?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=ANALISIS+AVO%2C+INVERSI+DAN+NEURAL+NETWORK+UNTUK+KARAKTERISASI+RESERVOAR+EARLY+MIOCENE+LAPANGAN+OFFSHORE+AL-FITRA%0D%0A&rft.creator=Wahyuda+Alfin%2C+1015051037&rft.subject=QE+Geology&rft.subject=Teknik+Pertambangan.+metalurgi&rft.description=Keberadaan+anomali+amplitudo+(brighspot)+pada+penampang+seismik+bisa+menjadi+salah+satu+indikator+kehadiran+hidrokarbon+pada+suatu+reservoar.+Namun%2C+banyak+kondisi-kondisi+lain+yang+dapat+memberikan+efek+brightspot%2C+seperti+sisipan+tipis+batubara%2C+rekah-rekah%2C+lapisan+garam%2C+konglomerat%2C+turbidit%2C+ataupun+efek+tuning+dari+lapisan+tipis.+Karena+itu%2C+diperlukan+analisis+amplitudo+terhadap+offset+(AVO)+agar+meningkatkan+kepercayaan+terhadap+kemungkinan+kehadiran+hidrokarbon+terutama+gas+di+reservoar+lapangan+ini.+Dalam+penelitian+ini+dilakukan+analisis+AVO+untuk+mengidentifikasi+kelas+anomali+AVO%2C+inversi+dan+transformasi+Lambda-Mu-Rho+agar+reservoar+dapat+terdeleniasi+lebih+jelas%2C+serta+penerapan+Neural+Network+untuk+memprediksi+distribusi+nilai+porositas+dan+saturasi+air+pada+zona+reservoar+batupasir+Belumai.+Dari+penelitian+ini%2C+diketahui+bahwa+zona+reservoar+batupasir+Belumai+pada+sumur+AW-1%2C+AW-2%2C+AW-3%2C+dan+AW-4+tergolong+sebagai+anomali+batupasir+kelas+IV%2C+dengan+nilai+impedansi+yang+lebih+rendah+dibandingkan+batuan+penutupnya%2C+intercept+bernilai+negatif%2C+gradient+bernilai+positif+serta+berada+di+kuadran+II+pada+crossplot+intercept+%26+gradient.+Berdasarkan+hasil+inversi%2C+zona+reservoar+batupasir+dapat+terpisahkan+dengan+karbonat+dan+serpih%2C+ditandai+dengan+nilai+AI+rendah+7800-9100+((m%2Fs)*(g%2Fcc))%2C+nilai+SI+rendah+4400-5200+((m%2Fs)*(g%2Fcc))%2C+nilai+Mu-Rho+rendah+16-22+((GPa)*(g%2Fcc))%2C+serta+nilai+Lambda-Rho+yang+juga+rendah+22.5-25.5+((GPa)*(g%2Fcc))+menunjukkan+batuan+porous+berasosiasi+fluida+gas.+Sedangkan+berdasarkan+hasil+prediksi+neural+network+PNN+dengan+nilai+korelasi+porosity+%3D+0.97+dan+water+saturation+%3D+0.98%2C+reservoar+di+lapangan+Al-Fitra+memiliki+nilai+porositas+15-25%25+dan+nilai+saturasi+air+15-35%25.+Dan+slice+map+pada+volume+AI%2C+SI%2C+LMR%2C+porosity+dan+water+saturation%2C+sebaran+reservoar+batupasir+gas+di+bagian+selatan+terpetakan+dengan+jelas+yang+berorientasi+NW-SE+serta+ditemukan+juga+2+zona+potensi+sebagai+reservoar+batupasir+gas+dan+perlu+dievaluasi+lebih+lanjut.%0D%0AKata+Kunci%3A+AVO%2C+Inversi+Seismik%2C+Lambda-Mu-Rho+(LMR)%2C+Neural+Network.%0D%0A%0D%0AThe+existence+of+anomalous+amplitude+(brighspot)+on+the+seismic+section+may+be+an+indication+of+hydrocarbon+presence+in+a+reservoir.