New Downhole Fluid Analyzer Tool for Improved Reservoir Characterization

Dong, Chaofang; O'Keefe, Michael William; Elshahawi, Hani; Hashem, Mohamed; Williams, Steven; Stensland, Dag; Hegeman, Peter S.; Vasques, Ricardo; Terabayashi, Toru; Mullins, Oliver C.; Donzier, Eric

doi:10.2523/108566-ms

Cited by 23 publications

(8 citation statements)

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“…It should be noticed that the fitted asphaltene average molar mass (680 to 711) g 3 mol -1 , molar volume (669 to 697) cm 3 3 mol -1 , and diameter (1.28 to 1.30) nm are consistent with the values from the Yen-Mullins model, 10 such as the molar mass of an asphaltene monomer being about 750 g 3 mol -1 . The obtained results show that the colored asphaltene-like components are molecularly dispersed in the oil columns in the Norway field.…”

Section: ' Results and Discussion: Field Case Studiessupporting

confidence: 80%

“…The third generation of DFA tools was introduced recently. 3 The new DFA tool integrates multiple sensors in a single platform and provides significantly more accurate and complete fluid properties than previous fluid analyzers. It From combination principle, hydrocarbon composition is derived in groups of methane, ethane, propane to pentane, and hexane and heavier hydrocarbons.…”

Section: ' Downhole Fluid Analysis and Eos Based Data Interpretationmentioning

confidence: 99%

“…Downhole fluid analysis (DFA) has been successfully used to delineate reservoir attributes such as vertical and lateral connectivity and properties of the produced fluids. − DFA not only measures bulk fluid properties such as the gas−oil ratio (GOR), density, and light-end compositions of CO 2 , CH 4 , C 2 H 6 , C 3 H 8 −C 5 H 12 fraction, and hexane and heavier (hexane +) fractions more accurately but also color (optical density, OD) that is linearly related to the heavy ends (asphaltenes and heavy resins) in real time at downhole conditions. In addition, the color measurement is one of the most robust measurements in DFA.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Downhole Asphaltene Gradients in Oil Reservoirs with a New Bimodal Asphaltene Distribution Function

et al. 2011

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Downhole fluid analysis (DFA) has been successfully used to describe reservoir connectivity and fluid properties. DFA not only measures bulk fluid properties such as the gas-oil ratio (GOR), density, and light-end compositions of CO 2 , CH 4 , C 2 H 6 , C 3 H 8 -C 5 H 12 fraction, and hexane and heavier (hexane þ) fractions but also color (optical density) that is related to the heavy ends (asphaltenes and resins) in real time at downhole conditions. Therefore, color gradient analysis in oil columns becomes essential to determine reservoir complexities. In this paper, a new bimodal Γ-distribution function (asphaltene molecules þ nanoaggregates and clusters) was proposed to characterize asphaltene components. A thermodynamic asphaltene-grading model was also developed to describe equilibrium distributions of heavy ends (heavy resins and asphaltenes) in oil columns using the multicomponent Flory-Huggins regular solution model coupled with a gravitational contribution. The variations of oil properties (such as molar volume, molar mass, solubility parameter, and density) with depth were calculated by the equation of state (EOS). The primary factors governing asphaltene distribution in reservoirs are the gravitational term, which is determined in part by the size of the asphaltene colloidal particle, and the solubility term, which is determined in large part by the GOR (composition). Consequently, it is critical to accurately measure both the fluid coloration and the GOR (composition) to understand the asphaltene gradient in oil columns. The results obtained in this work are in accordance with the Yen-Mullins model in asphaltene science. In particular, if asphaltenes are equilibrated in an oil reservoir, then a massive fluid flow through the reservoir had to have taken place, and permeable rocks are required, thereby implying connectivity, because asphaltenes necessarily enter the reservoir out of their ultimate equilibrium at the beginning of the reservoir charging. Therefore, a new powerful approach is established for conducting DFA color and GOR gradient analysis by coupling advanced asphaltene science with DFA technology (profiling of fluids) to address reservoir connectivity.

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Section: ' Results and Discussion: Field Case Studiessupporting

confidence: 80%

Section: ' Downhole Fluid Analysis and Eos Based Data Interpretationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysis of Downhole Asphaltene Gradients in Oil Reservoirs with a New Bimodal Asphaltene Distribution Function

et al. 2011

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“…DFA can be used for an early understanding of reservoir compartmentalization and compositional gradients for optimal field development (Hani et al, 2013), and it enables accurate measurement of asphaltene content variations through fluid coloration via OD (Hani et al, 2007;Dong et al, 2008). In addition, DFA measures fluid properties such as composition, density, GOR, OD and fluorescence intensity.…”

Section: Amg-dfa Integration Processmentioning

confidence: 99%

Integrated reservoir fluid characterization in thinly laminated formations – A case study from deepwater Sabah

