tailieunhanh - Petro Vietnam Journol Vol 10/2018

Journal with the situation of Vietnam Oil and Gas industry, domestic and international cooperation of the petroleum industry in October year 2018. With the following articles: Application of seismic attribute analysis tostudy fractured basement; sources, mechanism and prediction method of scale formation in oil production in Vietnam; maximizing production in shale reservoirs; predicting hydrocarbon migration and accumulation in block 09-3/12, Cuu Long basin by 3D petroleum system modelling. | PETROVIETNAM Vol 10-2018 An Official Publication of the Vietnam National Oil and Gas Group Vol 10 - 2018 PETROVIETNAM JOURNAL IS PUBLISHED MONTHLY BY VIETNAM NATIONAL OIL AND GAS GROUP EDITOR-IN-CHIEF Dr. Nguyen Quoc Thap DEPUTY EDITOR-IN-CHIEF Dr. Le Manh Hung Dr. Phan Ngoc Trung EDITORIAL BOARD MEMBERS Dr. Trinh Xuan Cuong Dr. Nguyen Minh Dao BSc. Vu Khanh Dong Dr. Nguyen Anh Duc MSc. Nguyen Ngoc Hoan MSc. Le Ngoc Son Dr. Cao Tung Son Eng. Le Hong Thai MSc. Ton Anh Thi MSc. Nguyen Van Tuan Dr. Phan Tien Vien Dr. Tran Quoc Viet Dr. Nguyen Tien Vinh SECRETARY MSc. Le Van Khoa . Nguyen Thi Viet Ha DESIGNED BY Le Hong Van MANAGEMENT Vietnam Petroleum Institute CONTACT ADDRESS Floor M2 VPI Tower Trung Kinh street Yen Hoa ward Cau Giay district Ha Noi Tel 84-24 37727108 Fax 84-24 37727107 Email tcdk@ pvj@ Mobile 0982288671 Publishing Licence No. 100 GP-BTTTT dated 15 April 2013 issued by Ministry of Information and Communications PETROlili lllv JDURNALn pnHBU iiPiiiinia iMitnia PETROVIETNAM JOURNAL Volume 10 2013 p. 4 - 11 ISSN-0356-854X PETRC PETROVIETNAM JOURNAL Volume 10 2018 p. 4 - 48 ISSN-0866-854X PETR LU 1S Application of machine learning techniques in estimation of fracture porosity using fuzzy inference system for a FGB reservoir in Cuu Long basin Vietnam Pham Huy Giao Nakaret Kano Kushan Sandunil Bui Due Trung Aslan Institute ofTechnolocy AIT Email hgiaor@ Summary Determination of porosity of a fractured granite basement FGB reservoir in the Cuu Long basin has always been a challenge for petrophysicists. In this study an analysis of fracture porosity was successfully conducted using a machine-learning technique . fuzzy inference system FIS the well log data including gamma ray GR deep resistivity LLD shallow resistivity LLS sonic DT bulk density RHOB neutron porosity NPHI photoelectric factor PEF and caliper CAL from two wells BHX01 and BHX02 were used as the input for FIS analyses. Fracture porosity calculated by conventional method