eprintid: 12255
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/22/55
datestamp: 2023-11-10 03:26:48
lastmod: 2023-11-10 03:26:48
status_changed: 2023-11-10 01:17:15
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; Elasticity; Forecasting; Gas industry; Geophysical prospecting; Hydrocarbons; Lithography; Seismology, Bayesian probabilities; Elastic modeling; Elastic properties; High confidence; Hydrocarbon predictions; Oil and gas fields; Pre-stack seismic data; Well location, Petroleum prospecting
note: cited By 5; Conference of 88th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2018 ; Conference Date: 14 October 2018 Through 19 October 2018; Conference Code:143290
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: 2019
publisher: Society of Exploration Geophysicists
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059431247&doi=10.1190%2fsegam2018-2968514.1&partnerID=40&md5=04b153898e29cc435714c7c0d8a7c8ed
id_number: 10.1190/segam2018-2968514.1
full_text_status: none
publication: 2018 SEG International Exposition and Annual Meeting, SEG 2018
pagerange: 3141-3145
refereed: TRUE
citation:   Babasafari, A.A. and Ghosh, D.P. and Salim, A.M.A. and Ratnam, T. and Sambo, C. and Rezaee, S.  (2019) Petro Elastic Modeling for enhancement of hydrocarbon prediction: Case study in SE Asia.  In: UNSPECIFIED.