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Innovative modeling of heavy crudes provides competitive advantages

08.01.2014  |  Beck, R.,  Aspen Technology Inc., Burlington, MassachusettsAjikutira, D.,  Aspen Technology Inc., Burlington, MassachusettsYe, V. ,  Aspen Technology Inc., Burlington, MassachusettsRumyantseva, I.,  Aspen Technology, Burlington, Massachusetts

The increase in heavy crude production, together with the diversity of heavy crude characteristics and sources, leads to technical challenges in accurately predicting production and refining process performance.

Keywords: [software] [modeling] [crude] [projection] [process control] [simulation] [optimize] [reactor] [sulfur]

The increase in heavy crude production, together with the diversity of heavy crude characteristics and sources, leads to technical challenges in accurately predicting production and refining process performance. This has placed a heightened importance on understanding the way in which these crudes will perform in all phases of the oil production cycle. At the same time that natural gas prices in North America place that resource at an advantage, those same low prices, paradoxically, keep the cost of producing heavy crudes competitive (with low prices for steam production and for use of gas as an agent in extraction and transport). The stakes are high for engineers and planners who are under pressure to make engineering and operational decisions that will lead to a competitive advantage with the right decisions as opposed to lowered profitability and operational reliability when the analysis is not timely or is wrong.

With that backdrop, researchers and software providers have redoubled their focus on improving our understanding of the behavior of heavy oils throughout the extraction, transport, and processing stages, including the detailed behavior of heavy crudes in the most commonly applied refinery reactor units. There is no one silver bullet: A number of inter-related aspects need to be accurately characterized and modeled to achieve a high-fidelity and accurate representation of how the heavy crudes will perform.

Some important new software innovations are being adopted by leading oil producers and refiners. One of the leaders in implementing these innovations is Sinopec.1 The company reports an economic payback of $119 million per year through modeling and optimizing 300 process units in the Sinopec system.


Heavy crudes are associated with increasingly complex production and processing challenges. This goes far beyond simply understanding the evolving crude viscosity properties. The increased presence of contaminants and need to crack the heavy end also leads to more sophisticated and energy-intensive refining processes. It is important to understand the detailed behavior of crude units such as delayed cokers, visbreakers, fluid catalytic crackers (FCCs) and hydrocrackers under varying crude conditions.

Strategies for extraction and transport involve introducing steam for extraction, water and water-chemical mixtures to lubricate flow within pipelines, natural gas and blending heavy and light crudes for transport. Ongoing research into the hydraulics of these multi-phase and multi-component hydrocarbons is the subject of groups such as the University of Tulsa Consortium, that bring together researchers, industry and software developers; this provides a pipeline to get the latest research findings into process modeling software. For instance, flow assurance and corrosion control are increasingly important in complex crudes, with the reliability of pipeline flow critical to economics.

In addition to crudes becoming heavier, they are becoming sourer. It is estimated that as much as 80% of the world’s crude reserves can be classified as medium/heavy and sour.2 Refineries capable of processing heavy sour crudes as efficiently as possible will have an advantage in the current market and in the future. Innovations in process simulation software now allow engineers to advise how to tune refineries to be able to process challenging crudes, handle changing crude blends, remove sulfur in a cost-effective manner, and operate in the most energy-efficient way possible.


The most sophisticated models in the world are still completely dependent on the accuracy of the characterization of the crudes that will be processed. This all begins with the crude assay, and how that assay data (whether skeletal or complete) is handled in the model to present characterized results that are as accurate as possible with respect to the actual crude properties. One of the biggest advances in process modeling software in the past two years is the introduction of advanced assay management based on molecular characterization and representation of the crude assay. Also, the availability of extremely comprehensive and updated libraries of commercially available crude assays with the process simulators adds to that capability. Together these two advances improve the ability of process modelers to accurately predict separation, hydraulic flow, and refining processes by easily using simulation software. Further, the availability of identical assay systems within both the explicit engineering simulation models and the LP-based planning models of the same refining process increases the accuracy of refinery planning models (Fig. 1).

  Fig. 1. Crudes and assay management libraries
  within the process simulator provide an innovative
  work flow that increases both accuracy and
  speed of analysis.


