its capacity towards the distillates that will have the highest profit on the market.

Crude switching is a common practice in many refineries. Implementation of NMR process analyzers reduces the impact of the transition period, until optimized process conditions are restored.

Beside petroleum industries, chemical process industries can benefit from NMR process analyzers. NMR technology can provide accurate information about the substances available in the process stream. As a molecular determining method, NMR distinguishes between and enables quantification of raw materials, intermediates and final products. It provides an efficient tool for analyses of reaction proceedings and failure analyses in chemical processes. NMR spectra can be analyzed by chemist throughout the entire production process. 

Other applications of NMR analyzers can be found in the pharmaceutical industries, the food industries, fermentation processes in biotechnology industries, in all other processes, where organic substances are available with NMR distinguishable chemical compositions.

Process NMR can be applied for at many locations within refinery processes. Its ability to not be restricted to transparent streams provide an effected tool to continuously monitor the feed and product streams of refinery units, especially those units where optical spectrometry methods fail.

In other process chemical industries, NMR technology can provide accurate information about the substances available in the process stream. As a molecular determining method, NMR enables quantification of raw materials, intermediates and final products.

The incorporation of NMR analyzer in process stream monitoring prevents the production of border-line and off-spec materials and avoids the investment of time and money to upgrade these products.

Summary: Comparison between NIR and 3rd Generation NMR Technology

A comparison between the characteristics of NIR and third generation NMR technology is summarized in table I.

Table I — Comparisons between NIR and NMR Technology

[TABLE]

Payback of 3rd Generation NMR Analyzers in Refineries and Process Industries

Laboratory analyses are time consuming and expensive. In many cases, lab analytical results come too late, to establish adequate process control. Integration of the new third generation NMR process analyzers in the process control of refinery units, such as crude distillation units, CCR, FCC, and in the process chemical industries gives the opportunity to effectively monitor the quality of feed and process streams. It provides an effective tool for ongoing optimization of process conditions to produce most valuable products with at maximum quality and at minimum cost. It minimizes the production of borderline and off-spec material, and reduces time to be invested in reprocessing.

Conclusions

The successful application of on-line process analyses is dictated by its stability, its feasibility to provide reliable analytical results process streams and its capability to switch without any impact between different process streams. Previously, its high sensitivity towards temperature fluctuations, its lack of stability of the magnetic systems and its deficient reliability harmed the reputation of NMR process analyzers in refineries and process industries. The conclusions of a thorough and all including failure analyses of first and second generation on-line NMR process analyzers were implemented in the entirely new design of the third generation. Incorporation of innovative hardware and software has eliminated the drawbacks of previous generations and increased its stability accuracy and reliability. The cost of human resources required for calibration and maintenance is reduced. It will benefit chemical industries and refineries to effectively monitor and control its entire process. It enables the entire production unit to run at maximum efficiency and profitability. Stability, Reliability and accuracy of the third generation of NMR process analyzers is the major challenge in restoring the reputation of NMR technology for process control in the chemical and petroleum industries.

References

1. Giammatteo, Paul J., Edwards John C., Cohen Tal, «Integrated analyses and control to enhance clean fuel production», ISA 54th Analysis Division Symposium, 2009

2. Shahnovsky, Gregory «Innovation in Petroleum Process Analyzers Technology», ISA 53th Analysis Division Symposium, 2008.

3. McMahon, Terrence K., Process Analytical Technology, John Wiley & Sons, Inc, 2005.

4. Clevett, Kenneth J., Process Analyzer Technology, John Wiley & Sons, Inc, 1986.

5. Giammatteo, Paul J., «More from the Barrel — On-line NMR Increased Diesel Production and Quality», presented to the NMR symposium at the Eastern Analytical Symposium in Somerset New Jersey, November 12-15, 2007 (www.nmrautomation.com)

Comprehensive and adequate control of the process parameters of the Crude Distillation Unit (CDU) is an obligatory requirement for the optimal production of naphtha, kerosene and gasoil. This has a direct impact on the economics and the profit of the refinery.

Integrated real-time and on line monitoring of the feed and the distillates allow immediate adjustment of the process conditions. This increases the capacity to produce high value distillates by stringent cutting, and reduces the impact of the fluctuations that occur during the process. 

Utilizing the 4IR AI-60 Petroleum analyzer (based on an NMR technology) along with propriety software ensure the operation of the CDU to produce its distillates continuously, effectively and at the highest yields.

The Challenges

Optimization of the process conditions for the crude distillation unit is a main challenge for each refinery. It results in maximum profit at minimum cost.

To achieve this target, full real time monitoring of the quality of the incoming crude oil and outgoing distillates is a minimal requirement in order to ensure: 

  • Minimum influence on the production capacity of each distillate and its quality due to changes in crude oil.
  • Maximum production of high value distillates on the account of heavier distillates of lower value. This is achieved by shifting the cutting temperature as such that the T90 – FBP of the high value distillate will be as high as possible and the IBP – T10 of the heavier fraction as low as possible.
  • Maximum stability of the product quality of each distillate throughout the entire distillation process.
  • Prevention to produce borderline or off-spec material due to failures.

Full control of the product quality can only be achieved by employing the NMR analyzer to monitor continuously and simultaneously the quality of the incoming crude oil and the outgoing streams (Naphtha, Kerosene, LGO, HGO and the vacuum distilled products LVGO and HVGO). This enables real time actions to be taken to allow the CDU to be operated with optimal production effectiveness.

Refineries include a complex of processes. If these processes are not controlled properly it will have its impact on the efficiency of the refinery. It will affect the product quality, the product yield and the energy consumption. This leads directly to an increase of the cost of production for each distillate.

Complete on-line and continuous monitoring and control of the process parameters reduces the danger of an inadequate production of the required petroleum products.

The efficiency of a refinery to produce its petroleum distillates directly linked to:

  1. The crude oil that is delivered to the refinery.
  2. The equipment of the refinery.
  3. The maximum throughput of the crude oil and the petroleum products alike.
  4. The ability to produce the distillates with the highest value at maximum yield.

Each refinery is built differently according to its initial destination, the sources of crude oil and the required quantity of different petroleum products, which is based on the direct request of the market and long-term planning according to the trend of the price fluctuations of each distillate.

The quality and the cost of the crude oil highly depend of its origin. Blending of various types of crude oil is required to reduce the cost of the crude oil feed to be distilled. Furthermore, as each refinery is constructed differently, blending of different types of crude oils may be inevitable to obtain a proper feed that can be processes in the equipment available in refinery.

Different sources of the crude are of different compositions. The result is that under similar process conditions a different distribution of the distillates, as produced by the CDU, is obtained. To achieve a maximum production efficiency and product yield, continuous readjustment and fine tuning of the process conditions is unavoidable.

Inadequate on-line and real time control of the crude oil and the product quality will directly affect the efficiency and the profit of the refinery. Failures in continuous chemical processes do occur, and result in the production of non-desired materials or the need for a partial or total shut down of the plant. Time consuming investigations are conducted and taken corrective actions have to be implemented.

These actions directly affect the overall efficiency, the profit and the economics of the production plant, an answer has to be given to:

IDENTITY       – What is observed?

LOCATION     Where is the problem observed?

TIMING           – When is the problem observed?

MAGNITUDE How many similar occurrences are observed now and in the past?

COST              – What is the short term and long-term price to be paid?

These investigations are complicated. In many cases failures are not the outcome of one single event. Often, they are the result of a combination of several events that occur together.

Off line laboratory quality control, which includes sampling and laboratory analyses is time consuming. Any delay in data collection will affect optimal and effective control and adjustment of the process parameters.

Continuous on-line monitoring of the product properties minimizes financial loss due to unexpected failures or inappropriate production conditions.

The Solution

4IR AI Ltd. has a total solution for the CDU to allow control of the process in an economic manner and at low cost.

4IR Ai’s solution covers the entire CDU processes, starting from the incoming crude oil, the feed, and the distillates.

4IR AI total refinery monitoring system includes:

  1. AI-60 Petroleum Analyzer (based on NMR technology)
  2. Process NMR software
  3. Model Gate Way software

A combination of this analytical method along with distinctive software, establishes a continuous and overall monitoring of the entire refinery processes.

CDU Feed

Physical and chemical properties of crude oils correlate directly with the chemical composition of these, and vary according to their place of origin.

Quality properties determine the market value of each type of crude individually. Most important quality characteristics are the density, the TAN and the sulfur content. The API (Density) ranges from light crudes (high API, low density) to heavy crude oils (low API, high density). Sulfur is present in crude oils as hydrogen sulfide and as polysulfide. Partially these sulfur containing molecules will decompose during the distillation, while hydrogen sulfide evolves. The sulfur content and other acidic components in crude oil, such as naphthenic acids, are highly corrosive, and responsible for the crude oil to be of a sour or sweet character.

High TAN crude oils, crude oils with high acid numbers/value, are heavy crude oils with high acidity. High TAN crude oils are characterized by fewer light components, high density and viscosity, low solidification point, high nitrogen content, high gel-asphalt content, high salts and high heavy metals contents and a low yield of light oil distillates. It causes water – oil separation by the De-Salter being more difficult than in conventional crudes. These properties also cause these crudes to give low quality products and being very corrosive. Commonly, these TAN crude oils are called “opportunity crude oils”. 

