Search

Implication Statement An Internal Medicine (IM) specific, near-peer mentorship program was initiated at the University of Ottawa (uOttawa) in 2017. Medical students were paired with IM resident mentors in an effort to improve career decision-making. Additionally, residents had the opportunity to formally teach mentees various high-yield IM topics. Program evaluation was completed using data from three participant cohorts, and showed that the program had a positive impact on students’ career decision making. Given the program’s flexible nature and ease of implementation, it is well suited for adaptation at other institutions.

One of the main problems during oil well completion and cementing operation is fluid migration through cement bulk or behind the cemented casing. Slurry composition and characteristic have been focused and improved in last decades to mitigate gas migration and, recently, aspects such as using nanotechnology have been investigated to amend the conditions. In this research, two moderate base slurries with 95 and 120 Pound per Cubic Feet (PCF) densities containing different percentages of nanosilica have been examined using a perfect test package. The results of Fluid Migration Analyzer (FMA) demonstrated that using correct percentage of nanosilica particles modified rheological behavior of the slurries and decreased fluid migration volume. Moreover, adding nanoparticles did not have any negative effects on any conventional parameters. However, static gel strength analyzer showed significant transient time reduction which is an important key in cement setting profile. Triaxial test results together with Mohr circles analyzing presented considerable progress in cement stability and compressive strength.

Miscible injection of carbon dioxide (CO2) with ability to increase oil displacement as well as to reduce greenhouse effect has become one of the pioneering methods in Enhanced Oil Recovery (EOR). Minimum Miscibility Pressure (MMP) is known as a key indicator to ensure complete miscibility of two phases and maximum efficiency of injection process. There are various experimental and computational methods to calculate this key parameter. Experimental methods provide the most accurate and valid results. However, such methods are time consuming and expensive leading researchers to use mathematical methods. Among computational methods, empirical correlations are the most straight-forward and simple tools to precisely estimate MMP, especially for gases with impurities. Furthermore, in predicting the miscibility state of oil–gas system, phase behavior is a vital issue which should be taken into account to achieve reliable results. In this regard, equations of state have an indisputable role in predicting the phase behavior of reservoir fluids. Remarkable improvements have been introduced to elevate performance of equations of state, based on Pitzer’s acentric factor. Hereupon, this study aims to enumerate acentric factor of injected gas (impure CO2) as a correlating parameter alongside conventional parameters including reservoir temperature, oil constituents (molecular weight of C5+, ratio of volatiles to intermediates) and critical properties of injected gas (pseudo-critical pressure & temperature). Thus, in this study an effective empirical correlation is created, implementing the Group Method of Data Handling (GMDH) algorithm along with including the acentric factor of injected gas, which eventuated to precise predictions of MMP for impure CO2 injection. The GMDH is one of the most robust mathematical modeling methods for predicting physical parameters using linear equations. A comparison with well-known correlations, demonstrated at least 2% improvement in average absolute error with enumerating the acentric factor and the final error was equal to 12.89%.