Chouya¹,

Jong²,

Boay³

et al. 2018

BGSM

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Reservoir properties such as fluid compositions, formation pressures, and fluid contacts are critical in the early phase of the well life and represent the key inputs for comprehensive production and reservoir engineering studies in the development phase. Accurate measurements and evaluations of reservoir fluid properties tend to become more complex in challenging drilling environments, coupled with complicated reservoir facies such as the thinly laminated formations. To reduce the uncertainty in the estimations of hydrocarbon in place and fluid contacts in clastic reservoirs, it is paramount to integrate various measurements such as core data, log analysis, image logs, pressure data, and fluid sampling results for a holistic and meaningful evaluation approach. Several methods are available nowadays for reservoir fluid characterization but each method has its own limitations and advantages. However, technical advancement achieved in individual technology alone may not necessarily provide a complete solution for the formation fluid evaluation task. To reduce this uncertainty and to improve reservoir fluid evaluations, an integrated approach that combined various methods such as Advanced Mud Gas Logging (AMG), wireline Downhole Fluid Analysis (DFA) and PVT laboratory analysis is developed, based on a case study of an exploration well from deepwater Sabah. The integrated approach and workflow that combined these independent measurement methods proved to be the key to the success for formation fluid characterization. This paper is focused on how the integration of various methodologies can complement each other through the following strategies: assessment of reservoir fluid properties, starting from the early stages of open hole measurements, can be complemented by measurements obtained from AMG logging and wireline DFA and sampling. The AMG provides an early approach to reservoir fluid identification through its capability to generate a continuous fluid facies logged across the entire drilling interval. This study presents a successful case evaluation conducted for two drilling sections of the investigated exploration well. It demonstrates the strategies used for accurate fluid characterization assessments in a challenging deepwater environment, which is beneficial as a comparison for the subsurface assessment of other discoveries made in similar depositional setting.

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“…This reduction in pressure can cause changes in the composition of the hydrocarbon phases as heavy hydrocarbons precipitate from the gas phase into the liquid phase. Dong et al 23 developed a downhole NIR analyzer to predict the concentration of hydrocarbons in the gas phase using chemometric methods under in situ pressure up to 137.89 MPa and temperature up to 423.15 K. It should be mentioned that, in that study, propane, butanes, and pentanes were grouped together in order to improve the accuracy of gas analyzer, and these components cannot be measured separately in gas samples by the analyzer.…”

Section: Introductionmentioning

confidence: 99%

Fourier Transform Near-Infrared (FTNIR) Spectroscopy and Partial Least-Squares (PLS) Algorithm for Monitoring Compositional Changes in Hydrocarbon Gases under In Situ Pressure

Haghi

Tohidi

2017

Energy Fuels

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The ability of Fourier transform near-infrared (FTNIR) spectroscopy and chemometric method was investigated to determine the concentration of major hydrocarbon components of natural gases at pressures from 3.44 to 13.78 MPa and temperatures from 278.15 to 313.15 K. Various partial least-squares (PLS) models were developed to determine the concentration of methane, ethane, propane, i-butane, and n-butane simultaneously in gas phase at different pressures and temperatures, using the acquired FTNIR spectra. Several preprocessing techniques were tested prior to the construction of the calibration models. The first Savitzky−Golay derivative with smoothing over five points plus orthogonal signal correction (OSC) was found to be the best method for FTNIR data preprocessing. Good agreement was obtained between the predicted data by PLS models and the measured values with a standard error of prediction (SEP) of 0.184−0.217, 0.165−0.209, 0.136−0.181, 0.098−0.154, and 0.096−0.142 cmol/mol for methane, ethane, propane, i-butane, and n-butane, respectively, under different temperature and pressure conditions. The developed PLS models were evaluated for a real natural gas, and a good agreement between the PLS model prediction and the gas chromatography (GC) analysis was gained at different pressures. Finally, the sensitivity of the FTNIR spectroscopy technique to the system pressure and temperature was investigated. It was verified that changes in pressure and temperature within a certain range affect the accuracy of the PLS models. The results suggest that FTNIR spectroscopy in association with chemometric method, based on the PLS algorithm, is a viable approach for monitoring changes in the concentration of major components in the gas phase.

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New Downhole Fluid Analyzer Tool for Improved Reservoir Characterization

Cited by 23 publications

References 0 publications

Analysis of Downhole Asphaltene Gradients in Oil Reservoirs with a New Bimodal Asphaltene Distribution Function

Analysis of Downhole Asphaltene Gradients in Oil Reservoirs with a New Bimodal Asphaltene Distribution Function

Integrated reservoir fluid characterization in thinly laminated formations – A case study from deepwater Sabah

Fourier Transform Near-Infrared (FTNIR) Spectroscopy and Partial Least-Squares (PLS) Algorithm for Monitoring Compositional Changes in Hydrocarbon Gases under In Situ Pressure

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