CDU Distillate

Crude oil is transferred from the de-salter to the CDU to be fractionated according to their TBP into:

  • Gasses with low boiling points (≤32 °C)
  • Light Straight run naphtha        (32-88 °C)
  • Heavy straight run naphtha      (88-193 °C)
  • Kerosene                                  (193 -271 °C)
  • Light gas oil                              (271-321 °C)
  • Heavy Gas Oil                          (321 – 427 °C)
  • Vacuum Gas Oil                       (427-566 °C)

Cutting temperatures between the distillate streams must be maintained as such the IBP and FBP of final distillates and other physical properties comply with the specification of the final product. The cutting points for distillates that are blended or further processes are determined a to achieve maximal production capacity, with an optimum use of various distillates to achieve final product to comply with the required specification, i.e. diesel-oil, or the requirements needed if further processed.  Overlap between the boiling ranges of neighboring distillates is common. It is up to each refinery to specify the exact cutting point, to allow a production capacity for each product according to their marketing commitments.

The distillation residue from the atmospheric tower is further distilled under vacuum into light and heavy vacuum gas oil (LVGO) and (HVGO), used for further processing.

Physical properties of a distillate are the outcome of their chemical composition which correlates with each other. This enables NMR spectroscopy to be applied to quantify different physical properties.

Predication of a physical property by using NMR spectrometric method is based on a statistical correlation between quantitative value of a certain physical property and its corresponding measured spectral data.  The accuracy of correlative methods depends entirely on the quantity, quality and the variation of reference samples.

The product streams are scanned instantaneously during the production and analyzed by NMR spectrometric method. The data obtained by these measurements mathematically converted to required parameters of the product which is produced.

4IR AI monitors the product quality in the CDU by applying the Nuclei Magnetic Resonance (NMR)

4IR’s NMR Technology

Nuclear Magnetic Resonance — is an effect whereby magnetic nuclei in a magnetic field absorb and re-emit electromagnetic (EM) energy at a specific resonance frequency. The introduction of on line NMR technology is a unique tool to monitor the feed and the distillates of the crude distillation unit.

Its spectrum is an outcome of the arrangement of carbon, hydrogen and oxygen atoms in the molecule. The NMR spectrum of crude oil and petroleum distillates, depend directly on the distribution of hydrogen atoms in the molecule and is influenced by the type of carbon-carbon bond to which the hydrogen atom is connected. Quantification of the molecules is achieved by concentration of the hydrogen atoms assigned to each peak response

NMR can distinguish between compounds which are present in petroleum distillates. These include linear and branched olefins and aliphatic, mono-aromatics and poly-aromatic, substituted aromatics or oxygen containing species aliphatic, parafines, olefins, acids, oxygenates and water.

Nuclear Magnetic Resonance — is an effect whereby magnetic nuclei in a magnetic field absorb and re-emit electromagnetic (EM) energy at a specific resonance frequency. The introduction of on line NMR technology is a unique tool to monitor the feed and the distillates of the crude distillation unit.

Its spectrum is an outcome of the arrangement of carbon, hydrogen and oxygen atoms in the molecule. The NMR spectrum of crude oil and petroleum distillates, depend directly on the distribution of hydrogen atoms in the molecule and is influenced by the type of carbon-carbon bond to which the hydrogen atom is connected. Quantification of the molecules is achieved by concentration of the hydrogen atoms assigned to each peak response

NMR can distinguish between compounds which are present in petroleum distillates. These include linear and branched olefins and aliphatic, mono-aromatics and poly-aromatic, substituted aromatics or oxygen containing species aliphatic, parafines, olefins, acids, oxygenates and water.

Crude OilNaphthaKeroseneDiesel OilLGOHGO
      
APIDensityAPIDensityDensityDensity
Distillation ASTM D 86Distillation ASTM D 86Distillation ASTM D 86Distillation — ASTM D 86Distillation ASTM D 86Distillation ASTM D 86
AromaticityPONAFlashpointCetane IndexPour PointCloud point
Water in crudeRVPFreeze pointCloud PointCloud PointPour point
Pour Point AromaticsViscosityFlash pointFlash point
Sulfur OlefinsPour Point  
  NaphtalenesCFPP  
  Hydrogen-ContentFlash Point  

Major benefits of NMR technology:

  • Allows analyses to be performed in dense and opaque materials (Crude oil, LGO, HGO).
  • Linear Spectral Response across broad range.
  • Allows multi-property analysis in one single run.
  • Allows real time, continuous flow-through stream analysis.
  • Physical properties correlate accurately with spectral data.
  • Replaces conventional analyzers and provide much faster results (e.g. PIONA in seconds.
  • Reduction in response time from Lab allows tighter control.
  • Requires simple sample conditioning (no water removal).

These features along with the Process NMR software and the Model Gate Way software allow 4IR’s AI-60 Process Analyzer to monitor on line observation of any discrepancy in the production process and the product quality. It allows immediate corrective actions to be taken whenever required.  The result is a reduction loss caused by producing of off-spec material. It also eliminates the need for frequent sequential laboratory analyses until the process is back on track.

Process NMR Software

The AI-60 Process NMR software is a GUI, windows-based application that controls the NMR analyzer operation along with the Sample Conditioning System and the Stream Switching System through TCPIP and/or Modbus and enables the user to perform the following operations:

  • NMR scan
  • NMR Signal Processing
  • NMR Analyzer Shimming
  • Archive results
  • Report predicted values through Modbus protocol
  • Enable the NMR Analyzer to run in a fully automatic mode for process control

Model Gate Way Software

  • Software only solution (Windows XP or higher)
  • Automatic generation of PLS models (Patent protected)
  • Supports most correlative analyzers
  • Integrates with Plant network through Modbus protocol
  • Supports traditional Thermo Grams models
  • Graphic model comparison
  • Automatic / Manual feeding of lab data
  • Reporting / Alerts / Status indications

Comparison between NIR and NMR

 NIR AnalyzerNMR Analyzer
MethodNear Infra-Red (Optical)Magnetic resonance   
Sample ProbeAllocated near the sample line (no lag time)Fast loop bypass pipes (introduce lag time between the actual sample to the predicted results)  
Multi-StreamsOptical multiplexer (no need for sample switching system  Require sample switching system
Chemometric ModelsNo-linear Response;  Cannot perform extrapolations of the model  Linear Response; Allow extrapolations of the model
Sample properties  Applicable to transparent distillates onlyApplicable for transparent and opaque samples
Crude Changing influenceInfluenced by compounds, containing others than carbon or hydrogen atoms.No sensitivity to Crude changing. Depended on the hydrogen content only.  
  • NMR spectrometry characterized by a better linear response then NIR spectrometry with respect to changes in the composition of the distillates.
  • NIR is restricted to transparent distillates only (Naphtha, Kerosene and Diesel). NMR is applicable to transparent and opaque distillates which cover the entire product range of the CDU.

Case Study: CDU Optimization Yanshan Refinery (Kerosene yield)

   Before NMR CommissionAfter NMR Commission
Month201220132014
   
Jan9.779.8711.7
Feb9.289.9510.58
Mar9.269.5411.32
Apr9.2310.0910.98
May5.0610.0312.22
Jun9.2911.0311.14
Jul9.910.5911.29
Aug9.5112.911.85
Sep9.0610.911.51
Oct9.2611.5711.37
Nov9.1911.3911.37
Dec6.2511.2911.34
Average yield8.7610.7611.39
Yield improvement 2.012.63

After commissioning of the NMR analyzer: Kerosene yield increased by 2% to 2.5% which is equivalent to additional of 5000 to 6500 barrels of Kerosene per day!

(for a typical Refinery of 250K BPD capacity)

Given the Kerosene average price in 2015 was $1.735, the total saving on Kerosene is $3,157,000 USD per Year. Obviously, there is additional saving on the other distillate as well.

Conclusion

The efficiency of the crude distillation unit is linked to its capability to change the production conditions as such that an optimal yield of naphtha, kerosene and diesel oil is achieved. The demands for certain distillates in the marked and prices these have its impact CDU to produce the most valuable distillates at maximum capacity.  Process conditions have to be adjusted to shift of the production ratio between the distillates without affecting its quality. This requires clear control over the initial and final boiling points of the

On line monitoring of each distillate allows accurate measurement of the upper distillation points (T90 – FBP) from the (IBP – T10) lower boiling distillate with accurate measurement of the lower distillation points. It allows accurate cutting between two neighboring distillates towards the fraction of higher value (i.e. kerosene in diesel, diesel in AGO) from the heavier cut.This can be achieved by adjusting the distillation tower temperature profile. Uncontrolled adjustment of the process conditions may lead to the production off spec distillates. On-line monitoring of the quality of distilled naphtha, kerosene and diesel is inevitable. It shows the stability of the process and avoid while changing the process conditions to prevent overshooting.

With strategic implementation at the crude unit mid-section, on-line NMR analyzer will enable the recovery of additional 300-500 barrels per day of critical distillate products from a typical 100,000 barrel per day crude distillation unit.

 4IR On-line NMR analyzer along with the Model Gate Way software, offer a viable means for accurate process analysis and control of the CDU, from crude feed to finished distillates.

Utilization of AI-60 NMR 3rd generation process analyzers is gaining momentum to engineer precise blends at much lower operating costs; Utilization of this technology gives refineries a large advantage in coping with changing costs of crude oils and distillates

Introduction

Traditionally refineries were constructed to distill conventional light crude oils. Changing economic conditions, wide variations in the price of crude oils and shifting of distillates, as requested by the market, force refineries to optimize the cost of their distillation feedstock.  This is achieved by blending high value light crude oils with heavy (unconventional) crude oils of varying qualities, or buying readymade blends. Lower quality crudes include heavy crudes from known source locations, as well as opportunity crudes that are brought to the market by traders worldwide. These crudes, of variable quality, can be purchased at lower costs than known proven stock. Blending these with standard more expensive grades of crude is the current best way to produce crude blends that bear optimal properties to be processed and at minimum refining cost.

