TY - JOUR
T1 - Comprehensive assessment and evaluation of correlations for gas-oil ratio, oil formation volume factor, gas viscosity, and gas density utilized in gas kick detection
AU - Sleiti, Ahmad K.
AU - Al-Ammari, Wahib A.
AU - Abdelrazeq, Motasem
AU - El-Naas, Muftah
AU - Rahman, Mohammad Azizur
AU - Barooah, Abinash
AU - Hasan, Rashid
AU - Manikonda, Kaushik
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/12
Y1 - 2021/12
N2 - For reliable gas kick detection modeling and simulation, the PVT properties of the gas must be predicted accurately. The property correlations available in open literature are developed mostly for certain regions and conditions, which usually over-predict or under-predict when applied to different regions and conditions. To assess these correlations and to determine their applicability and accuracy, a comprehensive evaluation is performed for 63 empirical correlations of four gas properties; gas-oil ratio GOR, oil formation volume factor OFVF, gas viscosity, and gas density based on published laboratory measurements. The GOR and OFVF correlations were evaluated on a regional basis and three best-fit correlations are recommended for each selected region including the Middle East, Central & South America, North America, Africa, and Asia. A universal new correlation for the GOR is developed in this study that can be used for any region in the world with better accuracy and wider range than all available correlations. Furthermore, based on the evaluation results, the most accurate correlations for gas viscosity and density at high-temperature and high-pressure (HTHP) conditions are recommended. The density-based models of the gas viscosity show close results within a minimum average absolute relative error (AARE) of 3.50% to a maximum of 4.45%. Further assessment for the equations of state based on real compositions of the gas kick is recommended for future work. The present work provides a comprehensive and one-stop source database for property correlations and measured data related to gas kick detection.
AB - For reliable gas kick detection modeling and simulation, the PVT properties of the gas must be predicted accurately. The property correlations available in open literature are developed mostly for certain regions and conditions, which usually over-predict or under-predict when applied to different regions and conditions. To assess these correlations and to determine their applicability and accuracy, a comprehensive evaluation is performed for 63 empirical correlations of four gas properties; gas-oil ratio GOR, oil formation volume factor OFVF, gas viscosity, and gas density based on published laboratory measurements. The GOR and OFVF correlations were evaluated on a regional basis and three best-fit correlations are recommended for each selected region including the Middle East, Central & South America, North America, Africa, and Asia. A universal new correlation for the GOR is developed in this study that can be used for any region in the world with better accuracy and wider range than all available correlations. Furthermore, based on the evaluation results, the most accurate correlations for gas viscosity and density at high-temperature and high-pressure (HTHP) conditions are recommended. The density-based models of the gas viscosity show close results within a minimum average absolute relative error (AARE) of 3.50% to a maximum of 4.45%. Further assessment for the equations of state based on real compositions of the gas kick is recommended for future work. The present work provides a comprehensive and one-stop source database for property correlations and measured data related to gas kick detection.
KW - Empirical correlations
KW - Equations of state
KW - Gas kick
KW - Gas viscosity
KW - Gas-oil ratio
KW - PVT properties
UR - http://www.scopus.com/inward/record.url?scp=85108602403&partnerID=8YFLogxK
U2 - 10.1016/j.petrol.2021.109135
DO - 10.1016/j.petrol.2021.109135
M3 - Article
AN - SCOPUS:85108602403
SN - 0920-4105
VL - 207
JO - Journal of Petroleum Science and Engineering
JF - Journal of Petroleum Science and Engineering
M1 - 109135
ER -