SPE Seminar : Open Source Software Potential

Open Source Reservoir Simulators

Last week I was asked to present as part of the first SPE Seminar at London South Bank University. This was part of our long engagement with the Petroleum Engineering Department at the university. The student chapter invited us to participate with our work and experience in utilizing open source simulators and associated workflows. The session was kick started by Joel Turnbull from Sasol, presenting his extensive experience on asset management.

The presentation I gave was titled “Open Source Reservoir Simulation Software Tools”. In the presentation I gave, it was important for us to highlight the benefits of working in research as well in commercially utilizing these tools. Of these benefits are the following:

  • Access to license 24/7 for research.
  • Not a black box, access to full code.
  • With access to full code more challenging projects can be executed and physics and numerical methods can be edited.
  • Evolving user interface Options such as ResInsight (also open source) and integrating with Octave.
  • Develop programming skills that could be a differentiator in their careers.

Figure 1 Generating Maps Using Octave and Visualizing in ResInsight

There was great enthusiasm and interest from the students regarding the potential associated with these software not only for their personal career development but also in particular for their BEng and MSc projects. Going forward, we are keen to engage with universities and students mentoring on projects.

Figure 2 Egg Model run in MRST

If you are interested in this presentation for your company or university please let me know at amuftaha@pres.energy . We will be happy to organize an onsite or remote presentation. For companies, we offer a presentation on how we use open source simulators and tools in a Field Development Planning workflow exploiting multiple probability models and cloud computing.

Author : Ahmed Muftah
SDM & EOR Specialist

Primera Reservoir

Uncertainty Analysis in the Oil & Gas Industry- Why we keep underplaying uncertainty? Variables & Probability Distributions

Uncertainty Analysis in the Oil & Gas Industry- Why we keep underplaying uncertainty? Variables & Probability Distributions

In the last article, we looked at the current industry perception towards uncertainty analysis where we exposed some of the common biases we may have and how they may affect our decision making. We also considered some examples during the life of a field of decisions O&G professionals will face and the tools they have in order to quantify these risks. First however let’s try and define what uncertainty analysis is.

Probabilistic approach to benchmarking three numerical simulators Using the Egg Model

Probabilistic approach to benchmarking three numerical simulators Using the Egg Model

A large number of the decisions taking by oil & gas companies rely on the evaluation of simulators to project resources and hence infrastructure, production, wells and operations. These simulators integrate rock physics and fluid dynamics to give a more realistic representation of the reservoir and its response during the field development. The inputs used for the simulators vary but mostly rely on data from geology, seismic as well as exploration and production in order for the models to be as accurate as possible.

Aspen HYSYS simulation and economic analysis of CO2 removal from flue gas by amine absorption for CCS and EOR

Aspen HYSYS simulation and economic analysis of CO2 removal from flue gas by amine absorption for CCS and EOR


This was an MSc project undertaken in order to study the feasibility of a post combustion carbon capture plant using amine absorption if a carbon tax £/tonne CO2 were introduced. Aspentech HYSYS software was used to model the carbon capture plant whereby carbon dioxide (CO2) is removed using a Monoethanolamine (MEA) solution by absorption from a flue gas exiting a combined cycle gas turbine (CCGT) plant. This study has incorporated two configurations to model the CO2 capture process, a base case configuration and a vapour recompression configuration. The base case model achieved a CO2 removal of 86% and heat consumption in the reboiler of 3.48 MJ/kg CO2 removed. Its total capital cost was £110.63 million and an net present value (NPV) of -£490.29 million over 20 years at a 7% discount rate. The vapour recompression model achieved a CO2 removal of 88% and heat consumption in the reboiler of 3.19 MJ/kg CO2 removed. Its total capital cost was £160.67 million and an NPV of -£551.94 million. An MEA concentration of 32-33% for the lean amine stream entering the absorber column was been found give the lowest heat consumption value in the reboiler. It has also been shown that the first stage is ideal for the rich amine to enter the desorber with the vapour stream entering directly underneath. A flash drum pressure of 110 kPa produced the lowest operating costs however, it was not known if there are more optimal pressures as the model failed to converge for higher pressures. The findings produced a minimum carbon tax of 31.01 and 34.04 £/tonne CO2 for the base case and the vapour recompression model respectively in order to achieve an NPV of 0. As sale of CO2 is in £/tonne, the price at which the CO2 is sold for can be subtracted directly from the minimum carbon tax value needed in order to obtain a new minimum that can achieve an NPV of zero.


