Numerical Simulation and Experimental Study of a Multistage Multiphase Separation System

Abstract

Nowadays, most oilfields have entered the high water cut stage of waterflood development. The importance of oil–water separation technology becomes more obvious. Gravity separation is one of the most commonly used treatment techniques for produced fluid. The gravitational separator has a large processing capacity and a wide application range, but its structure is relatively simple and the separation efficiency gradually falls behind to meet current production needs. The key difficulties to improve the separation efficiency are to analyze the flow field and coalescing components inside the separator. Aiming at these difficulties, this paper reports an innovatively designed series-parallel multistage multiphase separation system (MMSS). A horizontal separator is connected in series with a vertical separator, and the vertical separator consists of five discrete pipes connected in parallel. Different coalescing components are then set inside the vertical separator. The separation effect of the MMSS is studied by numerical simulation and laboratory experiments. The oil phase volume distribution cloud diagrams of coalescing components are analyzed by numerical simulation, including semicircle baffle, spiral track plate, four-hole plate and seven-hole plate. Laboratory experiments show that MMSS has a high separation efficiency, and the water content at the oil outlet is 3.0% less than that of the horizontal separator. By observing the shape of oil droplets at the outlet and measuring the oil cut and water cut at the sampling outlet, the separation effect of four coalescent plates is obtained. According to the statistics, when the volumetric flow at the inlet of the separator is 1.5 m3/h, the average particle size of oil drops in the blank pipe, semicircular baffle, four-hole plate, spiral track and seven-hole plate increases in turn. A continuous oil layer appears at the outlet of the vertical separator in the fully open state. The water content at the oil outlet of the semicircular baffle coalescing component is always at a high level under different flow rates. When the inlet volumetric flow rate is less than 1.6 m3/h, the performance of the spiral track coalescing component is better. With the increase of the inlet volumetric flow rate, the separation efficiency of the spiral track is lower than that of the orifice. The results show that the semicircular coalescing component has the worst performance, the spiral track coalescing component is superior at small volumetric flow rates, and the orifice coalescing component is superior at large volumetric flow rates.

Advances in Produced Water Treatment Technologies: An In-Depth Exploration with an Emphasis on Membrane-Based Systems and Future Perspectives

“…Chen et al analyzed the coalescing separator mechanism based on the principles of gravity separation, shallow pool theory, and equal flow theory [71]. They innovatively designed horizontal and vertical separators with different coalescing components, which were linked to make a multistage multiphase separation system (MMSS).…”

Using ANN and Combined Capacitive Sensors to Predict the Void Fraction for a Two-Phase Homogeneous Fluid Independent of the Liquid Phase Type

“…Artificial intelligence (AI) is one of the most common methods in the industrial sector [31]. ANN is a capable tool that has been widely utilized in various fields, such as electrical engineering and control engineering [32][33][34][35][36][37][38][39][40][41][42][43][44][45]. The things that affects the performance of capacitance sensors are fluid properties.…”

Intelligent Measuring of the Volume Fraction Considering Temperature Changes and Independent Pressure Variations for a Two-Phase Homogeneous Fluid Using an 8-Electrode Sensor and an ANN

“…The proliferation of ANN as a tool has experienced a substantial surge in popularity spanning diverse disciplines, including but not constrained solely to the domains of electrical engineering and control engineering [ 29 , 30 , 31 , 32 ].…”