With the variability and complexity of the heavy hydrocarbon sources, using the same model to optimize the entire system from wellhead to sales point increases the accuracy of predictions. These provide users much value for a number of reasons. First, faster and better decisions can be made throughout the value chain, including buy/sell decisions, operating decisions, regulatory compliance, minimizing safety risks, and optimizing energy use throughout the system. Process simulation software capable of characterizing hydrocarbons flexibly and rigorously is essential to understanding operating and debottlenecking tradeoffs in existing facilities for optimized process energy consumption.


Accurate process modeling and flow behavior predictions are essential for flow assurance and to support the changing crude compositions, ensure product quality, and lower process costs. The ability to predict flow problems is essential in preventing them, and the ability to predict hydrocarbon behavior is essential in ensuring that the desired product quality standards are met. In addition, the ability to look at the entire process will help optimize the process’ energy consumption.

One of the challenges is to simulate the behavior of multiphase flow, where oil, water, gases, and sand are present in the pipelines at the same time. Heavy oils are also very strongly temperature dependent, and they can have very high viscosities at low temperatures.3 In some situations, heavy crudes are mixed with other compounds (light crudes, water or air) to ensure their transport through the pipelines, which makes predicting their flow behavior even more challenging.3, 4

Another flow assurance issue is that some crude oils contain a large amount of wax in solution, which is usually removed by lowering the temperatures to get wax to solidify and settle.3 Lower temperatures also lead to hydrate formation. Being able to predict the behavior of the multiphase flow is essential to ensure uninterrupted flow through the pipelines.

Recent innovations in process modeling software have incorporated rigorous multi-phase and dynamic hydraulic modeling within the process simulator. Additionally, specific flow assurance models have been made simpler and more accessible to the general process modeler within process simulators to enable accurate modeling of the behavior of multiphase flow. As Fig. 2 indicates, accurate modeling of multiphase flow behavior in various temperatures, pressures, and flowrates is crucial in predicting common flow assurance obstacles such as corrosion, erosion, wax deposition and hydrate formation to prevent their occurrences.5

  Fig. 2. Flow-assurance models within
  the process simulator.


In the past, detailed reactor models, such as FCC units, hydrocrackers, reformers and so forth, were handled as stand-alone analytical problems, and involved extensive customization for each individual unit to fit these fragile models to current operating data. An important innovation has been to integrate rigorous and robust refinery reactor unit models into broader engineering simulation models, empowering the engineer to model the individual reactors in detail and then to simulate the refinery trains more completely, to analyze crude blend alternatives, to optimize energy use, to understand their interaction with heat exchanger subsystems, and to improve refinery efficiency and yields.

The most advanced of these rigorous models incorporate molecular characterization of crude properties, equation-oriented modeling of the behavior of the reactor units, application of thermal cracking kinetics research, and modeling of molecular lumps within the reactors. This, combined with improved and easier-to-use tools to fit plant data to models, has achieved significantly increased precision of these reactor models, all within the broader process simulator.

Companies such as Sinopec, Taiyo Oil and BP are getting excellent results with these advanced models. Finally, of practical importance in the refinery operations, tools to use these robust models for updating vectors for planning LP models have enabled refinery planners to more closely match refinery plans with actual performance.6, 7, 8


Refining is an energy-intensive process, and it is crucial to configure heat exchanger networks in a way that will minimize energy costs. New advances in process modeling software allow for the optimization of heat exchanger network design without having to be an expert in heat exchangers. With a click of a button, a process simulator will suggest options for optimal heat exchanger network design for maximum energy recovery by making suggestions on adding heat exchangers, increasing heat exchanger surface area or moving existing heat exchangers around. Energy optimization with a process simulator can be further enhanced with incorporating accurate and detailed heat exchanger models into the overall process design. Another benefit of having access to software capable of rigorous heat exchanger design is being able to evaluate the vibration and erosion risks. S-Oil, a large Korean refiner, reported in 2013 that it was able to save 102 MW of energy and $39 million in one refinery through this approach.9

Another valuable benefit of using process simulation software when dealing with heavy crudes is being able to calculate pressure drops, as there are large pressure drops associated with heavy crudes. Software with rigorous heat exchanger modeling capabilities is capable of calculating pressure drops, which will aid in operations as well as the design of pumps and other related equipment.

Saving energy costs in refining is ensured by the optimal performance of heat exchanger units. Heat exchanger fouling over time is contributing to the increase in energy consumption by the process, and processing heavy crudes leads to a higher rate of fowling. Here, another important innovation has been the introduction of rigorous heat exchanger design models completely within the process simulation environment, capable of evaluating operating heat exchangers, to understand when exchanger cleaning is cost-effective, and additionally to evaluate the energy and capital tradeoffs of modifying, replacing or altering heat exchangers (Fig. 3).