Increasing concentrations of greenhouse gases such as CO2 into the atmosphere is one of the leading causes of global warming, therefore governments and institutions are actively looking for a way reduce emissions of CO2. A significant amount of CO2 emissions come from power plants used to generate electricity from the combustion of fossil fuels such as coal, natural gas and other CO2 emitting sources (Committee on climate change, 2015). However, with world energy demand increasing yearly and current constraints on non-greenhouse sources of energy such as cost, availability and storage along with the time needed to transition, it is likely that fossil fuels are still the main source of energy for many years to come (EIA, 2016). Removal of carbon dioxide using amine absorption from streams is not a new concept in industry however, it is generally applied to high pressure streams from oil field reservoirs. The reason for this is to increase heating value, lessen the load on the compressors and minimise potential corrosion of pipes. Post combustion removal from electricity generation facilities has not been done on a large scale due to the likely cost restrictions it presents (Caldecott et al., 2016). Storage of captured CO2 also presents major problems as it incurs the additional cost of transportation and pumping into geological formations. There is also the risk of the leakage of CO2 back into the atmosphere.

CO2 can be injected into an oil field for enhanced oil recovery (EOR) in order to recover more oil than would be feasible using traditional methods therefore, an ideal scenario would be to sell the captured CO2 to oil companies for EOR although that option is not always readily available. The most common capture technologies employ amine gas treating which involves the CO2 being absorbed into the amine solution in an absorber column. The amine is then regenerated from the resultant stream in a desorber column by the reboiler and stripper. The amine is recycled back into the absorber and the CO2 stream is condensed to remove water before it is ready to store. Diethanolamine (DEA), Monoethanolamine (MEA), Methyldiethanolamine (MDEA) are the most commonly used amines for gas treating.

A carbon capture pilot plant testing facility TCM exists in Mongstad, Norway (MIT, 2012). This pilot plant is being used to test two alternative post combustion CO2 removal techniques, one of which is using chilled ammonia and the other is using amines. It is a joint venture being undertaken by the Norwegian state, Statoil, Shell and Sasol. The project was undertaken in order to use the information gathered to build a full scale plant however, it was decided in September 2013 by the Norwegian Oil and Energy Ministry that it will drop plans to build a full scale plant. Regardless, the pilot plant has remained operational as a testing facility.

Aspentech  HYSYS simulation software has been used to model two plant configurations as shown in Figures 1 and 2 (Birkelund, 2013).

Figure 1: Base case configuration

Figure 2: Vapour recompression configuration

Base case

The amine fluid package in HYSYS was used which comes pre-prepared with the relevant reactions and is optimised for amine solvents in general.