Operating Refineries worldwide have been built and designed for handling very specific ranges of crudes and blends for optimal production and cost efficiency.  Due to the wide expansion of drilling into unconventional energy plays as well as an expanding global footprint of pipelines and shipping the makeup of the crude supply has drastically changed and will continue to evolve…

The majority of distillation of crude oil has been targeted to produce gasoline components, such as light and middle distillate. During the past decade, especially in the most developed countries demand for fuels is shifting from gasoline towards diesel fuels. In the past predominately light crudes were distilled for gasoline, today refineries must be capable to efficiently distill heavier crude oils to increase the yield of middle and heavier distillates.   Refining margins for most refineries, which were not able to adapt to this market demand shift find themselves running in the red.  Technological limitations caused many refineries to buy expensive light crudes that do not to produce specifically those distillates that are most demanded in the market, and have the more profitable prices. Many refineries suffered large losses. A large number of refineries either, closed or changed their activities from distilling toward blending due to the new market conditions.

Currently crude blending is performed by blenders or refineries, who buy varying types and grades of crude oils. These locations upgrade the crude’s chemical and physical properties to produce a synthetic crude oil at optimal cost, which can be easily processed in the equipment of refinery and will predominately yield high value distillates.

Characteristics  of Crude Oils Worldwide

Physical and chemical properties of crude oils correlate directly with the chemical composition, and vary according to their place of origin, as can be seen in figure 1. Crude oils are characterized as light or heavy, sweet our sour.

Quality properties determine the market value of each type of crude individually. The most important quality characteristics are: density, the TAN and the sulfur content. The API (Density) ranges from light crudes (high API, low density) to heavy crude oils (low API, high density). Sulfur is present in crude oils as hydrogen sulfide and as polysulfide. Partially these sulfur containing molecules will decompose during the distillation process, while hydrogen sulfide evolves. The sulfur content and other acidic components in crude oil, such as naphthenic acids, are highly corrosive, and responsible for the crude oil to be characterized as sour or sweet. These characteristics determine the price paid to suppliers for ”raw” crude oils.

Refinery equipment

Crude oils with high acid numbers/value are heavy crude oils with high acidity or High TAN. High TAN crude oils are characterized by having:

 High density and viscosity

High nitrogen content

High gel-asphalt content

High salts and high heavy metals

Fewer light components,

Low solidification point,

Low yield of light oil distillates

 This type of crude causes water – oil separation by the De-Salter to be more difficult than in conventional crudes. These properties also cause these crudes to give low quality products that are very corrosive. Commonly, TAN crude is called “opportunity crude”.  The price is about 70% of conventional crude oil. The additional cost of processing high TAN crude is within the range $3/bbl., but the savings compared to conventional crude processing can reach $20/bbl. Utilizing opportunity crude is very attractive to refineries who have the technology to efficiently process it.

Most refineries have been designed and constructed specifically based upon the crude oil availability and ease of purchase. This limits many refineries to purchasing only a few types of crude oil. Many refineries that are constructed to distill light and low sulfur crude oils are not currently capable to process heavy fuels efficiently or for a profit.

  1. The distillation unit and its pipelines are not constructed from high TAN and hydrogen sulfide resisting metals. This causes increased corrosion which will increase the expenses of maintenance and risk of failure.
  • Critical differences between the physical and chemical properties make heavier crudes oils more difficult to distill than lighter crudes. Higher viscosities, fouling tendencies, and different flow streams, make it problematic to maintain stable crude charge rates. These are required for stable product yields, quality and reliability. Difference in boiling points between light and heavy crudes require different temperature process conditions such as preheating and different distillation temperatures, overhead etc. Heavy fuels are rich in asphaltenes and metals and other contaminants, which cause poor desalting performance.

Oil refineries are custom designs based on the types/grades and supply of incoming crude supplies as well as the market demands for outputs. The most refineries are built and designed, for a limited number of crude oil types. Historically, refineries purchased their crude oil from specific locations and with specified chemical and physical properties. Many refineries were designed to refine light and sweet (low sulfur content) crude oils based on the regional availability of this type of oil.

The limitation for refineries to distill a broad range of crude oil types, forced many refineries to change their strategies. Dozens of refiners in the US and in Europe closed down and turned into terminals or put them up for sale to private companies. Other refineries decided to invest and upgrade their equipment and processing facilities to enable distillation of a wider range of crudes including heavy oils. These key refineries also increased production volumes of distillates that are highly demanded by the market driving growth and profitability.

Upgrading legacy distillation units, constructed to distill light sweet crude into units that distill heavy sour crude oils requires enormous investments in equipment and process planning. It is up to each refinery to consider whether the upgrade is going to drive revenue and profit growth.

Product shifting:

Demand continues to shift for certain distillates and refinery products. Global demand for diesel oil is replacing that of gasoline. It is expected that middle distillates will comprise 45% of global demand barrel by 2016, which is a rise of 10% as compared to 2005. It can be expected that the diesel gasoil in developing nations will increase by 10 M/M d/d from 2009 to 2030.

Currently the United States is the largest consumer of crude oil. While the US demands remains relatively stable, China is the second largest consumer of crude oil with an annual 4% yearly increase in demand. The latest generation of refineries constructed today, are designed so that they can process a wide range of crude oil grades and types from domestic and international markets.

The global consumption of heavy fuel oils is decreasing as environmental regulations restrict the emission of gasses originated from the use of “dirty” fuels. As a result of environmental restrictions, natural gas is the preferred “clean fuel” as opposed to conventional refinery fuels. This influences the properties of heavy fuel that can be blended, without producing and accumulating large quantities of heavy bottom fuels. To be profitable a refinery must adapt itself quickly to the supply and demand changes arising from regulatory and environmental drivers.

The major operational cost of the refinery is contributed by the price of the input crude oil.  It is typically 80% to 90% of cash flow. Reducing the cost of the crude feedstock, without changing the range and volumes of high valued distillates, increases the refining margin significantly and by that the profit of the refinery.  Refinery profits are a direct outcome of the strategy applied by the refinery to purchase low cost crudes and to produce distillates with a high market value. To increase the refining margins and be competitive with their competitors, refineries are obliged to minimize the cost of their crude feed, without affecting the capacity to produce of high valued distillates. Heavier crudes are typically more difficult to process based on legacy technologies, and the increase of consumption of diesel oil as compared to gasoline, light sweet crude oils are sold at a higher price than heavy crudes.  Reducing the cost of the crude input, without changing the range and volumes of high valued distillates increases drastically the refining margins.  

Potential Crude Blenders

To achieve increased refining margins, refineries have changed their feed stock from pure crude oils to synthetic crudes, by blending two or more different crudes of different market value. The resulting blend should still bear the required properties to process them efficiently in the refinery, without influencing the product range, product volumes and product qualities.

There are two major supplies of blended crude (synthetic crude):

  1. Refinery industries:

Crude blending is done directly at the refineries to prepare low cost and compatible blends for internal consumption or for trading them in the global oil market

  • Blend producers and Trading companies:

Efficient crude blending open opportunities for oil blenders, oil trading companies and terminals to bring low cost blends on the market, which can be sold to the refineries with a high market value and with a marketable quality.

Crude mixing can be applied throughout the entire supply chain of crude oil, from its well (upstream) enabling transportation, through terminal blending (midstream) to the refineries (downstream users). The final supply to the distillation unit may be a combination of these applications.

Crude oil blending is a common practice to reduce the cost of the crude oil mixtures being distilled in refineries. Efficient blending of crude oils of different origins and of different qualities can result in the highest possible refining margins. Increasing the refining margins is achieved when blending of different low cost crude oils does not affect the production capacity of high value distillates. The Strategic value of crude oil blending includes several parameters. Each of them contributes to the overall final cost of the crude oil entering the crude distillation unit, and the refining margins.

  1. Systems limitations of crude distillation units to refine any type of crude oil.
  2. Cost differences of crude oils according to their location of origin, market demand their chemical and physical properties. An increased ability to process unconventional crudes leads to an improved refinery margins.
  3. Demand shift in the major markets from gasoline towards diesel fuels. Throughout the last decade an increased demand of diesel fuels in the European market caused the refineries to increase the diesel yield and reducing the naphtha yield.
  4. High viscosity, especially in heavier crude oils, affects the flow properties of the crude during transportation through pipe lines. Blending these types of crude oils with diluents or conventional crudes may be required to reduce the viscosity and to increase its flow properties to reduce transportation cost.

Crude oil economics

Global political and economic changes forced refineries to change their sources of feedstock. Refineries used to distilled crude oil from single locations, today refinery profits are a direct result of the ability to create blends that compose minimal quantities of high value crude oils such as Brents, and maximize quantities of unconventional crudes, such as heavy and extra heavy crudes, sour crudes and bitumen extracted from oil sands.  The final blends should still bear those physical and chemical properties that are required to enable a smooth and continuous operation of the distillation unit at the lowest possible operating cost.

