Applied Novel Quality Check Method for PVT Data with High Impurities Using Various Samples from Malaysian Fields

2021 ◽  
Author(s):  
Luky Hendraningrat ◽  
Intan Khalida Salleh
Keyword(s):  
Molecular Weight ◽  
Equation Of State ◽  
Gas Phase ◽  
Oil And Gas ◽  
Comprehensive Evaluation ◽  
Gas Condensate ◽  
Fluid Composition ◽  
Essential Information ◽  
Pvt Data ◽  
Wide Range

Abstract PVT analysis of reservoir fluid samples provides essential information for determining hydrocarbon in place, depletion strategy, and hydrocarbon flowability. Hence, quality checking (QC) is necessary to ensure the best representative sample for further analysis. Recently, a novel tool based on Equation of State (EOS) was introduced to tackle the limitation of the Hoffmann method for surface samples with high impurities and heavier components. This paper presents comprehensively evaluating a novel EOS-based method using various PVT data from Malaysian fields. Numerous PVT separator samples from 30 fields with various reservoir fluids (Black Oil, Volatile, and Gas Condensate) were carried out and evaluated. The impurities contain a wide range of up to 60%. The 2-phase P-T (pressure and temperature) diagram of each oil and gas phase before recombination was calculated using PVT software based on Equation of State (EOS). The 2-phase P-T diagram was created and observed the intersection point as calculated equilibrium at separator conditions. Once it is observed and compared with written separator condition in the laboratory report and observed its deviation. Eventually, the result will be compared with the Hoffmann method. The Hoffmann method is well-known as a traditional QC method that was initially developed using gas condensate PVT data to identify possible errors in measured separator samples. If the sample has high impurities and/or heavier components, the Hoffmann method will only show a straight line to the lighter components and those impurities and heavier components will be an outlier that engineers will misinterpret that it has errors and cannot be used for further analysis such PVT characterization. The QC using EOS-based were conducted using actual fields data. It shows potential as novel QC tools but observed only less than 10% of data with complete information that can meet intersection points located precisely similar with reported in the laboratory. There is some investigation and evaluation of the EOS-based QC method. First, most of the molecular weight of the heavier fluid composition of gas and oil phase was not reported or used assumptions especially when its mole fraction is not zero. Second, properties of heavier components of the oil phase (molecular weight and specific gravity) were not measured and assumed similar as wellstream. Third, pressure and temperature data are inconsistent between the oil and gas phase at the separator condition. This study can provide improvement in laboratory measurement quality and help engineers to have a better understanding of PVT Report, essential data requirements, and assumptions used in the laboratory. Nevertheless, the Hoffmann method can be used as an inexpensive QC tool because it can be generated in a spreadsheet without a PVT software license. Both combination techniques can provide a comprehensive evaluation for separator samples with high impurities before identifying representative fluid for further analysis.

An Equation of State Compositional Model

1980 ◽  
Vol 20 (05) ◽  
pp. 363-376 ◽  
Author(s):  
Keith H. Coats
Keyword(s):  
Equation Of State ◽  
Critical Point ◽  
Oil And Gas ◽  
Numerical Models ◽  
Volatile Oil ◽  
Gas Condensate ◽  
Numerical Dispersion ◽  
Stable Convergence ◽  
Compositional Model ◽  
Miscible Flooding

Abstract This paper describes an implicit, three-dimensional formulation for simulating compositional-type reservoir problems. The model treats three-phase flow in Cartesian (x-y-z) or cylindrical (r-theta-z) geometries. Applicability ranges from depletion or cycling of volatile oil and gas condensate to miscible flooding operations involving either outright or multicontact-miscibility.The formulation uses an equation of state for phase equilibrium and property calculations. The equation of state provides consistency and smoothness as gas- and oil-phase compositions and properties converge near a critical point. This avoids computational problems near a critical point associated with use of different correlations for K values as opposed to phase densities. Computational testing with example multicontact-miscibility (MCM) problems indicates stable convergence of this formulation as phase properties converge at a critical point. Results for these MCM problems show significant numerical dispersion, primarily affecting the calculated velocity of the miscible-front advance. Our continuing effort is directed toward reduction of this numerical disperson and comparison of model results with laboratory experiments for both MCM and outright-miscibility cases.We feel that the implicit nature of the model enhances efficiency as well as reliability for most compositional-type problems. However, while we report detailed problem results and associated computing times, we lack similar reported times to compare the overall efficiency of an implicit compositional formulation with that of a semi-implicit formulation. Introduction Many papers have treated increasingly sophisticated or efficient methods for numerical modeling of black-oil reservoir performance. That type of reservoir allows an assumption that reservoir gas and oil have different but fixed compositions, with the solubility of gas in oil being dependent on pressure alone.A smaller number of papers have presented numerical models for simulating isothermal "compositional" reservoirs, where oil and gas equilibrium compositions vary considerably with spatial position and time. With some simplification, the reservoir problems requiring compositional treatment can be divided into two types. The first type is depletion and/or cycling of volatile oil and gas condensate reservoirs. The second type is miscible flooding with MCM generated in situ.A distinction between these types is that the first usually involves phase compositions removed from the critical point, while the second type generally requires calculation of phase compositions and properties converging at the critical point. A compositional model should be capable of treating the additional problem of outright miscibility where the original oil and injected fluid are miscible on first contact.A difficulty in modeling the MCM process is achievement of consistent, stable convergence of gas-and oil-phase compositions, densities, and viscosities as the critical point is approached. A number of studies have reported models that use different correlations for equilibrium K-values as opposed to phase densities. Use of an equation of state offers the advantage of a single, consistent source of calculated K-values, phase densities, and their densities near a critical point. SPEJ P. 363＾

