eprintid: 10070
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/00/70
datestamp: 2023-11-09 16:36:42
lastmod: 2023-11-09 16:36:42
status_changed: 2023-11-09 16:30:30
type: conference_item
metadata_visibility: show
creators_name: Babasafari, A.A.
creators_name: Ghosh, D.P.
creators_name: Salim, A.M.A.
creators_name: Ratnam, T.
creators_name: Sambo, C.
creators_name: Rezaee, S.
title: Petro Elastic Modeling for enhancement of hydrocarbon prediction: Case study in SE Asia
ispublished: pub
keywords: Acoustic fields; Acoustic impedance; Forecasting; Gas industry; Geophysical prospecting; Hydrocarbons; Petroleum prospecting; Seismology, Case-studies; Data inversion; Elastic models; Elastic properties; Hydrocarbon predictions; Oil and gas fields; Pre-stack seismic data; SE Asia; Uncertainty; Well location, Elasticity
note: cited By 4; Conference of Society of Exploration Geophysicists International Exposition and 88th Annual Meeting, SEG 2018 ; Conference Date: 14 October 2018 Through 19 October 2018; Conference Code:175271
abstract: One of the widely used methods for litho-facies classification in oil and gas fields is conducted through cross plotting elastic properties e.g. Acoustic Impedance vs. Vp/Vs ratio. First at well locations the cross plot is color coded by litho-facies classes. Afterwards, to predict litho-facies away from the wells, pre-stack seismic data inversion is performed. Cross plot of predicted elastic properties between the wells aid to discriminate each class. However, discrimination of defined litho-facies classes represents uncertainty particularly at overlapped zones between classes. This study reveals how Petro Elastic Modeling (PEM) generates a more suitable differentiation of litho-facies classification through elastic properties estimation. This process allows predicting the hydrocarbon zones more precisely and rational continuity of pay-zone layers is obtained due to high confidence value of each class in Bayesian probability classification. © 2018 SEG
date: 2018
publisher: Society of Exploration Geophysicists
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121100069&doi=10.1190%2fsegam2018-2968514.1&partnerID=40&md5=d6fb6b21a73b532d0795a5b3b950392d
id_number: 10.1190/segam2018-2968514.1
full_text_status: none
publication: SEG Technical Program Expanded Abstracts
pagerange: 3141-3145
refereed: TRUE
issn: 10523812
citation:   Babasafari, A.A. and Ghosh, D.P. and Salim, A.M.A. and Ratnam, T. and Sambo, C. and Rezaee, S.  (2018) Petro Elastic Modeling for enhancement of hydrocarbon prediction: Case study in SE Asia.  In: UNSPECIFIED.