Basically crude oils can be divided into 4 major groups:

  1. Light Low sulfur crude oils (API 30-40°, S ≤ 0.5% mass)     Cost  55 USD*
  2. Light Sulfur crudes (API 30-40°, S=0.5-1.5% mass)             Cost  53 USD*
  3. Heavy, high sulfur (API 1-30°, S 1.5 – 3.1% mass)               Cost  43 USD*
  4. Extra Heavy high Sulfur (API = 15°, S ≥ 3% mass)                          Cost  35 USD *

* (Prices Are Given In Us $ / Barrel, Sources: Bloomberg, January 20 2017).

The numbers illustrate how the value of crude oil can be increased by blending higher grade crude with lower grades. The ratio of a component in the blend is actually limited by the physical properties required for production of the highest valued distillates to the largest extent, and by the refining infrastructure on location to process the blend.

Opportunity crudes, which are those heavy crudes with high TAN values, are the least expensive feedstock. Various crude oils, such as some Venezuelan crude and some Canadian crude (WCS) are very heavy, and are attractive for bitumen production. Its processing is very limited by their very low API.  To produce other distillates from these crude oils, they must be upgraded by dilution with light crudes or kerosene.

The high viscosity of heavy crude is another drawback. Blending with light crude oils, kerosene or other diluents, is required to give them flow properties that enable their transport through pipelines without heating.

To reach or grow profitability refineries are investing and upgrading so they can maximize the consumption of “opportunity crudes”, as these crudes are far less expensive than conventional crude oils and when done properly make the same outputs as previously done with the high feed cost of conventional crude.

Heavy oils are hydrogen deficient and have high levels of contaminants, such as sulfur, nitrogen, organic acids, vanadium, nickel, silica and asphaltenes. The method of upgrading heavy oils, considered as a low cost, is to dilute these with hydrogen rich higher-quality light crude oils or by using hydrogen rich diluents to increase the H/C ratio.

  1. Blending of heavy crudes with lighter crudes or upgrading the API.
  2. Blending heavy crudes with lighter crudes, upgrading by creating sweeter crudes oil with a higher API.
  3. Diluting heavy crudes with light crudes or diluents to increase the pump ability through pipelines.

Prices of crude oils fluctuate on an hourly basis. Price differences between heavy and light, sweet and sour crude oils are variable. Crude oil prices are also influenced by the global demand, and the amount of crude oil offered by oil producing countries. Therefore, refineries are obliged to buy there feed-stocks as such, that blending will provide the lowest cost feed for the refinery and still make products that satisfy market demand.

Blending Processes

Crude oil blending is performed by two different methods:

  1. In-tank blending (Batch Blending):

Specific volumes of different kinds of crude oils, which are stored in separated tanks, are loaded into a blending tank, where they are mixed until a homogenous composition is achieved. The tanks are mechanically stirred. Samples must be withdrawn to determine whether the blend is homogeneous and whether it conforms its predetermined specification. In any case of discrepancy, correction of the blend must be conducted. The process of in-tank blending is a very old practice, very time consuming and highly expensive technique.

  • In-line blending:

In contrast to “tank blending” in line blending is performed by simultaneously transferring different crude oils through an on line static mixing device to the final blend tank. The predetermined flow ratio between the different crudes will provide the blend of the required quality. In-line blending allows on-line correcting the quality of the blend, by changing the ratio between different feeds.

Main advantages of in line blending over in-tank blending are:

  1.    The blend is produced instantaneously.
  2.     No stirred “blending tanks” are required – all tanks are designated to final    products saving footprint, time and complexity.

To efficiently and errorless operate the blending process, on-line process analyzers are required to instantaneously measure the blend downstream and to feed the blending operators with the required quality details of the blend in production. This enables real-time and on-line to automatically correct the feeds during the blending process, providing the blend of requested predetermined quality properties perfectly the first time. It eliminates the need of corrective re-blending of an entire tank, as well as unnecessary “giveaways» and losses.

Determination of the blending recipes

Simulation software, such as LP (Linear Programming) modeling is commonly used to predict the ratio between individual components, to prepare the blend. Based on composition data of various crudes applied, and using the proper algorithm, this software is commonly applied to calculate and predict physical properties of blends to be produced.

This software calculates the ratio of different crudes to be blended, resulting in a crude blend with the desired properties, leading to the desired distillates at optimal yield. Incorporation of a large database, which covers a broad range of various crude oils is required to accurately predict a blend of predetermined physical properties and with the potential of maximized production capability of high valued distillates. Adequate blending simulation models should not only be restricted to the chemistry of the crude oil distillation, but also to its economics. It must be capable to calculate the composition of different crudes that provides the best economic blend of the lowest cost. Such blends, contain maximized volumes of those crude oils of lowest cost, but still bear the most attractive refining properties. This strategy will minimize the variable costs and maximize its profitability.

The LP is based on the assay of different crudes oils to be blended. Any changes in the assay will affect the LP predicted blend.

Fundamentals of effective crude blending simulation software should include the following features:

  • Calculation of the blend components and their ratio.
  • Ratio limits.
  • Predicted fractions temperatures.
  • Properties constraint of the blend.
  • Properties of the fractions.
  • Constraint limits.

Next to the chemical – physical properties of the blend, the software should also be focused on the potential economic profit of the blend. This requires software also to relate to:

  • Cost of various crude oils and crude oil blends.
  • Prices of final distillates and other refinery products.
  • Volumes of final distillates required by the market.

Currently time consuming and costly laboratory analyses are required to verify the «real» physical properties of the output blends. Re-blending is required if these properties are not achieved after testing is completed. 

To achieve maximum cost efficiency blending requires on-line monitoring of the blend properties throughout its entire production. Chemical compositions differ from crude to crude. Notwithstanding whether the crude oil is pure or a blend of crude oils, on-line corrections are continuously conducted to maintain a stable product quality. This requires real time collection and validation of physical properties from the blend throughout its entire production process. Among all analyzers available in the market, NMR process analyzers are most suitable for this purpose.

The first generation NMR process analyzers were launched in the late nineties to very limited success. Nuclear Magnetic Resonance is an effect whereby magnetic nuclei in a magnetic field absorb and re-emit electromagnetic (EM) energy at a specific resonance frequency.  The basics of NMR process analyzers are the alignment of nuclei in a magnetic field. An external RF pulse is applied which distort the alignment of the nuclei in the magnetic field. The resonance frequency depends mainly on the strength of the magnetic field. When the RF pulse ends, protons relax and align back to their initial equilibrium position, which generates a decay signal: Free induction Decay Signal (FID).  

Crude oil is a mixture of organic chemical compounds, mainly carbon and hydrogen atoms based molecules. Neighboring atoms, such as carbon, oxygen and sulfur, and neighboring chemical bonds, influence the strength of the energy absorption and emission of the hydrogen nuclei, in a magnetic field. According to that, the signal of each hydrogen atom shifts differently in the NMR spectrum. These well-defined chemical shifts represent the chemical structure of molecular species. Linear correlation between the intensity of the signal and the hydrogen concentration enables to quantify the different hydrogen nuclei.

Figure 2: Typical NMR Spectra of Crude Oils

Physical properties in crude oils and in distillates correlate with their chemical composition. This allows chemo-metrics methods to correlate between the measured spectral data and the physical – chemical properties of crude oil, or other distillates. In contrast to other chemometrics based spectral technologies, such as Raman and NIR spectrometry, which are based on fingerprints, due to its molecular specificity, and its linear quantitative correlation, the NMR technology requires far less reference samples to establish a chemometrics model.

NMR based on-line spectrometers are not limited to transparent fluids, but can be applied to opaque liquids as well. Crude oils contain water heteroatom molecules, which are easily distinguished by NMR spectrometry.

NMR on line spectrometry with appropriate chemo-metrics has the ability to determine the following properties in the crude oil, such as

  • Specific Gravity
  • TBP (True Boiling Point) yield
  • Aromatic content %
  • Olefin content %
  • Pour Point
  • Water %
  • Sulfur %

Follow up of these parameters are highly important during crude blending. On line measurement of these critical parameters allows to blend synthetic crude of predefined properties, either from a physical-chemical point of view or from an economic point of view.

Online monitoring of the blending process prevents the production of blends that are not compliant with the requirement of the refinery. A conservative 1% or 2% in blending error correction will save millions of dollars per year. 

Precision of 3rd Generation NMR process analytics

The concern when investing in on-line process analyzers is the credibility of the analytical data provided by the analyzer. When the accuracy of predicted results lacks, the instrument loses its credibility to rely on its analytical data. The occurrence of such events does not only cause financial losses to the customer, but in many cases also to the developer, manufacturer and the service provider.

High accuracy in the correlation between NMR process analyzer obtained results and laboratory results, characterizes the latest developed production of NMR process analyzers.. Early generations of NMR process analyzers were sensitive to temperature differences, due to the accumulation of too much heat by electronics and a heat conducting measuring probe.  This made it difficult for early generation systems to make the move from the lab environment into a hostile production environment. This latest generation of NMR process analyzers the overall design excludes any accumulation of heat in the magnet or in its surroundings by uncontrollable fluctuations, such as heat transformation by electronics, the magnet itself and by the material, which is measured. Not only did this increase its stability to heat fluctuation by some eight degrees in also allowed for the system to be installed in more hostile environments for in line processing. This means that any required heating of the crude oil prior to blending, or after the de-Salter is possible, without affecting the analytical results, as long as by the end a temperature deviation of 10 °C is maintained.

The figures 3-5, show the correlation between NMR results and laboratory analyses of different crude oils.

