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DETAILED ANALYSIS OF PRESSURE DROP IN A LARGE DIAMETER VERTICAL PIPE

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DETAILED ANALYSIS OF PRESSURE DROP IN A LARGE DIAMETER VERTICAL PIPE

 

ABSTRACT

With the ever increasing need to optimize production, the accurate understanding of the mechanics of multi-phase flow and its effect on the pressure drop along the oil-well flow string is becoming more pertinent. The efficient design of gas-lift pump, electric submersible pumps, separators, flow strings and other production equipment depends on the accurate prediction of the pressure drop along the flow pipe. Pressure is the energy of the reservoir/well and it is crucial to understand how a change in fluid properties, flow conditions and pipe geometric properties affect this important parameter in the oil and gas industry. Extensive work on this subject has been done by numerous investigators albeit in small diameter pipes. Reliance on the empirical correlations from this investigators has been somewhat misleading in modelling pressure drop in large diameter pipes (usually >100 mm) because of the limitations imposed by the diameter at which they were developed and the range of data and conditions used in deriving them. In this work, experimental data from the experimental study by Dr. Mukhtar Abdulkadir was used as the data source. The gas velocities, liquid velocities, film fraction, gas and liquid properties and the pipe geometric properties from the above mentioned experiment were used to model the frictional and total pressure drop from six correlations. Results were analyzed and compared with the experimental results.

 

CHAPTER ONE

INTRODUCTION

1.1 General introduction

Profitable production of oil and gas fields relies on accurate prediction of the multi-phase well flow. The determination of flowing bottom-hole pressure (BHP) in oil wells is very important to petroleum engineers. It helps in designing production tubing, determination of artificial lift requirements and in many other production engineering aspects such as avoiding producing a well below its bubble point in the sand-face to maintain completion stability around the wellbore (Ahmed, 2011). Well fluids above bubble point pressure exist as a single phase as it is being produced from the reservoir. However, as they navigate their way through the network of interconnected pores in the reservoir to the wellbore, there is a continuous reduction in pressure as overburden stress is gradually reduced. This phenomenon leads to the liberation of the entrained gas. As the single-phase fluid rises in the tubing, a critical point is reached where some of the gases begin to come out of solution along the length of the pipe. In other words, it changes from single-phase flow to multi-phase flow.

This leads to some level of complexity as regards to the identification of the physical properties of the individual phases, the flow pattern, the relative volume occupied by the separate phases inside the pipe, and most importantly the implication of the phase separation on the pressure drop along the well tubing string. Although most if not all calculations for flow lines in multiphase production systems have been and continue to be based on empirical correlations, there is now a strong tendency to introduce more physically based (so called mechanistic) approaches to supplement if not replace correlations. This is because the latter are well known for their unreliability when applied to systems operating under conditions different to those from which the correlations are derived; such conditions encompass: pressure, temperature, fluid properties and pipe diameter. Furthermore, correlations exist for limited geometrical configurations (i.e. vertical or horizontal pipes) and simple physical phenomena (no mass transfer between phases, constant temperature, etc.). With the advent of more complex production systems involving deviated wells as well as the move to exploit gas condensate resources the production of which will inevitably involve strong mass transfer effects, calculation methods will be required to account for such complexities.

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