Predict Reservoir Fluid Properties of Yemeni Crude Oils Using Fuzzy Logic Technique

Author(s):  
Salem O. Baarimah ◽  
Al-Gathe Abdelrigeeb ◽  
Amer Badr BinMerdhah
Author(s):  
Swati Jayade ◽  
D. T. Ingole ◽  
Manik D. Ingole ◽  
Aditya Tohare

SPE Journal ◽  
2020 ◽  
Vol 25 (06) ◽  
pp. 2867-2880
Author(s):  
Ram R. Ratnakar ◽  
Edward J. Lewis ◽  
Birol Dindoruk

Summary Acoustic velocity is one of the key thermodynamic properties that can supplement phase behavior or pressure/volume/temperature (PVT) measurements of pure substances and mixtures. Several important fluid properties are relatively difficult to obtain through traditional measurement techniques, correlations, or equation of state (EOS) models. Acoustic measurements offer a simpler method to obtain some of these properties. In this work, we used an experimental method based on ultrasonic pulse-echo measurements in a high-pressure/high-temperature (HP/HT) cell to estimate acoustic velocity in fluid mixtures. We used this technique to estimate related key PVT parameters (such as compressibility), thereby bridging gaps in essential data. In particular, the effect of dilution with methane (CH4) and carbon dioxide (CO2) at pressures from 15 to 62 MPa and temperatures from 313 to 344 K is studied for two reservoir fluid systems to capture the effect of the gas/oil ratio (GOR) and density variations on measured viscosity and acoustic velocity. Correlative analysis of the acoustic velocity and viscosity data were then performed to develop an empirical correlation that is a function of GOR. Such a correlation can be useful for improving the interpretation of the sonic velocity response and the calibration of viscosity changes when areal fluid properties vary with GOR, especially in disequilibrium systems. In addition, under isothermal conditions, the acoustic velocity of a live oil decreases monotonically with decreasing pressure until the saturation point where the trend is reversed. This observation can also be used as a technique to estimate the saturation pressure of a live oil or as a byproduct of the target experiments. It supplements the classical pressure/volume measurements to determine the bubblepoint pressure.


Author(s):  
Viswanathan Ramasamy ◽  
Jagatheswari Srirangan ◽  
Praveen Ramalingam

In Intelligent Transport Systems, traffic management and providing stable routing paths between vehicles using vehicular ad hoc networks (VANET's) is critical. Lots of research and several routing techniques providing a long path lifetime have been presented to resolve this issue. However, the routing algorithms suffer excessive overhead or collisions when solving complex optimization problems. In order to improve the routing efficiency and performance in the existing schemes, a Position Particle Swarm Optimization based on Fuzzy Logic (PPSO-FL) method is presented for VANET that provides a high-quality path for communication between nodes. The PPSO-FL has two main steps. The first step is selecting candidate nodes through collectively coordinated metrics using the fuzzy logic technique, improving packet delivery fraction, and minimizing end-to-end delay. The second step is the construction of an optimized routing model. The optimized routing model establishes an optimal route through the candidate nodes using position-based particle swarm optimization. The proposed work is simulated using an NS2 simulator. Simulation results demonstrate that the method outperforms the standard routing algorithms in packet delivery fraction, end-to-end delay and execution time for routing in VANET scenarios.


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