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In the June 2008 Tip of the Month (TOTM), we demonstrated how general-purpose process simulation programs can be used to simulate gas dominated two-phase pipelines. In the August 2008 TOTM, we discussed the value of the simple Flanigan correlation and how it can be used to model and analyze the behavior of a wet gas transmission pipeline. The results of the Flanigan correlation were compared with more rigorous calculation methods for multiphase pipelines. In this TOTM, we will study the impact of gas-oil ratio (GOR) on pressure drop in crude oil gathering systems. Specifically, pressure drop along a gathering line for nominal pressures of 690, 3450, and 6900 kPag (100, 500, and 1000 psig) and nominal pipe size of 101.6 and 152.4 mm (4 and 6 inches) was calculated using multiphase rigorous method from commercial simulator. The calculated pressure drops are presented in graphical format as a function of the oil stock tank volume flow rate and GOR. Variation of thermophysical properties was considered. [Keep reading]

In the October, November, December 2007 and February 2014 Tips of the Month (TOTM), we studied in detail the water phase behaviors of sweet and sour natural gases and acid gas systems. We also evaluated the accuracy of different methods for estimating the water content of sour natural gas and acid gas systems. The water vapor content of natural gases in equilibrium with water is commonly estimated from Figure 6.1 of Campbell book or Figure 20.4 of Gas Processors and Suppliers Association (GPSA), including corrections for the molecular weight (relative density) of gas and salinity of water. In this article, we will present two new correlations for estimating the water content of lean and sweet natural gases. The performance of the proposed correlations is compared with the rigorous simulation and shortcut method software and other correlations. [Keep reading]

PRESS RELEASE -- KATY, TX (September 2, 2014) – PetroSkills announced today that Kevin Lacy has joined PetroSkills as Executive Vice President, Technical Staff and Disciplines. In this role, Mr. Lacy will be responsible for leading and building the PetroSkills technical staff organization into the petroleum industry’s leading source of technical subject matter expertise. Mr. Lacy will also work with the PetroSkills senior leadership team in developing and implementing PetroSkills’ strategy and future business objectives. [Keep reading]

The first pillar of Risk Based Process Safety Management is “Commitment to Process Safety.” A formalized mentoring system can ensure workforce involvement, compliance with company and regulatory requirements, increase the competency of personnel and enhance the process safety culture of the entire organization. Within this element there are several essential features that lead to a more effective process safety culture. Providing strong leadership is critical for any organization that strives to manage the risk associated with the activities associated with process safety. Leadership is a skill that is not necessarily intuitive to managers and mentors. Leadership is a skill that can be learned. In this Tip of the Month (TOTM), we explore process safety leadership. [Keep reading]

Several alkanolamines have been used for acid gas removal from natural gas streams. In this study only a primary monoethanolamine (MEA), a secondary diethanolamine (DEA) and a tertiary methydeithanolamine (MDEA) are considered. MEA has the highest reactivity and MDEA has the highest selectivity. In this TOTM, we will study and compare the performance of these three amines by simulation of a simplified process flow diagram for removal of H2S and CO2 from a sour gas stream. The H2S and CO2 concentration in the sweet gas, amine solution circulation rate, reboiler duty, amine losses, pump power, and lean-rich heat exchanger (HEX) duty are calculated and plotted for a wide range of steam rates needed to regenerate the rich solution. In addition, the optimized steam rate and corresponding design variables are determined and reported. [Keep reading]

This article describes simple equations to approximate changes to the properties of crude oil with changing temperature. Changes in crude oil density and specific heat, or heat capacity, can be estimated from graphs and/or more elaborate computer simulation. The latter generally requires access to a process simulator and characterization data for the crude oil. A suitable, tuned computer model is likely the most accurate method of estimating the fluid properties, but is not always available. Direct laboratory measurement is also possible if facilities and oil samples are available and a high degree of accuracy is required. [Keep reading]