Uncertainty Analysis of Visible and Near-Infrared Data of Hydrocarbons

Venkataramanan, Lalitha; Fujisawa, Go; Mullins, Oliver C.; Vasques, Ricardo; Valero, Henri‐Pierre

doi:10.1366/000370206777670594

Cited by 11 publications

(4 citation statements)

References 10 publications

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“…3 might be due to the few tenths of a percent expected for laboratory error. The Fluid Comparison Algorithm (FCA) [23] applied to the data shows that these color variations are statistically significant and cannot be explained by variations in the levels of OBM contamination. Because we have a statistically significant variation of asphaltene content vs. depth, and which is not produced by any appreciable GOR change, we then considered an asphaltene gravitational gradient.…”

Section: Asphaltene Gravitation Gradient By Dfamentioning

confidence: 99%

Asphaltene Gravitational Gradient in a Deepwater Reservoir as Determined by Downhole Fluid Analysis

Mullins¹,

Cribbs²,

Betancourt³

et al. 2007

Proceedings of International Symposium on Oilfield Chemistry

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fax 01-972-952-9435. AbstractThe fluids in large reservoirs can be in equilibrium -especially if conditions conducive to convective mixing prevail. A large vertical column of reservoir hydrocarbons offers a unique laboratory to investigate potential gravitational grading. Asphaltenes are known to exist in crude oils as a colloidal suspension, but which had not been well characterized in the laboratory until recently. In this paper, we review a gravitational gradient of asphaltenes in a reservoir and a simple theory is shown to apply. The corresponding downhole and laboratory analyses are consistent; asphaltenes exist in these crude oils in nanoaggregates. The corresponding asphaltene gradients provide a stringent and new method to test reservoir connectivity (as opposed to compartmentalization), which is key to the efficient economic development for many deepwater projects.

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Section: Asphaltene Gravitation Gradient By Dfamentioning

confidence: 99%

Asphaltene Gravitational Gradient in a Deepwater Reservoir as Determined by Downhole Fluid Analysis

Mullins¹,

Cribbs²,

Betancourt³

et al. 2007

Proceedings of International Symposium on Oilfield Chemistry

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“…The GOR computed from the downhole spectrum (580 scf/stb) is indeed higher than the one obtained with the lab spectrum (320 scf/stb). A fluid comparison algorithm 19 was used to analyze the two spectra and the probability of similarity between these two samples. This algorithm accounts for spectral and other error bars to determine a statistical likelihood of fluid differences.…”

Section: Resultsmentioning

confidence: 99%

“…This algorithm accounts for spectral and other error bars to determine a statistical likelihood of fluid differences. 19 Here, the fluids are computed to be 93% likely to be different. The conclusion is that this sample has been compromised.…”

Section: Resultsmentioning

confidence: 99%

Chain of Custody for Samples of Live Crude Oil Using Visible—Near-Infrared Spectroscopy

et al. 2006

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In order to design oil production facilities and strategies, it is necessary to acquire crude oil samples from subsurface formations in oil wells in so-called openhole prior to production. In some environments, such as deepwater production of oil, decisions of huge economic importance are based on such samples. To date, there has been little quality control to verify that the crude oils collected in the sample bottles and analyzed up to a year later in the laboratory have any relation to the actual crude oils in the subsurface reservoirs. These high-pressure samples can undergo myriad deleterious alterations. Here, we introduce the chain-of-custody concept to the oilfield. The visible-near-infrared spectrum of the crude oil is measured in situ in the wellbore at the point of sample acquisition. This spectrum is compared with the spectrum measured on putatively the same fluid in the laboratory at the start of laboratory sample analysis. First, quantitative assessment is made of whether the fluid in the (high-pressure) sample bottle remains representative of formation fluids. Second, any specific changes in the spectrum of the fluid can be related to possible process control failures. Here, the entire process of chain of custody is proven. The chain of custody process can rapidly become routine in the petroleum industry, thereby significantly improving the reliability of any process that depends on fluid property determination.

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“…A common approach is to record spectra in mixtures with known composition and properties and feed the data into a large data base. The spectrum from an unknown sample can then be compared using appropriate numerical algorithms, e.g., Venkataramanan's fluid comparison algorithm (FCA) [81] or a conventional cross-correlation method [82].…”

Section: Petrochemical Liquid Fuelsmentioning

confidence: 99%

Recent Advances in the Characterization of Gaseous and Liquid Fuels by Vibrational Spectroscopy

Kiefer

2015

Energies

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Most commercial gaseous and liquid fuels are mixtures of multiple chemical compounds. In recent years, these mixtures became even more complicated when the suppliers started to admix biofuels into the petrochemical basic fuels. As the properties of such mixtures can vary with composition, there is a need for reliable analytical technologies in order to ensure stable operation of devices such as internal combustion engines and gas turbines. Vibrational spectroscopic methods have proved their suitability for fuel characterization. Moreover, they have the potential to overcome existing limitations of established technologies, because they are fast and accurate, and they do not require sampling; hence they can be deployed as inline sensors. This article reviews the recent advances of vibrational spectroscopy in terms of infrared absorption (IR) and Raman spectroscopy in the context of fuel characterization. The focus of the paper lies on gaseous and liquid fuels, which are dominant in the transportation sector and in the distributed generation of power. On top of an introduction to the physical principles and review of the literature, the techniques are critically discussed and compared with each other.

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Uncertainty Analysis of Visible and Near-Infrared Data of Hydrocarbons

Cited by 11 publications

References 10 publications

Asphaltene Gravitational Gradient in a Deepwater Reservoir as Determined by Downhole Fluid Analysis

Asphaltene Gravitational Gradient in a Deepwater Reservoir as Determined by Downhole Fluid Analysis

Chain of Custody for Samples of Live Crude Oil Using Visible—Near-Infrared Spectroscopy

Recent Advances in the Characterization of Gaseous and Liquid Fuels by Vibrational Spectroscopy

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