1. Full name:     Dang Song Ha                                      2. Sex: Male

3. Date of birth: 21/06/1990                                            4. Place of birth: Ha Noi

5. Admission decision number: 5396/QĐ-ĐHKHTN, signed date 18/12/2014 by the rector of VNU University of Sciences

6. Changes in academic process:

7. Official thesis title: Research on artificial neural networks to predict the storage capacity of oil and gas fields of Oligocene sediments in the north of Cuu Long Basin.

8. Major: Geology                                                         9. Code: 9440201.01

10. Supervisors: Assoc. Prof.Dr Le Hai An, Assoc. Prof .Dr. Do Minh Duc

11. Summary of the new findings of the thesis

- The thesis has researched the correlation between the well log curves (including GR, DT, NPHI, RHOB, LLD, LLS) with the petrographic features of Oligocene sediments in the north of Cuu Long basin.

- The ANN recover the missing well log curves for the northern area of ​​Cuu Long basin. The training set of network was built from the data of the well need to be recover.

- The ANN that determines the petrophysic parameters was optimally designed with 4 inputs and the test results show that the calculated network has high accurate, satisfying the criteria (a, R, P) with a >0.95, R > 0.95 and P = 0.000n.

- The application of ANN allows to calculate the thickness of the reservoir. From there, the reserves can be recalculated, and the oil and gas potential of the study area can be assessed.

12. Practical applicability, if any:

ANN is completely applicable in practice. In fact, ANN was calculated the porosity for 15 wells in Rang Dong field, helping operator build the diagram of mining.

13. Further research directions, if any:

The application of ANN can be extended to other research such as: determining the formation factors, determining the capillary pressure.

Expands the thesis to study other potential oil and gas area.

14. Thesis-related publications:

[1]. “Calculation the Irreducible water saturation and determination Capillary pressure curve Pc from Well log data”, VNU, Journal of Earth and Environmental Sciences.

[2]. “Determination of the Mineral Volumes for The Pre-Cenozoic Magmatic basement rocks of Cuu Long basin from Well log data via using the Artificial Neural Networks”, VNU, Journal of Earth and Environmental Sciences.

[3]. “Determination of the porosity for the sedimentary clastic and the magmatic basement rocks of Cuulong basin from well log data via using the artificial neural networks”, Hanoi University of Mining and Geology, Journal of Mining and Earth.

[4]. “Correction and supplementation of the well log curves for Cuu Long oil basin by using the Artificial Neural Networks”, VNU, Journal of Science Earth and Environmental.