| Author | Parkpum Amornrujiroj |
| Call Number | AIT Thesis no.GE-09-13 |
| Subject(s) | Oil well logging--Thailand--Bang Oil Field
|
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Geosystem Exploration and Petroleum Geoengineering, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. GE-09-13 |
| Abstract | The continual reduction in the hydrocarbon reserve makes the small oil field become more important. One of the examples is the Fang oil field that has been developed and operated by the Northern Petroleum Development Center Defense Energy Department. In this study, the forces were emphasized on characterization of a small reservoir located in the Fang oil field. As the production of the Fang oil field is very small, investment in well logging was not that much. Consequently, the well logging data were very old and available only in form of paper records. The first work in this study was to collect core and well logging data from two wells in Sansai area which is one of mainly eight production zones in Fang oil field. A lot of efforts were spent on digitizing and calibrating SP, GR, DT, RHOB, NPHI, and LLD. The well logging data are available in soft file (ready for log analysis). Then, well logging interpretation identified six reservoir intervals with total thickness 81 ft in well 1 and 4 reservoir zones with total thickness 93 ft in well 2. Another major work of this study to predict reservoir parameter (porosity) based on artificial neural network analysis (ANN). The ANN is a useful tool to predict porosity. The most popular ANN method used in this study is the backpropagation algorithm. The improving generalization called early stopping was used to make ANN prediction better. Water saturation was calculated for reservoir intervals. Poroperm was plotted to determine flow zone indicator (FZI) and free fluid index (FFI). The well 1&2 have FZI equal to 16.90 and 15.38 and FFI equal to 96.8 % and 96.1 %, respectively. |
| Year | 2010 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. GE-09-13 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Department of Civil and Infrastucture Engineering (DCIE) |
| Academic Program/FoS | Geotechnical Engineering (GE) |
| Chairperson(s) | Pham Huy Giao; |
| Examination Committee(s) | Noppadol Phien-wej;Pinan Dawkrajai; |
| Scholarship Donor(s) | RTG Fellowship; |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2010 |