+However%2C+many+other+conditions+can+also+give+brightspot+effect%2C+such+as+a+thin+insert+of+coal%2C+fractured+rock%2C+a+layer+of+salt%2C+conglomerate%2C+turbidite%2C+or+tuning+effect+of+thin+layers.+Therefore%2C+it+is+necessary+to+analyse+amplitude+variation+with+offset+(AVO)+in+order+to+increase+confidence+in+possibility+of+hydrocarbon+presence%2C+especially+gas+in+the+reservoir+of+this+field.+In+this+research%2C+AVO+analysis+is+to+identify+the+class+of+AVO+anomalies%2C+application+of+inversion+and+Lambda-Mu-Rho+transformation+so+that+the+reservoir+can+be+well+delineated%2C+and+application+of+Neural+Network+is+to+predict+the+distribution+of+porosity+and+water+saturation+in+sandstone+reservoir+at+Belumai+level.+From+this+research%2C+it+is+known+that+Belumai+sandstone+reservoir+on+well+AW-1%2C+AW-2%2C+AW-3%2C+and+AW-4+are+classified+as+class+IV+anomaly%2C+which+identified+by+impedance+value+is+lower+than+the+overlying+rock%2C+intercept+value+is+negative%2C+gradient+value+is+positive+and+plotted+in+quadrant+II+at+intercept+and+gradient+crossplot.+Based+on+the+inversion+results%2C+sandstone+reservoir+zones+can+be+separated+with+carbonate+and+shale%2C+characterized+by+a+low+AI+value+7800-9100+((m%2Fs)*(g%2Fcc))%2C+low+value+of+SI+4400-5200+((m%2Fs)*(g%2Fcc))%2C+the+value+of+Mu-Rho+is+relatively+low+16-22+((GPa)*(g%2Fcc))%2C+as+well+as+the+value+of+Lambda-Rho+is+also+relatively+low+22.5-25.5+((GPa)*(g%2Fcc))+that+indicate+a+porous+rock+with+gas+associated.+While%2C+PNN+neural+network+prediction+obtains+correlation+value+of+porosity+%3D+0.97+and+water+saturation+%3D+0.98%2C+reservoir+in+the+Al-Fitra+field+has+porosity+of+15-25%25+and+water+saturation+15-35%25.+And+based+on+slice+map+results+on+volume+of+AI%2C+SI%2C+LMR%2C+porosity+and+water+saturation%2C+the+distribution+of+sandstone+reservoir+in+southern+part+of+Al-Fitra+field+is+clearly+delineated%2C+which+has+NW-SE+orientation+and+also+found+two+potential+zones+which+are+considered+as+sandstone+reservoir+and+need+to+be+evaluated+further.%0D%0AKeywords%3A+AVO%2C+Seismic+Inversion%2C+Lambda-Mu-Rho+(LMR)%2C+Neural+Network&rft.publisher=Fakultas+Teknik&rft.date=2016-08-25&rft.type=Skripsi&rft.type=NonPeerReviewed&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F24380%2F1%2FABSTRAK%2520%2528ABSTRACT%2529.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F24380%2F2%2FSKRIPSI%2520FULL.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F24380%2F3%2FSKRIPSI%2520TANPA%2520PEMBAHASAN.pdf&rft.identifier=++Wahyuda+Alfin%2C+1015051037++(2016)+ANALISIS+AVO%2C+INVERSI+DAN+NEURAL+NETWORK+UNTUK+KARAKTERISASI+RESERVOAR+EARLY+MIOCENE+LAPANGAN+OFFSHORE+AL-FITRA.++Fakultas+Teknik%2C+Universitas+Lampung.++++(Tidak+diterbitkan)++&rft.relation=http%3A%2F%2Fdigilib.unila.ac.id%2F24380%2F