{"id":747,"date":"2010-10-04T15:57:49","date_gmt":"2010-10-04T19:57:49","guid":{"rendered":"https:\/\/www.bu.edu\/pasi\/?page_id=747"},"modified":"2010-10-05T11:02:16","modified_gmt":"2010-10-05T15:02:16","slug":"computational-methods-for-oil-recovery","status":"publish","type":"page","link":"https:\/\/www.bu.edu\/pasi\/courses\/computational-methods-for-oil-recovery\/","title":{"rendered":"Computational methods for oil recovery"},"content":{"rendered":"

by Dr Luis M. de la Cruz<\/h3>\n

Universidad Nacional Aut\u00f3noma de M\u00e9xico<\/strong><\/p>\n

What is EOR?<\/h3>\n

In the first stage of oil reservoir production (primary recovery), the oil is extracted by natural drive mechanism, solution gas, water influx, gas cap drive or gas drainage. \u00a0In order to maintain reservoir pressure, techniques such as gas or water injection are applied; this is known as secondary recovery<\/em>.<\/p>\n

Tertiary or Enhanced Oil Recovery (EOR) is a generic term that embraces several techniques used to increase the amount of crude oil that can be extracted from an oil field. \u00a0These techniques are based on the injection of materials not normally present in the reservoir, and is the most advanced stage of the exploitation of a reservoir.<\/p>\n

Primary recovery techniques produce 10\u201315% of the reservoir’s oil content. \u00a0Combining the processes of secondary and tertiary recovery techniques, it is possible to produce 30\u201360% of the reservoir’s total oil content.<\/p>\n

Mathematical and computational modeling of EOR<\/h3>\n

Mathematical and computational models permit studying complex systems and natural phenomena that otherwise would be very costly, dangerous or even impossible to study by direct experimentation. \u00a0EOR simulations take advantage of mathematical and computational models to design optimal experiments, reducing costs and times of oil production.<\/p>\n

In a typical numerical simulation, several millions of unknowns need to be calculated each time step. \u00a0Because the simulation’s objective is to reproduce the daily history of an exploited field during, for example, 20 years of operation, we require tens of thousands of time steps to generate the complete production history. \u00a0On the other hand, due to the uncertainty of many physical parameters, hundreds of numerical experiments are required.<\/p>\n

Parallel computing is an obvious way to accelerate the generation of numerical information and many efforts on this area have been made. Also, with the advent of new and ubiquitous GPU hardware, it is possible to accelerate many of the calculations using modern programming techniques.<\/p>\n

The aim of this course<\/h3>\n

In this course, a brief introduction to EOR will be presented along with some numerical and computational techniques currently applied in this research field. \u00a0The tentative schedule includes:<\/p>\n