The figures demonstrate the high accuracy in correlation between NMR results and traditional laboratory measurements. Partially these measurements relate to chemical matter such as water and sulfur, and partially to physical properties such as the distillation curve, and an excellent overlap between SimDis and NMR analytical results. Without any doubt, taking into account the time required for laboratory analyses, the cost to perform crude oil assays or the purchase and maintenance of SimDis, more than justify the incorporation of new generation NMR process analyzers in for crude blending processes, especially in cases of in-line blending. It enables precisely to monitor the quality of the blend in production, and if required to change the ratio between different crude oil feeds to establish and maintain the requested quality of the final blend.

Optimized crude oil blending station setup

Crude Blending Station consists of a blending skid, which is available to receive liquid or gas streams, optimization software and analytical equipment.  Analytical equipment should be able to provide online measured data of a component and product streams involved in a blending. This data is transferred to optimization software whose target is to optimize produce a blended product with minimum product cost, minimal quality giveaway, and minimal individual raw material formula deviation. In order to achieve this objective, the optimization system continuously receives quality feedback of the finished product using on-line analyzers.

Figure 6: Set Up Of A Blending Station With Incorporated next generation NMR Process Analyzer, Simulation Modeling and Blending Control. (Components can be high and low quality crude oils, diluents and/or gasses (NLG).

Using the inputs from online analyzers, the optimization system performs either a feed forward or feedback control of raw materials based on the quality of instantaneous product samples obtained from the blend header.

Both technologies LP simulation and NMR process analyzers can operate «stand alone». However, to enhance the optimization of the crude blending process, it is essential to integrate between both technologies.

Efficient blending optimization is a dynamic process of mixing, continuous blend analyses, simulation model adjustment and process control. All influencing elements should be taken into account, as shown in figure 8. Any missing step in this chain will have its impact on the efficiency of the entire process and reduce its revenue.

Figure 7: Dynamic Process of Mixing, Continuous Blend Analyses, Simulation Model Adjustment and Process Control.

Additional applications for on line process NMR process analytics.

Additional applications for NMR on-line process analytics are of interest in the application of NMR process analyzers for blending of different crude oils achieving a crude oil suitable for production at the highest refining margin, in equipment available at a refinery,

  1. Crude oil compatibility during blending:

Blending different crudes, especially those which involve unconventional crudes, may cause precipitation of asphaltenes, which causes fouling in the pipes and process units. Asphaltenes are soluble in polar aromatics, such as toluene, but insoluble in paraffinic non polar solvents. On line analyses of the SARA content (Saturates, resins, aromatics and asphaltenes) can be a potential tool for on line determination of quantitate ratio between different crudes to be blended, or between crude oils and polar solvents, without causing asphaltenes to precipitate. This will reduce operational and repair costs.

  • Natural gas application in crude oil blending.

NLG’s are produced via refrigeration and distillation processes that take place in gas plants and refineries. NLGs are considered “by-products” in the oil and gas industry. Gas plants extract NLGs for profit and/or to ensure production of pipeline quality natural gas. Liquid condensate of natural gas contains carbohydrates heavier that methane: ethane (33-55%), Propane (20-30%) normal butane (10-15%), isobutene (4-8%) and compounds with a carbon content higher than pentane, «pentane plus»+, also called natural gasoline.

NLG prices are relatively low. NLG and other off spec grade materials from the natural gas production industries are applied by refineries and blending companies to upgrade heavy crude oils. Another option for its application is to lower the viscosity of heavy crudes, to make them easier to flow through pipe lines. Implementation of on-line NMR process analyzers provides an effective tool for efficient blending of NLG and crude oil to such a blend that has the required physical properties and at lowest cost.

Conclusions

Crude oil blending is a major way to increase the refining margin. This can be achieved either by the increase of those distillates that have a high demand on the market or by decreasing the cost of the crude feed and efficiency of the process.  Physical properties of crudes oils limit the process ability of crude oils in refineries. Further to that, many crude oils are either too expensive or result in economically less attractive distillates. Crude blending is a common strategy applied by refineries to overcome these drawbacks, either by in-house blending or buying crude oil blends.

Different blending options exist to upgrade unconventional crude oil into synthetic crudes of higher values. A proposed automatic crude blending station integrates between LP in combination with on-line NMR process analytics. It can be used either by traders who offer blending services, or proposed directly to traditional refineries. Some crude traders are integrated with refineries, while others produce material that meets certain minimum quality requirements to be sold. Cost, market value, availability and technology decisions are the main factors, to be considered in planning the configuration to be used for upgrading unconventional raw crude oil.

Two major principles for are required for the success of efficient and optimized crude blending:

  • Accurate On-line process analytics – knowing the crude oil and blend quality properties at any time and at any stage.
  • Dynamic Simulation modeling — blending simulation models are commonly used to determinethe required blend composition.  Highest blending optimization can only be achieved by updating the simulation program with real time analytical data of the crude oil and blending quality properties.

Incorporation of appropriate process analyzers is highly efficient tool for on-line monitoring of blended crudes qualities, such as NMR spectroscopy based process analyzer, which is efficiently used to determine chemical composition and physical properties in dark and opaque streams. The benefit of NMR spectrometry lies in its linear correlation between hydrogen atoms of the molecules present in the crude oil, and the distinguished chemical shifts representing the chemical nature of its components. Chemo-metrics transforms the spectrometric measurements into physical properties which are characteristic for the crude oils and blends.

This technology provides real-time data and information about the physical and chemical properties of the blend in process. On-line adjustments and changes between blend components can be performed accordingly, until the proper required physical properties are achieved.

Incorporation of the latest generation of Process NMR analyzer enables to increase the blending efficiency and accuracy of crude oils of different prices and qualities, and to reduce unnecessary giveaways. Efficient blending reduces the cost of the feedstock. It will significantly contribute to improve the refining margins, and the profitability of the entire refinery.

This article establishes the capability of NMR, specifically using a mid-field 60 MHz NMR analyzer, as a viable alternative to amide analysis using the current HPLC method.

It describes the work in the following areas:

The identification of pure reference compounds, which constitute the mixture present in the amide stage including:

  • Methacrylamide (MAM)
  • Methacrylic acid (MAA)
  • α-Hydroxyisobutyramide (HIBAM)
  • α-Sulphatoxyisobutyramide (SIBAM)
  • Ammonium acetonedisulphonate (AADS)

The profiling of simple, binary mixtures of components to establish resolution and the suitability of the technique for quantification:

  • HIBAM+SIBAM
  • MAM+MAA

The analysis of “real” amide samples from the mixer and reactor of MM7.

Introduction

Presently, amide mixer and reactor samples from MM7, MM8 and MAA2 are analyzed offline via high performance liquid chromatography (HPLC). Values obtained from this analysis include conversion index (CI), water balance and decomposition index (DI).

Recent requirements for amide reactors have created a need for a continuous optimization program, which will ensure that reactors run at consistently high efficiencies and give the maximum possible output.

Despite the reliance on HPLC to assess the performance of the amide stage (what is the amide ‘stage’),  there  are several  drawbacks that  limit  the  convenience of  this  analysis  for optimization purposes:

1.  Frequency of data collection – Currently 1-2 samples are collected and analyzed every 24 hour period per reactor, this is dictated by the long HPLC system preparation and analysis times required for each sample. Each analysis only yields one data point for each parameter. This low rate of data collection severely limits the rate with which the reactors can be optimized and is insufficient.

2.  Offline sampling – There are difficulties in the handling of amide mixture samples. Many of the components within the amide samples themselves are not stable towards ambient conditions (for instance HIBAM/SIBAM), meaning that the sample composition is prone to change post-sampling. This introduces a further degree of uncertainty and impacts the reliability of the technique. In addition, samples solidify below 40°C and due to preferential crystallization of components; if this is allowed to happen to any degree then samples may not be representative of the amide mix. Both of these factors may give rise to high standard deviations in the observed data and hamper optimization efforts.

3.  Delay – It will often be a matter of hours before HPLC data are fed back for response of the technical team. This means that any measures taken are well after the event that gave rise to the results, by which time the situation may well have already changed. This long delay between sampling and feedback is clearly not ideal.

4.  Reliability – Although not proven, the reliability of the HPLC method itself has often been questioned. Being high in sulfuric acid and sensitive to moisture, the nature of the samples makes them difficult to analyze by HPLC. To overcome this, the current measurement uses specialized graphite columns in the HPLC instruments but resolution of certain peaks in the analysis is not good and the column deteriorates quickly (requiring replacement every 6 months).

Clearly, a need exists for an alternative analysis method which addresses some or preferably all of these challenges in order to provide the technical team with frequent, quick, sample-free (?) and reliable feedback from the amide stage.

Proton Nuclear Magnetic Resonance (1H NMR) Spectroscopy has been identified as a potential technique for the achievement of this aim and offers numerous advantages:

·    Very little system preparation – 1H NMR only requires periodic “shimming”, in order to maintain  homogeneity  of  the  magnetic  field.  

·    Frequency of feedback – A major advantage of 1H NMR is that individual scans only require a matter of seconds to collect. Depending on sample concentration, several scans may be required to obtain a reliable, composite spectra but the high concentration of the amide stage mix will work in our favor in this respect. This has the potential to generate data points numbering in the order of thousands for any given 24 hour period.

·    Online analysis – 1H NMR does not need to come into physical contact with samples and therefore lends itself to being adapted to online analysis. Thus all the problems associated with physical sampling can be circumvented.

