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To predict asphaltene precipitation problem, Hansen solubility parameter (HSP) analyses were applied to three Japanese oil fields: Minami-Kuwayama, Yabase, and Minami-Aga. The analyzed samples were stock tank oil（STO） and heptane-insoluble asphaltene (Asp) of each oil. Comparing the relative distances between the HSPs of STO and Asp (Ra) to the radius of Hansen solubility sphere of STO (R0) in each oil field, the smaller Ra/R0（ RED: Relative Energy Difference） means the higher affinity of Asp with STO. As a result, the REDs of Minami-Kuwayama, Yabase, and Minami-Aga were 0.90, 0.45, and 0.65, respectively. The result indicated that Minami-Kuwayama oil should have the highest probability in asphaltene precipitation problem, corresponds to the fact that only this oil field has encountered asphaltene problems from the beginning of field development stage. It was found that HSP analyses were very helpful for the prediction of asphaltene problem. [ABSTRACT FROM AUTHOR]

Engineering science largely relies on a fundamental understanding on the structure-property relationships at various spatial and time scales. Digital oil is a molecular model of crude oil that is represented by multiple representative molecules created based on analytical data. This concept was proposed by our group in 2014 inspired by the concepts of digital field and digital rock, which emerged, historically, in the oil industry as critical technical revolutions. For five years, my colleagues and I have been working on digital oil and constructed two types of light crude oil as well as two types of heavy crude oil models with one being oil sand bitumen. So far, the applications include: (1) predicting asphaltene precipitation, (2) better solutions to asphaltene problems, and (3) heavy oil development. For heavy oil, we developed the method for constructing molecular models of saturates and aromatics. To predict phase behavior, we are working on a coarse-grained digital oil model. Digital oil builds a bridge between basic petroleum chemistry and engineering via molecular simulation techniques. We believe that this technique will be widely used for solving problems in both upstream and downstream in oil industry. [ABSTRACT FROM AUTHOR]

Asphaltene inhibitor (AI) is widely used to mitigate and/or prevent asphaltene deposition problems in reservoir, tubing and surface facilities. Many types of commercial AIs are available. To select suitable AI is a key to success of asphaltene mitigation. Currently, asphaltene dispersancy test (ADT) under ambient condition has been widely applied as a standard procedure of AI screening. However, more practical screening tests at the operating conditions are required. In this paper, a new workflow of selecting proper AI is introduced, consisting of lcompatibility testingz, ldynamic asphaltene inhibitor tests (DAIT), core flooding test, evaluation for squeeze lifetimes on the basis of core flooding test and so on. Those series of tests consider with actual operation condition. [ABSTRACT FROM AUTHOR]

The recent asphaltene onset pressure (AOP) detecting method has widely applied Laser-light Scattering Technique (LST) that shows a sudden drop of laser-light transparent due to disturbance by asphaltene precipitated solid particles during isothermal depressurizing test. However, the dependence on one measuring source for deciding AOP might be vulnerable for robust analysis. To improve the reliability of AOP detection, therefore a comprehensive method was established for the interpretation of AOP through simultaneous measuring experiments using synthetic live oil in a certain oil field. For this method, AOPs were simultaneously measured for identical subsamples with various technologies: laser-light scattering, high pressure microscopic observation of asphaltene particle count and size, and viscosity in the previous report by Miyagawa et al. (2016). This method can provide significant advantage such as decrease of experimental error, maximizing effective utilization of costly collected live oil samples, and back up for mistakes in other measuring methods. However, the previous oil samples to be tested were collected from the unique source of domestic oil field. Therefore, the established interpreting method was concerned to fluid-characteristicsdepended with low multiplicity of use. This paper demonstrated that the established method could work with versatility using different source oil sample. Furthermore, for more expanded application such as CO2 EOR investigation, the method was used for CO2-Oil mixtures and successfully interpreted AOP. Consequently, the interpretation approach was revealed to have universal adaptability. [ABSTRACT FROM AUTHOR]

Asphaltenes are the components of heavy fraction of oil. Once they deposit and clog the pore throats of reservoir rock, tubing pipes in production wells, and pipelines for oil transportation, it causes a serious problem for oil production. The objective of this paper is to show the applicability of "digital oil", which is a full molecular model of a crude oil, and Molecular Dynamics（MD）simulation to solve the asphaltene problems. For this purpose, a digital oil of "A-crude oil" produced from an oil field actually confronting asphaltene problems was generated. On the generation of the digital oil, some analytical experiments were conducted and Quantitative Molecular Representation（QMR）method was applied. As a result, the digital oil was successfully generated. Then, asphaltene-asphaltene association energies in 7 different solvents: n-heptane, toluene, benzene, xylene, isopropyl alcohol（IPA）, an azeotrope mixture of toluene and IPA, and a ternary azeotrope mixture of water, toluene, and IPA, were evaluated by calculating the Potential of Mean Force（PMF）using MD simulations and umbrella sampling technique. As expected, aromatics（toluene, benzene, and xylene）presents much lower association energies of asphaltene in absolute value than that in n-heptane. Among the 7 solvents, the ternary mixture provides the lowest association energy in absolute value. Therefore it can be the most effective solvent for the asphaltene of "A-crude oil". Furthermore, it can be supposed from the result of this study that the association energy becomes lower in absolute value when the aromatic asphaltene solvents tend to distribute near around the edge of asphaltene molecule much more. Thus the digital oil and MD simulation would be a useful tool to solve the asphaltene problems in oil production. [ABSTRACT FROM AUTHOR]

For accelerating asphaltene evaluation, a commercial packaged apparatus applying laser light scattering technique was installed in our laboratory in 2010. This apparatus can measure asphaltene onset pressure（AOP）, count/size of precipitated asphaltene particles and density/viscosity. During isothermal de-pressurizing test, AOP is detected by mainly using solid detection system（SDS）equipped in the apparatus. The SDS consists of laser light source, receiver, and glass cell. Measuring by SDS provides continuous profile for power of transmitted light(PTL)that can typically show a sudden drop when asphaltene particles start precipitating. However, our laboratory experience is sometimes faced to untypical PTL profiles. This paper focused on a case that did not detect SDSbasis AOP for a single phased fluid from domestic oil field. To find a way for solution, it was applied to estimate AOP by comprehensively interpreting whole measured data(i.e. particle count/size, density and viscosity)that were simultaneously taken at the SDS application. As a result, appropriate and practical AOP was estimated successfully. [ABSTRACT FROM AUTHOR]