The model consists of a flue gas fan, an absorber column, rich amine pump, rich/lean heat exchanger, desrober column, condenser, reboiler, lean pump, lean cooler, CO2 cooler and a separator. A direct contact cooler (DCC) is modelled by a flue gas cooler in order to simplify the simulation. HYSYS also enables the addition of a make-up object which can help simplify the addition of lost components to the stream before being recycled. Pressure drops across the various units have not been taken into account.  Hot flue gas from the power plant enters a transport fan before being cooled to 40˚C (Kallevik, 2010) in the DCC. The flue then enters the absorber column from the bottom and a lean amine stream enters from the top. The lean amine stream is a stream that consists of approximately 29 wt% MEA, 64.5 wt% water and 5.5 wt% CO2. The CO2 present in the stream is because not all of the CO2 is removed during the regeneration process.  Sweet gas exits the absorber at the top and is released into the atmosphere. Additional water is recycled through the absorber column to aid the process. A rich amine stream exits the bottom of the absorber and is pumped to 200kPa by the rich amine pump. The pressurised stream enters the lean/rich heat exchanger where the hot lean amine stream to be recycled heats the rich amine stream to 104-109.5˚C. The rich amine stream then enters the desorber column where regeneration of the amine takes place. The amine is heated to 120˚C in the reboiler (Øi, 2007) and the CO2 and some water leave the top of the desorber as vapour and the lean amine liquid stream exits at the bottom. The recovered CO2 stream is cooled before it enters a separator to split the CO2 from the water. The lean amine stream feed is then pumped into the lean/rich heat exchanger in order to reduce its temperature and provide heat for the rich amine stream. The lean amine stream temperature that exits the lean/rich heat exchanger is still too high therefore it undergoes further cooling. Any lost MEA or water is added back before being recycled back into the Absorber.

Vapour recompression

The vapour recompression model contains the same units as the base case model with the addition of a lean amine pump, a flash drum and a compressor. The purpose of this set up is to reduce the reboiler duty through the addition of a recycle vapour stream in the desorber (Karimi et al., 2016).
In the vapour recompression configuration, the lean amine stream exiting the desorber column is reduced to 101 kPa by the pressure reducing valve which has the effect of reducing the temperature to 102˚C. This stream enters the flash drum which then separates some of the water from the lean amine stream. The liquid stream (lean amine) exits at the bottom of the vessel where it is then pumped to 120 kPa. This stream then enters the lean/rich heat exchanger and is recycled back into the desorber using the same steps as the base case model. The vapour stream consisting of 95.5 mol% water vapour exits at the top of the flash drum and enters the compressor where it is compressed to 200 kPa (desorber column pressure). The pressure increase on the vapour stream has the effect of increasing the temperature to 190˚C before it enters the desorber to provide additional heat to the system.


In order to calculate the NPV the capital costs and operating costs need to found. The costs of the major equipment were calculated by applying scaling factors, currency conversion and price index equations to similar work in carried out by Vozniuk (2010). Once the costs were determined an estimate of the capital costs can be made using Lang factors. The Lang factor is a ratio of the total cost of installing the plant to the cost of the total purchase equipment cost (Sinnott, 2005).
The cost of the liquefaction plant has been included as an estimate from Øi et al. (2016). The capital costs are shown in Table 1. The operating costs are calculated for the two models by calculating the energy consumption per year (8000 hr.) and multiplying it to the utility cost estimates from a CCGT plant (Department for Business, Energy & Industrial Strategy, 2016) and are shown in Table 2. The net NPV is calculated for a period of 20 years at a 7% discount rate.

Table 1: Capital costs

Table 2: Operating costs

Sensitivity analysis

Case studies were run in HYSYS in order to see the effect of changing the parameters on NPV and heat consumption. The sensitivity analysis for NPV incorporated a 10 £/tonne CO2 carbon tax in order to fairly assess variations where operating cost is higher but the captured CO2 is also higher. NPV has also been taken as positive therefore, for the sensitivity analysis graphs a lower NPV represents a lower investment cost than a higher NPV.

Variation of MEA concentration

The concentration of MEA was varied from 30-36 wt% in order to see the effects on heat consumption in the reboiler [MJ/kg CO2] (Figure 3).

Figure 3: Heat consumption [MJ/kg CO2] as a function of MEA concentration

It can be seen in figure 3 that an MEA concentration of 32-33% for the lean amine stream entering the absorber column gives the lowest heat consumption value in the reboiler. However, the range of values for MEA wt% needs to be increased in order to accurately assess the findings.

