Application of fuzzy analysis to predict the effective porosity in a clastic reservoir, Pattani Basin | |
| Author | Dissakul Duangngern |
| Call Number | AIT Thesis no.GE-14-17 |
| Subject(s) | Oil well logging--Thailand--Pattani Basin Oil reservoir engineering--Thailand--Pattani Basin |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Geotechnical and Earth Resources Engineeringwith Area of Specialization in Geosystem Exploration and Petroleum Geoengineering, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. GE-14-17 |
| Abstract | The clastic reservoirsarean important producer of hydrocarbon in the world.Petrophysical parameters such as porosity, permeabilityand hydrocarbon saturation are difficult to estimate since there have never been the tools tomeasurethemdirectly.Therefore, core analysis is applied for estimationpetrophysical parametersbecause itcan estimate the most reliable data of petrophysical parameters. However, core analysis for the whole depth and for every well is very expensive and spend more time that arenotprovidingreasonableresultsorprofits. The objective of this researchis aimed at applying various Fuzzy logic techniques, which are Fuzzy C-mean by Mamdani method, Fuzzy C-mean by Sugeno methodand Fuzzy subtractive clustering,for predictionof effective porosityof a clastic reservoir inJasmine field, Pattani basinby using well logging and core data.There are two wells in this research denoted to A and B. Regarding to the log responses data from these wells, gamma ray (GR), bulk density (RHOB), deep resistivity (LLD), interval transit time (DT) and neutron-density cross plot (N-D) indicatedthat oil is the possible fluid type of most reservoir zones of these wells. These wells were divided into two major zones by using gamma rayand seven and fourteen reservoirzones for well A and well B, respectively. Total porosity, which isneutron-density porosity, effective porosity and porosity derived from fuzzy logic techniques, were used to calculate water saturation.Among three fuzzy techniques applied,fuzzy subtractive clustering is the best technique for prediction effective porositybecause the result of fuzzy logic model’s performance showed low value of root mean square error, high value of R2and high value of R-value. The predicted effective porosity by fuzzy subtractive clustering is higher than effective porosity calculated by conventional method therefore it results to increase in hydrocarbon saturation in reservoir zones. |
| Year | 2015 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. GE-14-17 |
| 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) | Royal Thai Government;Asian Institute of Technology Fellowship; |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2015 |