  Fig. 3. The introduction of rigorous heat
  exchanger models within the process
  simulation environment.


Sulfur is present in all crude oil samples, ranging from insignificant amounts to 5–6%. When it comes to processing sourer crudes, having a reliable process simulator capable of modeling the entire process is essential in optimizing plant operations. Innovations in simulation software make acid-gas cleaning modeling more reliable than ever. Historically, process simulation software used to model acid-gas cleaning was using equilibrium-based calculations; however, the software that is using a rate-based approach results in more accurate calculations, comparable to the real-life behavior of the plant. This eliminates ability to overcompensate with more amines, saving operating costs. This is especially important with sour crudes processing, which requires more amines to sweeten in the first place.

Another important newly innovated capability to look for in process simulators, when it comes to complex and contaminated sour gas processing, is the ability to perform rigorous column design, which will allow facilities to contend with changing feed compositions a lot easier. A process simulator capable of performing rigorous process calculations for either tray columns or increasingly widely applied packed columns is essential in ensuring preparedness for changes.

Transferring data between different simulators is a painful and time-consuming process, and it may jeopardize the accuracy of the results. Having a simulator capable of modeling the entire process is ideal to accomplish the ultimate project speed and design accuracy and optimization.


Heavy sour crudes’ low prices make them an attractive market opportunity, but their processing is complex and requires a lot of resources in equipment investment and utilities. Long-term economics of the heavy sour crude processing are important to consider so an informed decision can be made about any proposed capital improvements. Process models that can be easily passed onto cost estimators are ideal in this case to speed up the preliminary cost estimation to see what market opportunity if worth pursuing. Another area of recent innovation has been the introduction of rigorous costing models within the conceptual design process, closely integrated within the process model. Pemex has reported on over 30 refinery projects within the past five years in which this approach has achieved extremely accurate capital budgeting predictions, enabling informed decision-making.10


The technical advances and innovations covered above are enabling leading downstream players today to improve their accuracy in refinery planning and performance prediction, leading to more profitable operations. Rapid increases in the utilization rates of the process modeling tools have been observed as a result.

A number of areas continue to be studied with the view of introducing software innovations for optimizing refining and chemical processes. Some current work areas include closer integration of dynamic simulation within the process models and more detailed modeling of column performance. Columns tend to be drivers of heavy energy consumption within the process as well as key determinants of process yields.

A combination of such innovations and collaborative tools packaged in an easy-to-use software solution will further empower process engineers to continually optimize operations, capital and operating costs. HP


1 Li, D., “Accelerate the Process of Smart Plant and Promote Ecological Civilization Construction,” Chemical Industry and Engineering Society of China (CIESC) Journal, February 2014.
2 International Council on Clean Transportation “Production of Ultra Low Sulfur Gasoline and Diesel Fuel,” October 2011.
3 Lines, L. R., D. R. Schmitt and M. L. Batzle, “Heavy Oils: Reservoir Charaterization and Production Monitoring,” October 10, 2010.
4 Meyer, R. F., and E. D. Attanasi, “Heavy oil and natural bitumen-strategic petroleum resources,” 2003.
5 Herrmann, L., “An Integrated Approach to Modeling Pipeline Hydraulics in a Gathering and Production System,” Aspen Technology White Paper Series, 2013.
6 Pashikanti, K. and Y. A. Liu, “Modeling Integrated Reactor Models and Fractionation Systems,” AspenTech Global Conference: Optimize 2011, Washington, DC, May 2011.
7 Takeda, K., “Refinery Margin Improvement,” AspenTech Global Conference: Optimize 2011, Washington, DC, May 2011.
8 Briggs, B. and K. Lau, “Improve Refinery Margins with Hydroprocessing Model Applications,” Public webinar viewable online, delivered January 2012.
9 Kim, J. J., “Energy Efficiency Gains and Improved Solomon Energy Ratings with Aspen Energy Analyzer,” AspenTech Global Conference: Optimize 2013, June 2013.
10 Monterrubio, O., “A Lifecycle Approach to Downstream Capital Estimating and Risk Management,” Aspen Global Conference: Optimize 2013, June 2013.

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