Impact of Uncertainty of Heavy Oil Fluid Property Measurements
- F. Zabel (DBR Technology Center, Schlumberger) | D.H.-S. Law (DBR Technology Center, Schlumberger) | S. Taylor (DBR Technology Center, Schlumberger) | J. Zuo (DBR Technology Center, Schlumberger)
- Document ID
- Society of Petroleum Engineers
- Journal of Canadian Petroleum Technology
- Publication Date
- March 2010
- Document Type
- Journal Paper
- 28 - 35
- 2010. Society of Petroleum Engineers
- 4.1.2 Separation and Treating, 4.1.5 Processing Equipment, 4.3.3 Aspaltenes, 4.3.1 Hydrates, 5.3.9 Steam Assisted Gravity Drainage, 5.1.1 Exploration, Development, Structural Geology, 5.5 Reservoir Simulation, 5.2 Fluid Characterization, 5.6.9 Production Forecasting, 4.6 Natural Gas, 4.3 Flow Assurance, 5.1.5 Geologic Modeling, 5.2 Reservoir Fluid Dynamics, 5.2.1 Phase Behavior and PVT Measurements, 5.2.2 Fluid Modeling, Equations of State
- fluid properties, uncertainty
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Heavy oil is particularly known for the difficulty it presents in obtaining accurate fluid property measurements. The uncertainty of heavy oil fluid property measurements affects the quality of fluid property data which in turn affecting the accuracy of production forecast. In our investigation, we included the impact from certain heavy oil fluid property uncertainties, including live oil viscosity and saturation pressure [or the initial gas-oil ratio (GOR)]. The reservoir simulations were performed for case studies with a 9°API reservoir fluid and geology similar to those typically found in the Faja region in Venezuela. Two base cases and the underlying process mechanisms were established, one assuming primary production process and one assuming steam-assisted gravity drainage process (SAGD). We then performed sensitivity studies of the different fluid property variations to determine the effect on the process performances. We found that the process mechanism dictated the magnitude of the sensitivity to different fluid properties. The uncertainties of the recovery prediction obtained from a reservoir simulator confirmed importance of selecting accurate fluid property data on the dynamic simulation prediction.
In upfront reservoir engineering study, the reservoir and fluid properties are very important input data for the dynamic reservoir simulation as they dictate the accuracy of the simulation prediction. The uncertainties of the reservoir properties, such as the geologic and petrophysic data, are often given more attention than the uncertainties of the fluid properties, such as oil viscosity and initial GOR.
It is well known that there are uncertainties in fluid property data, especially for heavy oil, because accurate measurements of heavy oil properties are quite difficult to obtain. For example, it has been observed that a large variation exists in the heavy oil viscosity measured from different laboratories using different measuring techniques. In addition to the inconsistency from the measurements, fluid sampling is another main source contributing to the accuracy of fluid property data. Therefore, it is essential to study the effect of the variation in fluid properties, such as oil viscosity and oil saturated pressure (or initial GOR), to predict the heavy oil recovery performance by means of dynamic reservoir simulation.
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1. de Mirabal, M., Gordillo, R., Rojas, G., Rodriguez, H., and Huerta, M.1996. Impact of Foamy OilMechanism on the Hamaca Oil Reserves Orinoco Belt-Venezuela. Paper SPE36140 presented at the SPE Latin America/ Caribbean Petroleum EngineeringConference, Port-of-Spain, Trinidad, 23-26 April. doi: 10.2118/36140-MS.
2. Gipson, L.J., Owen, R., and Robertson, C.R. 2002. Hamaca Heavy Oil Project—LessonsLearned and an Evolving Development Strategy. Paper SPE 78990 presented atthe SPE International Thermal Operations and Heavy Oil Symposium andInternational Horizontal Well Technology Conference, Calgary, 4-7 November.doi: 10.2118/78990-MS.
3. ECLIPSE Technical Description 2007.1: Thermal Option, 925. 2007. Houston:Schlumberger GeoQuest.
4. Crookston, H.B., Culham, W.E., and Chen, W.H. 1979. Numerical Simulation Model for ThermalRecovery Processes. SPE J. 19 (1): 37-58; Trans., AIME, 267. SPE-6724-PA.doi: 10.2118/6724-PA.
5. ECLIPSE Reference Manual 2007.1, 1274. 2007. Houston:Schlumberger/GeoQuest.