·    Reliability —  1H NMR is  inherently quantitative as it  measures the  relative  signals from hydrogen nuclei (protons) present on each of the molecules in the mix, given that complete relaxation  of  these  nuclei  is  allowed  to  occur.  The relative ratios of components can therefore be accurately determined from first principles, without the need for continuous calibration.

1H NMR has the potential to address all the issues surrounding the current HPLC analysis. Conventional NMR spectroscopy however, is both expensive and unwieldy due to the high cost of the instrumentation, the constant supply of cryogens required to cool the magnets and the large, magnetically shielded space required to house equipment.

Technological advances have enabled the use of rare-earth permanent magnets for building relatively small, albeit relatively low field-strength spectrometers. These instruments are typically small enough to fit on the bench, require no cryogens and have their own built-in   magnetic   shielding.   Such   an   instrument, 4IR AI-60 60 MHz   NMR analyzer, was used for this study.

This report describes the preliminary work to analyze pure reference compounds, binary mixtures of particular analysts of interest and finally the analysis of amide samples from MM7 in order to assess the suitability of the technique.

Methods of Investigation

Pure reference compounds were analyzed diluted in both deuterated DMSO (DMSO-d6) and pure sulfuric acid (H2SO4). DMSO-d6 is a commonly used NMR solvent and produces virtually no interference with the rest of the spectrum. However in order to realize the goal of operating a NMR spectrometer on-line with recycling of materials, only components already present in the amide mix should be added and recycled, therefore H2SO4 will also be utilized despite its strong signal at about

11.0 ppm in the resultant spectra.

The analysis of the following reference compounds in both DMSO-d6 and H2SO4 were recorded:

·    Methacrylamide (MAM)

·    Methacrylic acid (MAA)

·    α-Hydroxyisobutyramide (HIBAM)

·    α-Sulphatoxyisobutyramide (SIBAM)

·    Ammonium acetonedisulphonate (AADS)

Some simple binary mixture experiments were also carried out, investigating the resolution and quantitative relationship between the following analysts:

·    HIBAM/SIBAM

·    MAM/MAA

Two final experiments will be carried out to analyze and quantify one amide mixer and one amide reactor sample from MM7.

Preliminary spectra were carried out using a standard 1 dimensional, high-sensitivity 1H NMR experiment dubbed “power scan” in the AI-60 software unless otherwise stated. The parameters of a power scan are as follows:

·    40 scans

·    6.4 second acquisition time

·    15 second repeat time.

·    90° pulse angle

Results and Discussion

Reference Spectra

MAM

Figure 1. The structure of MAM.

Shift/ppmMultiplicityIntegralgroup
1.63Singlet3.00CH3
5.11Triplet1.03C=CHH
5.46Singlet1.03C=CHH
6.81Doublet (broad)1.83CONH2
Figure 2. The 1H NMR Spectrum of MAM in DMSO-d6.

The multiplicity only identifies the visual appearance of the signals, as  some of the true NMR fine structure of the peaks might  not be resolved at this field strength

When reviewing the 1H NMR spectrum of MAM in DMSO-d6, a large singlet is observed at 1.60 ppm with an integral of 3, this signal originates from the 3 methyl protons. Two signals occurring at

5.11 and 5.46 ppm respectively and each integrating for a single proton are assigned to the 2 methylene protons. A broad doublet is observed at 6.81 ppm and is assigned to the 2 amide protons.

Tal, I don’t think that we should enter into any speculations about the fine structure. It is almost certainly more complicated than you think. We can be sure about the assignments only if I look in the literature for high-field spectra. I can do it but it will take much more time

Shift/ppmMultiplicityIntegralgroup
2.20Singlet3.00CH3
6.29Singlet0.98C=CHH
6.62Singlet0.97C=CHH
8.20Singlet (broad)1.53CONH2
Figure 3. The 1H NMR Spectrum of MAM in H2SO4.

When reviewing the 1H NMR spectrum of MAM in H2SO4, the HsSO4 contributes a large singlet peak at 11.22 ppm but otherwise many of the same features are present. All signals have shifted downfield, the methyl singlet to 2.20 ppm, the two  methylene  singlets  to 6.29  and  6.62  ppm respectively and the broad amide singlet to 8.20 ppm.

  • MAA
Figure SStructure of MAA.

Shift/ppmMultiplicityIntegralgroup
1.26Singlet3.00CH3
4.98Triplet1.00C=CHH
5.56Singlet0.99C=CHH
12.10Singlet0.99COOH
Figure 5. The 1H NMR Spectrum of MAA in DMSO-d6.

When reviewing the 1H NMR spectrum of MAA in DMSO-d6, a large singlet is observed at 1.26 ppm with an integral of 3, this signal originates from the 3 methyl protons. Two signals occurring at 4.98 and  5.56ppm  respectively and  each  integrating  for  a  single  proton  are  assigned  to the  2 methylene protons. The singlet at 12.10 ppm is assigned to the carboxylic acid proton.

Shift/ppmMultiplicityIntegralgroup
2.13Singlet3.00CH3
6.45Singlet0.99C=CHH
6.89Singlet0.98C=CHH
Figure 6. The 1H NMR Spectrum of MAA in H2SO4.

When reviewing the 1H NMR spectrum of MAA in H2SO4, many of the same features are present. Similar to  MAM,  all  signals  have  shifted  downfield,  the  methyl  singlet  to  2.13  ppm,  the  two methylene  singlets  to  6.45  and  6.89  ppm  respectively  and  the  carboxylic  acid  singlet  has presumably disappeared beneath the H2SO4 peak.

  • SIBAM
Figure 7. The structure of SIBAM.

Shift/ppmMultiplicityIntegralgroup
0.94Singlet6.00CH3
9.56Singlet (broad)0.81CONH2
Figure 8. The 1H NMR Spectrum of SIBAM in DMSO-d6.

When reviewing the 1H NMR spectrum of SIBAM in DMSO-d6, a large singlet is observed at 0.94 ppm; this signal is assigned to the 6 chemically equivalent methyl protons with an integral of 6. A broad singlet is present at 9.56 ppm, which is tentatively assigned to the 2 amide protons but the integral is difficult to determine due to the broad peak shape.

Shift/ppmMultiplicityIntegralgroup
1.94Singlet6.00CH3
2.17Singlet1.34?
9.56Doublet (broad)1.30CONH2
Figure 9. The 1H NMR Spectrum of SIBAM in H2SO4.

When reviewing the 1H NMR spectrum of SIBAM in H2SO4, the methyl singlet appears to have been shifted downfield and now occurs at 1.94 ppm. Finally, the broad amide doublet can be seen at 8.86 ppm but is poorly resolved from the large, sulfuric acid singlet.

Tal, both up field ‘singlets’ could be from the methyl groups, the solvent could have induced some in equivalence.

  • HIBAM
Figure 10. The structure of HIBAM.

Shift/ppmMultiplicityIntegralgroup
0.93Singlet6.05CH3
4.86Singlet1.00COH
6.67Singlet (broad)1.56CONH2
Figure 11. The 1H NMR Spectrum of HIBAM in DMSO-d6.

When reviewing the 1H NMR spectrum of HIBAM in DMSO-d6, a large singlet with an integral of 6 is observed at 0.93 ppm; this signal is assigned to the 6 chemically equivalent methyl protons. A singlet with an integral of 1 is observed at 4.86 ppm, which is assigned to the OH group proton. A broad singlet is present at 6.67 ppm, which is assigned to the 2 amide protons but, as with SIBAM, the integral is difficult to determine due to the poor peak shape.

Shift/ppmMultiplicityIntegralgroup
1.95Singlet6.00CH3
2.17Singlet1.56?
8.88Doublet (broad)2.04CONH2
Figure 12. The 1H NMR Spectrum of HIBAM in H2SO4.

When reviewing the 1H NMR spectrum of HIBAM in H2SO4, the methyl singlet appears to have been shifted downfield and now occurs at 1.95 ppm and as with SIBAM, there is now a second singlet at

2.17ppm. Finally, the broad amide doublet can be seen at 8.88 ppm but is poorly resolved from the large, sulfuric acid  singlet.  It  is  interesting  that  the  alcohol  singlet  formerly  at  4.86ppm  has

disappeared entirely, which could be caused by rapid exchange with the solvent. The next sentence is too speculative. Interconversion does not necessarily give rise to identical spectra.

  • AADS
Figure 13. The structure of AADS.

Shift/ppmMultiplicityIntegralgroup
1.95Singlet4.00CH2COCH2
2.17Singlet7.69NH + 4
Figure 14. The 1H NMR Spectrum of AADS in DMSO-d6.

When reviewing the 1H NMR of AADS, a large singlet with an integral of 4 can be observed, which is assigned due to the 4 chemically equivalent methylene protons. A second, broader singlet is observed at 6.78ppm with integral value 8, and is likely due to the ammonium protons from the two ammonium groups.

Figure 15. The 1H NMR Spectrum of AADS in H2SO4.

Perhaps the most interesting reference spectrum reviewed here is the spectrum of AADS in H2SO4, which is vastly different from the spectrum acquired in DMSO-d6. At first, there appear to be three signals present, a large doublet at 4.72 ppm and two smaller singlets at 5.93 and 7.17 ppm. However this does not correlate to the known structure present in solution, in particular the doublet is anomalous as there can be no proton-proton coupling present.