Perdido Development: Unified Fluid Model for Integrated-Production-System Modeling

2015 ◽  
Vol 18 (03) ◽  
pp. 303-317 ◽  
Author(s):  
D.. Galvan ◽  
G.. McVinnie ◽  
B.. Dindoruk
Keyword(s):  
Production System ◽  
Oil And Gas ◽  
Fluid Model ◽  
Wide Spectrum ◽  
System Modeling ◽  
Operating Conditions ◽  
Fluid Composition ◽  
Integrated Production ◽  
Wide Range ◽  
Fluid Properties

Summary The Perdido development is one of the most-complex deepwater projects in the world. It is operated by Shell in partnership with Chevron and BP. It currently produces hydrocarbons from 12 subsea wells penetrating four separate reservoirs. The properties of produced fluid vary per reservoir as well as spatially. The producing wells display a relatively wide range of fluid gravities, between 17 and 41 °API, and producing gas/oil ratios (GORs), between 480 and 3,000 scf/bbl. The fluids produced from the subsea wells are blended in the subsea system and lifted to the topside facilities by means of five seabed caisson electrical submersible pumps. In the topside facility, gas and oil are separated, treated, and exported by means of dedicated subsea pipelines. The fluid compositions and properties across the various elements of the production system are used as input data to the respective simulation models, and the corresponding outcomes (e.g., fluid properties, compositions) vary upon the well/caisson lineup and daily operating conditions. Given the wide spectrum of fluids produced through the Perdido spar, a special equation-of-state (EOS) characterization of the fluids had to be developed. Because a common EOS model was used to characterize the fluids, we will call this the unified fluid model (UFM) throughout this study. This approach enables accurate and efficient prediction of the properties of blended fluids and is suitable for use in an integrated-production system model (IPSM) that connects reservoirs, wells, subsea-flowline networks, and topside-facilities models. Such a modeling scheme enables effective integration among relevant engineering disciplines and can represent production and fluid data from field history with high confidence. The IPSM uses a black-oil fluid description for the well and subsea-flowline network models. By use of the initial composition and producing GOR of each well, the fluid composition is estimated by means of a simple delumping scheme. The resulting composition is tracked through the subsea network to the topside-facilities model, where compositional flash calculations are performed. The IPSM can forecast production rates together with fluid properties and actual oil- and gas-volumetric rates across the whole production system. The model can be used to optimize production under constrained conditions, such as limited gas-compression capacity or plateau oil production.

scholarly journals New Concepts of Hydrogen Production and Storage in Arctic Region

Resources ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 3
Author(s):  
Mikhail Dvoynikov ◽  
George Buslaev ◽  
Andrey Kunshin ◽  
Dmitry Sidorov ◽  
Andrzej Kraslawski ◽  
...  
Keyword(s):  
Natural Gas ◽  
Carbon Footprint ◽  
Oil And Gas ◽  
Gas Condensate ◽  
Added Value ◽  
Hydrogen Energy ◽  
Low Carbon ◽  
Associated Petroleum Gas ◽  
Wide Range ◽  
Production Of Hydrogen

The development of markets for low-carbon energy sources requires reconsideration of issues related to extraction and use of oil and gas. Significant reserves of hydrocarbons are concentrated in Arctic territories, e.g., 30% of the world’s undiscovered natural gas reserves and 13% of oil. Associated petroleum gas, natural gas and gas condensate could be able to expand the scope of their applications. Natural gas is the main raw material for the production of hydrogen and ammonia, which are considered promising primary energy resources of the future, the oxidation of which does not release CO2. Complex components contained in associated petroleum gas and gas condensate are valuable chemical raw materials to be used in a wide range of applications. This article presents conceptual Gas-To-Chem solutions for the development of Arctic oil and gas condensate fields, taking into account the current trends to reduce the carbon footprint of products, the formation of commodity exchanges for gas chemistry products, as well as the course towards the creation of hydrogen energy. The concept is based on modern gas chemical technologies with an emphasis on the production of products with high added value and low carbon footprint.

