Product Mix Optimization for an Oil Field Operating Company
- Najla Abdulaziz Khonji
- Saad M. A. Suliman
Abstract
In this study, a mathematical model is formulated to select the optimal product mix of wells in terms of numbers and types of wells that helps to maximize profit. The optimization model comprises two main components, the first component is revenue which includes forecasting of production and oil price, and the second component is cost which includes capital and operating costs. In addition, the model considers all related constraints such as budget, production targets, surface facility limitations, drilling rigs availability and others. Time has influence on the model, since its output is not limited only to the types and numbers of wells to be drilled during the planned period, but also when each well to be drilled for the same plan. Actual planning data for three consecutive years is used for model testing. The results show that 42% to 47% cost saving can be achieved by using the model. The analysis shows that with every 10% increase in oil price, the profit increases by about 6%. Also, it shows that the number of rigs and the rig daily cost affect the profit tremendously, where by reducing these two parameters by 50% an increase of 66% in oil profit can be achieved. The study confirms that oil field operating companies can stand a better chance of maximizing their profit by using product mix optimization model to define the optimum schedule for the number of wells, type of wells and time of drilling.
- Full Text: PDF
- DOI:10.5539/mas.v14n10p20
Journal Metrics
(The data was calculated based on Google Scholar Citations)
h5-index (July 2022): N/A
h5-median(July 2022): N/A
Index
- Aerospace Database
- American International Standards Institute (AISI)
- BASE (Bielefeld Academic Search Engine)
- CAB Abstracts
- CiteFactor
- CNKI Scholar
- Elektronische Zeitschriftenbibliothek (EZB)
- Excellence in Research for Australia (ERA)
- JournalGuide
- JournalSeek
- LOCKSS
- MIAR
- NewJour
- Norwegian Centre for Research Data (NSD)
- Open J-Gate
- Polska Bibliografia Naukowa
- ResearchGate
- SHERPA/RoMEO
- Standard Periodical Directory
- Ulrich's
- Universe Digital Library
- WorldCat
- ZbMATH
Contact
- Sunny LeeEditorial Assistant
- mas@ccsenet.org