Understanding AICD Gravel Packing

In recent years, it has become common practice for operating companies to make a significant effort in the planning of gravel pack installations, especially in their most important wells. Typically, the placement of the gravel pack is accurately modelled, and multiple contingencies developed for potential alternative scenarios to reduce the overall risk of execution. After the pack has been placed, the use of down-hole gauge data enables the gravel pack to be fully evaluated in order to confirm success and investigate any issues or failures. This understanding feeds into improved designs and ever higher success rates for future completions. The most challenging gravel packs Operators are installing today are those placed in long horizontal open holes, around screens fitted with Inflow Control Devices (ICDs) or Autonomous Inflow Control Devices (AICDs). Simulating gravel pack placement in wells such as these requires the effective modelling of unusually dynamic and complex flow paths. Until recently, no simulator could adequately model these treatments. Most jobs have also been done without the downhole gauges necessary for a complete job evaluation, which has resulted in a lack of data for job evaluation and understanding. Consequently, completions requiring the pack to be placed around ICD/AICD screen assemblies have, until recently, been done without the assurance of pre-job gravel pack placement modelling. The lack of an adequate simulator has also meant that, even on these complex and valuable wells, Operators have been restricted to simple volumetric evaluation of their success. With no way to understand actual packing mechanisms or investigate root causes of failures, the assumptions made on how packing occurs in these complex wells have remained unconfirmed. Recent evolution of gravel pack simulators has made the effective pre-job simulation, and post-job evaluation, of gravel packs placed around ICD/AICDs a reality. This paper presents the results of the first evaluation of a multi-proppant deep water horizontal alpha beta gravel pack around AICD screens. It facilitates the understanding of how such gravel packs are placed, validates the packing efficiencies, and illustrates the benefits of using multiple gravels for packing.

Developing an industry job simulation program for graduate and postdoctoral trainees in life sciences

In the life sciences, many graduate students and postdoctoral fellows find it challenging to enter the non-academic workforce after completing their programs. Through experiential learning, trainees can develop the knowledge, technical skills, soft skills, and project portfolio that employers value, and compete effectively in the job market. In this article, we share design considerations for developing a job simulation program based on our experience over five years with the Industry Team Case Study program at the University of Toronto. In this program, which is focused on the biopharmaceutical sector, trainees identify a business or policy challenge, conduct in-depth research, develop a solution to address the problem, and present their findings to industry professionals. For mentorship and coaching, trainees are matched with industry professionals. This article covers four areas of program development: starting the program, recruiting advisors and trainees, designing the program and project framework, and evaluating program effectiveness. Academic institutions and student organizations can use this information to start their own job simulation programs focused on their employment sector of interest. Employers can participate in these programs to develop and scout talent.