Restimulation candidate selection using virtual intelligence

Due to the importance of well deliverability maintenance, a committee of specialists from Dominion East Ohio and other service companies meets every year to select the wells to be included in the deliverability maintenance plan. The application tool not only help in selecting the wells for deliverability maintenance plan but goes beyond that by designing the most optimum frac recipe.;The purpose of this study is to develop an engineering tool that will help petroleum engineers making a better decision for selecting well candidate and design well restimulation. The project focuses on a gas storage field and use data such as well location, stimulation time and recipe and deliverability statistics.;This tool reduces the time engineers spend designing optimum treatment schedules by proposing a solution based on virtual intelligence. Neural networks, genetic algorithms and a fuzzy support system are integrated into a software application to achieve the required goals.;The software application is a user-friendly application compiled in a Visual Basic programming language linked to and access database.

Name thesis:degree_name

MS

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Petroleum and Natural Gas Engineering

Year dc:date.available

2000

Author dc:creator

• Mohamad, Khalid Y.

Contributors dc:contributor

• Sam Ameri.

• Petroleum engineering
• Operations research
• Artificial intelligence

Identifier

https://researchrepository.wvu.edu/etd/1083

OAI identifier oai:identifier

oai:researchrepository.wvu.edu:etd-2086