As most of the light and easy oil fields have been produced or are nearing their end-life, the emulsion stability is enhanced and water cut is increasing in produced fluid which have brought challenges to oil–water separation in onshore and offshore production trains. The conventional solution to these challenges includes a combination of higher chemical dosages, larger vessels and more separation stages, which often demands increased energy consumption, higher operating costs and larger space for the production facility. It is not always feasible to address the issues by conventional means, especially for the separation process on offshore platforms. Electrostatic coalescence is an effective method to achieve demulsification and accelerate the oil–water separation process. In this paper, a novel compact electrostatic coalescer with helical electrodes was developed and its performance on treatment of water-in-oil emulsions was investigated by experiments. Focused beam reflectance measurement (FBRM) was used to make real-time online measurements of water droplet sizes in the emulsion. The average water droplet diameters and number of droplets within a certain size range are set as indicators for evaluating the effect of coalescence. We investigated the effect of electric field strength, frequency, water content and fluid velocity on the performance of coalescence. The experimental results showed that increasing the electric field strength could obviously contribute to the growth of small water droplets and coalescence. The extreme value of electric field strength achieved in the high-frequency electric field was much higher than that in the power-frequency (50 Hz) electric field, which can better promote the growth of water droplets. The initial average diameters of water droplets increase with higher water content. The rate of increment in the electric field was also increased. Its performance was compared with that of the plate electrodes to further verify the advantages of enhancing electrostatic coalescence and demulsification with helical electrodes. The research results can provide guidance for the optimization and performance improvement of a compact electrocoalescer.

Rotodynamic multiphase pumps are usually equipped with many compression units to provide sufficient boosting pressure for the transportation of production fluid in gas oil field. It is a challenge to maintain pump performance while flow parameters in each stage vary due to the compressibility of gas-liquid phase. In this article, a stage-by-stage design method is proposed to improve the boosting capability of a multiphase pump. Variations of flow parameters in each stage are investigated based on computational fluid dynamics (CFD) numerical simulation. Available methods to determinate main impeller geometry parameters of impeller are discussed. The stage-by-stage design method is applied on a five-stage multiphase pump when the inlet gas volume fraction (GVF) are 30% and 50% separately. The second stage is modified base on its corresponding inlet flow parameters when inlet GVF is 30% while the second and third stage are modified when inlet GVF is 50%. Flow parameters, pressure distribution and velocity distribution are compared between the original pump and modified pump. Differential pressure of the modified pump increases by 53.72 kPa and 58.57 kPa respectively when inlet GVFs are 30% and 50%. The feasibility of the stage-by-stage design method is verified through the comparison results.

The inline gas-liquid cyclone separator has been gradually used in oil & gas industry due to its high separation efficiency and less footprint. However, under the inlet flow conditions with large range of gas volume fractions, the research on structure design and separation performance are seriously insufficient. The preliminary structural design of the inline gas-liquid separator was carried out according to the particle separation theory, and the key structural parameters were optimized by using the Response Surface Method (RSM) together with Computational Fluid Dynamics (CFD). The structure optimization has improved the degassing efficiency by 17.44% and dehydration efficiency by 7.59%. With air and water as working medium, the separation performance of the inline gas-liquid cyclone separator was experimentally investigated in laboratory under a large range of gas volume fractions. The results show that the separation efficiency for both degassing and dehydration can exceed 80% with the inlet gas volume fraction ranges from 0.2 to 0.8. The optimum normalized flow split and liquid volume flow rate are 0.9 –1.2 and 8 m³/h, respectively.

Assembled in series with multistage, Electrical Submersible Pumps (ESP) are widely used in offshore petroleum production due to the high production rate and efficiency. The hydraulic performance of ESPs is subjected to the fluid viscosity. High oil viscosity leads to the degradation of ESP boosting pressure compared to the catalog curves under water flow. In this paper, the influence of fluid viscosity on the performance of a 14-stage radial-type ESP under varying operational conditions, e.g. rotational speeds 1800–3500 r/min, viscosities 25–520 cP, was investigated. Numerical simulations were conducted on the same ESP model using a commercial Computational Fluid Dynamics (CFD) software. The simulated average pump head is comparable to the corresponding experimental data under different viscosities and rotational speeds with less than ±20% prediction error. A mechanistic model accounting for the viscosity effect on ESP boosting pressure is proposed based on the Euler head in a centrifugal pump. A conceptual best-match flowrate Q_BM is introduced, at which the impeller outlet flow direction matches the designed flow direction. The recirculation losses caused by the mismatch of velocity triangles and other head losses resulted from the flow direction change, friction loss and leakage flow etc., are included in the model. The comparison of model predicted pump head versus experimental measurements under viscous fluid flow conditions demonstrates good agreement. The overall prediction error is less than ±10%.