Inlet stage variation

The inlet stage of the rich amine stream was varied while keeping the reboiler duty the same in order to find the heat consumption in the reboiler [MJ/kg CO2] and the reboiler temperature (Figure 4).

Figure 4: Heat consumption [MJ/kg CO2] and reboiler temperature (°C) as a function of inlet stage of rich amine stream into the desorber for vapour recompression model

It can be seen that having the rich amine stream enter the absorber in the first stage gave the lowest value for heat consumption. This is because it gave the highest reboiler temperature for the same duty. It was found that in order to provide the best heat for the rich amine stream the vapour recycle stream would need to enter in the stage directly under it.

Variation of flash drum pressure

A case study on the effects of changing the flash drum pressure in the vapour recompression model has been plotted in Figure 5.

Figure 5: Heat consumption [MJ/kg CO2] as a function of MEA concentration

It can be seen that as the flash drum pressure increases the heat consumption by the reboiler (MJ/kg CO2 removed) increases but the NPV decreases. This is because although there are higher operating costs from the reboiler when the flash drum pressure is increased the vapour outlet decreases therefore, the compressor operating costs decrease. The study could not converge beyond 110 kPa therefore it is unknown if the NPV would decrease more at a higher flash drum pressure and when the point is reached where the NPV stops decreasing. These findings are similar to those found by Birkelund (2013) who has analysed the effects of changing the flash drum pressure on Equivalent work of the whole process [kJ/kg] which is comparable to the NPV findings for this study as capital costs did not change with respect to the flash drum pressure. Birkelund (2013) has found that the equivalent work decreases until approximately 115 kPa where it then starts to increase.

NPV variations based on Carbon Tax and income of CO2

In order to estimate a carbon tax price (£/tonne CO2) that would results in a 0 or positive NPV, carbon tax was treated as income in the NPV calculations.

Figures 6 and 7 show the change in NPV if the CO2 captured was sold for EOR for the base case model and vapour recompression model respectively.

Figure 6: NPV as a function of carbon tax in the range of 0-35 £/tonne CO2 incorporating income obtained from the sale of CO2 for EOR at 0, 5, 10, and 15 £/tonne CO2 for the base case configuration

Figure 7: NPV as a function of carbon tax in the range of 0-35 £/tonne CO2 incorporating income obtained from the sale of CO2 for EOR at 0, 5, 10, and 15 £/tonne CO2 for the vapour recompression configuration

The figures show a linear relationship between carbon tax and sale price to NPV. Goal seek function was used in order to find the carbon tax needed for NPV to equal 0 for both the base case model and the vapour recompression model not taking in into account  income received from the sale of CO2. The resultant carbon tax needed was 31.01 and 34.04 £/tonne CO2 for the base case and the vapour recompression model respectively.

Calculations used to find NPV assumed no additional operating or capital costs incurred from the sale of CO2 based on the assumption of Kemp and Kasim (2012) that with slight modification most of the pipeline in the UK Central North Sea can be re-used as they are metallurgically suitable. It can be seen that in order to have a 0 NPV when including the sale of CO2 £/tonne, the price at which the CO2 is being sold can be subtracted from the minimum carbon tax needed of 31.01 and 34.04 £/tonne CO2 for base case and vapour recompression model respectively to find the new minimum price of carbon tax for 0 NPV. It is worth noting that Reid (2015) has that said offshore oil companies in the North Sea may be more likely to accept the CO2 for free as an exchange for providing free storage for the captured CO2.


The base case model and vapour recompression model achieved a CO2 removal of 86% and 88% and heat consumption in the reboiler of 3.48 and 3.19 MJ/kg CO2 removed respectively. The value achieved for the base case is close to that observed in literature for Øi (2007) and Karimi et al. (2016). However, the value obtained for the vapour recompression model is higher than that found in literature which was 2.7 MJ/kg CO2 removed for Birkelund (2013) and 2.58 MJ/kg CO2 removed for Karimi et al. (2016). It was seen during simulation that the CO2 present in the recycle stream has a great effect on the overall CO2 removal % therefore it is preferable to keep the concentration of CO2 in the recycle stream low.

