�������� ���������������������������������������������������������� ������������������ ��������� ����� "����������������������"������������������"����# ������������� �������� !������ ����� �������������� ������ ���������������� ������������� ������� ����������������� ������������ ����������� ����������� ����� Multi-Attribute PNN Results ���������������������������������������������������� ������������������������������� ����� ��������� ����� ������������� �������� !������ ����� �������������� ������ ���������������� ������������� ������� ����������������� ������������ ����������� ����������� ��$�� �
�������� Raw Seismic Image Vs Relative AI Inversion Raw Seismic Image Vs Relative AI Inversion &������''������������������� Raw Seismic �����(�������)����������� � %�������������� *���!����� ��%+�+� ������� �������������������� % ���)������� �������� ����������������������� Relative AI Inversion � % Absolute AI Inversion Vs Absolute AI PNN Absolute AI Inversion Vs Absolute AI PNN Absolute AI PNN Absolute AI Inversion �
�������� Absolute AI from Inversion Vs Absolute AI from PNN Absolute AI from Inversion Vs Absolute AI from PNN %+�'����+� �����%+�'����,&&���%+�-���������%����'�%+���� ��� PNN Results for AI and Porosity PNN Results for AI and Porosity %��������+�������� ,������� #
�������� PNN Result for Resistivity PNN Result for Resistivity �!"" �!"" Acoustic Impedance to Porosity Relationship from Available Log Data #� �����������$����#%�������������& ,������� 1 /�����/23 %+ 4 ���� ,������� ����� ,/��������� '��� ��� ����0 ���� �� ���� � � ����� �� ��� ��� �)������ %+ '��� �� ������ ���� �������� .
�������� INVERSION VERSUS PNN FOR POROSITY PREDICTION ,��������'����%+�+� ������ ,��������'����,&& INVERSION VERSUS PNN FOR POROSITY PREDICTION ,���'����+� ���,���'����,&&���-���,����������%����'�,������ ���� -���,5+ ,5+/+&� ,5+/,&& �
�������� Conclusions • Successful predictions of Oligocene carbonates reservoir properties in the East Java Basin. • Acoustic impedance, porosity and resistivity reservoir properties were predicted with mixed results. In good seismic data quality areas the results agreed with well calibration. In poor seismic data areas the results were poor. • The final post-stack seismic inversion result showed improvements over the seismic. • Using an AI to porosity relationship derived from log data the AI from inversion was converted into a pseudo porosity model, in the zone of interest. • Multi-attribute PNN method was observed to be more sensitive to seismic noise than the conventional Inversion method. RECOMENDATIONS • The results of this 2D seismic pilot showed some encouraging results and suggest that additional work with multi-attribute PNN is warranted. • The results would have benefited by using more wells to train and calibrate the analysis. • Using a 3D volume rather than a 2D seismic line would have also been of value to the project. 2
�������� ACKNOWLEDGEMENTS ExxonMobil Oil Indonesia and Mobil CEPU Limited are thanked for the • opportunity to work on this project. • Prof.Dr.rer.Nat Bagus Jaya S. SU as advisor in campus for guidance patiently, advice and readiness to discuss. • Dr. William Soroka as advisor at EMOI for the mentoring and help provided. Dr. Widya Utama, DEA as guardian lecturer during studying for • encouragement and guidance • Geophysics lectures (Mr. Seno Pudji (alm), Mr. Dwa Desa Warnana, Mr. Makky Sandra Jaya, Mr. Syaeful Bahri, Mr. Eko Minarto, Ms. Anik Hilyah, Mrs. Siti Zulaikah); Physics lecturers and the employee at physics department, thanks for the knowledge and the support. • I am grateful for nice friendship and discussion for all my friends in Geophysics and Physics. • I am grateful for GE by IIEF that has given me scholarship, IPA, HAGI, AAPG, SEG, SPE, FESI, HIMASIKA, BEM MIPA, etc as media improvement of my knowledge and skill. THANK YOU �
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