Application of artificial intelligence to reservoir characterization: An interdisciplinary approach. Final report, August 31, 1997

PDF Version Also Available for Download.

Description

The primary goal of the project is to develop a user-friendly computer program to integrate geological and engineering information using Artificial Intelligence (AI) methodology. The project is restricted to fluvially dominated deltaic environments. The static information used in constructing the reservoir description includes well core and log data. Using the well core and the log data, the program identifies the marker beds, and the type of sand facies, and in turn, develops correlations between wells. Using the correlations and sand facies, the program is able to generate multiple realizations of sand facies and petrophysical properties at interwell locations using geostatistical ... continued below

Physical Description

168 p.

Creation Information

Kerr, D.R.; Thompson, L.G. & Shenoi, S. March 1, 1998.

Context

This report 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 report can be viewed below.

Who

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

Sponsor

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 report. Follow the links below to find similar items on the Digital Library.

Description

The primary goal of the project is to develop a user-friendly computer program to integrate geological and engineering information using Artificial Intelligence (AI) methodology. The project is restricted to fluvially dominated deltaic environments. The static information used in constructing the reservoir description includes well core and log data. Using the well core and the log data, the program identifies the marker beds, and the type of sand facies, and in turn, develops correlations between wells. Using the correlations and sand facies, the program is able to generate multiple realizations of sand facies and petrophysical properties at interwell locations using geostatistical techniques. The generated petrophysical properties are used as input in the next step where the production data are honored. By adjusting the petrophysical properties, the match between the simulated and the observed production rates is obtained. Although all the components within the overall system are functioning, the integration of dynamic data may not be practical due to the single-phase flow limitations and the computationally intensive algorithms. The future work needs to concentrate on making the dynamic data integration computationally efficient.

Physical Description

168 p.

Notes

OSTI as DE98000465

Source

  • Other Information: PBD: Mar 1998

Language

Item Type

Identifier

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

  • Other: DE98000465
  • Report No.: DOE/BC/14894--15
  • Grant Number: AC22-93BC14894
  • DOI: 10.2172/587949 | External Link
  • Office of Scientific & Technical Information Report Number: 587949
  • Archival Resource Key: ark:/67531/metadc696669

Collections

This report 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 report?

When

Dates and time periods associated with this report.

Creation Date

  • March 1, 1998

Added to The UNT Digital Library

  • Aug. 14, 2015, 8:43 a.m.

Description Last Updated

  • Nov. 10, 2015, 6:55 p.m.

Usage Statistics

When was this report last used?

Yesterday: 0
Past 30 days: 0
Total Uses: 4

Interact With This Report

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

Kerr, D.R.; Thompson, L.G. & Shenoi, S. Application of artificial intelligence to reservoir characterization: An interdisciplinary approach. Final report, August 31, 1997, report, March 1, 1998; United States. (digital.library.unt.edu/ark:/67531/metadc696669/: accessed July 22, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.