A Novel Approach to Determine Reservoir Fluid Composition from Separator Test Data

2021 ◽  
Author(s):  
Daryl S. Sequeira ◽  
Okechukwu M. Egbukole ◽  
Ahmed M. Sahl
Keyword(s):  
Test Data ◽  
Material Balance ◽  
Fluid Composition ◽  
Pvt Data ◽  
Reservoir Fluid ◽  
System Pressure ◽  
Novel Approach ◽  
Wide Range ◽  
Black Oil

Abstract High quality composition and PVT data can directly improve a wide range of upstream and downstreamengineering calculations. The quality of PVT Black oil experiments depends on awide variety of factors that includes type of PVT system, pressure-temperature conditions, stability and composition. The objective of this study is to emphasize the need to use material balance calculations obtainedfrom separator test data to back-calculate the reservoir composition andvalidate it against the original reservoir fluid composition. The methodologies employed in this study involve the following steps;

Fluid Viscosity-Residual Entropy Correlation

2011 ◽  
Vol 9 (1) ◽  
Author(s):  
Lawrence T. Novak
Keyword(s):  
Molecular Weight ◽  
Equation Of State ◽  
Residual Entropy ◽  
Fluid Viscosity ◽  
Entropy Model ◽  
Absolute Deviation ◽  
Linear Polyethylene ◽  
Wide Range ◽  
S Model

Chemical reaction engineering, process engineering, and product engineering models are used for design and analysis. Often, transport coefficient models are needed in equipment and in-situ models to account for the importance of momentum, heat, and mass transfer. Previous work+ demonstrated a novel component-based reference equation of state approach for correlating self-diffusion coefficient and viscosity over the entire fluid region (liquid, gas, and critical fluid). In this paper, a segment-based approach is used to extend the previous work+ from a limited number of individual component correlations to a predictive fluid viscosity correlation for a class of components consisting of n-alkanes, up to 1300 molecular weight, covering a wide range of components, temperatures, and pressures. A scaled segment viscosity-segment residual entropy correlation (V-S model) was introduced and evaluated here. PC-SAFT segment parameters and residual entropy were used in a correlation model linking viscosity to the PC-SAFT equation of state. Experimental evaluation of this V-S model used 3122 data points for eighteen n-alkanes, ranging from methane up to 2390 molecular weight linear polyethylene. Temperatures ranged from 96 °K to 650 °K, and pressures ranged from 10-4 atmospheres to 4990 atmospheres. The conditions studied are relevant to oil and gas reservoir engineering and other in-situ processes. Based on this work, covering the entire fluid region, the V-S model was found to result in a group correlation squared (R2) of -0.998 and group average absolute deviation (AAD) of 3.9%. Individual viscosity segment correlation parameters (Bseg and Aseg) were fitted to molecular weight and used in the predictive mode. In the predictive mode, a group AAD of 6.7% was obtained for n-alkanes from methane up to 1300 molecular weight linear polyethylene, over the entire fluid region. The scaled segment viscosity-segment residual entropy model introduced here has potential for a much broader range of applications. In addition, this model would be easy to embed in existing in-house and commercial simulators to provide predictive properties and rate-based modeling capability. + Novak, http://www.bepress.com/ijcre/vol9/A63

Intrinsic Stacking Interactions of Natural and Artificial Nucleobases

2019 ◽  
Author(s):  
Drew P. Harding ◽  
Laura J. Kingsley ◽  
Glen Spraggon ◽  
Steven Wheeler
Keyword(s):  
Gas Phase ◽  
Electrostatic Interactions ◽  
Density Functional ◽  
Molecular Descriptors ◽  
Stacking Interactions ◽  
Interaction Energies ◽  
Functional Theory ◽  
Binding Partner ◽  
Heavy Atoms ◽  
Wide Range

The intrinsic (gas-phase) stacking energies of natural and artificial nucleobases were explored using density functional theory (DFT) and correlated ab initio methods. Ranking the stacking strength of natural nucleobase dimers revealed a preference in binding partner similar to that seen from experiments, namely G > C > A > T > U. Decomposition of these interaction energies using symmetry-adapted perturbation theory (SAPT) showed that these dispersion dominated interactions are modulated by electrostatics. Artificial nucleobases showed a similar stacking preference for natural nucleobases and were also modulated by electrostatic interactions. A robust predictive multivariate model was developed that quantitively predicts the maximum stacking interaction between natural and a wide range of artificial nucleobases using molecular descriptors based on computed electrostatic potentials (ESPs) and the number of heavy atoms. This model should find utility in designing artificial nucleobase analogs that exhibit stacking interactions comparable to those of natural nucleobases. Further analysis of the descriptors in this model unveil the origin of superior stacking abilities of certain nucleobases, including cytosine and guanine.

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