A very neat way to explain this unexpected phenomenon is to suggest that 14N-1H coupling of the ammonium signal is occurring here. 14N has a nuclear spin of 1 and is >99% abundant, the resultant splitting pattern would be a triplet with the relative intensities being 1:1:1 as opposed to a triplet arising from proton-proton coupling, the relative intensities for which would be 1:2:1. This is further supported when considering that the peaks at 4.69, 5.93 and 7.17 ppm are separated by a constant

1.24 ppm, i.e. JNH = 52.7 Hz.

Shift/ppmMultiplicityIntegralgroup
1.95Singlet4.00CH2COCH2
5.93Triplet (JNH=52.7Hz)8.71NH + 4

The reason for the stark increase in resolution of this coupling (with respect to AADS in DMSO-d6) is explained in literature1  as being due to an increase in symmetry of the environment of the nitrogen center. This causes a vast increase in the spin-lattice relaxation time (T1) of the nitrogen nucleus and  thus  greatly  increases  the  sharpness  of  this  signal.  This  can  be  explained  by

+

considering  that  the  NH4

protons  are  essentially no  longer  exchanging  in  H2SO4   due  to  the

extremely low pH and as a result, all ammonium ions have now become symmetrical (tetrahedral).

4

The practical implications of this are encouraging as NH +

is an indicator of amide decomposition

and therefore, a decrease in efficiency of the amide stage. The ability to monitor any one of these

+

three triplet peaks would enable the accurate monitoring of NH4 oncentration.

All of this is speculations. The ‘doublet ‘ may not be a doublet at all but two singlets due to some inequivalence. The only way to prove something conclusively is to see a spectrum at higher field strength! The N14 coupling is rarely observed because  its T1 is very short AND the NH4 protons are exchanging with the solvent

The remaining signal in this spectrum must again be due to the methylene protons. This signal poorly resolved from the ammonium triplet peak at 4.69 ppm but can still be observed as a singlet at

4.74 ppm. Integrals are difficult to assign due to this overlap but if an approximate integral of 4 is given, the resultant sum integral for the ammonium triplet equates to 8.7, which is not drastically different from the 8 that is expected.

Binary Mixture Experiments

  • SIBAM/HIBAM

Equal weights of HIBAM and SIBAM were dissolved in DMSO-d6 and a spectrum was obtained from this solution using a “power scan”.

Figure 16. The 1H NMR spectrum of 1:1 SIBAM + HIBAM in DMSO-d6.

The resultant spectrum is not indicative of a simple mixture of the two components. A large singlet is observed at 0.89 ppm, which is slightly up-field of the methyl protons of either SIBAM or HIBAM. Another, much smaller singlet is observed at 1.10 ppm, which is slightly down-field of the methyl protons of  either  SIBAM or  HIBAM.  Interestingly,  the  alcoholic  proton  of  HIBAM is  no  longer observed and only one amide peak is present at 6.99 ppm, which does not correlate well to either compound. The spectrum here does not look particularly like either pure compound and perhaps hints at some kind of intermediate or complex between the two.

A further solution of equal weights of SIBAM and HIBAM was prepared in H2SO4  and a spectrum

was obtained from this solution using a “power scan”.

Figure 17. The 1H NMR spectrum of 1:1 SIBAM + HIBAM in H2SO4

Again the resultant spectrum does not appear to be a simple mixture of the two components. A large singlet is observed at 1.81 ppm, which is slightly up-field of the methyl protons of either SIBAM or HIBAM. Another, much smaller singlet is observed at 2.03 ppm, which is slightly down-field of the methyl protons of either SIBAM or HIBAM. Again, the alcoholic proton of HIBAM is no longer observed and only one amide peak is present at 8.76 ppm, which does not correlate well to either compound. In this instance it is noteworthy that the spectrum bears a striking resemblance to those obtained for either pure SIBAM or HIBAM in H2SO4, adding to the evidence that in this medium, the two are not discreet entities.

In order to better understand these spectra, another mixture of SIBAM + HIBAM was made in H2SO4, this time in a 9:1 ratio. Any signal exhibiting an increased integral with respect to the 1:1 mixtures could be presumed to be due to SIBAM

Figure 18. The 1H NMR spectrum of 9:1 SIBAM + HIBAM in H2SO4

Interestingly, this spectrum hardly differs from the one obtained of the 1:1 mixture; the two singlets at 1.81 and 2.04 ppm are essentially the same relative intensity. The most likely explanation for this would be that, even at room temperature and in either DMSO-d6 or H2SO4, a dynamic equilibrium exists between SIBAM and HIBAM. In this case the proportion of each can be affected by the addition of water so a simple experiment was carried out whereby a drop of water was added to the

1:1 SIBAM + HIBAM solution.

Figure 19. The 1H NMR spectrum of 1:1 SIBAM + HIBAM in H2SO4 with 1 drop of water added.

The relative intensities of the two singlets does indeed appear to shift; the singlet at 2.10 ppm now has an integral of 0.95 vs. its original 1.35. A further 9 drops of water were added to the solution to accentuate this effect.

Figure 20. The 1H NMR spectrum of 1:1 SIBAM + HIBAM in H2SO4 with 10 drops of water added.

With the addition of so much water, the singlet at 2.14 ppm diminishes in intensity quite significantly, now with an integral of 0.31. It can therefore be concluded that the singlet at 2.14 ppm is SIBAM and that the singlet at 1.94 ppm is HIBAM and that SIBAM is hydrolyzing upon addition of water to the system, driving the equilibrium further towards HIBAM.

Tal, is the conclusion of the last 3 pages that quantification is not possible? In this case, no speculations are necessary. It is sufficient to say that we have shown that this solvent cannot be used for quantidication

  • MAM/MAA

As no advantage between DMSO-d6 and H2SO4  had been established up to this point in the investigation, H2SO4  was chosen as the sole diluent for further work. H2SO4  has the advantage of being the process solvent, meaning that a diluted in-line sample could be recycled back into the bulk stream.

Equal weights of MAM and MAA were dissolved in H2SO4  and a spectrum was obtained from this

solution using a “power scan”.

Shift/ppmMultiplicityIntegralgroupComponent
2.01Singlet3.00CH3MAM + MAA
6.09Singlet0.47C=CHHMAM
6.24Singlet0.50C=CHHMAA
6.43Singlet0.49C=CHHMAM
6.64Singlet0.52C=CHHMAA
8.30Singlet (broad)0.40CONH2MAM + MAA

Figure 21. The 1H NMR spectrum of 1:1 MAM +MAA in H2SO4.

This spectrum very clearly shows the mixture of the two components. The methyl protons of each are compounded as a singlet at 2.01 ppm but the methylene protons of each are clearly resolvable from one another. The methylene protons of MAM occur at 6.09 and 6.43 ppm respectively and the methylene protons of MAA at 6.24 and 6.64 ppm respectively.

Figure 22. An expanded view of 1H NMR spectrum of 1:1 MAM + MAA in H2SO4, showing the methylene protons of the two compounds.

A  comparison  of  the  two  integrals  6.64  and  6.43  ppm  can  be  used  to  evaluate  the  relative concentrations of MAM and MAA:

The recorded weights used were:

Table 1. The actual weights of MAM and MAA used for the 1:1 binary mixture.

This crudely derived theoretical value only differs with the actual values used by 0.5 mol%.

MAM and MAA in a ratio of 99:1 were then dissolved in H2SO4 and a spectrum was obtained from this solution using another “power scan”.

Shift/ppmMultiplicityIntegralgroupComponent
2.01Singlet3.13CH3MAM + MAA
6.09Singlet1.00C=CHHMAM
6.24Singlet1.03C=CHH/ C=CHHMAM + MAA
6.43Singlet0.02C=CHHMAA
8.25Singlet (broad)1.79CONH2MAM + MAA
Figure 23. The 1H NMR spectrum of 99:1 MAM + MAA in H2SO4.

Again, the two components can be seen in the spectrum. The methylene protons of each compound are less resolved. The methylene protons of MAM occur at 6.09 and 6.43 ppm respectively and the methylene protons of MAA at 6.24 and 6.64 ppm respectively.

Figure 24. An expanded view of 1H NMR spectrum of 99:1 MAM + MAA in H2SO4, showing the methylene protons of the two compounds.

A  comparison  of  the  two  integrals  6.77  and  6.16  ppm  can  be  used  to  evaluate  the  relative concentrations of MAM and MAA:

The recorded weights used were:

Table 2. The actual weights of MAM and MAA used for the 99:1 binary mixture.

This time the difference between the actual and measured values is greater at 1.0 mol%, which is unsurprising, given the poor resolution between the peaks. However, the conditions presented here are completely optimised and can be considered to be reasonably accurate although lacking in precision. It is also noteworthy that this accuracy is consistent with binary mixtures ranging from 1:1 to 99:1, without any form of calibration.

A decrease in sample viscosity will almost certainly result in narrower line widths and therefore increase  precision.  This  is  an  obvious  area  for  optimisation  and  can  be  achieved  either  by increasing the amount of H2SO4 diluent or by resorting to a less viscous solvent if needs be.

Amide samples

  • MM7 mixer sample.

A sample was taken directly after the static mixer of MM7 and diluted to varying degrees using

H2SO4. The resultant solutions were analysed via 1H NMR using a “powerscan”.


Figure 25. The 1H NMR spectrum of a MM7 amide mixer sample diluted 1:1 with H2SO4

By using a 1:1 dilution factor, a very good signal-to-noise ratio is achieved. However, as anticipated the high viscosity of the same sample has caused to broad line-width and poor resolution.

