Cover Image

New avo attributes and their applications for facies and hydrocarbon prediction: A case study from the northern malay basin

Amplitude versus offset (AVO) analysis integration to well log analysis is considered one of the advanced techniques to improve the understanding of facies and fluid analysis. Generating AVO attributes are one solution to give an accurate result in facies and fluid characterization. This study is fo...

Full description

Saved in:
Bibliographic Details
Main Authors: Ridwan, T.K., Hermana, M., Lubis, L.A., Riyadi, Z.A.
Format: Article
Published: MDPI AG 2020
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095749425&doi=10.3390%2fapp10217786&partnerID=40&md5=e38f2de3c8a150b0575dd73579ef1c89
http://eprints.utp.edu.my/29803/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utp.eprints.29803
record_format eprints
spelling my.utp.eprints.298032022-03-25T02:56:41Z New avo attributes and their applications for facies and hydrocarbon prediction: A case study from the northern malay basin Ridwan, T.K. Hermana, M. Lubis, L.A. Riyadi, Z.A. Amplitude versus offset (AVO) analysis integration to well log analysis is considered one of the advanced techniques to improve the understanding of facies and fluid analysis. Generating AVO attributes are one solution to give an accurate result in facies and fluid characterization. This study is focused on a field of Northern Malay basin, which is associated with a fluvial-deltaic environment, where this system has high heterogeneity, whether it is vertically or horizontally. This research is aimed to demonstrate an application of the scale of quality factor of P-wave (SQp) and the scale of quality factor of S-wave (SQs) AVO attributes for facies and fluid types separation in field scale. These methods are supposed to be more sensitive to predict the hydrocarbons and give less ambiguity. SQp and SQs are the new AVO attributes, which derived from AVO analysis and created according to the intercept product (A) and gradient (B). These new attributes have also been compared to the common method, which is the Scaled Poisson�s Ratio attribute. By comparing with the Scaled Poisson�s Ratio attribute, SQp and SQs attributes are more accurate in determining facies and hydrocarbon. SQp and SQs AVO attributes are integrated with well log data and considered as the best technique to determine facies and fluid distribution. They are interpreted by using angle-stack seismic data based on amplitude contrast on interfaces. Well log data, e.g., density and sonic logs, are used to generate synthetic seismogram and well tie requirements. The volume of shale, volume of coal, porosity, and water saturation logs are used to identify facies and fluid in well log scale. This analysis includes AVO gradient analysis and AVO cross plot to identify the fluid class. Gassmann�s fluid substitution modeling is also generated in the well logs and AVO synthetics for in situ, pure brine, and pure gas cases. The application of the SQp and SQs attributes successfully interpreted facies and fluids distributions in the Northern Malay Basin. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. MDPI AG 2020 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095749425&doi=10.3390%2fapp10217786&partnerID=40&md5=e38f2de3c8a150b0575dd73579ef1c89 Ridwan, T.K. and Hermana, M. and Lubis, L.A. and Riyadi, Z.A. (2020) New avo attributes and their applications for facies and hydrocarbon prediction: A case study from the northern malay basin. Applied Sciences (Switzerland), 10 (21). pp. 1-17. http://eprints.utp.edu.my/29803/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Amplitude versus offset (AVO) analysis integration to well log analysis is considered one of the advanced techniques to improve the understanding of facies and fluid analysis. Generating AVO attributes are one solution to give an accurate result in facies and fluid characterization. This study is focused on a field of Northern Malay basin, which is associated with a fluvial-deltaic environment, where this system has high heterogeneity, whether it is vertically or horizontally. This research is aimed to demonstrate an application of the scale of quality factor of P-wave (SQp) and the scale of quality factor of S-wave (SQs) AVO attributes for facies and fluid types separation in field scale. These methods are supposed to be more sensitive to predict the hydrocarbons and give less ambiguity. SQp and SQs are the new AVO attributes, which derived from AVO analysis and created according to the intercept product (A) and gradient (B). These new attributes have also been compared to the common method, which is the Scaled Poisson�s Ratio attribute. By comparing with the Scaled Poisson�s Ratio attribute, SQp and SQs attributes are more accurate in determining facies and hydrocarbon. SQp and SQs AVO attributes are integrated with well log data and considered as the best technique to determine facies and fluid distribution. They are interpreted by using angle-stack seismic data based on amplitude contrast on interfaces. Well log data, e.g., density and sonic logs, are used to generate synthetic seismogram and well tie requirements. The volume of shale, volume of coal, porosity, and water saturation logs are used to identify facies and fluid in well log scale. This analysis includes AVO gradient analysis and AVO cross plot to identify the fluid class. Gassmann�s fluid substitution modeling is also generated in the well logs and AVO synthetics for in situ, pure brine, and pure gas cases. The application of the SQp and SQs attributes successfully interpreted facies and fluids distributions in the Northern Malay Basin. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
format Article
author Ridwan, T.K.
Hermana, M.
Lubis, L.A.
Riyadi, Z.A.
spellingShingle Ridwan, T.K.
Hermana, M.
Lubis, L.A.
Riyadi, Z.A.
New avo attributes and their applications for facies and hydrocarbon prediction: A case study from the northern malay basin
author_facet Ridwan, T.K.
Hermana, M.
Lubis, L.A.
Riyadi, Z.A.
author_sort Ridwan, T.K.
title New avo attributes and their applications for facies and hydrocarbon prediction: A case study from the northern malay basin
title_short New avo attributes and their applications for facies and hydrocarbon prediction: A case study from the northern malay basin
title_full New avo attributes and their applications for facies and hydrocarbon prediction: A case study from the northern malay basin
title_fullStr New avo attributes and their applications for facies and hydrocarbon prediction: A case study from the northern malay basin
title_full_unstemmed New avo attributes and their applications for facies and hydrocarbon prediction: A case study from the northern malay basin
title_sort new avo attributes and their applications for facies and hydrocarbon prediction: a case study from the northern malay basin
publisher MDPI AG
publishDate 2020
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095749425&doi=10.3390%2fapp10217786&partnerID=40&md5=e38f2de3c8a150b0575dd73579ef1c89
http://eprints.utp.edu.my/29803/
_version_ 1738657017657032704
score 13.211869

Similar Items