PVT Properties of Black Crude Oil

El-hoshoudy, A.N.; Desouky, S.M.

doi:10.5772/intechopen.82278

Cited by 6 publications

(8 citation statements)

References 69 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The oil phase can be described by several correlations depending on the type of crude. For instance, the correlation of Al-Marhoun is adopted for Middle East crude oils, highlighting a trend for locally defined formulations . Surfactants locate at the O/W interface, a process described as adsorption.…”

Section: Physical Properties Of Emulsionsmentioning

confidence: 99%

See 1 more Smart Citation

Properties of Crude Oil-in-Water and Water-in-Crude Oil Emulsions: A Critical Review

Sousa

Matos

Pereira

2021

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

Water and crude oil emulsions can be produced during oilfield operations. Since most oilfields are in the secondary or tertiary recovery stages, the amount of produced water is not negligible. Furthermore, enhanced oil recovery makes use of surfactants injection (chemical substances that lower the surface tension of the liquid) and polymer flooding (polymers are large molecules, composed of repeating blocks bounded together, which are injected to decrease the water–oil mobility ratio), leading to increased emulsion problems. Knowledge of fluid petrochemical properties and behavior is fundamental for designing the production system, transport infrastructures, and refinery layout. Depending on the fluid composition, the flow rate, and the PVT conditions, different physical behaviors and flow patterns will occur. Even though significant effort has been carried out to take a broader view of liquid–liquid models, there is a wide range of correlations to consider with different crude oil compositions and diverse field conditions. In this work, a critical review was carried out to assess the main principles that affect an emulsion, how the flow patterns are influenced by the water fraction, which equations can be used to estimate the main physical properties, and last what are the methods or techniques for identifying or characterizing an emulsion. As a result, a strong background in this matter is offered, and future research directions are synthesized.

show abstract

Section: Physical Properties Of Emulsionsmentioning

confidence: 99%

“…For instance, the correlation of Al-Marhoun 157 is adopted for Middle East crude oils, highlighting a trend for locally defined formulations. 158 Surfactants locate at the O/W interface, a process described as adsorption. To treat surfactant adsorption, the second law of thermodynamics can be applied.…”

Section: Physical Properties Of Emulsionsmentioning

confidence: 99%

Properties of Crude Oil-in-Water and Water-in-Crude Oil Emulsions: A Critical Review

Sousa

Matos

Pereira

2021

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

show abstract

“…This can be attributed to crude oil containing predominantly acidic polar fractions (evident from TAN, and SARA analysis given in Table ). It is well known that polar compounds have profound effects on rock wettability in a carbonate formation, particularly the acidic components, which help the oil blobs adhere to the positively charged calcite surface, rendering them oil-wet. , Dodecane being void of any polarity is expected to have a lesser tendency to attach to the calcite surface. The 50:50 crude/dodecane results were in between the two extremes.…”

Section: Resultsmentioning

confidence: 99%

Standardization of Particle Size for Floating Particle Wettability Measurement for Carbonate Rocks

et al. 2023

View full text Add to dashboard Cite

Misrepresentation of the wettability of a reservoir can lead to potentially low ultimate hydrocarbon recovery resulting in substantial economic losses. At the same time, it is impossible to determine the wettability of a reservoir across its length and breadth on a continuous basis using standard procedures. This work presents the development and standardization of a quick, easy, and low-cost wettability measurement method using the adherence tendency of rock particles in the oil or aqueous phase. The most important aspect of this study was establishing the optimum particle size for sustained floatation and balancing the buoyancy and gravity effect. The results show that the particles sink with a larger than optimum particle size because of the gravity effect. Similarly, the particles would float if they are smaller than optimum due to buoyancy and viscosity advantages. A new scale is designed, and the midpoint analysis shows that a 63−90 μm particle size is the ideal size range for the carbonate reservoir's wettability measurements, as the midpoint of the size distribution coincides with the standard Amott−Harvey (A−H) index. However, this size range is found to be wider for oil-wet particles. The floating particle method has several advantages over the established methods once standardized against a reliable process. Not only is the process fast but it can be performed with basic laboratory tools and does not require a high skill set. Most importantly, reliable wettability information can be obtained from drill cuttings and core fragments, enabling the determination of reservoir wettability on a continuum basis and not as a point basis, thus providing a more reliable average value, particularly for heterogeneous and unconsolidated reservoirs.

show abstract

“…Inaccuracies in reservoir fluid characterization will result in errors in field development planning, uncertainty in the estimated prediction of oil and gas recovery, and thus in the overall asset value. It has been reported that one of the foremost methods of characterizing and predicting the behavior of reservoir fluids is the Pressure-Volume-Temperature (PVT) analysis [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

“…Reservoir fluid Pressure-Volume-Temperature (PVT) empirical methods are quite expensive [3][4][5][6]; hence correlations have been developed to obtain these PVT properties. These correlations are highly region-dependent and rarely work well in different regions since they were developed with data from particular regions.…”

Section: Introductionmentioning

confidence: 99%

Correlation for predicting bubble point pressure for 22.3≤°API≥45 crude oils: A white-box machine learning approach

Ikpabi¹,

Akinsete²

2022

Int. J. Front. Eng. Technol. Res.

View full text Add to dashboard Cite

Bubble point pressure (BPP) is a key parameter for oil and gas reservoir identification, characterization, and management. An accurate correlation of this property with the evolving digital technology of machine learning, in the absence of experimental PVT analysis, serves as guidance in the development and recovery of reservoir fluids. In this study, a predictive BPP correlation was derived by intrinsically linearizing a nonlinear multiple regression, with the best coefficients (global minimum) extracted using White-box (Linear Regression, Ridge Regression, and Lasso Regression) Machine Learning models. The new correlation was developed, validated, and tested using 314 measured PVT data points from the Niger Delta Region. The data were subdivided into four classes: extra-light crude for API > 45, light crude for 31.1 < API ≤ 45, medium crude for 22.3 < API ≤ 31.1, and heavy crude for API ≤ 22.3. Statistical evaluation metrics such as root mean squared error, average absolute relative error, and average relative error were employed to compare the performance of the new correlation with the existing empirical ones. Results showed that the new BPP correlation developed by White-box Linear Regression outperformed the other White box (Ridge Regression and Lasso Regression) and other existing BPP empirical models. Taking advantage of emerging data-driven and machine learning as BPP predictive model is effective and efficient in reservoir fluids analysis.

show abstract

PVT Properties of Black Crude Oil

Cited by 6 publications

References 69 publications

Properties of Crude Oil-in-Water and Water-in-Crude Oil Emulsions: A Critical Review

Properties of Crude Oil-in-Water and Water-in-Crude Oil Emulsions: A Critical Review

Standardization of Particle Size for Floating Particle Wettability Measurement for Carbonate Rocks

Correlation for predicting bubble point pressure for 22.3≤°API≥45 crude oils: A white-box machine learning approach

Contact Info

Product

Resources

About