Semester
Fall
Date of Graduation
2000
Document Type
Thesis
Degree Type
MS
College
Statler College of Engineering and Mineral Resources
Department
Petroleum and Natural Gas Engineering
Committee Chair
Sam Ameri.
Abstract
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.
Recommended Citation
Mohamad, Khalid Y., "Restimulation candidate selection using virtual intelligence" (2000). Graduate Theses, Dissertations, and Problem Reports. 1083.
https://researchrepository.wvu.edu/etd/1083