The main advantage of the vapour recompression model is that although the additional units incur a higher capital cost, the reduction in heat consumption of the reboiler should lower the operating costs enough to make it a viable alternative, however, it was found that the operating costs saved in the reboiler was £1.26 million in comparison to the base case model but an additional cost of £2.2 million was needed for the operating costs of the compressor therefore, irrespective of the capital costs the base case model presents the lowest investment cost.

Rich amine stream entering the absorber in the first inlet stage was found to have the lowest heat consumption value with the vapour stream entering directly underneath in order to best provide heat to the system. An optimum MEA concentration of 32-33% for the lean amine stream entering the absorber column has been found although the differences on heat consumption were minimal for the ranges tested. A flash drum pressure of 110 kPa produced the lowest operating costs but due to the model failing to converge at higher pressures it cannot be deduced that 110 kPa is the optimal flash drum pressure in the vapour recompression model and further research is needed.

The minimum carbon tax £/tonne CO2 needed to achieve an NPV of zero was 31.01 and 34.04 £/tonne CO2 for the base case and vapour recompression model respectively. These findings show that the proposed carbon tax plans in Canada (The Canadian Press, 2016) for a minimum of 10 Canadian dollars (£6.09) per tonne of CO2 are too low to enable a high adoption of carbon capture and storage by amine absorption. As the CO2 sold for EOR is in £/tonne the selling price can be deducted directly from the minimum price of carbon tax needed to achieve an NPV of zero to obtain a new minimum with respect to the sale of CO2. A more precise costing technique would need to be used in order to verify these results as Lang factors used in the estimation present a ±50% degree of accuracy.


        Employ the use of a Modified Hysim Inside-Out algorithm with adaptive damping to improve convergence (Øi, 2007).
        Use a programme to find capital costs as there are many variables that need to be taken into consideration.
        Research alternate forms of carbon capture technologies.


The study has found that carbon tax needs to be in excess of 30 £/tonne of CO2 in order to motivate companies to set up a carbon capture process as it would be cheaper for the company to pay the tax then employ CCS for lower carbon tax rates. The studies have found optimisations to the process for inlet stage and MEA wt%. There were issues in the convergence of the simulation which should be addressed for future studies using the technique proposed in the recommendations. In general the results obtained matched the results found in literature and therefore, this study with respect to carbon tax and income from CO2 can be used in order to assess feasibility of similar carbon capture plants.

Author : Nihad Kassem
Reservoir Engineer
Primera Reservoir LTD


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Karimi, M., Hillestad, M. and Svendsen, H.F. (2016) ‘Capital costs and energy considerations of different alternative stripper configurations for post combustion CO capture’, Chemical Engineering Research and Design, 89(8), pp. 1229–1236. doi: 10.1016/j.cherd.2011.03.005.

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Øi, L.E., Eldrup, N., Adhikari, U., Bentsen, M.H., Badalge, J.L. and Yang, S. (2016) ‘Simulation and cost comparison of CO2 Liquefaction’, Energy Procedia, 86, pp. 500–510. doi: 10.1016/j.egypro.2016.01.051.

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Oil and Gas Decision Making - Why we keep underplaying uncertainty ?

As the oil industry has high challenges running day to day activities such as reservoir monitoring, management of the field, field development planning as well as estimating reserves and resources. Deterministic workflows reflect the capacity that we have as humans to process information, but the nature of our work should be stochastic to account for uncertainty. This article will be the first in a series of articles explaining the current industry environment towards uncertainty analysis and how as petroleum engineers we can efficiently make use of statistical learning techniques to help us in the movement from deterministic to probabilistic workflows