A large singlet is observed at 1.62 ppm, which is due to the methyl protons of HIBAM. A second singlet at 1.84 ppm is assigned to SIBAM but is very poorly resolved.

A large singlet at 2.00 ppm is assigned to the methyl protons of MAM, although it is only partially resolved from the singlets at 1.62 and 1.84 ppm.

A weak signal is observed at 4.68 ppm and is thought to be one part of the ammonium (AADS) triplet, along with a signal at 7.13 ppm. The remaining part of the triplet is thought to be unresolved from the methylene protons of MAM, this idea is supported by the appearance of a shoulder on the peak at 6.07 ppm. Again, I am not sure about the triplet

The two singlets at 6.07 and 6.39 ppm are due to the methylene protons of MAM.

The large broad signal at 8.23 ppm is most likely a composite signal arising from amide groups in

MAM, SIBAM and HIBAM.

It is noteworthy that, at this dilution no signals accounting for MAA can be seen.

Shift/ppmMultiplicityIntegralgroupComponent
1.73Singlet3.42CH3HIBAM
1.96Singlet0.59CH3SIBAM
2.09Singlet3.00C=CHHMAM
5.88Triplet (JNH=51.0Hz)0.09*NH4AADS**
6.17Singlet1.00C=CHHMAM
6.50Singlet1.01C=CHH/ C=CHHMAM + MAA
6.85Singlet0.01C=CHHMAA
8.18Singlet (broad)2.05CONH2MAM
8.87Singlet (broad)0.53CONH2SIBAM + HIBAM

Figure 26. The 1H NMR spectrum of a MM7 amide mixer sample diluted 1:5 with H2SO4. *Obtained by taking the least interfered with signal from the triplet at 7.15 ppm and multiplying by 3.**All ammonium assumed to be arising from AADS at this time.

By increasing the dilution factor to 1:5, a good signal-to-noise ratio is still achieved and resolution is markedly improved.

In addition to the features noted in the previous spectrum, resolution between the three singlets at

1.73, 1.96 and 2.09 ppm is better but assigning an accurate integral for SIBAM remains challenging.

A new signal appearing at 5.88 ppm is thought to be the remaining part of the ammonium triplet and is no longer obscured by the singlet at 6.17 ppm.

Crucially, one of the MAA methylene singlets can now be resolved and can be seen as a very weak peak at 6.85 ppm.

Given the information already known about the components of the amide mix, the following rough approximation of their relative concentrations can be made.

Table 3. The predicted molar ratios of components in the MM7 mixer sample, based on 1H NMR integrals. *1.33 protons due to only one third of the NH + triplet being integrated.

It is emphasized that all values reported here are approximate and that the method used here must be subject to further optimization.

Figure 27. The 1H NMR spectrum of a MM7 amide mixer sample diluted 1:20 with H2SO4

When increasing the dilution factor further to 1:20, it can be remarked that the signal-to-noise ratio has now become unacceptable as the weaker signals are now obscured or lost altogether. This could in theory be remedied by increasing the number of scans and increasing run-times. However this spectrum shows no increased resolution with respect to the 1:5 dilution sample and therefore it appears to be unnecessary to operate at such high dilutions.

  • MM7 Reactor Sample.

A MM7 reactor sample was analyzed at the 1:5 “optimum” dilution using a “power scan”

Figure 28. The 1H NMR spectrum of a MM7 amide reactor sample diluted 1:5 with H2SO4. *Obtained by taking the least interfered with signal from the triplet at 7.15 ppm and multiplying by 3.**All ammonium assumed to be arising from AADS at this time.

A small singlet with an integral of 0.07 is observed a 1.75 ppm; this is most likely arising from the HIBAM methyl protons. The equivalent signal from SIBAM is barely visible at 1.95 ppm but is present with an integral of 0.04

A large singlet is once again produced at 2.11 ppm by the methyl protons of MAM and has an integral of 3.22.

All three peaks of the ammonium triplet can be observed at 4.67, 5.91 and 7.15 ppm. The peak at

7.15 ppm is thought to be least interfered with and has an integral of 0.07.

The  two methylene protons of  MAM once again produce two  singlets  at  6.20  and  6.52  ppm respectively. The signal at 6.20 ppm is assumed to be free of interference and has been assigned the integral of 1.00. The other singlet at 6.52 ppm has an integral of 1.07 ppm

One of the methylene peaks of MAA is clearly resolved at 6.86 ppm and has an integral of 0.03. The broad peak at 1.74 ppm is due to the amide protons of MAM.

As for the mixer sample, the following rough approximation of relative concentrations of components can be made.

Again, it is emphasized that the values reported here are approximate; further optimization will be required to develop a method for obtaining precise and repeatable quantitative results.

4.  Conclusions Summary

A range of purified components of the amide stage have been profiled via 1H NMR in DMSO-d6 and H2SO4, including:

  • Methacrylamide (MAM)
  • Methacrylic acid (MAA)
  • α-Sulphatoisobutyramide (SIBAM)
  • α-Hydroxyisobutyramide (HIBAM)
  • Ammonium acetonedisulphonic acid (AADS)

Binary mixtures of similar compounds have also been profiled:

  • SIBAM + HIBAM; 1:1 mixtures have been examined in both DMSO-d6 and H2SO4.
  • Interconversion between the two occurs within the NMR sample at room temperature, the degree of which is dependent on the water content. It is safe to assume the same is true of amide samples from the plants.
  • High degree of similarity between these compounds means the two can only be resolved from one another with difficulty. It remains to be seen if they can be separated mathematically to give a good indication of “water balance”.

MAM +MAA; varying concentrations have been investigated in  H2SO4

  • 1:1 mixture shows clear resolution between the two compounds
  • 99:1 mixture shows that resolution can still be achieved but would benefit from further optimization to give a reliable value for MAA.
  • A good quantitative approximation can be drawn from these mixtures.

Amide samples from MM7 have been studied from both mixer and reactor.

  • The ideal dilution of these samples has been identified as 1:5 in H2SO4.
  • At this dilution, all aforementioned components can be observed in these samples, however further development of the method will be needed to quantify some of the more minor components of the mixture, such as HIBAM, SIBAM and MAA.

5.  Recommendations.

·    Parameters of the 1H NMR experiment now need to be developed; until now the majority of

experiments have been conducted using the instrument’s default experiment settings. It is

possible that scan times can be significantly reduced without detrimentally affecting the quality of spectra. Both acquisition and repetition times will be investigated in order to achieve this.

·    A suitable internal reference may be required in order to determine absolute concentrations (as opposed to relative ones) in spectra. Many conventional 1H NMR reference compounds rely on the Si-Me group to provide a signal with a neutral chemical shift, i.e. 0 ppm. However this group is decomposed by H2SO4 and so an alternative should be found.

·    Further work needs to be done to investigate separating various signals mathematically to give more reliable integrals and aid with quantification.

·    If possible, values for CI, water balance and DI should be derived from 1H NMR, however more suitable metrics than these values may arise as a result of further work.

·    Pending the definition of an “optimum” experiment. A regime of sample analysis alongside the current HPLC method should be undertaken and a rolling comparison made to establish the suitability and reliability of 1H NMR for quantification.

The strategic importance of placing a Process NMR system at the pipeline point of entry is to verify that the pipeline tender is fully intact and meets delivery specifications.  Placement of the on-line analyzer at the point of entry verifies that the supplier’s product tender is on specification. Thus, removing liability of the supplier should such product tender experience changes/contamination during pipeline transmission to the end user.  Placement at the point of entry also provides the supplier with an early warning should the product tender properties not meet the desired qualities due to issues such as:

Stratification of product while in delivery storage tanks prior to shipment.

Detrimental co-mingling with tank heels from previous tender.

Asphaltene precipitation (plugging).

Water Separation which typically causes corrosives.With this early warning, the supplier can take early corrective actions (i.e. diverting tender to upstream holding tankage) such that improper delivery to the end user is avoided.  Once the improper material is segregated, corrective measures can be applied (i.e. blending to specification, re-processing, etc.).

 

The properties measured rapidly and simultaneously, such as those listed below, fall into three types of information:

1.      Quality/Value Measures:

a.       Distillation Cut Point: IBP; Cumulative Yields at 150°c, 220°c, 350°c, 520°c

b.      Density at 60°c

c.       Simulated Distillation: T10, T30, T50, T70, T90.

d.      % Sulfur

2.      Performance Measures:

a.       TAN (Total Acidity Number)

b.      Asphaltenes

c.       Water

3.      Integrity Measures:

a. TAN (Total Acidity Number)

b.      Asphaltenes

c.       Water

Quality/Value Measures are typically set by the end user.  The distinctiveness of crude oil is defined by the Distillation Cut Point. Any undesirable mixing between different types of crudes will appear immediately through these measurements. The fluidity of the crude oil is mainly defined by its density as the pipelines have restrictions on the level of crude density. Sulfur concentration is one of the major parameters of the crude product and indicates the propriety of the stream.

Performance Measures are used to ensure the proper operation of pipelines and process units. TAN is a measurement that is critical in defining the corrosive capacity of the crude oil for protecting the integrity of the pipeline.  Asphaltenes are critical in defining and avoiding pipeline plugging and fouling.   Integrity Measures are used to ensure storage tank and pipeline tender integrity, as TAN, Asphaltenes and Water are immediate indicators of improper co-mingling (crude incompatibility and/or tank heel mixing) and tank stratification.

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