A sampling-based Bayesian model for gas saturation estimationusing seismic AVA and marine CSEM data

PDF Version Also Available for Download.

Description

We develop a sampling-based Bayesian model to jointly invertseismic amplitude versus angles (AVA) and marine controlled-sourceelectromagnetic (CSEM) data for layered reservoir models. The porosityand fluid saturation in each layer of the reservoir, the seismic P- andS-wave velocity and density in the layers below and above the reservoir,and the electrical conductivity of the overburden are considered asrandom variables. Pre-stack seismic AVA data in a selected time windowand real and quadrature components of the recorded electrical field areconsidered as data. We use Markov chain Monte Carlo (MCMC) samplingmethods to obtain a large number of samples from the joint posteriordistribution function. Using those ... continued below

Creation Information

Chen, Jinsong; Hoversten, Michael; Vasco, Don; Rubin, Yoram & Hou,Zhangshuan April 4, 2006.

Context

This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this article can be viewed below.

Who

People and organizations associated with either the creation of this article or its content.

Publisher

Provided By

UNT Libraries Government Documents Department

Serving as both a federal and a state depository library, the UNT Libraries Government Documents Department maintains millions of items in a variety of formats. The department is a member of the FDLP Content Partnerships Program and an Affiliated Archive of the National Archives.

Contact Us

What

Descriptive information to help identify this article. Follow the links below to find similar items on the Digital Library.

Description

We develop a sampling-based Bayesian model to jointly invertseismic amplitude versus angles (AVA) and marine controlled-sourceelectromagnetic (CSEM) data for layered reservoir models. The porosityand fluid saturation in each layer of the reservoir, the seismic P- andS-wave velocity and density in the layers below and above the reservoir,and the electrical conductivity of the overburden are considered asrandom variables. Pre-stack seismic AVA data in a selected time windowand real and quadrature components of the recorded electrical field areconsidered as data. We use Markov chain Monte Carlo (MCMC) samplingmethods to obtain a large number of samples from the joint posteriordistribution function. Using those samples, we obtain not only estimatesof each unknown variable, but also its uncertainty information. Thedeveloped method is applied to both synthetic and field data to explorethe combined use of seismic AVA and EM data for gas saturationestimation. Results show that the developed method is effective for jointinversion, and the incorporation of CSEM data reduces uncertainty influid saturation estimation, when compared to results from inversion ofAVA data only.

Source

  • Journal Name: Geophysics; Journal Volume: 72; Journal Issue: 2; Related Information: Journal Publication Date: Mar.-Apr.2007

Language

Item Type

Identifier

Unique identifying numbers for this article in the Digital Library or other systems.

  • Report No.: LBNL--60249
  • Grant Number: DE-AC02-05CH11231
  • Office of Scientific & Technical Information Report Number: 923190
  • Archival Resource Key: ark:/67531/metadc899002

Collections

This article is part of the following collection of related materials.

Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

What responsibilities do I have when using this article?

When

Dates and time periods associated with this article.

Creation Date

  • April 4, 2006

Added to The UNT Digital Library

  • Sept. 27, 2016, 1:39 a.m.

Description Last Updated

  • Sept. 29, 2016, 6:55 p.m.

Usage Statistics

When was this article last used?

Yesterday: 1
Past 30 days: 1
Total Uses: 6

Interact With This Article

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

International Image Interoperability Framework

IIF Logo

We support the IIIF Presentation API

Chen, Jinsong; Hoversten, Michael; Vasco, Don; Rubin, Yoram & Hou,Zhangshuan. A sampling-based Bayesian model for gas saturation estimationusing seismic AVA and marine CSEM data, article, April 4, 2006; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc899002/: accessed October 18, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.